Car Black Box System for Accident Analysis using IoT

The main objective of this paper is to develop a prototype of a Black Box system that can be installed in any vehicle. The system aims to monitor both the driver's behaviour and the car's condition in real-time, enabling accident investigators to determine the cause of an accident. By utilizing sensors and GPS technology, the system can provide crucial information about the accident. To record and store data related to the vehicle's operation and behaviour leading up to and during an accident, such as speed, braking, steering, and acceleration. It provide real-time feedback to the driver on their driving behaviour, such as excessive speed or hard braking, which can help prevent accidents in the future and also provide evidence for legal and insurance claims, which can be used to determine fault and liability in an accident. The car's black box serves as a tool for tracking the vehicle's speed, tilting status, and precise location. Various sensors, such as a Raspberry Pi microcomputer, camera, audio, and alcohol sensor modules, were employed in constructing this system. Similar to the black boxes found in airplanes, this system functions similarly to an aircraft's “black box” by employing a specific algorithm to record all flight data. This allows authorities to access the recorded data whenever necessary.