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Original research AN EDGE-ENABLED CYBER-PHYSICAL SMART HELMET FRAMEWORK FOR REAL-TIME MOTORCYCLE ACCIDENT DETECTION AND AUTOMATED EMERGENCY RESPONSEPages 447-458
Abstract
Motorcycle accidents constitute a grave public health issue in Ghana, where motorcycles constitute 37% of all accidents on the roads, with response times of 30–60 minutes leading to needless deaths. This work develops an Edge-Enabled Cyber-Physical Smart Helmet System that enables automatic accident detection and response in real time. The developed system incorporates a multi-layer framework comprising sensing, edge computing, and communication and action layers embedded within a motorcycle helmet. All computations are done locally in the absence of cloud connectivity. Empirical estimation of the detection threshold based on rigorous testing carried out on Ghana's roads showed 100% accuracy with a detection threshold of 49 ms⁻² ≈ 5g. Once an accident is detected, GPS coordinates are captured in tandem with a 20-second cancelation period, after which a GSM communication chip automatically calls emergency contacts providing recorded GPS coordinates. The time interval between when the collision occurred to when the link is established to the ambulance services was recorded at around 32 seconds, equating to a decrease of between 28 minutes to 59 minutes compared to that of the baseline system manually. Tests of the system integrated showed 100% efficiency costing GH₵ 459.15. .
Keywords:
Automatic crash notification, cyber-physical systems, edge computing, emergency medical services, Ghana, motorcycle safety, smart helmet.
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Patrick Effraim, 
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