diff --git a/en/sitemap.xml b/en/sitemap.xml
index 87251db4..16dc6be6 100644
--- a/en/sitemap.xml
+++ b/en/sitemap.xml
@@ -1 +1 @@
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 <?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>SensorLab at Jozef Stefan Institute on SensorLab — Jozef Stefan Institute</title><link>https://sensorlab.github.io/</link><description>Recent content in SensorLab at Jozef Stefan Institute on SensorLab — Jozef Stefan Institute</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>SensorLab</copyright><lastBuildDate>Fri, 10 May 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://sensorlab.github.io/index.xml" rel="self" type="application/rss+xml"/><item><title>Electricity knowledge graph datasets</title><link>https://sensorlab.github.io/results/knowledge-graph/</link><pubDate>Fri, 10 May 2024 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/knowledge-graph/</guid><description>The repository includes downloads for the datasets and all the neccesary code to run the pipeline for preprocessing the data and generating the knowledge graph. The knowledge graph is generated from a set of raw datasets containing electricity consumption data from multiple regions and households. The data is preprocessed and harmonized to generate a knowledge graph containing information about the households, appliances, and electricity consumption. We also provide a model training pipeline that can be used to train a model for on/off appliance classification.</description></item><item><title>PhD Student in AI Planning Techniques for 6G</title><link>https://sensorlab.github.io/opportunities/2024-phd-ai-planning-6g/</link><pubDate>Fri, 08 Mar 2024 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/opportunities/2024-phd-ai-planning-6g/</guid><description>Deadline: Till the position is filled. Description:
 The position focuses on the generation of network configurations, such as Service Function Chaining (SFC), by framing it as a planning problem in the field of Artificial Intelligence (AI). This problem will be tackled using a wide range of AI methods, including Neuro-Symbolic Reasoning, Neural Algorithmic Reasoning, Reinforcement Learning, etc. The successful candidate will have the opportunity to work in an international environment and build a pan-European collaborative network by working on EU-funded collaborative projects.</description></item><item><title>Smart Home Energy Trading with Deep Reinforcement Learning</title><link>https://sensorlab.github.io/results/smart-home-energy-trading-drl/</link><pubDate>Tue, 26 Sep 2023 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/smart-home-energy-trading-drl/</guid><description>This python library storest code for a conference paper about smart home energy management using Deep Reinforcement Learning. It is possible for the user to train their own DRL agent, as well as load pre-trained models and test the agent&amp;rsquo;s performance.</description></item><item><title>Early-stage researcher to work on an applied project</title><link>https://sensorlab.github.io/opportunities/2023-phd-position/</link><pubDate>Fri, 15 Sep 2023 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/opportunities/2023-phd-position/</guid><description>SensorLab, in collaboration with ComSensus is looking for a early-stage researcher to work in the area of smart infrastructure management using artificial intelligence, with a focus on algorithms in the field of Deep Reinforcement Learning. The position will offer a unique academia-industry set-up in which the candidate will work both at the &amp;ldquo;Jožef Stefan&amp;rdquo; Institute, where SensorLab is located, and at the ComSensus office in Ljubljana. ComSensus is a young tech company where the candidate will design and conduct experiments, perform data analysis, and deploy developed deep learning models on experimental setups.</description></item><item><title>CCWEBAPP</title><link>https://sensorlab.github.io/results/ccwebapp/</link><pubDate>Mon, 01 Aug 2022 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/ccwebapp/</guid><description>This tool helps estimate the computational complexity of neural networks. It implements the computations according to the methodology explained in the IEEE ICC paper linked below. It supports &lt;strong>fully connected&lt;/strong>, &lt;strong>convolutional&lt;/strong>, and &lt;strong>pooling&lt;/strong> layers.</description></item><item><title>BLE Fingerprints Dataset</title><link>https://sensorlab.github.io/results/ble-fingerprints-dataset/</link><pubDate>Sun, 15 May 2022 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/ble-fingerprints-dataset/</guid><description>The available dataset contains received signal strength (RSS) measurements made with Bluetooth Low Energy (BLE) technology, which can be used for outdoor fingerprinting based localization applications. The dataset was collected with 25 nodes of the LOG-a-TEC testbed positioned at the campus of the Jozef Stefan Institute, Ljubljana.</description></item><item><title>For undergraduate and master students</title><link>https://sensorlab.github.io/opportunities/students/</link><pubDate>Sat, 01 Jan 2022 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/opportunities/students/</guid><description>Do you want to build up your career by doing research during your undergrad studies? Are you interested in smart infrastructures and artificial intelligence?
 We offer Work on real projects with European partners and industry. Learn from a world class team of researchers. Build knowledge and experience that will catapult your carrer. Additional training through summer schools, international conferences, etc. Flexible working time with focus on results. We are looking for highly motivated and pro-active collaborators.</description></item><item><title>Data-Driven Link Quality Estimation</title><link>https://sensorlab.github.io/results/data-driven-link-quality-estimation/</link><pubDate>Mon, 28 Jun 2021 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/data-driven-link-quality-estimation/</guid><description>This repository hosts the source code used in a comprehensive tutorial and survey paper focused on link quality estimation research. The materials contained herein provide a detailed overview and practical applications of various methodologies and technologies employed in the study of link quality estimation. This repository serves as a valuable resource for researchers and practitioners in the field, offering insights and tools developed as part of this significant research effort.</description></item><item><title>Kubitect</title><link>https://sensorlab.github.io/results/kubitect/</link><pubDate>Thu, 27 May 2021 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/kubitect/</guid><description>Kubitect is an open source project that aims to simplify the deployment and subsequent management of Kubernetes clusters. It provides a CLI tool written in Golang that lets you set up, upgrade, scale, and destroy Kubernetes clusters. Under the hood, it uses Terraform along with terraform-libvirt-provider to deploy virtual machines on target hosts running libvirt. Kubernetes is configured on the deployed virtual machines using Kubespray, the popular open source project.</description></item><item><title>UWB Localization Dataset</title><link>https://sensorlab.github.io/results/uwb-dataset/</link><pubDate>Fri, 15 May 2020 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/uwb-dataset/</guid><description>UWB localization data set contains measurements from four different indoor environments. The data set contains measurements that can be used for range-based localization evaluation in different indoor environments using 9 DW1000 UWB transceivers (DWM1000 modules) connected to the networked RaspberryPi computer using in-house radio board SNPN_UWB. 8 nodes were used as localization anchor nodes with fixed locations in individual indoor environment and one node was used as a mobile localization tag.</description></item><item><title>LPWAN Trace Set</title><link>https://sensorlab.github.io/results/ws-traffic-dataset/</link><pubDate>Tue, 01 Jan 2019 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/ws-traffic-dataset/</guid><description>A dataset containing 24 hours of continuous spectrum measurements. A proprietary spectrum sensing device placed on top of a building in a mid-sized European city recorded 5 PSD measurements per second using 1024 FFT bins in a 192 kHz wide band inside the unlicensed European 868 MHz SRD band.</description></item><item><title>LOG-a-TEC</title><link>https://sensorlab.github.io/results/log-a-tec/</link><pubDate>Fri, 01 Jan 2016 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/results/log-a-tec/</guid><description>LOG-a-TEC is a diverse testbed used for research purposes. It started in 2016 and evolved overtime into its third iteration. It covers ultra narrow band and ultra wide band, packet based experimentation, clean slate protocol design, composable and modular protocol stacks, custom and advanced spectrum sensing and signal generating functions in sub-GHz spectrum.</description></item><item><title>Andrej Čampa</title><link>https://sensorlab.github.io/people/acampa/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/acampa/</guid><description/></item><item><title>Anomaly detection</title><link>https://sensorlab.github.io/00-anomaly-detection/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/00-anomaly-detection/</guid><description>Time series anomaly detection is an important and yet unsolved challenge that is relevant for developing, maintaining and monitoring various aspects of smart infrastructures. One of our original contributions to the area consists in the definition of four types of anomalies relevant for monitoring the quality of the wireless links between various smart objects. A second original contribution consists of using time series to image transformations for advancing the state of the art in detection performance.</description></item><item><title>BD4OPEM</title><link>https://sensorlab.github.io/projects/bd4opem/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/bd4opem/</guid><description>Energy power systems face big challenges to cope with grid integration demands of an ever-increasing number of distributed generation and consumption devices in an interconnected world. Technology offers a huge range of opportunities to develop solutions in the uncertain current and upcoming Energy market situation. This proposal considers Open Innovation as a natural solution to create a seamless link and balance between energy stakeholders needs and the solutions to be developed.</description></item><item><title>Blaž Bertalanič</title><link>https://sensorlab.github.io/people/bbertalanic/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/bbertalanic/</guid><description>Blaž Bertalanič received his Master’s degree in electrical engineering from the Faculty of Electrical engineering, University of Ljubljana. He is currently pursuing his PhD at the same faculty and is working as a researcher at the Department of Communication Systems, Jožef Stefan Institute.</description></item><item><title>Carolina Fortuna</title><link>https://sensorlab.github.io/people/cfortuna/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/cfortuna/</guid><description>I am a research fellow working at the Department of Communications Systems at the Jozef Stefan Institute in Ljubljana, Slovenia. I also work with the Data Science team in Bloomberg Media and co-founded Comsensus.
