Accident detection using Automotive Smart Black-Box based Monitoring system

Abstract

Autonomous vehicles want reliable and strong sensor suites and alert systems. This paper discusses the composition and performance of a sophisticated monitoring and alert system for automobile vehicle parameters. The number of automobiles has also grown quickly to meet the enormous population. Additionally, this resulted in an increase in accidents. The accident prevention strategies now in use are all static and dated. Additionally, there is no reliable accident detection system. Automobile vehicle parameters are continuously monitored by a micro-controller which stores the data logs containing vehicle parameter data into a sheltered digital memory card and in the cloud storage. The system doesn't solely record the vehicle parameters data of the automobile periodically, but also actively monitors for any sudden vehicle accident detection. The sensor may facilitate folks to analyze the accident quickly and lawfully when a collision happens to alert the emergency services to that location. The system will update the information whenever an abnormal system event happens. A black box in a vehicle gather driving information about the vehicle before, during and after a crash. The data gathered includes, speed, acceleration, braking, steering and air-bag deployment. The Automotive black box system can aid with vehicle safety, increase collision victim care, assist insurance corporations with vehicle crash investigations, and improve road conditions to reduce death rates. According to experimental findings, the proposed technique achieves 29.3103%, 22.70 %, 18.103% and 11.206 % higher accuracy compared to RFID, SVM,CNN and RNN Methods.

Keywords

• Internet of things
• Black box
• Vehicle alert system
• Vehicle accident detection system
• Zigbee
• Vehicle accident analysis