CARTRAC: A LIGHTWEIGHT IOT-BASED SYSTEM FOR POST-CRASH ACCOUNTABILITY IN HIT-AND-RUN INCIDENTS

“Internet of Things (IoT)-Based Intelligent Transportation Systems, with a focus on real-time accident detection, hit-and-run accountability, V2X communication, and smart traffic management.”

Road accidents and hit-and-run incidents are major challenges in transportation safety, often resulting in delayed emergency responses and difficulties in identifying the vehicles involved. The proposed project, **CarTrac**, is a lightweight Internet of Things (IoT)-based system designed to improve road safety through automatic accident detection, vehicle identification, and wireless alert transmission. The hardware prototype uses an ESP32 microcontroller integrated with an ADXL345 accelerometer to detect sudden impacts and an ultrasonic sensor to monitor nearby obstacles. When an impact is detected, the system records the vehicle identification details, event type, and timestamp, displays the information on an LCD, and transmits the alert wirelessly to a receiver unit for monitoring. In addition, CarTrac incorporates a web-based traffic simulation platform developed using Python and the Flask framework. The platform demonstrates Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Pedestrian (V2P), and Vehicle-to-Everything (V2X) communication. It includes adaptive traffic signal control, emergency vehicle prioritization, pedestrian safety management, collision warnings, and real-time traffic monitoring. By combining low-cost hardware with open-source software, the system provides a scalable approach to accident reporting and intelligent traffic management. Future enhancements include GPS-based location tracking, camera-based number plate recognition, integration of the hardware with the web dashboard, and quantitative testing of detection speed and communication reliability.

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