Testing: IoT-Based Lake Monitoring System
Overview
Testing is essential to ensure the reliability, accuracy, and performance of the IoT-Based Lake Monitoring System. This section outlines various testing strategies applied at hardware, software, and system levels.
1. Hardware Testing
Ensures sensor accuracy, device reliability, and data transmission stability.
Sensor Calibration
| Sensor | Test Method | Expected Outcome |
|---|---|---|
| pH Sensor | Test with known buffer solutions | Accuracy ±0.1 pH |
| Turbidity Sensor | Compare with lab results | Accuracy ±5 NTU |
| Temperature Sensor | Test in controlled water samples | Accuracy ±0.5°C |
| Dissolved Oxygen Sensor | Compare with standard DO meter | Accuracy ±0.2 mg/L |
| Conductivity Sensor | Test with standard salt solutions | Accuracy ±5% |
Connectivity & Communication Testing
- MQTT Communication: Verify real-time data transmission.
- WiFi & 4G Stability: Test under different network conditions.
- Data Loss Rate: Ensure less than 1% packet loss.
2. Backend Testing
Ensures data integrity, API functionality, and database performance.
API Testing
Tested using Postman / Jest / Pytest.
| API Endpoint | Test Case | Expected Result |
|---|---|---|
POST /api/sensor-data | Send sample data | Data stored successfully |
GET /api/data/latest | Fetch latest readings | Returns valid JSON response |
GET /api/alerts | Query for anomalies | Returns correct alerts |
Database Testing
| Test Type | Description |
|---|---|
| Data Integrity | Ensure correct data is stored in PostgreSQL/MongoDB |
| Query Performance | Test execution time under high load |
| Data Retention | Verify old data archiving mechanisms |
3. Frontend Testing
Ensures UI/UX quality, responsiveness, and real-time data updates.
UI Testing
Tested using Cypress / Selenium.
| Test Case | Expected Behavior |
|---|---|
| Dashboard Load Time | Loads within 2 seconds |
| Graph Updates | Real-time data refresh |
| Alerts & Notifications | Displayed correctly on abnormal conditions |
| Map Integration | Sensors appear correctly on the map |
Responsiveness Testing
- Devices Tested: Mobile, Tablet, Desktop.
- Browsers Tested: Chrome, Firefox, Safari, Edge.
4. System Testing
Ensures the end-to-end functionality and robustness of the system.
Performance Testing
| Metric | Expected Outcome |
|---|---|
| Concurrent Users | Supports 100+ users |
| Data Ingestion Rate | Handles 1000+ sensor readings per second |
| Server Uptime | 99.9% availability |
Security Testing
| Test Type | Description |
|---|---|
| Authentication | Verify JWT & OAuth2 implementation |
| Encryption | Ensure TLS encryption for data transmission |
| Penetration Testing | Identify vulnerabilities using ethical hacking |
5. Deployment Testing
Ensures successful cloud deployment and scalability.
Cloud Environment Tests
- Docker Container Testing → Verify images work correctly.
- Kubernetes Load Testing → Test auto-scaling behavior.
- CI/CD Pipeline → Ensure automated deployment works.
Final Acceptance Testing
- Real-world Sensor Deployment → Test data collection in a live lake environment.
- System Stress Testing → Simulate high traffic & sensor data influx.
- User Feedback Collection → Gather insights from early users.
Conclusion
Testing is a continuous process that ensures the accuracy, reliability, and security of the IoT-Based Lake Monitoring System. By implementing unit, integration, and system testing, the system achieves high stability and performance.