Sensor Based System to Detect Driver's Stress, Fatigue and Drowsiness using Data Analytic Approach

The level of stress for drivers will have a greater impact while driving. Driver stress may affect driver performance and create many accidents. Sometimes many innocent lives are lost because of driver stress level. Stress is something we cannot able to physically see and identify, hence different types of sensors like heartbeat, pupil dilation, blood pressure, respiration rate, skin response are used to predict stress level of the driver and driver behavior while driving. Driver behavior parameters like ECG, eye blinking, speed, steering angle, turn signal can be monitored while driving. These parameters might be helpful to observe driver's distractions as well. In this project, to overcome the challenge we have proposed real data collection, IoT based sharing and data analytics. To obtain driver stress, we are planning to integrate heartbeat and eye blink sensors to predict the stress level and drowsiness of the driver during driving. In real time these sensors would be embedded in the driver glass. The real time data are processed from NetBeans as an excel file to R programming studio for data analysis. Citation: Suma. S, Kamala Kannan R. V, Akash. J, Kishan. R. "Sensor Based System to Detect Driver's Stress, Fatigue and Drowsiness using Data Analytic Approach." Global Research and Development Journal For Engineering 4.4 (2019): 1 - 7.