Stress Detection and Employee Well-Being Monitoring System Project

The Stress Detection and Employee Well-Being Monitoring System is an AI-powered platform designed to identify and manage stress among IT professionals and employees. The system continuously collects behavioral and physiological data from multiple sources including keyboard activity, screen time tracking, application usage, voice analysis, and wearable devices. Using machine learning algorithms, the collected data is cleaned, processed, normalized, and analyzed to identify stress patterns and anomalies. The platform also includes an interactive mental health assessment chatbot powered by Rasa, which evaluates the user's emotional state through questionnaires and generates stress scores and risk levels. Based on the assessment results and behavioral analytics, personalized recommendations, alerts, wellness resources, and intervention strategies are provided. The system offers separate dashboards for users and administrators, enabling real-time monitoring of stress trends, behavioral metrics, feedback analysis, and overall employee well-being. The solution aims to promote a healthier work environment by enabling early stress detection and timely intervention.