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Vahan Samvedak: a comprehensive real-time college bus tracking and safety system
Yash Chauhan1, Sujal Dhiman1, Shubham Negi1
1Department of Computer Science and Engineering, Graphic Era Deemed to Be University, Dehradun, 248002, India.
Scientific Reports
|April 16, 2026
Summary
Vahan Samvedak enhances campus transportation safety and efficiency using IoT and AI. This real-time vehicle tracking system improves security and reduces student wait times significantly.
Area of Science:
- Computer Science
- Artificial Intelligence
- Internet of Things
Background:
- Real-time tracking technologies are transforming transportation.
- Existing systems often lack advanced safety and efficiency features.
- College campus transportation presents unique challenges for tracking and safety.
Purpose of the Study:
- To introduce Vahan Samvedak, an advanced real-time vehicle tracking and safety system.
- To enhance safety and operational efficiency in college campus transportation.
- To integrate IoT and multi-modal AI for improved vehicle monitoring.
Main Methods:
- Developed a system combining IoT and multi-modal AI, focusing on GPS tracking, emergency notifications, and passenger counting.
- Integrated AI features including facial recognition and drowsiness detection using OpenCV, TensorFlow, and PyTorch.
- Utilized GPS for accurate location data and real-time alert systems.
Main Results:
- Achieved GPS accuracy within 2.5 meters and alert delivery in under two seconds.
- Demonstrated high accuracy rates for authentication (95%) and drowsiness detection (97.81%).
- Reported 99.2% system uptime and a 68% reduction in student wait times with five campus buses.
Conclusions:
- Vahan Samvedak offers a reliable and safe solution for smart campus transportation.
- The system significantly improves user experience and operational efficiency.
- It presents a viable alternative to traditional vehicle tracking systems for public transport.
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