-In my research I use technologies from the broad field of artificial intelligence, including machine learning, data mining and symbolic AI to solve problems in wireless and IoT networks. For more details, see my publications on Google Scholar, Research Gate, and my LinkedIn profile.</description></item><item><title>CREW</title><link>https://sensorlab.github.io/projects/crew/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/crew/</guid><description>The main target of the Cognitive Radio Experimentation World – CREW project is to establish an open federated test platform, which facilitates experimentally-driven research on advanced spectrum sensing, cognitive radio and cognitive networking strategies in view of horizontal and vertical spectrum sharing in licensed and unlicensed bands.</description></item><item><title>DEFENDER</title><link>https://sensorlab.github.io/projects/defender/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/defender/</guid><description>Defending the European Energy Infrastructures is a research project funded by is a research project funded by the European Comission under the Horizon2020 programme (Call: CIP-2016-2017-1. Topic: CIP-01-2016-2017). Critical Energy infrastructures (CEI) protection and security are becoming of utmost importance in our everyday life. However, cyber and system-theoretic approaches fail to provide appropriate security levels to CEIs, since they are often used in isolation and build on incomplete attack models, resulting in silos-like security management fragmented operational policies. To face these challenges, DEFENDER will (i) model CEIs as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats. DEFENDER will adapt, integrate, upscale and validate a number of TRL 4-5 technologies and deploy them within a TRL7 integrated yet adaptable framework for CEI security, resilience and self-healing “by design”, with a view to address, detect, and mitigate cyber-physical threats.</description></item><item><title>Denis Sodin</title><link>https://sensorlab.github.io/people/dsodin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/dsodin/</guid><description/></item><item><title>Deployment and operation automation</title><link>https://sensorlab.github.io/05-test-automation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/05-test-automation/</guid><description>Automation infrastructure for developing testing and deploying software for embedded/constrained devices is currently approaching market adoption. Our group pioneered continuous integration for embedded development by proposing the COINS framework and then implementing and evaluating it on LOG-a-TEC. We also touched on improving the efficiency of zero-touch device provisionining.</description></item><item><title>Din Mušić</title><link>https://sensorlab.github.io/people/dmusic/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/dmusic/</guid><description/></item><item><title>e.BOTTLE</title><link>https://sensorlab.github.io/projects/ebottle/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ebottle/</guid><description>Vzpostavitev naprednih IKT storitev za analizo življenjskega cikla steklene embalaže – eBOTTLE. Naročnik projekta je RAZVOJNI CENTER eNeM Novi materiali, d.o.o. Sodelovanje se nanaša na izvajanje projekta pod naslovom »Pametno multikomponentno embalažno steklo» – projekt eBOTTLE, ki je bil s strani Ministrstva za gospodarski razvoj in tehnologijo potrjen za sofinanciranje v okviru Javnega razpisa. Odsek za komunikacijske sisteme sodeluje na operaciji kot zunanji izvajalec raziskovalno-razvojnih aktivnosti pri razvoju in vzpostavitvi naprednih IKT storitev za analizo življenjskega cikla steklene embalaže.</description></item><item><title>Education and knowledge transfer</title><link>https://sensorlab.github.io/08-education/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/08-education/</guid><description>We offer various activities targeting education and knowledge transfer. Through our work with undergraduate, graduate and post-graduate students on individual cutting edge projects and their theses, we make sure they are better prepared for the market needs. We also organize summer schools, tutorials at conferences and locally in collaboration with the University of Ljubljana and the Jozef Stefan Internation Postgraduate School. For general practitioners and decision makers we also reccommend the edited book The Internet of Things: From Data to Insight.</description></item><item><title>EuConNeCts3</title><link>https://sensorlab.github.io/projects/euconnects3/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/euconnects3/</guid><description>It is the purpose of EuConNeCts3, a Supporting Action, to organise the following 2 editions, 2018 and 2019, of the EC sponsored conference in the area of communication networks and systems (EuCNC – European Conference on Networks and Communications), continuing the successful organisation of this conference since 2014. EuCNC will continue to serve as a technical and scientific conference for researchers, namely European ones, to show their work in the area of Telecommunications, focusing on communication networks and systems, and also reaching services and applications. The conference will not be restricted to European researchers, rather aiming at attracting others from all the other regions in the world. It will also serve as a showcase for the work developed by projects co-financed by the EC, namely those arising from H2020 calls, and more specifically, those addressing 5G and beyond. Nonetheless, it also aims at attracting works in the area of communication networks and systems from other objectives.</description></item><item><title>eWINE</title><link>https://sensorlab.github.io/projects/ewine/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ewine/</guid><description>The elastic Wireless Networking Experimentation (eWINE) is a research project funded by the European Comission under the Horizon2020 programme (Call: H2020-ICT-2015. Topic: ICT-12-2015). The main goal of eWINE is to realize elastic networks that can scale to a high number of users in a short timespan through the use of an agile infrastructure (intelligent software and flexible hardware), enabling: 1) dynamic on-demand end-to-end wireless connectivity service provisioning, 2) elastic resource sharing in dense heterogeneous and small cell networks (HetSNets), 3) intelligent and informed configuration of the physical layer.</description></item><item><title>Experimental infrastructure</title><link>https://sensorlab.github.io/06-experimental-infrastructure/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/06-experimental-infrastructure/</guid><description>We developed the LOG-a-TEC experimental infrastructre that enables a wide range of outdoor and indoor experimentation such as with ultra narrow band and ultra wide band, packet based experimentation, clean slate protocol design, composable and modular protocol stacks, custom and advanced spectrum sensing and signal generating functions in sub-GHz spectrum.</description></item><item><title>FED4FIRE+</title><link>https://sensorlab.github.io/projects/fed4fire/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/fed4fire/</guid><description>Fed4FIRE+ is an Integrating Project under the European Union’s Programme Horizon 2020, addressing the work programme topic Future Internet Research and Experimentation. It started in January 2017 and will run for 60 months, until the end of September 2021. The Fed4FIRE+ project is the successor of the Fed4FIRE project.</description></item><item><title>Gregor Cerar</title><link>https://sensorlab.github.io/people/gcerar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/gcerar/</guid><description>Gregor Cerar received his Bachelor&amp;rsquo;s (2013) and Master&amp;rsquo;s (2016) degrees from the Faculty of Electrical Engineering of the University of Ljubljana, where he completed the Telecommunications study programme, and the Ph.D. degree (2021) from International Postgraduate School of Jožef Stefan in Information and Communication technologies with the Department of Communication Systems, Jožef Stefan Institute. He is currently a research associate with the Department of Communication Systems, Jožef Stefan Institute.</description></item><item><title>Halil Yetgin</title><link>https://sensorlab.github.io/people/hyetgin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/hyetgin/</guid><description>Halil Yetgin received the B.Eng. degree in computer engineering from Selcuk University, Turkey, in 2008, the M.Sc. degree in wireless communications from the University of Southampton,U.K., in 2010, and the Ph.D. degree in wireless communications with the Next Generation Wireless Research Group under the supervision of Prof. Lajos Hanzo and Dr. Mohammed El-Hajjar, University of Southampton in 2015. He is an Assistant Professor with the Department of Electrical and Electronics Engineering, Bitlis Eren University, Turkey and a research fellow at the Department of Communication Systems of Jožef Stefan Institute, Ljubljana, Slovenia.</description></item><item><title>Jernej Hribar</title><link>https://sensorlab.github.io/people/jhribar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/jhribar/</guid><description>Jernej Hribar is a Marie Skłodowska-Curie Action Fellow in the Department of Communication Systems since October 2022. His MSCA action - TimeSmart - investigates the applicability of the novel Age of Information metric in smart grids. From 2019-2022, he was a postdoctoral researcher in the CONNECT Centre for Future Networks and Communications at Trinity College Dublin, Ireland. He was involved in an international collaborative project between Trinity College Dublin and Tsinghua University using machine learning techniques to assist future networks with decision-making problems in smart cities.</description></item><item><title>Klemen Bregar</title><link>https://sensorlab.github.io/people/kbregar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/kbregar/</guid><description/></item><item><title>Link quality classification</title><link>https://sensorlab.github.io/01-link-quality-classification/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/01-link-quality-classification/</guid><description>Wireless links are crucial to cost efficiently connecting various components in smart infrastructures. Recently, machine learning techniques proved to be suitable for more accurate estimation and classification. As original contribution to this area, we provide a comprehensive survey on link quality estimators developed from empirical data and then focus on the subset that use ML algorithms. We analyze ML-based Link Quality Estimation (LQE) models from two perspectives using performance data. Firstly, we focus on how they address quality requirements that are important from the perspective of the applications they serve.</description></item><item><title>Ljupcho Milosheski</title><link>https://sensorlab.github.io/people/lmilosheski/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/lmilosheski/</guid><description/></item><item><title>Marko Hudomalj</title><link>https://sensorlab.github.io/people/mhudomalj/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mhudomalj/</guid><description/></item><item><title>Marko Mihelin</title><link>https://sensorlab.github.io/people/mmihelin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mmihelin/</guid><description/></item><item><title>Matevž Vučnik</title><link>https://sensorlab.github.io/people/mvucnik/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mvucnik/</guid><description/></item><item><title>Miha Smolnikar</title><link>https://sensorlab.github.io/people/msmolnikar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/msmolnikar/</guid><description/></item><item><title>Mihael "Miha" Mohorčič</title><link>https://sensorlab.github.io/people/mmohorcic/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mmohorcic/</guid><description>Dr. Mihael Mohorcic (DrSc in ElecEng from University of Ljubljana, 2002) is head of the Department of Communication Systems and Scientific Advisor at the Jozef Stefan Institute, and associate professor at the Jozef Stefan International Postgraduate School. His research and working experience include development and performance evaluation of network protocols and architectures for mobile and wireless communication systems, and resource management in terrestrial, stratospheric and satellite networks. His recent research interest is focused on cognitive radio networks, cross-layer protocol design and optimization, “smart” applications of wireless sensor networks, dynamic composition of communication services and wireless experimental testbeds.</description></item><item><title>MLOps</title><link>https://sensorlab.github.io/04-mlops/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/04-mlops/</guid><description>Reasearching MLOps pipelines and end-to-end machine learning development processes to design, build and deploy ML models.</description></item><item><title>NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution</title><link>https://sensorlab.github.io/projects/nancy/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/nancy/</guid><description>The overall aim of NANCY is to introduce a secure and intelligent architecture for the beyond the fifth generation (B5G) wireless network. Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation will be designed.
