Human Stress Level Based Motor Speed Controlling System Using AI

Human Stress Level Based Motor Speed Controlling System Using AI

Bhuvana Shree V¹, Deepadharshini R², Divya S³, R K Shavitha⁴, Mrs. K. Thamaraiselvi⁵

1,2,3,4 Students, 5 Assistant Professor, Department of Computer Science and Engineering,

Avinashilingam Institute for Home Science and Higher Education for Women, India

ABSTRACT

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.

Keywords: Stress detection, CNN, PWM, artificial intelligence, machine learning, user experience.