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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

SensorTest MethodExpected Outcome
pH SensorTest with known buffer solutionsAccuracy ±0.1 pH
Temperature SensorTest in controlled water samplesAccuracy ±0.5°C

Connectivity & Communication Testing

  • MQTT Communication: Verify real-time data transmission.
  • WiFi 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 Pytest.

MethodAPI EndpointTest CaseExpected Result
POST/api/v1/sensors/readingsSend sensor dataData stored successfully
GET/api/v1/sensors/readings/latestFetch latest readingsReturns valid JSON response
GET/api/v1/alertsQuery for anomaliesReturns correct alerts
GET/api/v1/sensorsRetrieve all sensor nodesReturns list of sensors
GET/api/v1/dashboard/statsFetch dashboard statisticsReturns system stats

Database Testing

Test TypeDescription
Data IntegrityEnsure correct data is stored in PostgreSQL/MongoDB
Query PerformanceTest execution time under high load
Data RetentionVerify old data archiving mechanisms

3. Frontend Testing

Ensures UI/UX quality, responsiveness, and real-time data updates.

Test CaseExpected Behavior
Dashboard Load TimeLoads within 2 seconds
Graph UpdatesReal-time data refresh
Alerts & NotificationsDisplayed correctly on abnormal conditions
Map IntegrationSensors 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

MetricExpected Outcome
Concurrent NodesSupports 100+ nodes
Data Ingestion RateHandles 1000+ sensor readings per second
Server Uptime99.9% availability

5. Deployment Testing

Ensures successful cloud deployment and scalability.

Cloud Environment Tests

  • Docker Container Testing → Verify images work correctly.
  • 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.