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Driver lethargy is one of the main explanations for traffic accidents and the associated fiscal losses. Existing drowsiness detection techniques does not concentrate on all the key factors of drowsy drivers. The proposed system designed for the analysis and detection of drowsiness uses visual based features. The eye state, eye blinking frequency, eye closure duration, redness level detection, mouth state, yawning frequency are the key factors for detecting drowsiness. Systems that use this technique usually monitor eye states and the position of the iris through a specific time period to estimate the eye blinking frequency and the eye closure duration. On the other hand, mouth analysis and tracking the yawning frequency of a driver is an alternative way of detecting the drowsy driver. These techniques will identify the drowsing state of the driver and if he is drowsy, then an alert message is sent to the driver stating that the driver is no longer capable of driving the vehicle safely thus preventing accidents.