Human Stress Level Based Motor Speed Controlling System Using AI

Human psychological stress and emotions are deeply interconnected and play a critical role in shaping behaviour , particularly in high- pressure environments like driving. This project introduces a multi- modal stress detection system utilizing Convolutional Neural Networks (CNNs), which integrates facial recognition, emotion analysis, and physiological data to assess real-time driver stress levels. By monitoring stress indicators, the system enables an adaptive vehicle speed control mechanism that responds to the driver’s stress, enhancing road safety. The proposed model validates stress levels through theoretical and experimental analysis using a labelled dataset. Biomarkers and physiological responses linked to stress are analyzed to predict stress in previously unobserved individuals, ultimately fostering an intelligent and safety-oriented driving ecosystem.