+In my research I use technologies from the broad field of artificial intelligence, including machine learning, data mining and symbolic AI to solve problems in wireless and IoT networks. For more details, see my publications on Google Scholar, Research Gate, and my LinkedIn profile.</description></item><item><title>CREW</title><link>https://sensorlab.github.io/projects/crew/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/crew/</guid><description>The main target of the Cognitive Radio Experimentation World – CREW project is to establish an open federated test platform, which facilitates experimentally-driven research on advanced spectrum sensing, cognitive radio and cognitive networking strategies in view of horizontal and vertical spectrum sharing in licensed and unlicensed bands.</description></item><item><title>DEFENDER</title><link>https://sensorlab.github.io/projects/defender/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/defender/</guid><description>Defending the European Energy Infrastructures is a research project funded by is a research project funded by the European Comission under the Horizon2020 programme (Call: CIP-2016-2017-1. Topic: CIP-01-2016-2017). Critical Energy infrastructures (CEI) protection and security are becoming of utmost importance in our everyday life. However, cyber and system-theoretic approaches fail to provide appropriate security levels to CEIs, since they are often used in isolation and build on incomplete attack models, resulting in silos-like security management fragmented operational policies. To face these challenges, DEFENDER will (i) model CEIs as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats. DEFENDER will adapt, integrate, upscale and validate a number of TRL 4-5 technologies and deploy them within a TRL7 integrated yet adaptable framework for CEI security, resilience and self-healing “by design”, with a view to address, detect, and mitigate cyber-physical threats.</description></item><item><title>Denis Sodin</title><link>https://sensorlab.github.io/people/dsodin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/dsodin/</guid><description/></item><item><title>Deployment and operation automation</title><link>https://sensorlab.github.io/05-test-automation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/05-test-automation/</guid><description>Automation infrastructure for developing testing and deploying software for embedded/constrained devices is currently approaching market adoption. Our group pioneered continuous integration for embedded development by proposing the COINS framework and then implementing and evaluating it on LOG-a-TEC. We also touched on improving the efficiency of zero-touch device provisionining.</description></item><item><title>Din Mušić</title><link>https://sensorlab.github.io/people/dmusic/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/dmusic/</guid><description/></item><item><title>e.BOTTLE</title><link>https://sensorlab.github.io/projects/ebottle/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ebottle/</guid><description>Vzpostavitev naprednih IKT storitev za analizo življenjskega cikla steklene embalaže – eBOTTLE. Naročnik projekta je RAZVOJNI CENTER eNeM Novi materiali, d.o.o. Sodelovanje se nanaša na izvajanje projekta pod naslovom »Pametno multikomponentno embalažno steklo» – projekt eBOTTLE, ki je bil s strani Ministrstva za gospodarski razvoj in tehnologijo potrjen za sofinanciranje v okviru Javnega razpisa. Odsek za komunikacijske sisteme sodeluje na operaciji kot zunanji izvajalec raziskovalno-razvojnih aktivnosti pri razvoju in vzpostavitvi naprednih IKT storitev za analizo življenjskega cikla steklene embalaže.</description></item><item><title>Education and knowledge transfer</title><link>https://sensorlab.github.io/08-education/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/08-education/</guid><description>We offer various activities targeting education and knowledge transfer. Through our work with undergraduate, graduate and post-graduate students on individual cutting edge projects and their theses, we make sure they are better prepared for the market needs. We also organize summer schools, tutorials at conferences and locally in collaboration with the University of Ljubljana and the Jozef Stefan Internation Postgraduate School. For general practitioners and decision makers we also reccommend the edited book The Internet of Things: From Data to Insight.</description></item><item><title>EuConNeCts3</title><link>https://sensorlab.github.io/projects/euconnects3/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/euconnects3/</guid><description>It is the purpose of EuConNeCts3, a Supporting Action, to organise the following 2 editions, 2018 and 2019, of the EC sponsored conference in the area of communication networks and systems (EuCNC – European Conference on Networks and Communications), continuing the successful organisation of this conference since 2014. EuCNC will continue to serve as a technical and scientific conference for researchers, namely European ones, to show their work in the area of Telecommunications, focusing on communication networks and systems, and also reaching services and applications. The conference will not be restricted to European researchers, rather aiming at attracting others from all the other regions in the world. It will also serve as a showcase for the work developed by projects co-financed by the EC, namely those arising from H2020 calls, and more specifically, those addressing 5G and beyond. Nonetheless, it also aims at attracting works in the area of communication networks and systems from other objectives.</description></item><item><title>eWINE</title><link>https://sensorlab.github.io/projects/ewine/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ewine/</guid><description>The elastic Wireless Networking Experimentation (eWINE) is a research project funded by the European Comission under the Horizon2020 programme (Call: H2020-ICT-2015. Topic: ICT-12-2015). The main goal of eWINE is to realize elastic networks that can scale to a high number of users in a short timespan through the use of an agile infrastructure (intelligent software and flexible hardware), enabling: 1) dynamic on-demand end-to-end wireless connectivity service provisioning, 2) elastic resource sharing in dense heterogeneous and small cell networks (HetSNets), 3) intelligent and informed configuration of the physical layer.</description></item><item><title>Experimental infrastructure</title><link>https://sensorlab.github.io/06-experimental-infrastructure/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/06-experimental-infrastructure/</guid><description>We developed the LOG-a-TEC experimental infrastructre that enables a wide range of outdoor and indoor experimentation such as with ultra narrow band and ultra wide band, packet based experimentation, clean slate protocol design, composable and modular protocol stacks, custom and advanced spectrum sensing and signal generating functions in sub-GHz spectrum.</description></item><item><title>FED4FIRE+</title><link>https://sensorlab.github.io/projects/fed4fire/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/fed4fire/</guid><description>Fed4FIRE+ is an Integrating Project under the European Union’s Programme Horizon 2020, addressing the work programme topic Future Internet Research and Experimentation. It started in January 2017 and will run for 60 months, until the end of September 2021. The Fed4FIRE+ project is the successor of the Fed4FIRE project.</description></item><item><title>Gregor Cerar</title><link>https://sensorlab.github.io/people/gcerar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/gcerar/</guid><description>Gregor Cerar received his Bachelor&amp;rsquo;s (2013) and Master&amp;rsquo;s (2016) degrees from the Faculty of Electrical Engineering of the University of Ljubljana, where he completed the Telecommunications study programme, and the Ph.D. degree (2021) from International Postgraduate School of Jožef Stefan in Information and Communication technologies with the Department of Communication Systems, Jožef Stefan Institute. He is currently a research associate with the Department of Communication Systems, Jožef Stefan Institute.</description></item><item><title>Halil Yetgin</title><link>https://sensorlab.github.io/people/hyetgin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/hyetgin/</guid><description>Halil Yetgin received the B.Eng. degree in computer engineering from Selcuk University, Turkey, in 2008, the M.Sc. degree in wireless communications from the University of Southampton,U.K., in 2010, and the Ph.D. degree in wireless communications with the Next Generation Wireless Research Group under the supervision of Prof. Lajos Hanzo and Dr. Mohammed El-Hajjar, University of Southampton in 2015. He is an Assistant Professor with the Department of Electrical and Electronics Engineering, Bitlis Eren University, Turkey and a research fellow at the Department of Communication Systems of Jožef Stefan Institute, Ljubljana, Slovenia.</description></item><item><title>Jernej Hribar</title><link>https://sensorlab.github.io/people/jhribar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/jhribar/</guid><description>Jernej Hribar is a Marie Skłodowska-Curie Action Fellow in the Department of Communication Systems since October 2022. His MSCA action - TimeSmart - investigates the applicability of the novel Age of Information metric in smart grids. From 2019-2022, he was a postdoctoral researcher in the CONNECT Centre for Future Networks and Communications at Trinity College Dublin, Ireland. He was involved in an international collaborative project between Trinity College Dublin and Tsinghua University using machine learning techniques to assist future networks with decision-making problems in smart cities.</description></item><item><title>Klemen Bregar</title><link>https://sensorlab.github.io/people/kbregar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/kbregar/</guid><description/></item><item><title>Link quality classification</title><link>https://sensorlab.github.io/01-link-quality-classification/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/01-link-quality-classification/</guid><description>Wireless links are crucial to cost efficiently connecting various components in smart infrastructures. Recently, machine learning techniques proved to be suitable for more accurate estimation and classification. As original contribution to this area, we provide a comprehensive survey on link quality estimators developed from empirical data and then focus on the subset that use ML algorithms. We analyze ML-based Link Quality Estimation (LQE) models from two perspectives using performance data. Firstly, we focus on how they address quality requirements that are important from the perspective of the applications they serve.</description></item><item><title>Ljupcho Milosheski</title><link>https://sensorlab.github.io/people/lmilosheski/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/lmilosheski/</guid><description/></item><item><title>Marko Hudomalj</title><link>https://sensorlab.github.io/people/mhudomalj/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mhudomalj/</guid><description/></item><item><title>Marko Mihelin</title><link>https://sensorlab.github.io/people/mmihelin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mmihelin/</guid><description/></item><item><title>Matevž Vučnik</title><link>https://sensorlab.github.io/people/mvucnik/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mvucnik/</guid><description/></item><item><title>Miha Smolnikar</title><link>https://sensorlab.github.io/people/msmolnikar/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/msmolnikar/</guid><description/></item><item><title>Mihael "Miha" Mohorčič</title><link>https://sensorlab.github.io/people/mmohorcic/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/mmohorcic/</guid><description>Dr. Mihael Mohorcic (DrSc in ElecEng from University of Ljubljana, 2002) is head of the Department of Communication Systems and Scientific Advisor at the Jozef Stefan Institute, and associate professor at the Jozef Stefan International Postgraduate School. His research and working experience include development and performance evaluation of network protocols and architectures for mobile and wireless communication systems, and resource management in terrestrial, stratospheric and satellite networks. His recent research interest is focused on cognitive radio networks, cross-layer protocol design and optimization, “smart” applications of wireless sensor networks, dynamic composition of communication services and wireless experimental testbeds.</description></item><item><title>MISA: Multi-lidar Intelligence for Smart City Applications</title><link>https://sensorlab.github.io/projects/misa/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/misa/</guid><description>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</description></item><item><title>MLOps</title><link>https://sensorlab.github.io/04-mlops/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/04-mlops/</guid><description>Reasearching MLOps pipelines and end-to-end machine learning development processes to design, build and deploy ML models.</description></item><item><title>NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution</title><link>https://sensorlab.github.io/projects/nancy/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/nancy/</guid><description>The overall aim of NANCY is to introduce a secure and intelligent architecture for the beyond the fifth generation (B5G) wireless network. Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation will be designed.
