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 |
Files in This Item:
File | Description | Size | Format | |
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14.IJMTST0811041.pdf | 1 MB | Adobe PDF | View/Open |
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