Crowd-Sourced AQI Monitoring System

Description

An IoT-based, community-driven air quality monitoring system designed to provide real-time AQI (Air Quality Index) estimation using multiple sensors. Built for both urban and rural coverage, this project empowers individuals to participate in environmental monitoring and decision-making.

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Overview

This project presents a low-cost, scalable solution for air quality monitoring using IoT. It uses MQ-series gas sensors, particulate matter sensors, temperature & humidity sensors, and Bluetooth communication to calculate and visualize AQI in real-time.

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What is AQI (Air Quality Index)? The Air Quality Index (AQI) is a standardized system used to measure and report the quality of air in a specific location. It tells you how clean or polluted the air is, and what associated health effects might be a concern for you.

• AQI ranges from 0 to 500.
• Lower AQI = cleaner air
• Higher AQI = more polluted air

AQI Range	Air Quality	Health Impact
0–50	Good	Air quality is satisfactory
51–100	Moderate	Acceptable; some pollutants may affect very sensitive people
101–150	Unhealthy (Sensitive Groups)	May cause health effects for sensitive groups
151–200	Unhealthy	Everyone may begin to experience health effects
201–300	Very Unhealthy	Health warnings of emergency conditions
301–500	Hazardous	Health alert: everyone may be affected

AQI is calculated based on concentrations of pollutants like:

• PM2.5, PM10
• CO (Carbon Monoxide)
• O₃ (Ozone)
• SO₂ (Sulfur Dioxide)
• NO₂ (Nitrogen Dioxide)

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What is Crowd-Sourcing?

Crowd-sourcing is the practice of collecting data, services, or information by engaging a large number of people, especially from a community or public platform. In this project:

• Crowd-sourced AQI monitoring means many individuals place sensors in different locations (homes, streets, neighborhoods).
• These devices collect air quality data from multiple locations simultaneously.
• The data is combined to create a detailed and widespread pollution map, much more efficiently and cheaply than using a few government stations.

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Hardware Used

Component	Functionality
Arduino UNO	Main microcontroller
MQ135	CO₂, NH₃, benzene detection
MQ7	Carbon Monoxide (CO)
MQ2	Smoke, LPG, Methane
PMS5003	PM2.5, PM10 detection
DHT11 / DHT22	Temperature & Humidity
BME280	Pressure, Temp, Humidity
HC-05 Bluetooth	Mobile communication
16x2 LCD Display	Real-time local display

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Block Diagram

System Design

My Crowd-Sourced AQI Monitoring System is designed using IoT architecture with low-cost, easily available hardware components. It consists of:

1. Sensor Unit

• Gas Sensors: MQ135, MQ7, MQ2 – detect CO₂, NH₃, CO, smoke, etc.
• Particulate Matter Sensor: PMS5003 – measures PM2.5 and PM10.
• Environmental Sensors: DHT11/DHT22 and BME280 – for temperature, humidity, and pressure.

2. Processing Unit

• Arduino UNO: Reads data from all sensors and processes it.

3. Display Unit

• 16x2 LCD: Displays real-time values of gas concentrations, PM levels, temperature, humidity, and calculated AQI.

4. Communication Module

• HC-05 Bluetooth: Sends processed data to a mobile app for visualization and logging.

5. Crowd-Sourcing

• Multiple such devices are deployed in various locations by different users (the crowd), forming a distributed monitoring network.

6. Optional Mobile App

• Receives real-time AQI data via Bluetooth.

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Working Principle

1. Data Sensing

Each sensor continuously reads the concentration of gases (like CO, CO₂, NH₃), particulate matter (PM2.5, PM10), temperature, and humidity.

2. Data Processing

• Arduino processes the raw values.
• Using standard EPA formulas, it calculates the AQI for each pollutant.
• The maximum AQI among CO, PM2.5, PM10 is selected as the overall AQI.

3. Display and Transmission

• The AQI and sensor readings are shown on the LCD.
• The same data is sent to a connected mobile device via Bluetooth.

4. Crowd-Sourcing Model

• When many users deploy this system in different areas, a network of real-time AQI monitors is created.
• This increases the spatial coverage and data accuracy of air quality reports.

5. Validation

The system's output was compared with official AQI data from the US Embassy in Islamabad and showed 99% accuracy.

Sample AQI Calculation

Pollutant	Concentration	AQI Value	AQI Category
PM2.5	162 µg/m³	212.5	Very Unhealthy
PM10	170 µg/m³	108.4	Unhealthy (Sensitive Groups)
CO	0.32 ppm	3.6	Good
Overall AQI	—	212.4	Very Unhealthy

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Methodology

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Results & Analysis

Taken on 19th December, 2024 – 10:42 PM – Islamabad

Parameter	Value	AQI Value	Health Impact
PM2.5	162 µg/m³	212.40	Very Unhealthy
PM10	170 µg/m³	108.42	Unhealthy (Sensitive)
CO	0.32 ppm	0	Good

• Our AQI: 212.40
• Accuracy: 99% vs US Embassy AQI System

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Future Work

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Contributors

• Awais Asghar
• Muhammad Hammad Sarwar
• Muhammad Ashar Javid
• School of Electrical Engineering & Computer Science (SEECS), NUST