 These architectures and protocols will make the most by jointly optimizing the midhaul, and fronthaul. This is expected to enable truly distributed intelligence and transform the network to a low-power computer. Likewise, by following a holistic optimization approach and leveraging the developments in blockchain, NANCY aims at supporting E2E personalized, multi-tenant and perpetual protection.</description></item><item><title>NRG5</title><link>https://sensorlab.github.io/projects/nrg5/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/nrg5/</guid><description>The NRG-5 project envisages contributing to the 5G PPP/5G Initiative research and development activities and participation at the relevant 5G Working Groups by delivering a novel 5G-PPP compliant, decentralized, &lt;strong>secure&lt;/strong> and &lt;strong>resilient&lt;/strong> framework, with &lt;strong>highly availability&lt;/strong> able to homogeneously model and virtualize multi-homed, static or moving, hardware constrained (smart energy) devices, edge computing resources and elastic virtualized services over electricity and gas infrastructure assets combined with the telecommunications infrastructure covering the full spectrum of the communication and computational needs.</description></item><item><title>Open Science</title><link>https://sensorlab.github.io/07-open-science/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/07-open-science/</guid><description>We are commited to open science principles and we make available our early work as arxiv pre-prints, openly access(ible) versions of our accepted papers as well as datasets and code.</description></item><item><title>PlanetData</title><link>https://sensorlab.github.io/projects/planetdata/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/planetdata/</guid><description>The PlanetData project is built around three objectives that together ensure the creation of a durable community made up of academic and industrial partners. This community will be supported in conducting research in the large-scale data management area through the provision of data sets and access to tailored data management technology. From the research point of view, the focus is on large-scale data management. Sensorlab provides sensor data, raw and annotated and services based on these.</description></item><item><title>RESILOC</title><link>https://sensorlab.github.io/projects/resiloc/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/resiloc/</guid><description>Resilience is defined by the United Nations as “the ability to resist, absorb and accommodate to the effects of a hazard, in a timely and efficient manner”. Thus, resilient communities are those in which their citizens, environment, businesses, and infrastructures have the capacity to withstand, adapt, and recover in a timely manner from any kind of hazards they face, either planned or unplanned. In recent years efforts have been spent to tackle resilience and there is, still, a long path forward in defining an EU valid and sound approach to the problem. RESILOC aims at studying and implementing a holistic framework of studies, methods and software instruments that combines the physical with the less tangible aspects associated with human behaviour. The study-oriented section of the framework will move from a thorough collection and analysis of literature and stories from the many approaches to resilience adopted all over the World. The results of the studies will lead to the definition of a set of new methods and strategies where the assessment of the resilience indicators of a community will be performed together with simulations on the “what-if” certain measures are taken.</description></item><item><title>SAAM: Supporting Active Ageing Through Multimodal Coaching</title><link>https://sensorlab.github.io/projects/saam/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/saam/</guid><description>The project aims to develop and validate a Virtual Assistant-Coach that supports the process of healthy ageing by preserving physical, cognitive, mental, and social well-being of older citizens, and prolonging the period of life they can live safely at home. SAAM focuses on innovative, unobtrusive technology-enabled approaches, with a novel and practical emphasis on wearable and ambient sensing.</description></item><item><title>Shih-Kai Chou</title><link>https://sensorlab.github.io/people/skchou/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/people/skchou/</guid><description>I received my Master’s degree in communication engineering from National Chung Cheng University (CCU), Taiwan in 2014 and a Ph.D. from Queen’s University, Belfast, U.K. in 2023. My Ph.D. focused on Reconfigurable Intelligent Surface (RIS/IRS), more specifically, the real-world setup and optimization of RIS-aided wireless systems.</description></item><item><title>SiQUID: Slovenian Quantum Communication Infrastructure Demonstration</title><link>https://sensorlab.github.io/projects/siquid/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/siquid/</guid><description>The European Union is currently preparing to implement the infrastructure for a Europe-wide network for quantum communication. Research groups, industrial partners, and government representatives from all European member states have devised projects to perform proof-of-principle demonstrations of quantum communication and quantum key distribution (QKD). To this end, quantum communication infrastructure will be implemented on the national level in all EU member states to facilitate the international connection of those networks later. The Slovenian Quantum Communication Infrastructure Demonstration (SiQUID) project will be the first to implement quantum key distribution (QKD) in Slovenia. The project will establish quantum communication links between multiple government nodes in Slovenia and a test-bed quantum network between research institutions in Ljubljana for the research and development of advanced quantum communication protocols.</description></item><item><title>Time series classification</title><link>https://sensorlab.github.io/02-appliance-classification/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/02-appliance-classification/</guid><description>One important aspect of smart infrastructure research and development consists of automatic classification of time series data. Our recent work using shallow and deep machine learning methods for appliance classification in smart grids is documented in two recent papers and the code is available also as a CaaS service.</description></item><item><title>TimeSmart: Timeliness of Information in Smart Grids Networks</title><link>https://sensorlab.github.io/projects/timesmart/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/timesmart/</guid><description>TimeSmart project will investigate the applicability of the novel Age of Information metric in smart grid networks. While the metric has become a valuable tool for measuring the system&amp;rsquo;s performance, its practical value and impact in the real-time system are left unanswered. This project seeks to remedy that by applying the metric to a system in which the timing of collected data, currently measured through jitter or latency, profoundly impacts management and control. The AoI offers a new perspective on how the system should collect and process information, as such decisions are also based on the context of processed information(their semantic nature). In turn, the new approach can offer an innovative way of improving the efficiency of renewable electrical energy supply and electrical loads by taking advantage of the available edge infrastructure. This project aims to adopt the AoI metric in smart grid networks to improve the energy transmission efficiency, achievable through more timely collected information, to save energy.</description></item><item><title>TIMIN6: Timely and Sustainable Information Management in 6G Networks</title><link>https://sensorlab.github.io/projects/timin6/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/timin6/</guid><description>The main goal of the TIMIN6 project is to design a new data collection method based on the Age of Information (AoI) metric in connection with aspects of sustainable resource management. AoI is a relatively new and not yet fully understood metric in the field of information science. Considering the AoI can significantly impact energy consumption in data collection, but many aspects and the actual applicability of the metric still need to be explored. While most research in this area focuses on finding more efficient ways to extract information from already collected data, the TIMIN6 project will focus on the question of how frequently devices should collect and transmit data to operate in a more sustainable manner. The goal of this approach is to reduce unnecessarily wasted energy in the billions of devices that will make up 6G networks, enabling a more sustainable future. The project is funded by Slovenian Research and Innovation Agency (ARIS).</description></item><item><title>Wireless localization</title><link>https://sensorlab.github.io/03-localization/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/03-localization/</guid><description>Location based services, already popular with end users, are now inevitably becoming part of new wireless infrastructures and emerging business processes. The increasingly popular Deep Learning (DL) artificial intelligence methods perform very well in wireless fingerprinting localization based on extensive indoor radio measurement data. Check out our work and datasets on improving ML based localization using traces from the LOG-a-TEC testbed and soon to come sustainable fingerprinting.</description></item><item><title>WISHFUL</title><link>https://sensorlab.github.io/projects/wishful/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/wishful/</guid><description>The WiSHFUL project (Wireless Software and Hardware platforms for Flexible and Unified radio and network controL) will reduce the threshold for experimentation in view of wireless innovation creation and by increasing the realism of experimentation. The WiSHFUL project is funded by the European Commission’s Horizon 2020 Programme under grant agreement n645274. The project started on January 1st 2015 and will last for 36 months.
 Our role: Open call extension of the WiSHFUL project with addition of LOG-a-TEC testbed 5G capillary capabilities and adaptation of WiSHFUL universal programming interfaces for the use in the LOG-a-TEC testbed.</description></item></channel></rss>
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 <!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/projects/><link rel=alternate hreflang=en href=https://sensorlab.github.io/projects/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/projects/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Projects"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/projects/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Projects"><meta name=twitter:description content><title>Projects &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
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-<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class="nav-link active" href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container my-4" aria-role=main><h1>Projects</h1><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/nancy/ class="link-underline link-underline-opacity-0 text-reset">NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution</a></h2><p>Jan 2023 &mdash; Dec 2025</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/nancy/><img src=https://sensorlab.github.io/projects/nancy/NANCY_hu006c965f010fc742b2a68d203836a2a6_56514_200x0_resize_box_3.png alt="NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution logo" class="float-md-start me-3 mb-2" height=193 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The overall aim of NANCY is to introduce a secure and intelligent architecture for the beyond the fifth generation (B5G) wireless network. Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation will be designed.
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class="nav-link active" href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container my-4" aria-role=main><h1>Projects</h1><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/misa/ class="link-underline link-underline-opacity-0 text-reset">MISA: Multi-lidar Intelligence for Smart City Applications</a></h2><p>Apr 2024 &mdash; Apr 2026</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/misa/><img src=https://sensorlab.github.io/projects/misa/aris_logo_hub08622e5c39b8cb3af485e5245357ede_10856_200x0_resize_q75_box.jpg alt="MISA: Multi-lidar Intelligence for Smart City Applications logo" class="float-md-start me-3 mb-2" height=200 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/nancy/ class="link-underline link-underline-opacity-0 text-reset">NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution</a></h2><p>Jan 2023 &mdash; Dec 2025</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/nancy/><img src=https://sensorlab.github.io/projects/nancy/NANCY_hu006c965f010fc742b2a68d203836a2a6_56514_200x0_resize_box_3.png alt="NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution logo" class="float-md-start me-3 mb-2" height=193 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The overall aim of NANCY is to introduce a secure and intelligent architecture for the beyond the fifth generation (B5G) wireless network. Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation will be designed.
