Abstract
The condition to trigger the Automatic crash detection for motorcycles is more complex, since the collisions in real life are usually different than those in the lab. so in order to boost the accuracy and affectivity, the researchers must reduce inconsequential deployments, the occupant weight, and riding condition, as well as re-calculate the speed to crash conditions. In this paper was present a continuously evaluates and innovate for crash detection with support automated notification system. The accident detection, communicates the accelerometer, vibration, speed and lean values to the determine accident status and level. In this concept, three different variable measurements are attached to head of the motorist and motorcycle body, Crash dummy tests are done for trial particular systems in helmet by throwing the helmet with different altitudes to simulate the effect of crash to the motorist, and for capture the location of accident, real data is collected by driving the motorcycle. The implemented prototype system showed promising results for automatic crash detection, and the system also showed its success for deliver real-time notifications when an accident was happening.
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