Drowsy Driver Detection with Crash Alert Mechanism using Arduino and Image Processing
Driver drowsiness is a major cause of automobile accidents, resulting in many fatalities each year. The use of face detection techniques for identifying and warning fatigued drivers can solve this problem and improve transportation safety. This technique detects drowsiness using computer vision technologies based on facial landmarks. Image processing is used by the system to recognize the driver’s face, extract pictures of the eyes, and detect tiredness. The camera monitors the driver’s eyes in real-time, processing visual data to detect symptoms of tiredness. When sleepiness is detected, an alarm sounds to wake and notify the driver. Furthermore, the system is deployed with an Arduino UNO board with GSM, GPS, and MPU 6050 models to detect and alert emergency services in the case of a car accident, as well as to notify the driver’s family. Here the MPU- 6050 sensor detects angular position changes, while the NEO- 6m GPS module identifies the vehicle’s location. The SIM800L GSM module delivers an SMS including the location as well as a warning message. This system could be kept in automobiles to improve driver and passenger safety and security.
@article{pokhrel2023,
author = {Anisha Pokhrel and Laxmi Mahara and Monika Upadhyaya and Shikshya Shrestha and Badri Raj Lamichhane},
title = {{Drowsy Driver Detection with Crash Alert Mechanism using Arduino and Image Processing}},
journal = {Journal of Soft Computing Paradigm},
volume = {5},
number = {2},
pages = {194-217},
year = {2023},
publisher = {IRO Journals},
doi = {10.36548/jscp.2023.2.008},
url = {https://doi.org/10.36548/jscp.2023.2.008}
}
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