 These architectures and protocols will make the most by jointly optimizing the midhaul, and fronthaul. This is expected to enable truly distributed intelligence and transform the network to a low-power computer. Likewise, by following a holistic optimization approach and leveraging the developments in blockchain, NANCY aims at supporting E2E personalized, multi-tenant and perpetual protection.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/timin6/ class="link-underline link-underline-opacity-0 text-reset">TIMIN6: Timely and Sustainable Information Management in 6G Networks</a></h2><p>Oct 2023 &mdash; Sep 2025</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/timin6/><img src=https://sensorlab.github.io/projects/timin6/aris_logo_hub08622e5c39b8cb3af485e5245357ede_10856_200x0_resize_q75_box.jpg alt="TIMIN6: Timely and Sustainable Information Management in 6G Networks logo" class="float-md-start me-3 mb-2" height=200 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The main goal of the TIMIN6 project is to design a new data collection method based on the Age of Information (AoI) metric in connection with aspects of sustainable resource management. AoI is a relatively new and not yet fully understood metric in the field of information science. Considering the AoI can significantly impact energy consumption in data collection, but many aspects and the actual applicability of the metric still need to be explored. While most research in this area focuses on finding more efficient ways to extract information from already collected data, the TIMIN6 project will focus on the question of how frequently devices should collect and transmit data to operate in a more sustainable manner. The goal of this approach is to reduce unnecessarily wasted energy in the billions of devices that will make up 6G networks, enabling a more sustainable future. The project is funded by Slovenian Research and Innovation Agency (ARIS).</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/siquid/ class="link-underline link-underline-opacity-0 text-reset">SiQUID: Slovenian Quantum Communication Infrastructure Demonstration</a></h2><p>Jan 2023 &mdash; Jul 2025</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/siquid/><img src=https://sensorlab.github.io/projects/siquid/SiQUID_logo_huc273cd9dda1bc7d4668f6bcce23cdd26_14971_200x0_resize_box_3.png alt="SiQUID: Slovenian Quantum Communication Infrastructure Demonstration logo" class="float-md-start me-3 mb-2" height=53 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The European Union is currently preparing to implement the infrastructure for a Europe-wide network for quantum communication. Research groups, industrial partners, and government representatives from all European member states have devised projects to perform proof-of-principle demonstrations of quantum communication and quantum key distribution (QKD). To this end, quantum communication infrastructure will be implemented on the national level in all EU member states to facilitate the international connection of those networks later. The Slovenian Quantum Communication Infrastructure Demonstration (SiQUID) project will be the first to implement quantum key distribution (QKD) in Slovenia. The project will establish quantum communication links between multiple government nodes in Slovenia and a test-bed quantum network between research institutions in Ljubljana for the research and development of advanced quantum communication protocols.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/timesmart/ class="link-underline link-underline-opacity-0 text-reset">TimeSmart: Timeliness of Information in Smart Grids Networks</a></h2><p>Oct 2022 &mdash; Mar 2025</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/timesmart/><img src=https://sensorlab.github.io/projects/timesmart/TimeSmart_logo_hu76ed9126e6b29b23f44b908978067ba8_124251_200x0_resize_box_3.png alt="TimeSmart: Timeliness of Information in Smart Grids Networks logo" class="float-md-start me-3 mb-2" height=63 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">TimeSmart project will investigate the applicability of the novel Age of Information metric in smart grid networks. While the metric has become a valuable tool for measuring the system&rsquo;s performance, its practical value and impact in the real-time system are left unanswered. This project seeks to remedy that by applying the metric to a system in which the timing of collected data, currently measured through jitter or latency, profoundly impacts management and control. The AoI offers a new perspective on how the system should collect and process information, as such decisions are also based on the context of processed information(their semantic nature). In turn, the new approach can offer an innovative way of improving the efficiency of renewable electrical energy supply and electrical loads by taking advantage of the available edge infrastructure. This project aims to adopt the AoI metric in smart grid networks to improve the energy transmission efficiency, achievable through more timely collected information, to save energy.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/bd4opem/ class="link-underline link-underline-opacity-0 text-reset">BD4OPEM</a></h2><p>Jan 2020 &mdash; Dec 2023</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/bd4opem/><img src=https://sensorlab.github.io/projects/bd4opem/BD4OPEM_logo_hu02ea3796bfafd3e7e92ab71a7e7225f4_21916_200x0_resize_box_3.png alt="BD4OPEM logo" class="float-md-start me-3 mb-2" height=80 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">Energy power systems face big challenges to cope with grid integration demands of an ever-increasing number of distributed generation and consumption devices in an interconnected world. Technology offers a huge range of opportunities to develop solutions in the uncertain current and upcoming Energy market situation. This proposal considers Open Innovation as a natural solution to create a seamless link and balance between energy stakeholders needs and the solutions to be developed.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/resiloc/ class="link-underline link-underline-opacity-0 text-reset">RESILOC</a></h2><p>Jan 2019 &mdash; Dec 2022</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/resiloc/><img src=https://sensorlab.github.io/projects/resiloc/resiloc_logo_hub9145a9df1a3f8fd6c0691ebdaaae04c_29930_200x0_resize_box_3.png alt="RESILOC logo" class="float-md-start me-3 mb-2" height=134 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">Resilience is defined by the United Nations as “the ability to resist, absorb and accommodate to the effects of a hazard, in a timely and efficient manner”. Thus, resilient communities are those in which their citizens, environment, businesses, and infrastructures have the capacity to withstand, adapt, and recover in a timely manner from any kind of hazards they face, either planned or unplanned. In recent years efforts have been spent to tackle resilience and there is, still, a long path forward in defining an EU valid and sound approach to the problem. RESILOC aims at studying and implementing a holistic framework of studies, methods and software instruments that combines the physical with the less tangible aspects associated with human behaviour. The study-oriented section of the framework will move from a thorough collection and analysis of literature and stories from the many approaches to resilience adopted all over the World. The results of the studies will lead to the definition of a set of new methods and strategies where the assessment of the resilience indicators of a community will be performed together with simulations on the “what-if” certain measures are taken.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/fed4fire/ class="link-underline link-underline-opacity-0 text-reset">FED4FIRE+</a></h2><p>Jan 2017 &mdash; Sep 2021</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/fed4fire/><img src=https://sensorlab.github.io/projects/fed4fire/fed4fire_logo_hu9dd23b009b8c5744fd3a51f98340a8f3_6334_200x0_resize_box_3.png alt="FED4FIRE+ logo" class="float-md-start me-3 mb-2" height=47 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">Fed4FIRE+ is an Integrating Project under the European Union’s Programme Horizon 2020, addressing the work programme topic Future Internet Research and Experimentation. It started in January 2017 and will run for 60 months, until the end of September 2021. The Fed4FIRE+ project is the successor of the Fed4FIRE project.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/defender/ class="link-underline link-underline-opacity-0 text-reset">DEFENDER</a></h2><p>Jan 2017 &mdash; Dec 2020</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/defender/><img src=https://sensorlab.github.io/projects/defender/defender_logo_hu26b804ac788440967d2a46246ac6f3b2_10888_200x0_resize_q75_box.jpg alt="DEFENDER logo" class="float-md-start me-3 mb-2" height=77 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">Defending the European Energy Infrastructures is a research project funded by is a research project funded by the European Comission under the Horizon2020 programme (Call: CIP-2016-2017-1. Topic: CIP-01-2016-2017). Critical Energy infrastructures (CEI) protection and security are becoming of utmost importance in our everyday life. However, cyber and system-theoretic approaches fail to provide appropriate security levels to CEIs, since they are often used in isolation and build on incomplete attack models, resulting in silos-like security management fragmented operational policies. To face these challenges, DEFENDER will (i) model CEIs as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats. DEFENDER will adapt, integrate, upscale and validate a number of TRL 4-5 technologies and deploy them within a TRL7 integrated yet adaptable framework for CEI security, resilience and self-healing “by design”, with a view to address, detect, and mitigate cyber-physical threats.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/ebottle/ class="link-underline link-underline-opacity-0 text-reset">e.BOTTLE</a></h2><p>Jan 2019 &mdash; Dec 2020</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/ebottle/><img src=https://sensorlab.github.io/projects/ebottle/ebottle_hands_hu51cf68dbeb5d91d8d19fc35a3dd41874_56834_200x0_resize_box_3.png alt="e.BOTTLE logo" class="float-md-start me-3 mb-2" height=200 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">Vzpostavitev naprednih IKT storitev za analizo življenjskega cikla steklene embalaže – eBOTTLE. Naročnik projekta je RAZVOJNI CENTER eNeM Novi materiali, d.o.o. Sodelovanje se nanaša na izvajanje projekta pod naslovom »Pametno multikomponentno embalažno steklo» – projekt eBOTTLE, ki je bil s strani Ministrstva za gospodarski razvoj in tehnologijo potrjen za sofinanciranje v okviru Javnega razpisa. Odsek za komunikacijske sisteme sodeluje na operaciji kot zunanji izvajalec raziskovalno-razvojnih aktivnosti pri razvoju in vzpostavitvi naprednih IKT storitev za analizo življenjskega cikla steklene embalaže.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/nrg5/ class="link-underline link-underline-opacity-0 text-reset">NRG5</a></h2><p>Oct 2017 &mdash; Sep 2020</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/nrg5/><img src=https://sensorlab.github.io/projects/nrg5/nrg5_logo_huaf719050d4a1c895f16feccf86545e77_11494_200x0_resize_box_3.png alt="NRG5 logo" class="float-md-start me-3 mb-2" height=67 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The NRG-5 project envisages contributing to the 5G PPP/5G Initiative research and development activities and participation at the relevant 5G Working Groups by delivering a novel 5G-PPP compliant, decentralized, <strong>secure</strong> and <strong>resilient</strong> framework, with <strong>highly availability</strong> able to homogeneously model and virtualize multi-homed, static or moving, hardware constrained (smart energy) devices, edge computing resources and elastic virtualized services over electricity and gas infrastructure assets combined with the telecommunications infrastructure covering the full spectrum of the communication and computational needs.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/saam/ class="link-underline link-underline-opacity-0 text-reset">SAAM: Supporting Active Ageing Through Multimodal Coaching</a></h2><p>Oct 2017 &mdash; Sep 2020</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/saam/><img src=https://sensorlab.github.io/projects/saam/saam_logo_huf59b55f0e4da4e0937d7013a1cfe56fc_11002_200x0_resize_box_3.png alt="SAAM: Supporting Active Ageing Through Multimodal Coaching logo" class="float-md-start me-3 mb-2" height=120 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The project aims to develop and validate a Virtual Assistant-Coach that supports the process of healthy ageing by preserving physical, cognitive, mental, and social well-being of older citizens, and prolonging the period of life they can live safely at home. SAAM focuses on innovative, unobtrusive technology-enabled approaches, with a novel and practical emphasis on wearable and ambient sensing.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/euconnects3/ class="link-underline link-underline-opacity-0 text-reset">EuConNeCts3</a></h2><p>Jan 2017 &mdash; Dec 2019</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/euconnects3/><img src=https://sensorlab.github.io/projects/euconnects3/eucnc3-feat_hu5fed40845076b86654f89b56693c6c08_27547_200x0_resize_q75_box.jpg alt="EuConNeCts3 logo" class="float-md-start me-3 mb-2" height=89 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">It is the purpose of EuConNeCts3, a Supporting Action, to organise the following 2 editions, 2018 and 2019, of the EC sponsored conference in the area of communication networks and systems (EuCNC – European Conference on Networks and Communications), continuing the successful organisation of this conference since 2014. EuCNC will continue to serve as a technical and scientific conference for researchers, namely European ones, to show their work in the area of Telecommunications, focusing on communication networks and systems, and also reaching services and applications. The conference will not be restricted to European researchers, rather aiming at attracting others from all the other regions in the world. It will also serve as a showcase for the work developed by projects co-financed by the EC, namely those arising from H2020 calls, and more specifically, those addressing 5G and beyond. Nonetheless, it also aims at attracting works in the area of communication networks and systems from other objectives.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/ewine/ class="link-underline link-underline-opacity-0 text-reset">eWINE</a></h2><p>Jan 2016 &mdash; Dec 2018</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/ewine/><img src=https://sensorlab.github.io/projects/ewine/ewine_logo_hudefacb793eeaf6252de9f0155c78a163_11020_200x0_resize_box_3.png alt="eWINE logo" class="float-md-start me-3 mb-2" height=112 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The elastic Wireless Networking Experimentation (eWINE) is a research project funded by the European Comission under the Horizon2020 programme (Call: H2020-ICT-2015. Topic: ICT-12-2015). The main goal of eWINE is to realize elastic networks that can scale to a high number of users in a short timespan through the use of an agile infrastructure (intelligent software and flexible hardware), enabling: 1) dynamic on-demand end-to-end wireless connectivity service provisioning, 2) elastic resource sharing in dense heterogeneous and small cell networks (HetSNets), 3) intelligent and informed configuration of the physical layer.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/wishful/ class="link-underline link-underline-opacity-0 text-reset">WISHFUL</a></h2><p>Jan 2015 &mdash; Dec 2017</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/wishful/><img src=https://sensorlab.github.io/projects/wishful/wishful_logo_hube36c8ddf29d921cbc664145aa30b815_8680_200x0_resize_box_3.png alt="WISHFUL logo" class="float-md-start me-3 mb-2" height=61 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The WiSHFUL project (Wireless Software and Hardware platforms for Flexible and Unified radio and network controL) will reduce the threshold for experimentation in view of wireless innovation creation and by increasing the realism of experimentation. The WiSHFUL project is funded by the European Commission’s Horizon 2020 Programme under grant agreement n645274. The project started on January 1st 2015 and will last for 36 months.
