A Fuzzy Expert System for The Drowsiness Detection from Blink Characteristics

One of the most common factors of road accidents is the drowsiness of drivers. The project's key purpose is to define the strategies for detecting and alerting driver somnolence, thus growing transportation safety. Via uses several physiological variables, such as pulse rate, EEG, ECG, eyelid closure, skin conductance. This scenario indicates that the driver is not in reasonable driving shape. EOG signals are used in this suggested framework. The Electrooculogram (EOG) is an electrical activity indicator related to eye motions. Other signal origins, called objects, may contaminate the electrooculography signal. Eye wink is one of the key causes of disturbance in the EOG signals among the various artefact sources. Blink attributes are determined from these signals, and they are evaluated using Fuzzy logic.