Live Video Analysis Platform for Continuous Driver State Evaluation and Proactive Accident Prevention Through Face Detection Technology
DOI:
https://doi.org/10.48047/jmygpy67Keywords:
Continuous Rapid Eye Motion Detection, Face Detection, Eye Aspect Ratio, Driver Safety, Autonomous Mode, Electric Buses, Road SafetyAbstract
The transportation sector is continuously evolving with the integration of advanced safety mechanisms aimed at reducing
accidents and safeguarding lives. This project introduces an innovative safety system specifically designed for electric buses,
utilising Continuous Rapid Eye Motion Detection (CREM) technology. The system is bifurcated into two primary modules:
software and hardware. The software module leverages Python programming and face detection algorithms to monitor the
driver's eye status in real-time.
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References
Gupta, R., & Patel, S. (2021). Advanced Safety Mechanisms in Autonomous Vehicles. International Journal of Automotive Engineering, 8(2), 88-99 [2] Lee, J., & Kim, D. (2018). Machine Learning Approaches for Detecting Driver Fatigue. Journal of Intelligent Transportation Systems, 15(4), 201-210
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