Smart Health Monitoring System
Project Description
A hybrid health monitoring system designed to empower individuals to monitor their vital signs in real-time using wearable sensors. The system leverages both edge and cloud computing to ensure reliable operation across diverse environments — even when internet connectivity is unavailable. It integrates a Flutter-based mobile app, MQTT-based IoT data acquisition, and intelligent AI models for both heart disease prediction and X-ray-based pneumonia detection.
Key Features
- Real-time monitoring of vital signs such as heart rate, SpO₂, and temperature via sensors
- Automatic switching between local (Edge/TFLite) and cloud (AWS SageMaker) AI models based on network availability
- Dual-mode heart and pneumonia prediction using machine learning
- Cross-platform mobile app built with Flutter, ensuring accessibility on both iOS and Android
- Offline capability with support for manual data entry and local database storage
- Full-stack integration with AWS services including Cognito, Lambda, DynamoDB, and QuickSight for authentication, inference, storage, and analytics
System Architecture
AWS Cloud Integration Diagram
Mobile App Navigation & Prediction Flow
Full System Workflow (ACOSO-Meth)
These diagrams illustrate the end-to-end integration of the Smart Healthcare Monitoring System across cloud, mobile, and IoT layers. They include:
- Detailed AWS Service Architecture (Cognito, Lambda, SageMaker, DynamoDB, QuickSight)
- Mobile Application Page Flow for Edge vs Cloud AI models
- Complete ACOSO-Meth Functional and Domain Modeling
Gallery
