IoT based Automatic Smart Black Box System to Detect Accidents

Sensor models that are dependable and resilient are required for autonomous vehicles, and continuing validation must be accomplished through the collection of data from across an entire fleet. This essay covers the components that make up an advanced controller system for automobile recording equipment as well as the functionality of that system. The system is able to not only precisely and completely capture the majority of an automobile's driving data over the course of time, but it is also capable of reconstructing an accident using information method code. This enables individuals to quickly and legally assess an accident after a collision, which is a significant benefit of the system. A controller is responsible for performing continuous monitoring of the sensor parameters contained within the SD card module. The system will update the information whenever an abnormal system event takes place. When there is a shortage of storage space, prioritized data recording removes buffers with low importance, making room for more recent data. In addition, there is not a single metric in place that would make the collection of long-term data for on-road vehicles easier. In addition to this, it would be necessary to buffer all of the data over the course of a long journey in order to globally optimize the deletion and compression options for the data