Soft Computing Techniques for Driver Alertness

There has been an alarming increase in the number of accidents that occur due to drowsiness while driving. In order to reduce roadside accidents, the detection of driver fatigue or drowsiness is crucial. Detecting fatigue during driving is crucial for reducing accidents, as well as improving the saf...

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Veröffentlicht in:Journal of physics. Conference series 2022-08, Vol.2325 (1), p.12045
Hauptverfasser: Reddy, Penuballi Phani Srikar, Khadyoth, Gunturu Sasi Pavan, Raman, Vennalakanti Sri Ganesh, Reddy, Gadikota Sai Dheeraj, Valiveti, Hima Bindu
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Sprache:eng
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Zusammenfassung:There has been an alarming increase in the number of accidents that occur due to drowsiness while driving. In order to reduce roadside accidents, the detection of driver fatigue or drowsiness is crucial. Detecting fatigue during driving is crucial for reducing accidents, as well as improving the safety of both the driver and the passengers. Various methods can be used to detect drowsiness among drivers, but fuzzy logic-based detection stands out for its ability to avoid false alarms. As part of the proposed system, we are using eye-tracking in combination with methods such as Haar cascade to identify the level of drowsiness of the driver. This system has been tested in real-time.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2325/1/012045