| Summary: | When it comes to ride a motorcycle the drivers-centered road safety is quintessential; every year a remarkable number of accidents directly related to sleepiness and fatigue occur. With the objective of maximizing the security on a motorcycle, the reported system aims to prevent sleepiness related accidents and to attenuate the effects of a crash. The system was developed as the less intrusive as it could be, with sensors that allow the capture of reaction times to stimuli-response and collect acceleration values. To obviate the lack of data related to sleepiness during motorcycle riding, a machine learning system was developed, based on Artificial Immune Systems. This way, resourcing to a minimum amount of user input, a custom system is synthesized for each user, allowing to assess the sleepiness level of each subject differently.
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