Automobile accidents result in not just human fatality but also financial costs to both individuals and society. This special issue examines the history and backdrop of the automobile system while also highlighting modern advances. This study seeks to provide an overview of the current and future implementation of safety and security systems in automobiles. Drowsiness detection and the Anti pinch window effect are two crucial enabling technologies for active safety systems. Seat belt detection and alcohol detection are two more concepts that have been presented for implementation. The tiredness of drivers is tracked using an image processing methodology that is run through MATLAB. However, the fundamental limitation of this methodology is the processing speed on hardware. The aim described in this research is to use the Open CV library for real-time facial image analysis to detect driver tiredness and thereby avoid traffic accidents. Power window injuries can be avoided with the deployment of an anti-pinch window mechanism. The seat belt alert system emits an audible signal to remind people to buckle up for safety. Finally, if alcohol detection finds a drunk driver, a message with the vehicle's details and location is sent to a local police station. The suggested system accomplishes all of the aforementioned functions with the help of a Raspberry-Pi, camera, and a few sensors in its hard ware, as well as coding computations in Python, which provides the benefit of continuous monitoring at a low cost, hence reducing unintentional accidents to a considerable amount. The suggested system is a demonstration version of an automobile safety system that makes use of open CV software and associated hardware. Because this detection is based on a high-resolution camera, it will be more accurate.
Author (s) DetailsS. Sharmila Devi
Department of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore-22, Tamil Nadu, India.
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