Driver Alertness Detection Using Data Correlation

Abstract

Abstract

The number of accidents taking place across the globe is increasing at a fast pace and it's astonishing that around 20% accidents occur due to driver’s fatigue or due to lack of alertness. Non-alertness reduces reaction time and concentration, impairing the ability to execute decision making as well as attention-based activities. Being an aware and responsible citizen, it becomes essential to assure the driver’s vigilance and safety of passengers, co-passengers. Working on this predicament of driver alert detection, this paper proposes a solution to detect alertness based on an individual’s heart rate. In case of non-alertness through IoT, the working agency keeping a record of alertness would be discerned and driver is alarmed through a loud beep on his phone. The heartbeat detection is based on a piezo electric sensor; the electronic design basically detects heartbeat and is proposed to be attached on seatbelt of the driver to check attentiveness. The data analysis study done on Holter report of a heartbeat after consulting cardiologist deduced that as per circadian rhythm, a person is already in the non-alert zone during night hours and when a person is non-alert, his/her heartbeat goes slow. Further to this analysis, it was surmised that if a person's heartbeat is detected, alertness can be checked. The complete setup was further taken on IoT framework, so that data can be transferred over a network without requiring human-to-human or human-to-computer interaction. 

Keywords: Amplifier, cardiologist, data correlation, fatigue, MOSFET

Cite this Article

Shreya Chawla, Anisha Raheja, Akshar Vashist, Gourav Kumar Soni. Driver Alertness Detection Using Data Correlation. Journal of Electronic Design Technology. 2019; 10(2): 6–15p.