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Developed a comprehensive system integrating Dijkstra’s and A* algorithms to optimize metro navigation and constraint programming for scheduling. Proposed a model that minimizes travel time and enhances commuter satisfaction by providing the shortest paths, efficient transitions, and adaptive scheduling.
NeuroFleetX is an AI-powered, full-stack urban mobility platform that enables intelligent fleet management, route optimization, vehicle health monitoring, and role-based operational control through data-driven insights.
Bus NavX is a Flutter-based mobile application designed for students and commuters to track buses in real time, navigate routes, and manage attendance through QR code scanning. It integrates Firebase for authentication, data storage, and notifications, offering a seamless and interactive user experience.
This project develops predictive collision avoidance systems using ML and V2V/V2I communication. Featuring SUMO-based simulations, it enhances road safety, reduces congestion, and optimizes traffic flow for autonomous and traditional vehicles