Development of a Real Time Drowsy Driver Detection System
- February 26, 2022
- Posted by: RSIS
- Categories: Computer Science and Engineering, IJRIAS
International Journal of Research and Innovation in Applied Science (IJRIAS) | Volume VII, Issue I, January 2022 | ISSN 2454–6194
Development of a Real Time Drowsy Driver Detection System
Precious O.C.1, Kinsley C.I.2, Chukwuemeka E.E.3, Ebere U.C4
1,2Enugu State University of Science and Technology, Nigeria
3Department of Computer Science, Ebonyi State University, Abakaliki, Nigeria
4Destinet Smart Technologies, New layout, Enugu, Nigeria
Abstract: This paper presents the development of real time drowsy driver detection system. The study reviewed literature and identified that drowsy has remained a major cause of most road accidents. To address this problem a real time drowsy driver was developed using convolutional neural network and implemented as an accident prevention and control system using Mathlab. The result when tested showed that the system was able to detect drowsiness in real time which is very good.
Key words: Drowsy Driver, Real Time, Accident, Convolutional Neural Network
I. INTODUCTION
According to Kayode (2018), an estimated 90% of passengers depend on road network for transportation. This implies that the passengers reach out to their respective commercial service based, habitat or domain via vehicles. Some of the commercial driver’s piloting these vehicles spend most of their times on the steering wheel driving, since their pay checks depend on the number of passengers they convey to various destinations daily. This alone accumulates enough mental stress and fatigue on the driver’s brain and induces drowsiness while still on high way after some hours. This is the reason why some drivers take precautionary measures like eating bitter kola, drinking coffee, drinking alcohol, taking few minute refreshment breaks, eating chewing gums and even smoking sometimes with hope of countering this effect of drowsiness. However one cannot manipulate nature as these traditional techniques are not good enough or reliable. The use of alcohol for instance induces more fatigue to the brain cells and increases the rate of drowsiness contrary to the drivers aim and as a result can have a devastating effect on the driver concentration, thus endangering the lives of the passengers on board and most time leading to series of road accidents.
