Abstract: It aims to create a new driver perception analysis system using multi-modal machine learning technology. The proposed system combines facial recognition and speech analysis to accurately assess the driver's emotional state in various situations.The practice is to use pre-trained models and custom training to achieve accuracy. Regular updates and stringent testing ensure that the model is constantly improved, making it a powerful tool for implementing safety strategies and monitoring control driving in the automotive industry. This integration is achieved by combining computer vision and audio signal processing. The system adapts to various driving conditions to increase its effectiveness in real situations. The continuous development of the model through revisions makes it responsible for change in thinking. The program helps improve driver care to improve road safety and health.
Keywords: Transportation Safety, Behaviour Detection, Real-time Intervention, Driver Monitoring.
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DOI:
10.17148/IJARCCE.2024.13519
