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Automatic Black Box System for Accident Analysis Using IoT: A Review

Abdul Mateen, Shaik Mohammed Ainullah, Rabbani Jamadar, Mohammad Ziaullah, Uzma I Satteekar

Abstract


This research introduces an innovative approach to enhance vehicle safety through the implementation of an Internet of Things (IoT)enabled Automobile Black Box System. The proposed system aims to revolutionize accident analysis by seamlessly integrating advanced sensor technologies and real-time data communication. Utilizing a network of sensors within the vehicle, including accelerometers, gyroscopes, and GPS modules, the system captures crucial information surrounding an accident event. The collected data, comprising vehicle speed, direction, impact forces, and GPS coordinates, is transmitted in real-time to a centralized server for comprehensive analysis. Leveraging machine learning algorithms, the system can accurately reconstruct accident scenarios, providing valuable insights into the sequence of events leading to the collision. This data-driven approach not only aids in post-accident investigations but also facilitates the development of proactive safety measures to prevent future incidents.Furthermore, the IoT connectivity allows for immediate notifications to emergency services, streamlining response times and potentially reducing the severity of injuries. The proposed Automobile Black Box System serves as a pivotal tool for advancing road safety, offering a comprehensive solution for accident analysis, prevention, and emergency response in the ever-evolving landscape of connected vehicles.

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References


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