Comparative Performance Analysis of KNN (K-Nearest Neighbor) algorithm for Fatigue Detection in vehicular Drivers using pulse oximetry signal (International Journal of Engineering and Computer Science, 2015)
Vehicular accidents are taking place day by day and people are losing their lives across the world. It is important to detect physiological and Psychological parameter of the vehicular driver so that various levels of physical and mental fatigue can be measured. Research has been initiated at a great extent in India to develop an insidious solution for eliminating such accidents. In this paper the KNN (K-nearest neighbor) algorithm has been designed to organize Post and Pre driving fatigue levels. The performance analysis of K- nearest neighbor algorithm has been discussed here. This paper propose a method to plan and to execute the major element of this computing system which is wearable and the aim is to watch the Fatigue level of a driver using physiological parameters so that a simplified system can be built without disturbing the driver and unaffecting his comfort level. This paper also presents the usage of physiological parameters of the body such as oximetry pulse for classifying the post and pre driving fatigue state of the vehicular drivers.