Ask IoT v1.0

A Python-based command-line tool that leverages a custom implementation of the TF-IDF algorithm to provide interactive and concise three-point answers to IoT-related queries, making it a valuable resource for researchers and IoT enthusiasts.

I. Features

1. TF-IDF-based Querying: "ask_iot" uses the TF-IDF algorithm to process and analyze IoT-related data, allowing users to obtain relevant information based on their queries.

2. Command-Line Interface: The tool runs in a command-line interface (CLI), providing a straightforward and efficient way for users to interact with it.

3. Looped Prompting: "ask_iot" operates in a loop, continuously prompting users for queries and providing concise three-point answers, ensuring a smooth and interactive user experience.

4. Exit Command: To terminate the tool, users can simply enter the command "exit", allowing for easy and controlled termination of the program.

5. Open-Source and FOSS: "ask_iot" is released as free and open-source software (FOSS), enabling others to view, use, modify, and contribute to the tool's development.

II. Usage

1. Install the code from this repository.

2. Make sure python is installed on your system. Then install the dependencies by running:

   python -m pip install nltk

3. Then run the program using:

   python3 ask.py IoT_machine_learning_data

   Can ask IoT/Machine Learning related questions.

   Example usage

   Ask>>> What is the role of IoT and Machine Learning?

   Best Match Answers:

   1. The role of machine learning in IoT: Machine learning algorithms can enhance the capabilities of IoT devices by enabling them to process and analyze data in real-time, and take actions based on the insights they have gained.
   2. The role of IoT in machine learning: The IoT network generates a massive amount of data that can be leveraged to train machine learning algorithms and improve their accuracy.
   3. Introduction to IoT machine learning: The introduction to IoT machine learning involves understanding the integration of two cutting-edge technologies: the Internet of Things and machine learning.

III. Research Work

Contents

1. Introduction to Machine Learning
2. Machine Learning and IoT
3. Natural Language Processing with IoT

• Detailed Notes.
• Abstract Presentation.

Acknowledgments

This research work was carried out under the guidance of Pankaj Durole Sir, Assistant Professor in the Department of Computer Science and Engineering at Deogiri Institute of Engineering and Management Studies. The presentation and scripting were done or contributed by Untwale Waseb Ikramoddin, Kazi Mohammed Muneebuddin, and Syed Minnatullah Quadri.