In India, approximately 500,000 people are losing lives due to road accidents every year. With the rapid urbanization and development of big cities and towns, the graph of accidents is steadily increasing. Accidents due to driving after consuming alcohol and falling asleep behind the wheel have a share of about 8%. We have come up with a prototype to provide a solution to these crucial problems. This phenomenal rise in road accidents in cities is a matter of great concern and alarm to all of us. Drivers being drunk, sleeping, skipping signals, wrong route driving, and whatnot are the reasons for these frequent accidents. These recurring accidents have caused the citizens to fear driving around. They feel very insecure and vulnerable when stepping into their vehicles to travel in and around the city. So, we have designed a solution to detect drowsiness while driving. We are using image processing with the help of a camera to extract facial landmarks of the eye and image processing techniques that draw out the facial landmarks for detecting whether the driver is drowsy or awake. Additionally, we have planted an Arduino board with an MQ3 sensor to detect alcohol from the drivers’ breath to check drivers’ condition.
Drowsiness Detection Using IoT and Facial Expression
CogScienceTechnology
Proceedings of the International Conference on Cognitive and Intelligent Computing ; Chapter : 61 ; 679-692
2023-01-01
14 pages
Article/Chapter (Book)
Electronic Resource
English
ATmega328 processor , MQ3 alcohol sensor , Arduino board , Facial recognition , Alcohol detection , Computer vision (CV) , Image processing , Facial landmark detection (FLD) , Drivers breath Engineering , Computational Intelligence , Machine Learning , Cyber-physical systems, IoT , Professional Computing , Artificial Intelligence , Computer Science
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