Engineering World
E-ISSN: 2692-5079 An Open Access, Peer Reviewed Journal of Selected Publications in Engineering and Applied Sciences
Volume 4, 2022
A Modified Neural Network Model for Real-time Driver Drowsiness Detection System
Authors: ,
Abstract: World is running fast. With the speed of communication technology, there is a boom in the transportation industry also. The transportation vehicles are operating day and night to provide proper support of the need. This is really tiring for the transportation workers, especially the drivers who are driving the vehicle. A slight negligence of a driver may cause huge loss. The increasing number of road accidents are therefore a big concern. There is huge research going on to comfort the drivers and increase the security features of vehicles to avoid accidents. Here is this work, a model is proposed, which can efficiently detect driver drowsiness. The work mainly focused on building the learning model. A modified convolutional neural network is built to solve the purpose. The model trained with a dataset of 7000 images of open and closed eyes. For testing purposes, some real-time experiments are done by some volunteer drivers in different conditions, like gender, day, night, etc. the model is really good for daytime and if the driver is not wearing any glass. But with a glass in the eye and in night condition the system needs improvements.
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Pages: 77-84
DOI: 10.37394/232025.2022.4.10