 Our role: Open call extension of the WiSHFUL project with addition of LOG-a-TEC testbed 5G capillary capabilities and adaptation of WiSHFUL universal programming interfaces for the use in the LOG-a-TEC testbed.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/crew/ class="link-underline link-underline-opacity-0 text-reset">CREW</a></h2><p>Jan 2011 &mdash; Dec 2015</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/crew/><img src=https://sensorlab.github.io/projects/crew/crew_logo_hu2f1a37528addcd27a323fb770d0e94d5_14665_200x0_resize_box_3.png alt="CREW logo" class="float-md-start me-3 mb-2" height=186 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The main target of the Cognitive Radio Experimentation World – CREW project is to establish an open federated test platform, which facilitates experimentally-driven research on advanced spectrum sensing, cognitive radio and cognitive networking strategies in view of horizontal and vertical spectrum sharing in licensed and unlicensed bands.</p></div></section><section class=mt-5><header class=mb-2><h2><a href=https://sensorlab.github.io/projects/planetdata/ class="link-underline link-underline-opacity-0 text-reset">PlanetData</a></h2><p>Jan 2010 &mdash; Dec 2014</p></header><div class=clearfix><a href=https://sensorlab.github.io/projects/planetdata/><img src=https://sensorlab.github.io/projects/planetdata/PlanetData_logo_huab678480fd6b23bb877ba7ae82144d97_7626_200x0_resize_box_3.png alt="PlanetData logo" class="float-md-start me-3 mb-2" height=109 width=200 style=max-width:min(200px,100vw)></a><p class="mx-1 text-justify">The PlanetData project is built around three objectives that together ensure the creation of a durable community made up of academic and industrial partners. This community will be supported in conducting research in the large-scale data management area through the provision of data sets and access to tailored data management technology. From the research point of view, the focus is on large-scale data management. Sensorlab provides sensor data, raw and annotated and services based on these.</p></div></section></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
 <span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
diff --git a/projects/index.xml b/projects/index.xml
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-<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Projects on SensorLab — Jozef Stefan Institute</title><link>https://sensorlab.github.io/projects/</link><description>Recent content in Projects on SensorLab — Jozef Stefan Institute</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>SensorLab</copyright><atom:link href="https://sensorlab.github.io/projects/index.xml" rel="self" type="application/rss+xml"/><item><title>BD4OPEM</title><link>https://sensorlab.github.io/projects/bd4opem/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/bd4opem/</guid><description>Energy power systems face big challenges to cope with grid integration demands of an ever-increasing number of distributed generation and consumption devices in an interconnected world. Technology offers a huge range of opportunities to develop solutions in the uncertain current and upcoming Energy market situation. This proposal considers Open Innovation as a natural solution to create a seamless link and balance between energy stakeholders needs and the solutions to be developed.</description></item><item><title>CREW</title><link>https://sensorlab.github.io/projects/crew/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/crew/</guid><description>The main target of the Cognitive Radio Experimentation World – CREW project is to establish an open federated test platform, which facilitates experimentally-driven research on advanced spectrum sensing, cognitive radio and cognitive networking strategies in view of horizontal and vertical spectrum sharing in licensed and unlicensed bands.</description></item><item><title>DEFENDER</title><link>https://sensorlab.github.io/projects/defender/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/defender/</guid><description>Defending the European Energy Infrastructures is a research project funded by is a research project funded by the European Comission under the Horizon2020 programme (Call: CIP-2016-2017-1. Topic: CIP-01-2016-2017). Critical Energy infrastructures (CEI) protection and security are becoming of utmost importance in our everyday life. However, cyber and system-theoretic approaches fail to provide appropriate security levels to CEIs, since they are often used in isolation and build on incomplete attack models, resulting in silos-like security management fragmented operational policies. To face these challenges, DEFENDER will (i) model CEIs as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats. DEFENDER will adapt, integrate, upscale and validate a number of TRL 4-5 technologies and deploy them within a TRL7 integrated yet adaptable framework for CEI security, resilience and self-healing “by design”, with a view to address, detect, and mitigate cyber-physical threats.</description></item><item><title>e.BOTTLE</title><link>https://sensorlab.github.io/projects/ebottle/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ebottle/</guid><description>Vzpostavitev naprednih IKT storitev za analizo življenjskega cikla steklene embalaže – eBOTTLE. Naročnik projekta je RAZVOJNI CENTER eNeM Novi materiali, d.o.o. Sodelovanje se nanaša na izvajanje projekta pod naslovom »Pametno multikomponentno embalažno steklo» – projekt eBOTTLE, ki je bil s strani Ministrstva za gospodarski razvoj in tehnologijo potrjen za sofinanciranje v okviru Javnega razpisa. Odsek za komunikacijske sisteme sodeluje na operaciji kot zunanji izvajalec raziskovalno-razvojnih aktivnosti pri razvoju in vzpostavitvi naprednih IKT storitev za analizo življenjskega cikla steklene embalaže.</description></item><item><title>EuConNeCts3</title><link>https://sensorlab.github.io/projects/euconnects3/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/euconnects3/</guid><description>It is the purpose of EuConNeCts3, a Supporting Action, to organise the following 2 editions, 2018 and 2019, of the EC sponsored conference in the area of communication networks and systems (EuCNC – European Conference on Networks and Communications), continuing the successful organisation of this conference since 2014. EuCNC will continue to serve as a technical and scientific conference for researchers, namely European ones, to show their work in the area of Telecommunications, focusing on communication networks and systems, and also reaching services and applications. The conference will not be restricted to European researchers, rather aiming at attracting others from all the other regions in the world. It will also serve as a showcase for the work developed by projects co-financed by the EC, namely those arising from H2020 calls, and more specifically, those addressing 5G and beyond. Nonetheless, it also aims at attracting works in the area of communication networks and systems from other objectives.</description></item><item><title>eWINE</title><link>https://sensorlab.github.io/projects/ewine/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ewine/</guid><description>The elastic Wireless Networking Experimentation (eWINE) is a research project funded by the European Comission under the Horizon2020 programme (Call: H2020-ICT-2015. Topic: ICT-12-2015). The main goal of eWINE is to realize elastic networks that can scale to a high number of users in a short timespan through the use of an agile infrastructure (intelligent software and flexible hardware), enabling: 1) dynamic on-demand end-to-end wireless connectivity service provisioning, 2) elastic resource sharing in dense heterogeneous and small cell networks (HetSNets), 3) intelligent and informed configuration of the physical layer.</description></item><item><title>FED4FIRE+</title><link>https://sensorlab.github.io/projects/fed4fire/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/fed4fire/</guid><description>Fed4FIRE+ is an Integrating Project under the European Union’s Programme Horizon 2020, addressing the work programme topic Future Internet Research and Experimentation. It started in January 2017 and will run for 60 months, until the end of September 2021. The Fed4FIRE+ project is the successor of the Fed4FIRE project.</description></item><item><title>NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution</title><link>https://sensorlab.github.io/projects/nancy/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/nancy/</guid><description>The overall aim of NANCY is to introduce a secure and intelligent architecture for the beyond the fifth generation (B5G) wireless network. Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation will be designed.
+<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Projects on SensorLab — Jozef Stefan Institute</title><link>https://sensorlab.github.io/projects/</link><description>Recent content in Projects on SensorLab — Jozef Stefan Institute</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>SensorLab</copyright><atom:link href="https://sensorlab.github.io/projects/index.xml" rel="self" type="application/rss+xml"/><item><title>BD4OPEM</title><link>https://sensorlab.github.io/projects/bd4opem/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/bd4opem/</guid><description>Energy power systems face big challenges to cope with grid integration demands of an ever-increasing number of distributed generation and consumption devices in an interconnected world. Technology offers a huge range of opportunities to develop solutions in the uncertain current and upcoming Energy market situation. This proposal considers Open Innovation as a natural solution to create a seamless link and balance between energy stakeholders needs and the solutions to be developed.</description></item><item><title>CREW</title><link>https://sensorlab.github.io/projects/crew/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/crew/</guid><description>The main target of the Cognitive Radio Experimentation World – CREW project is to establish an open federated test platform, which facilitates experimentally-driven research on advanced spectrum sensing, cognitive radio and cognitive networking strategies in view of horizontal and vertical spectrum sharing in licensed and unlicensed bands.</description></item><item><title>DEFENDER</title><link>https://sensorlab.github.io/projects/defender/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/defender/</guid><description>Defending the European Energy Infrastructures is a research project funded by is a research project funded by the European Comission under the Horizon2020 programme (Call: CIP-2016-2017-1. Topic: CIP-01-2016-2017). Critical Energy infrastructures (CEI) protection and security are becoming of utmost importance in our everyday life. However, cyber and system-theoretic approaches fail to provide appropriate security levels to CEIs, since they are often used in isolation and build on incomplete attack models, resulting in silos-like security management fragmented operational policies. To face these challenges, DEFENDER will (i) model CEIs as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats. DEFENDER will adapt, integrate, upscale and validate a number of TRL 4-5 technologies and deploy them within a TRL7 integrated yet adaptable framework for CEI security, resilience and self-healing “by design”, with a view to address, detect, and mitigate cyber-physical threats.</description></item><item><title>e.BOTTLE</title><link>https://sensorlab.github.io/projects/ebottle/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ebottle/</guid><description>Vzpostavitev naprednih IKT storitev za analizo življenjskega cikla steklene embalaže – eBOTTLE. Naročnik projekta je RAZVOJNI CENTER eNeM Novi materiali, d.o.o. Sodelovanje se nanaša na izvajanje projekta pod naslovom »Pametno multikomponentno embalažno steklo» – projekt eBOTTLE, ki je bil s strani Ministrstva za gospodarski razvoj in tehnologijo potrjen za sofinanciranje v okviru Javnega razpisa. Odsek za komunikacijske sisteme sodeluje na operaciji kot zunanji izvajalec raziskovalno-razvojnih aktivnosti pri razvoju in vzpostavitvi naprednih IKT storitev za analizo življenjskega cikla steklene embalaže.</description></item><item><title>EuConNeCts3</title><link>https://sensorlab.github.io/projects/euconnects3/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/euconnects3/</guid><description>It is the purpose of EuConNeCts3, a Supporting Action, to organise the following 2 editions, 2018 and 2019, of the EC sponsored conference in the area of communication networks and systems (EuCNC – European Conference on Networks and Communications), continuing the successful organisation of this conference since 2014. EuCNC will continue to serve as a technical and scientific conference for researchers, namely European ones, to show their work in the area of Telecommunications, focusing on communication networks and systems, and also reaching services and applications. The conference will not be restricted to European researchers, rather aiming at attracting others from all the other regions in the world. It will also serve as a showcase for the work developed by projects co-financed by the EC, namely those arising from H2020 calls, and more specifically, those addressing 5G and beyond. Nonetheless, it also aims at attracting works in the area of communication networks and systems from other objectives.</description></item><item><title>eWINE</title><link>https://sensorlab.github.io/projects/ewine/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/ewine/</guid><description>The elastic Wireless Networking Experimentation (eWINE) is a research project funded by the European Comission under the Horizon2020 programme (Call: H2020-ICT-2015. Topic: ICT-12-2015). The main goal of eWINE is to realize elastic networks that can scale to a high number of users in a short timespan through the use of an agile infrastructure (intelligent software and flexible hardware), enabling: 1) dynamic on-demand end-to-end wireless connectivity service provisioning, 2) elastic resource sharing in dense heterogeneous and small cell networks (HetSNets), 3) intelligent and informed configuration of the physical layer.</description></item><item><title>FED4FIRE+</title><link>https://sensorlab.github.io/projects/fed4fire/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/fed4fire/</guid><description>Fed4FIRE+ is an Integrating Project under the European Union’s Programme Horizon 2020, addressing the work programme topic Future Internet Research and Experimentation. It started in January 2017 and will run for 60 months, until the end of September 2021. The Fed4FIRE+ project is the successor of the Fed4FIRE project.</description></item><item><title>MISA: Multi-lidar Intelligence for Smart City Applications</title><link>https://sensorlab.github.io/projects/misa/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/misa/</guid><description>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</description></item><item><title>NANCY: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution</title><link>https://sensorlab.github.io/projects/nancy/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/nancy/</guid><description>The overall aim of NANCY is to introduce a secure and intelligent architecture for the beyond the fifth generation (B5G) wireless network. Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation will be designed.
