Real-time Stress Monitoring And Care Prediction System For Personalized Relaxation And Sleep Enhancement

Abstract

Stress Significantly Impacts Mental And Physical Well- Being, Necessitating Effective Real-time Monitoring And Intervention Mechanisms. This Paper Presents A Stress Monitoring And Care Prediction System That Integrates Physiological Sensors With Adaptive Environmental Control To Provide Personalized Relaxation And Sleep Enhancement. The System Utilizes An Arduino UNO Microcontroller Interfaced With A DHT11 Temperature Sensor, A Heartbeat Sensor, And A Galvanic Skin Response (GSR) Sensor To Continuously Monitor Stress Indicators. The Collected Data Is Processed Using Python- Based Predictive Analytics To Offer Real-time Feedback And Adaptive Environmental Adjustments, Including Temperature Regulation, Sound Modulation, And Tactile Feedback. The Proposed System Aims To Provide A Comprehensive, Data-driven Approach To Stress Management, Ensuring Improved Relaxation And Sleep Quality.

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