The main goal of this project is to create a drowsiness detection system that monitors the eyes; it is thought that by identifying the signs of driver fatigue early, an accident can be prevented. When this happens and drowsiness is found, a warning signal is sent to the driver to let them know. ResNET system, which is a deep learning CNN system, enables early detection of a decline in driver alertness while driving and offers a noncontact technique for evaluating various levels of driver alertness. When this happens and fatigue is found, a warning signal is sent to the driver to let them know. If the driver doesn’t react to the alarm, the system also includes a feature that will slow down the car until it stops.
Driver Drowsiness Detection Using CNN and ESP32 CAM
Lect. Notes in Networks, Syst.
International Conference on Data Science, Computation and Security ; 2023 ; Indore, India November 02, 2023 - November 04, 2023
2024-05-31
16 pages
Article/Chapter (Book)
Electronic Resource
English
IEEE | 2020
|Springer Verlag | 2017
|Overview of Research on Driver Drowsiness Definition and Driver Drowsiness Detection
British Library Conference Proceedings | 1994
|