Umudike Journal of Engineering and Technology

Driver drowsiness is a major contributor to road accidents worldwide, resulting in countless fatalities and injuries annually. Conventional fatigue detection methods, such as self-reporting or basic most alert setups struggle to stay accurate minute by minute, also they miss chances to step in usefully. This effort, Drowsiness Detection and Alarm System for Drivers Using smart cameras along with the Eye Aspect Ratio method helps spot signs quickly during live tracking Yet sleepiness causes many crashes. A clear video camera watches closely instead A camera streams real-time footage of the person behind the wheel. This feed runs into OpenCV, which spots faces in the frame. Following that step, MediaPipe takes over to analyze specific features on the detected face watching how much the eyes close it uses a method called Eye Aspect Ratio. This checks changes in face points near the eyelids. It keeps tabs on whether the driver's eyes are shut too long. Position shifts around the eye help spot blinking patterns. A calculation based on width and height shows if lids are lowering. Tracking these movements helps understand drowsiness signs Later on, signs like yawning or how someone holds their head help show if they’re paying attention. Though If the EAR reading stays under a certain level for long enough, that signals to the system it has crossed a boundary worth noting When tiredness shows up, a built-in alert system kicks in. Built to save money while staying precise, Even when light shifts unpredictably, it keeps working without a hitch. Different kinds of drivers fit right in, thanks to its flexible design, even with glasses on. It uses several signs of tiredness along with accurate EAR math to reduce Fake alerts drop when roads get safer for cars plus trucks.