 These architectures and protocols will make the most by jointly optimizing the midhaul, and fronthaul. This is expected to enable truly distributed intelligence and transform the network to a low-power computer. Likewise, by following a holistic optimization approach and leveraging the developments in blockchain, NANCY aims at supporting E2E personalized, multi-tenant and perpetual protection.</description></item><item><title>NRG5</title><link>https://sensorlab.github.io/projects/nrg5/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/nrg5/</guid><description>The NRG-5 project envisages contributing to the 5G PPP/5G Initiative research and development activities and participation at the relevant 5G Working Groups by delivering a novel 5G-PPP compliant, decentralized, &lt;strong>secure&lt;/strong> and &lt;strong>resilient&lt;/strong> framework, with &lt;strong>highly availability&lt;/strong> able to homogeneously model and virtualize multi-homed, static or moving, hardware constrained (smart energy) devices, edge computing resources and elastic virtualized services over electricity and gas infrastructure assets combined with the telecommunications infrastructure covering the full spectrum of the communication and computational needs.</description></item><item><title>PlanetData</title><link>https://sensorlab.github.io/projects/planetdata/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/planetdata/</guid><description>The PlanetData project is built around three objectives that together ensure the creation of a durable community made up of academic and industrial partners. This community will be supported in conducting research in the large-scale data management area through the provision of data sets and access to tailored data management technology. From the research point of view, the focus is on large-scale data management. Sensorlab provides sensor data, raw and annotated and services based on these.</description></item><item><title>RESILOC</title><link>https://sensorlab.github.io/projects/resiloc/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/resiloc/</guid><description>Resilience is defined by the United Nations as “the ability to resist, absorb and accommodate to the effects of a hazard, in a timely and efficient manner”. Thus, resilient communities are those in which their citizens, environment, businesses, and infrastructures have the capacity to withstand, adapt, and recover in a timely manner from any kind of hazards they face, either planned or unplanned. In recent years efforts have been spent to tackle resilience and there is, still, a long path forward in defining an EU valid and sound approach to the problem. RESILOC aims at studying and implementing a holistic framework of studies, methods and software instruments that combines the physical with the less tangible aspects associated with human behaviour. The study-oriented section of the framework will move from a thorough collection and analysis of literature and stories from the many approaches to resilience adopted all over the World. The results of the studies will lead to the definition of a set of new methods and strategies where the assessment of the resilience indicators of a community will be performed together with simulations on the “what-if” certain measures are taken.</description></item><item><title>SAAM: Supporting Active Ageing Through Multimodal Coaching</title><link>https://sensorlab.github.io/projects/saam/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/saam/</guid><description>The project aims to develop and validate a Virtual Assistant-Coach that supports the process of healthy ageing by preserving physical, cognitive, mental, and social well-being of older citizens, and prolonging the period of life they can live safely at home. SAAM focuses on innovative, unobtrusive technology-enabled approaches, with a novel and practical emphasis on wearable and ambient sensing.</description></item><item><title>SiQUID: Slovenian Quantum Communication Infrastructure Demonstration</title><link>https://sensorlab.github.io/projects/siquid/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/siquid/</guid><description>The European Union is currently preparing to implement the infrastructure for a Europe-wide network for quantum communication. Research groups, industrial partners, and government representatives from all European member states have devised projects to perform proof-of-principle demonstrations of quantum communication and quantum key distribution (QKD). To this end, quantum communication infrastructure will be implemented on the national level in all EU member states to facilitate the international connection of those networks later. The Slovenian Quantum Communication Infrastructure Demonstration (SiQUID) project will be the first to implement quantum key distribution (QKD) in Slovenia. The project will establish quantum communication links between multiple government nodes in Slovenia and a test-bed quantum network between research institutions in Ljubljana for the research and development of advanced quantum communication protocols.</description></item><item><title>TimeSmart: Timeliness of Information in Smart Grids Networks</title><link>https://sensorlab.github.io/projects/timesmart/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/timesmart/</guid><description>TimeSmart project will investigate the applicability of the novel Age of Information metric in smart grid networks. While the metric has become a valuable tool for measuring the system&amp;rsquo;s performance, its practical value and impact in the real-time system are left unanswered. This project seeks to remedy that by applying the metric to a system in which the timing of collected data, currently measured through jitter or latency, profoundly impacts management and control. The AoI offers a new perspective on how the system should collect and process information, as such decisions are also based on the context of processed information(their semantic nature). In turn, the new approach can offer an innovative way of improving the efficiency of renewable electrical energy supply and electrical loads by taking advantage of the available edge infrastructure. This project aims to adopt the AoI metric in smart grid networks to improve the energy transmission efficiency, achievable through more timely collected information, to save energy.</description></item><item><title>TIMIN6: Timely and Sustainable Information Management in 6G Networks</title><link>https://sensorlab.github.io/projects/timin6/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/timin6/</guid><description>The main goal of the TIMIN6 project is to design a new data collection method based on the Age of Information (AoI) metric in connection with aspects of sustainable resource management. AoI is a relatively new and not yet fully understood metric in the field of information science. Considering the AoI can significantly impact energy consumption in data collection, but many aspects and the actual applicability of the metric still need to be explored. While most research in this area focuses on finding more efficient ways to extract information from already collected data, the TIMIN6 project will focus on the question of how frequently devices should collect and transmit data to operate in a more sustainable manner. The goal of this approach is to reduce unnecessarily wasted energy in the billions of devices that will make up 6G networks, enabling a more sustainable future. The project is funded by Slovenian Research and Innovation Agency (ARIS).</description></item><item><title>WISHFUL</title><link>https://sensorlab.github.io/projects/wishful/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/wishful/</guid><description>The WiSHFUL project (Wireless Software and Hardware platforms for Flexible and Unified radio and network controL) will reduce the threshold for experimentation in view of wireless innovation creation and by increasing the realism of experimentation. The WiSHFUL project is funded by the European Commission’s Horizon 2020 Programme under grant agreement n645274. The project started on January 1st 2015 and will last for 36 months.
