ElderEase

ElderEase is a modular, real-time senior health monitoring system designed to simulate, validate, classify, and log vital health parameters of elderly individuals through a scalable event-driven architecture.

Phase 1 establishes a fully functional rule-based monitoring pipeline using Node-RED and open-source technologies. The system simulates real-time wearable sensor data including heart rate, SpO₂, and body temperature, validates physiological ranges, and classifies health status into NORMAL, WARNING, or EMERGENCY categories using a structured decision engine.

The architecture follows a flow-based programming model with clear modular separation:

• Vital Data Simulation Module

• Data Validation Module

• Rule-Based Decision Engine

• Monitoring & Logging Module

• Manual Emergency Injection System

Each module communicates through structured JSON payloads, ensuring extensibility and maintainability.

The system tracks operational metrics such as:

• Total readings processed

• Emergency event count

• Last emergency timestamp

• Recent health history

ElderEase is fully compliant with FOSS principles:

• Built using Node.js and Node-RED

• No proprietary APIs

• No paid services

• Fully local execution

This phase serves as a scalable foundation for future expansion including:

• Express.js backend API

• MongoDB-based persistent health history

• React-based real-time dashboard

• Machine Learning–based anomaly detection and predictive health scoring

ElderEase aims to evolve into an intelligent, data-driven elderly healthcare monitoring ecosystem capable of proactive health risk detection and scalable deployment.

ElderEase focuses on building a production-grade, extensible monitoring backbone before moving toward predictive AI integration — ensuring stability, scalability, and long-term impact.