Driver Drowsiness Detection System
| Autor: | Mohammed Anes J, Dr.A.R.JayaSudha |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| DOI: | 10.5281/zenodo.8037359 |
| Popis: | Drowsy drivers cause several accidents every year. It's a major contributor to vehicular mishaps in the modern era. According to recent data, driver fatigue is a leading cause of accidents. Thousands of people lose their lives every year in vehicle accidents brought on by sleepy drivers. Drowsiness contributes to almost 30% of all accidents. A system that can detect driver fatigue and provide an alarm in time to avert an accident is essential. In this study, we provide a method for identifying sleepy drivers. In this system, the driver is constantly watched over by a camera. The driver's face and eyes are the primary targets of the image processing used in this model. The device takes a picture of the driver's face and uses eye tracking data to guess when he or she will blink. To quantify perclos, we use an algorithm to follow and analyse the driver's face and eyes. A warning tone is played if the blink rate is too high. {"references":["1.\tAssari, M. A., & Rahmati, M. (2011). Driver drowsiness detection using face expression recognition. 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).","2.\tTianyi Hong, Huabiao Qin, & Qianshu Sun. (2007). An Improved Real Time Eye State Identification . System in Driver Drowsiness Detection. 2007 IEEE International Conference on Control and Automation.","3.\tWarwick, B., Symons, N., Chen, X., & Xiong, K. (2015). Detecting Driver Drowsiness Using Wireless Wearables. 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems.","4.\tDwivedi, K., Biswaranjan K & Sethi, A. (2014). Drowsy driver detection using representation learning. 2014 IEEE International Advance Computing Conference (IACC).","5.\tYan, J.-J., Kuo, H.-H., Lin, Y.-F., & Liao, T.-L. (2016).","6.\tReal-Time Driver Drowsiness Detection System.Based on PERCLOS and Grayscale Image Processing. 2016 International Symposium on Computer, Consumer and Control (IS3C).","7.\tAlshaqaqi, B., Baquhaizel, A. S., Amine Ouis, M. E., Boumehed, M., Ouamri, A., & Keche, M. (2013). Driver drowsiness\tdetection\tsystem.2013\t8th\tInternational Workshop on Systems, Signal Processing and Their Applications (WoSSPA).","8.\tTripathi, D.P., Rath, N.P.(2009). A novel approach to solve drowsy driver problem by using eye-localization technique using CHT. International Journal of Recent Trends in Engineering.","9.\tSubbarao, A., Sahithya, K. (2019) Driver Drowsiness Detection System for Vehicle Safety, International Journal of Innovative Technology and Exploring Engineering (IJITEE).","10.\tSukrit Mehta, Sharad Dadhich, Sahil Gumber, Arpita Jadhav Bhatt (2019). Real-Time Driver Drowsiness Detection System Using Eye Aspect Ratio and Eye Closure Ratio International Conference on SustainableComputing in Science, Technology and Management."]} |
| Databáze: | OpenAIRE |
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