Development of a real-time drowsiness warning system based on an embedded system

Rapid pedestrian detection, distance cruise control, lane departure warning system, and reverse image system are widely used in automobile system, but the real-time detecting driver's drowsiness using the embedded system was not developed in the past. Recently, the biomedical signal processing have been using to solve biomechanical sciences problem, such as mind-brain imaging technology, magneto encephalogram, electroencephalography, analyzing cranial nerves active dynamic distributed and further brain message processing mechanism. The main reason of traffic accidents is because of drowsiness due to the long time driving. Analyzing brain signal based on the electroencephalography can provide the prediction of drivers' drowsiness to produce the warning for the driver. Therefore, this paper is to develop a real-time embedded system which consists of the embedded system, RF system and the mind wave machine called NeuroSky. The mind wave data is captured by NeuroSky to monitor driver's mind condition based on feature extraction method and data classify method. The RF system is used to transfer the data to the embedded system to reduce traffic accident rate.