Md Jahid Hasan
ABSTRACT
Accidents on the road are the primary cause of death, particularly among children and adolescents. Despite having fewer vehicles, low- and middle-income countries account for the preponderance of these fatalities. Consequently, a system that monitors vehicles and takes the necessary precautions to prevent collisions and fatalities is urgently required. This paper proposes a system of OpenCV image processing techniques to monitor the driver’s eye movements in order to prevent accidents caused by behavioral and psychological changes while driving. The main processing unit (MPU) of the system we have developed consists of Raspberry Pi, Microcontroller, and sensors. Both on day and night time, it detects driver drowsiness and alerts them with a wristband. In low-light conditions, two infrared (IR) blasters and multiple light-dependent resistors (LDR) sensors were used to accurately detect driver fatigue. During an accident, the MPU’s accident detection module will identify and send an SMS message to the vehicle owner with the vehicle’s location and data. Eventually, the local police station, fire department, and other safety agencies will be able to take immediate action. The novel aspect of this study is the combination of image processing techniques and sensors that accurately monitor driver behaviour and identify fatigue. The accident detection module of the system is also distinct and can provide emergency services with vital information in the event of an accident. If implemented, the proposed technology can enhance the safety features of cars and reduce the number of accidents caused by human error.
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Index Terms
- A Car Security System Based on Alerting Driver Drowsiness and Monitoring the State of the Vehicle
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