Drowsiness Detection and Alert System for Motorcyclist Safety

Driver exhaustion is a significant cause for many motorcycle accidents. Late insights approximately assess that yearly 1,200 deaths and 76,000 wounds can be credited to exhaustion related mishaps. Drowsiness and fatigue of the drivers are the main causes of accidents in the world as well as Sri Lanka. Drowsiness can occur due to the tiredness and lack of sleep while driving. The best way to avoid accidents caused by drowsiness is to detect it and warn the driver before falling asleep. This research mainly focuses on road accidents that are happening because of motorbikes. This study detected motorcyclist’s brain wave signals (EEG), heart rate variability (ECG) and forearm muscle condition (EMG) and proposed a novel hybrid approach in order to detect the drowsiness of the motorcyclist. The motorcyclist will receive real-time alerts about his driving. The study showed that the proposed hybrid approach achieved the highest accuracy for motorcyclist’s drowsiness detection over existing attentive predictive systems.