Real-Time Air Quality Monitoring System: Computer Engineering Guide
1. Introduction
Overview of the project.
Objectives of the system: Develop a real-time system for monitoring air quality parameters such as PM2.5, PM10, CO2, and AQI to ensure environmental health and safety.
Scope of the system: Applicable for urban areas, industrial zones, and indoor spaces.
2. Requirements Analysis
Functional Requirements:
· - Measure air quality parameters like particulate matter, CO2, temperature, and humidity.
· - Display real-time data on a web dashboard or mobile app.
· - Send alerts for poor air quality levels.
· - Store historical data for trend analysis.
Non-Functional Requirements:
· - Accurate sensor readings.
· - Reliable and uninterrupted data transmission.
· - Scalable for multiple monitoring stations.
3. System Design
Architecture:
· - IoT-based architecture with sensors, microcontrollers, and cloud integration.
· - Use of wireless communication protocols like Wi-Fi or LoRaWAN.
Data Flow Diagrams (DFDs):
· - Level 0: Overview of data collection, processing, and display.
· - Level 1: Detailed processes for sensor readings, data analysis, and alert generation.
Database Design:
· - Tables: Sensor Data, Alerts, Historical Data.
4. Technology Stack
Hardware:
· - Sensors: PM2.5/PM10 sensor (e.g., SDS011, PMS5003), gas sensor (e.g., MQ series), temperature and humidity sensor (e.g., DHT22).
· - Microcontroller: Arduino, Raspberry Pi, or ESP32 for data acquisition and processing.
Software:
· - IoT platforms: ThingSpeak, AWS IoT, or Azure IoT Hub for data management.
· - Backend: Python (Flask/Django) or Node.js for server-side processing.
Frontend:
· - Web dashboard using React, Angular, or Vue.js.
· - Mobile app using Flutter or React Native for real-time monitoring.
5. Implementation
Sensor Integration:
· - Connect sensors to microcontrollers and test for accurate readings.
· - Calibrate sensors as per manufacturer specifications.
Data Transmission:
· - Use MQTT or HTTP protocols to send data to the cloud.
· - Implement efficient data encoding for optimized transmission.
Dashboard and Visualization:
· - Develop a dashboard for real-time monitoring of air quality parameters.
· - Include features for historical data analysis and export options.
Alerts and Notifications:
· - Implement thresholds for air quality levels and generate alerts for deviations.
· - Send notifications via email, SMS, or mobile app.
6. Security
Encrypt data during transmission using secure protocols like TLS.
Authenticate devices using secure tokens or certificates.
Ensure secure storage of historical data.
7. Testing
Unit Testing: Validate individual components such as sensor readings and data transmission.
Integration Testing: Ensure proper interaction between sensors, microcontrollers, and the cloud.
System Testing: Test the complete system under real-world conditions for reliability.
Performance Testing: Assess the system’s handling of high data volumes and multiple sensors.
8. Deployment
Deploy sensors and microcontrollers in the desired locations.
Host the software platform on a reliable cloud server.
Provide user documentation and training.
9. Maintenance and Updates
Calibrate sensors regularly for accuracy.
Monitor system performance and address issues promptly.
Update the software with enhanced features and algorithms.
10. Appendix
Glossary of terms.
References and additional resources.