Researchers have developed a novel system to detect alcohol impairment in e-scooter riders during their trips using onboard sensors. This system analyzes inertial and throttle measurements to identify signs of intoxication, aiming to provide real-time alerts without requiring pre-ride tests or service suspensions. Experiments with 25 participants demonstrated the detector's ability to identify a significant percentage of impaired rides with a low false-alarm rate, suggesting its feasibility for onboard implementation and timely intervention. AI
IMPACT Could enable real-time safety interventions for shared mobility services, reducing alcohol-related accidents.
RANK_REASON Academic paper detailing a new detection method. [lever_c_demoted from research: ic=1 ai=0.7]
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