Personnel serving in Central Armed Police Forces (CAPFs), Armed Forces, and other uniformed services operate under physically demanding, psychologically stressful, and often hazardous conditions.Extended deployments, operational pressures, separation from families,irregular working hours, and exposure to traumatic incidents can significantly effect mental well-being.Currently, stress identification largely depends on manual observation and self-reporting, which may delay timely intervention. The
The proposed solution aims to develop an AI-powered Personnel Stress and Welfare Monitoring System that can identifying potential indicators of stress, burnout, emotional fatigue, and welfare concerns through...
Personnel serving in Central Armed Police Forces (CAPFs), Armed Forces, and other uniformed services operate under physically demanding, psychologically stressful, and often hazardous...
The proposed solution aims to develop an AI-powered Personnel Stress and Welfare Monitoring System that can identifying potential indicators of stress, burnout, emotional fatigue, and welfare concerns through analysis of organizational and voluntarily provided wellness data.The system should: • Analyze HR-related indicators such as leave patterns,deployment history, duty schedules, transfer frequency, training commitments, and workload trends. • Support optional self-reporting and wellness assessments through a secure mobile application. • Incorporate voluntary biometric and wellness data, where authorized and legally permissible. • Detect behavioral patterns associated with elevated stress risk. • Generate risk assessments and welfare recommendations for authorized welfare officers and