IoT-Based Driver Distraction Prevention System

Each year, many people pass away in car accidents. Drunk driving, distracted and fatigued driving are the leading causes of Some studies have noted that features relevant to drunk driver’s alcohol consumption, smoking, carbon monoxide (CO) concentration car. Hence, it is important necessary detect these factors during avoid driver drowsiness prevent collisions. In this paper, we develop an IoT-based preventative system monitor in-vehicle air quality check for head bending. To ensure users can easily deploy proposed system, used low-cost sensors tiny IoT devices run system. The suggested uses gas including MQ-2, MQ-3, MQ-7 track using Arduino D1. Additionally, developed a Banana Pi camera setup customized Teachable Machine model ascertain whether or not paying attention road. We showcase on ThingSpeak cloud platform. Finally, buzzer speaker will sound alarm warnings occupants if exceeds specified value distraction detected.