 Our role: Open call extension of the WiSHFUL project with addition of LOG-a-TEC testbed 5G capillary capabilities and adaptation of WiSHFUL universal programming interfaces for the use in the LOG-a-TEC testbed.</description></item></channel></rss>
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=keywords content="bilateral,graph neural networks,LiDAR,reinforcement learning,Japan,Slovenia,Shinkuma,sensor fusion"><meta name=description content="The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks."><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/projects/misa/><link rel=alternate hreflang=en href=https://sensorlab.github.io/projects/misa/><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="MISA: Multi-lidar Intelligence for Smart City Applications"><meta property="og:description" content="The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks."><meta property="og:type" content="article"><meta property="og:url" content="https://sensorlab.github.io/projects/misa/"><meta property="article:section" content="projects"><meta name=twitter:card content="summary"><meta name=twitter:title content="MISA: Multi-lidar Intelligence for Smart City Applications"><meta name=twitter:description content="The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks."><title>MISA: Multi-lidar Intelligence for Smart City Applications &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class="nav-link active" href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container post my-4" aria-role=main><aside class=my-4></aside><article class=mt-4><header class=mb-4><div><img src=https://sensorlab.github.io/projects/misa/aris_logo_hub08622e5c39b8cb3af485e5245357ede_10856_200x0_resize_q75_box.jpg alt="MISA: Multi-lidar Intelligence for Smart City Applications logo" class="me-3 mb-2" height=200 width=200 style=max-width:min(200px,100vw)></div><div><h1>MISA: Multi-lidar Intelligence for Smart City Applications</h1><p><span>Duration: Apr 2024 &mdash; Apr 2026</span></p></div></header><section class=my-4><p>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><h2 id=funding>Funding</h2><p>Τhe MISA bilateral project receives funding from the Slovenian Research and Inovation Agency (ARIS) under Grant Agreement No. BI-JP/24-26-001.</p></section></article></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/bilateral/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/bilateral/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/bilateral/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="bilateral"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/bilateral/"><meta name=twitter:card content="summary"><meta name=twitter:title content="bilateral"><meta name=twitter:description content><title>bilateral &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>bilateral</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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+<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>bilateral on SensorLab — Jozef Stefan Institute</title><link>https://sensorlab.github.io/tags/bilateral/</link><description>Recent content in bilateral on SensorLab — Jozef Stefan Institute</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>SensorLab</copyright><atom:link href="https://sensorlab.github.io/tags/bilateral/index.xml" rel="self" type="application/rss+xml"/><item><title>MISA: Multi-lidar Intelligence for Smart City Applications</title><link>https://sensorlab.github.io/projects/misa/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sensorlab.github.io/projects/misa/</guid><description>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</description></item></channel></rss>
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+<!doctype html><html lang=en><head><title>https://sensorlab.github.io/tags/bilateral/</title><link rel=canonical href=https://sensorlab.github.io/tags/bilateral/><meta name=robots content="noindex"><meta charset=utf-8><meta http-equiv=refresh content="0; url=https://sensorlab.github.io/tags/bilateral/"></head></html>
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/graph-neural-networks/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/graph-neural-networks/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/graph-neural-networks/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="graph neural networks"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/graph-neural-networks/"><meta name=twitter:card content="summary"><meta name=twitter:title content="graph neural networks"><meta name=twitter:description content><title>graph neural networks &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>graph neural networks</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
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 <span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
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diff --git a/tags/index.xml b/tags/index.xml
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/japan/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/japan/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/japan/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Japan"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/japan/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Japan"><meta name=twitter:description content><title>Japan &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>Japan</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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diff --git a/tags/japan/index.xml b/tags/japan/index.xml
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/lidar/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/lidar/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/lidar/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="LiDAR"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/lidar/"><meta name=twitter:card content="summary"><meta name=twitter:title content="LiDAR"><meta name=twitter:description content><title>LiDAR &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>LiDAR</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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 <!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/><link rel=alternate hreflang=sl href=https://sensorlab.github.io/sl/tags/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Tags"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Tags"><meta name=twitter:description content><title>Tags &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
 <button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
-<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4><h4>Translations:</h4><ul><li><a href=https://sensorlab.github.io/sl/tags/>(SL) Tags</a></li></ul></aside><article><header><h1>Tags</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/tags/entanglement/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>entanglement</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4><h4>Translations:</h4><ul><li><a href=https://sensorlab.github.io/sl/tags/>(SL) Tags</a></li></ul></aside><article><header><h1>Tags</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/tags/energy/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>energy</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/entanglement/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>entanglement</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
 <a href=https://sensorlab.github.io/tags/euroqci/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>EuroQCI</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
 <a href=https://sensorlab.github.io/tags/glassware/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>glassware</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/graph-neural-networks/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>graph neural networks</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
 <a href=https://sensorlab.github.io/tags/health-monitoring/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>health monitoring</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
 <a href=https://sensorlab.github.io/tags/horizon2020/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>horizon2020</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/msca-action/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MSCA Action</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/network/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>network</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/qkd/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>QKD</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/quantum/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>quantum</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/radio/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>radio</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"><ul class="pagination pagination-default"><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=First class=page-link role=button><span aria-hidden=true>&#171;&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=Previous class=page-link role=button><span aria-hidden=true>&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label="Page 1" class=page-link role=button>1</a></li><li class="page-item active"><a aria-current=page aria-label="Page 2" class=page-link role=button>2</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label="Page 3" class=page-link role=button>3</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label=Next class=page-link role=button><span aria-hidden=true>&#187;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label=Last class=page-link role=button><span aria-hidden=true>&#187;&#187;</span></a></li></ul></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<a href=https://sensorlab.github.io/tags/japan/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>Japan</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/lidar/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>LiDAR</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/msca-action/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MSCA Action</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"><ul class="pagination pagination-default"><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=First class=page-link role=button><span aria-hidden=true>&#171;&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=Previous class=page-link role=button><span aria-hidden=true>&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label="Page 1" class=page-link role=button>1</a></li><li class="page-item active"><a aria-current=page aria-label="Page 2" class=page-link role=button>2</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label="Page 3" class=page-link role=button>3</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/4/ aria-label="Page 4" class=page-link role=button>4</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label=Next class=page-link role=button><span aria-hidden=true>&#187;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/4/ aria-label=Last class=page-link role=button><span aria-hidden=true>&#187;&#187;</span></a></li></ul></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
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 <!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/><link rel=alternate hreflang=sl href=https://sensorlab.github.io/sl/tags/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Tags"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Tags"><meta name=twitter:description content><title>Tags &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
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-<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4><h4>Translations:</h4><ul><li><a href=https://sensorlab.github.io/sl/tags/>(SL) Tags</a></li></ul></aside><article><header><h1>Tags</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/tags/sensor-data/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>sensor data</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/spectrum/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>spectrum</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/testbed/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>testbed</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
-<a href=https://sensorlab.github.io/tags/wireless-networks/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>wireless networks</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"><ul class="pagination pagination-default"><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=First class=page-link role=button><span aria-hidden=true>&#171;&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/2/ aria-label=Previous class=page-link role=button><span aria-hidden=true>&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label="Page 1" class=page-link role=button>1</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/2/ aria-label="Page 2" class=page-link role=button>2</a></li><li class="page-item active"><a aria-current=page aria-label="Page 3" class=page-link role=button>3</a></li><li class="page-item disabled"><a aria-disabled=true aria-label=Next class=page-link role=button tabindex=-1><span aria-hidden=true>&#187;</span></a></li><li class="page-item disabled"><a aria-disabled=true aria-label=Last class=page-link role=button tabindex=-1><span aria-hidden=true>&#187;&#187;</span></a></li></ul></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4><h4>Translations:</h4><ul><li><a href=https://sensorlab.github.io/sl/tags/>(SL) Tags</a></li></ul></aside><article><header><h1>Tags</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/tags/network/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>network</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/qkd/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>QKD</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/quantum/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>quantum</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/radio/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>radio</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/reinforcement-learning/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>reinforcement learning</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/sensor-data/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>sensor data</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/sensor-fusion/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>sensor fusion</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/shinkuma/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>Shinkuma</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/slovenia/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>Slovenia</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/spectrum/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>spectrum</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"><ul class="pagination pagination-default"><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=First class=page-link role=button><span aria-hidden=true>&#171;&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/2/ aria-label=Previous class=page-link role=button><span aria-hidden=true>&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label="Page 1" class=page-link role=button>1</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/2/ aria-label="Page 2" class=page-link role=button>2</a></li><li class="page-item active"><a aria-current=page aria-label="Page 3" class=page-link role=button>3</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/4/ aria-label="Page 4" class=page-link role=button>4</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/4/ aria-label=Next class=page-link role=button><span aria-hidden=true>&#187;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/4/ aria-label=Last class=page-link role=button><span aria-hidden=true>&#187;&#187;</span></a></li></ul></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
 <span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
 <script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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diff --git a/tags/page/4/index.html b/tags/page/4/index.html
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/><link rel=alternate hreflang=sl href=https://sensorlab.github.io/sl/tags/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Tags"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Tags"><meta name=twitter:description content><title>Tags &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4><h4>Translations:</h4><ul><li><a href=https://sensorlab.github.io/sl/tags/>(SL) Tags</a></li></ul></aside><article><header><h1>Tags</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/tags/testbed/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>testbed</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a>
+<a href=https://sensorlab.github.io/tags/wireless-networks/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>wireless networks</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1></p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"><ul class="pagination pagination-default"><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label=First class=page-link role=button><span aria-hidden=true>&#171;&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label=Previous class=page-link role=button><span aria-hidden=true>&#171;</span></a></li><li class=page-item><a href=https://sensorlab.github.io/tags/ aria-label="Page 1" class=page-link role=button>1</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/2/ aria-label="Page 2" class=page-link role=button>2</a></li><li class=page-item><a href=https://sensorlab.github.io/tags/page/3/ aria-label="Page 3" class=page-link role=button>3</a></li><li class="page-item active"><a aria-current=page aria-label="Page 4" class=page-link role=button>4</a></li><li class="page-item disabled"><a aria-disabled=true aria-label=Next class=page-link role=button tabindex=-1><span aria-hidden=true>&#187;</span></a></li><li class="page-item disabled"><a aria-disabled=true aria-label=Last class=page-link role=button tabindex=-1><span aria-hidden=true>&#187;&#187;</span></a></li></ul></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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diff --git a/tags/reinforcement-learning/index.html b/tags/reinforcement-learning/index.html
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/reinforcement-learning/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/reinforcement-learning/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/reinforcement-learning/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="reinforcement learning"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/reinforcement-learning/"><meta name=twitter:card content="summary"><meta name=twitter:title content="reinforcement learning"><meta name=twitter:description content><title>reinforcement learning &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>reinforcement learning</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/sensor-fusion/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/sensor-fusion/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/sensor-fusion/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="sensor fusion"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/sensor-fusion/"><meta name=twitter:card content="summary"><meta name=twitter:title content="sensor fusion"><meta name=twitter:description content><title>sensor fusion &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>sensor fusion</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/shinkuma/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/shinkuma/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/shinkuma/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Shinkuma"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/shinkuma/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Shinkuma"><meta name=twitter:description content><title>Shinkuma &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>Shinkuma</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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+<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.6aded9aabec22e872a6f2b12c8ad60b2a6c803fd8401499d4c134899fade4af6.css" integrity="sha256-at7Zqr7CLocqbysSyK1gsqbIA/2EAUmdTBNImfreSvY=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.93058f41bd1dbb13445944582228d7c47003915c378d0ffa6daef4f14b5e04d7.js integrity="sha256-kwWPQb0duxNEWURYIijXxHADkVw3jQ/6ba708UteBNc="></script><meta name=generator content="Hugo 0.117.0"><meta name=author content="SensorLab"><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/tags/slovenia/><link rel=alternate hreflang=en href=https://sensorlab.github.io/tags/slovenia/><link rel=alternate type=application/rss+xml href=https://sensorlab.github.io/tags/slovenia/index.xml title="SensorLab — Jozef Stefan Institute"><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:title" content="Slovenia"><meta property="og:description" content><meta property="og:type" content="website"><meta property="og:url" content="https://sensorlab.github.io/tags/slovenia/"><meta name=twitter:card content="summary"><meta name=twitter:title content="Slovenia"><meta name=twitter:description content><title>Slovenia &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42></a>
+<button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
+<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container" aria-role=main><aside class=mt-4></aside><article><header><h1>Slovenia</h1></header><section></section><section class="list-group my-5"><a href=https://sensorlab.github.io/projects/misa/ class="list-group-item list-group-item-action flex-column align-items-start"><header class="d-flex w-100 justify-content-between"><h5 class=mb-1>MISA: Multi-lidar Intelligence for Smart City Applications</h5><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></header><p class=mb-1>The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.</p><small><time datetime=0001-01-01T00:00:00Z>Monday, January 1, 1</time></small></a></section></article><nav class="d-flex d-content justify-content-center"></nav></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem></a>
+<span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2024 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>
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