Enhancing Road Safety: A System for Vehicular Accident Detection, Prevention, and Rescue Alerts - Jayesh Khalane; Shraddha Tule; Rupesh Kayande; Soumitra Kulkarni (International Journal of Solid State Innovations & Research, 2024)
The Vehicular Accident Detection, Prevention, and Rescue Alert System is a comprehensive solution aimed at bolstering road safety by integrating multiple advanced technologies. It merges drowsiness detection, alcohol level monitoring, and instant emergency alerts to mitigate accidents and expedite rescue efforts. Modern computer vision and machine learning techniques are used by the Drowsiness Detection Alarm to track driver conduct and spot drowsiness indicators. Upon detecting drowsiness, an immediate alarm is activated, prompting the driver to refocus and prevent potential accidents. The Alcohol Level Indicator features a real-time alcohol level monitoring component that employs non-invasive sensors to continuously track the driver's alcohol level. If the alcohol level exceeds the legal limit, which varies depending on local laws and regulations, the system issues warnings and, if necessary, disables the vehicle's ignition system to prevent drunk driving. In the event of a vehicular accident, the Emergency Alert System automatically triggers an emergency alert mechanism. The device utilizes the LM35 temperature sensor, which is a compact and cost-effective integrated circuit capable of measuring temperatures ranging from –55 to 150°C. The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish direct fusion, indirect fusion and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and historical values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input.
Keywords: Geo Location (GPS); Vehicular Accident Detection; rescue alert System; sensor fusion; temperature sensor