Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/15830
Title: Automated Driver Drowsiness Detection System Using AI
Authors: Radha, R
Pujar, Naveen M
Ashfaque, Sahiba
Keywords: Drowsy Driving
Real Time
Automated
Machine Learning
Issue Date: 2022
Publisher: International Journal for Modern Trends in Science and Technology
Citation: Vol. 8, No. 12; pp. 86-92
Abstract: According to the survey a total of 21% of all accidents occur due to drowsy driving. Approx. eleven million drivers accepted that they faced accidents because they dozed off while driving or were too tired to drive. To minimize the number of accidents occurring due to driver drowsiness, we have designed and fabricated a device that alerts the driver if he falls asleep. The product’s end users can be truck drivers, cab drivers, long-distance travelers or people suffering from narcolepsy. The device that has been designed is a standalone device with precision sensor and analysis technology that can accurately detect the fatigue state of the driver and notify him/her by sending alarms in real time to ensure his/her safety during potentially dangerous driving situations. The device is automated and makes use of the latest technologies like Artificial Intelligence and Machine Learning. This device has wide applications. It can also be used for vigilance and surveillance purposes other than ensuring driver’s safety.
URI: https://doi.org/10.46501/IJMTST0812014
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/15830
ISSN: 2455-3778
Appears in Collections:Journal Articles

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