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smart-mobility

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SynapticGrid is an AI-driven system designed to make cities more efficient, sustainable, and livable by optimizing smart energy grids, waste management, and traffic flow through IoT sensors, real-time data processing, and reinforcement learning algorithms. The modular platform continuously learns and improves, helping urban environments

  • Updated Apr 3, 2025
  • Python

An AI-driven Smart Mobility solution for India, providing EV trip planning, on-route charging stops, and CO2 emission savings calculations.

  • Updated Jul 29, 2025
  • Jupyter Notebook

DeepTrafficQ is a reinforcement learning-based traffic signal control system that uses Deep Q-Networks (DQN) to minimize vehicle waiting times at a 4-way intersection. By leveraging Q-learning with experience replay and a convolutional neural network (CNN), the agent dynamically adjusts traffic light phases to optimize traffic flow.

  • Updated Jun 29, 2025
  • C

I'm an urban technologist and planner, trained at the **Massachusetts Institute of Technology (MIT)** with a focus on sustainable mobility and city innovation. My work blends engineering, design, data, and policy to create impactful urban solutions.

  • Updated Aug 20, 2025
  • HTML

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