Smart Vehicle Management System for Accident Reduction by Using Sensors and An IoT Based Black Box

Reckless driving is one of the prominent causes of human-based vehicle collisions, which are gradually increasing. Furthermore, due to a lack of real-time evidence, very few further investigations are done to determine the actual causes of these accidents. The central theme of this titled paper is to construct a few sensor-based black box systems that will assist us in reducing traffic collisions by giving accurate instructions to the driver constantly. At the same time, it will upload the evidence to its server for further analysis. Firstly, there is a variety of sensors in this black box system, including LIDAR, alcohol sensors, a camera, and RFID. This technology also has a method for detecting the driver's drowsiness. All of the information will be shown on a monitor directly in front of the driver's seat. Lastly, the relevant authority will receive information on the vehicle's condition and location via GPS and GSM.