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@article{188592,
        author = {Aryan N Wagh and Yash A. Baheti and Krishna Y. Bambale and Adarsh S. Arle and Ganesh Shelke and Vikas J. Nandeshwar},
        title = {IOT-Enabled Black Box System for Two-Wheelers with Real-Time Accident Detection and Emergency Alerting},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {2047-2050},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188592},
        abstract = {The aim of this this paper is to introduce Black Box System for Two-Wheeled Vehicles that seeks to maximize road safety by identifying crash mechanisms, providing real time alerts, and storing important information that can be used for post- accident analysis. The system is built using minimum circuitry which makes it very inexpensive and easy to use. It tracks and records the movement of the vehicle at regular intervals. It also has cameras that take images during the accident. When a crash occurs, it sends an alert and makes an emergency call with the coordinates of the crash. Helps. Reading and photographs from the crash are saved on the SD card for further investigation. Moreover, alcohol detection functionality prevents vehicle operation under the condition of alcohol intoxication. Accident detection, GPS, and emergency image capture were all reliably verified during prototype testing. There is great potential for adding cloud storage in the future and using remote monitoring, machine learning for accidents prediction and prevention.},
        keywords = {Black Box System, Accident Detection, Real-Time Alert, GPS Tracking, Two-Wheeler safety, Road safety},
        month = {December},
        }