Work place: Ahsanullah University of Science and Technology, Dhaka-1205, Bangladesh
E-mail: au.i.rafid15@gmail.com
Website:
Research Interests: Image Processing, Image Manipulation, Image Compression, Computer Vision, Computational Learning Theory, Artificial Intelligence
Biography
Anis-Ul-Islam Rafid - He has completed B.Sc on Computer science and Engineering from Ahsanullah University of Science and Technology. His research interests include computer vision, digital image processing, machine learning, artificial intelligence and software development. Former Jr. Software Engineer at Think Bricks. Now working as a Jr. Machine Learning Engineer at Pridesys IT Ltd, Dhaka, Bangladesh.
By Anis-Ul-Islam Rafid Amit Raha Niloy Atiqul Islam Chowdhury Nusrat Sharmin
DOI: https://doi.org/10.5815/ijigsp.2020.03.05, Pub. Date: 8 Jun. 2020
Driver drowsiness is the momentous factor in a huge number of vehicle accidents. This driver drowsiness detection system has been valued highly and applied in various fields recently such as driver visual attention monitoring and driver activity tracking. Drowsiness can be detected through the driver face monitoring system. Nowadays smartphone-based application has developed rapidly and thus also used for driver safety monitoring system. In this paper, a detailed review of driver drowsiness detection techniques implemented in the smartphone has been reviewed. The review has also been focused on insight into recent and state-of-the-art techniques. The advantages and limitations of each have been summarized. A comparative study of recently implemented smartphone-based approaches and mostly used desktop-based approaches have also been discussed in this review paper. And the most important thing is this paper helps others to decide better techniques for the effective drowsiness detection.
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