Kinematic signatures of impairment: Detecting alcohol intoxication in e-scooter riders using sensor data and machine learning
Leveraging sensor-based machine learning to detect motor impairment and enhance rider safety in real time.
Alcohol intoxication is a leading contributor to fatal and severe-injured e-scooterist crashes. Current countermeasures, such as temporal restrictions or pre-ride cognitive screening, cannot continuously assess an e-scooterist's physical motor control or impairment in real time. ...
ArXiv CS.LG
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By analyzing subtle kinematic data from e-scooter sensors, machine learning models can effectively identify motor impairment patterns indicative of alcohol intoxication. This technology provides a proactive safety layer that enables real-time intervention to prevent accidents in the expanding micro-mobility sector.
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