| Autor: |
Dr. K. Venkat Reddy, Dr. T. Ramaswamy, Sai Harshith Kumar, Channa Prajeeth, Choudhary Vineet |
| Rok vydání: |
2022 |
| Zdroj: |
International Journal for Research in Applied Science and Engineering Technology. 10:2087-2091 |
| ISSN: |
2321-9653 |
| DOI: |
10.22214/ijraset.2022.42740 |
| Popis: |
Driver drowsiness detection is a step to reduce the rate of road accidents that happen around the world. It integrates the technology of machine learning with computer vision for detection and alert generation. Year by year the degree of fatalities and road accidents has increased due to driver drowsiness and fatigue. The device is robust and cost-effective which can prevent road accidents in most cases. The device has a camera through which it monitors the driver’s eye continuously and processes the image for the sleep onset period. The images taken at random interval is passed through a Neural network that recognizes eye moments and classifies the sleep stage. If the driver is in the initial stage of falling asleep it can alert the driver to wake up and be attentive. If the driver is in a further stage of sleepiness the device will generate an alert to the respective emergency contacts that the driver is on the verge of sleep and they can able to alert the driver in any way. The emergency contacts can also get the location coordinates of the driver from the device's Gps tracking system. One’s inattentiveness driving or careless driving is not only a problem to himself but also to the others on the road, creating a devastating effect. So there is a level of prominence on every solution that can prevent road accidents. Not only the life of drivers but also the people who are dependent on them will have to face the consequences. Keywords: Computer Vision, Raspberry pi, GSM communication, Opencv. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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