Smart IoT-Based Stress Detection & Autonomous Relaxation System

Abstract: In contemporary high-pressure corporate and academic environments, physiological stress has emerged as a significant yet often undetected precursor to chronic health conditions and diminished productivity. Current wellness interventions are predominantly reactive, requiring users to manually initiate relaxation only after the onset of exhaustion. This delay often results in long-term health complications and a lack of sustainable mental well-being in the workspace.

The objective of this proposed system is to develop an "IoT-Enabled Autonomous Stress Detection and Relaxation Chair" that provides proactive, non-invasive health support. The system utilizes an ESP32-based architecture interfaced with a multi-sensor array, including biomedical sensors for heart rate monitoring and thermal sensors for body temperature tracking. By integrating these components into a standard seating environment, the chair acts as a continuous health- monitoring assistant.

The methodology follows a "Sense-Analyze-Act-Monitor" feedback loop. Physiological data is continuously polled and processed through embedded algorithms to classify stress states. Upon identifying a stress spike, the system autonomously triggers an integrated relaxation cycle consisting of targeted vibration massage, controlled heat therapy, and calming auditory stimulation. Simultaneously, real-time data is synchronized with a cloud-based dashboard using the HiveMQTT broker for long-term health visualization.