Smart Health Monitoring System: Computer Engineering Guide
1. Introduction
Overview of the project.
Objectives of the system: Enable real-time health monitoring, provide alerts for critical conditions, and store health data securely.
Scope of the system: Suitable for hospitals, remote patient monitoring, and personal health tracking.
2. Requirements Analysis
Functional Requirements:
· - Collect vital signs data (e.g., heart rate, blood pressure, oxygen levels).
· - Real-time data visualization for patients and healthcare providers.
· - Generate alerts for abnormal health readings.
· - Enable secure data storage and access for healthcare professionals.
Non-Functional Requirements:
· - High reliability and real-time performance.
· - Scalability for multiple patients and sensors.
· - Data security and privacy compliance (e.g., HIPAA, GDPR).
3. System Design
Architecture:
· - IoT-based architecture integrating wearable sensors, edge devices, and cloud storage.
· - Centralized or distributed database for storing patient health records.
Data Flow Diagrams (DFDs):
· - Level 0: Overview of data flow from sensors to healthcare providers.
· - Level 1: Modules like Data Collection, Processing, Alerts, and Reporting.
Database Design:
· - Tables: Patient Records, Vital Signs Data, Alerts, Logs.
4. Technology Stack
Hardware:
· - Wearable sensors: ECG monitors, pulse oximeters, blood pressure cuffs.
· - Gateway devices: Raspberry Pi, Arduino, or other microcontrollers.
Software:
· - IoT Platforms: ThingsBoard, AWS IoT, or Google Cloud IoT.
· - Backend: Python (Flask/Django), Node.js, or Java (Spring Boot).
· - Frontend: Mobile app (React Native/Flutter) or web app (React.js/Angular).
Communication Protocols:
· - Bluetooth, Wi-Fi, or MQTT for sensor-gateway communication.
Database:
· - Cloud-based solutions like Firebase, AWS RDS, or MongoDB.
5. Implementation
Hardware Integration:
· - Connect sensors to gateway devices for real-time data transmission.
· - Ensure device calibration and synchronization.
Software Development:
· - Write firmware for data collection and communication.
· - Implement backend APIs for data processing and storage.
· - Develop user-friendly interfaces for health monitoring and alerts.
Integration:
· - Combine sensor data with cloud services for data analytics and visualization.
· - Implement APIs for integration with healthcare systems.
6. Security
Encrypt patient data during transmission and storage.
Use secure authentication mechanisms for system access.
Implement access control policies for healthcare professionals.
Regularly audit the system for security vulnerabilities.
7. Testing
Unit Testing: Validate sensor data accuracy and API functionality.
Integration Testing: Ensure seamless communication between hardware and software.
System Testing: Test the system under different health monitoring scenarios.
Performance Testing: Evaluate system responsiveness and data handling capacity.
8. Deployment
Deploy wearable sensors and gateway devices for patient use.
Set up cloud infrastructure for backend services and data storage.
Train healthcare staff and provide user manuals for patients.
9. Maintenance and Updates
Regularly update sensor firmware for accuracy and reliability.
Implement software updates for improved functionality and security.
Monitor system logs and collect user feedback for continuous improvement.
10. Appendix
Glossary of terms.
References and additional resources.