@article{N.A_S_2021, title={Drivers’ Real-Time Drowsiness Identification Using Facial Features and Automatic Vehicle Speed Control}, volume={3}, url={https://sietjournals.com/index.php/ijcci/article/view/103}, DOI={10.34256/ijcci2114}, abstractNote={<p>The road crash is one of the significant problems that is of great concern in today’s world. Road accidents are often caused by drivers’ carelessness and negligence. The drowsy condition of the drivers, which occurs due to overwork, fatigue, and many other factors, is one of those causes. It is therefore most critical to establish systems that can detect the driver’s drowsy state and provide the drivers with the appropriate warning system. In addition to the automatic speed control of the car, this system thus supports drivers in incidents by providing warnings in advance. This means that road collisions that are harmful to living lives are minimised. This is achieved by using the technique of image recognition, where driver drowsiness is observed, and using this method, simultaneous warning and speed monitoring of the vehicle is carried out.</p&gt;}, number={1}, journal={International Journal of Computer Communication and Informatics}, author={N.A, Natraj and S, Bhavani}, year={2021}, month={May}, pages={44-52} }