INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue III, March 2025

www.ijltemas.in Page 151

IOT-Based Real-Time Air Quality Monitoring System Using

ESP8266

Manjit Kumar Nath., Debopoma Nath., Rupshikha Saikia., Nelson R Varte.,

Bornali Gogoi

Department of Computer, Application Assam Engineering College Guwahati, India

DOI : https://doi.org/10.51583/IJLTEMAS.2025.140300019

Received: 17 March 2025; Accepted: 24 March 2025; Published: 03 April 2025

Abstract: In today’s world, one of the growing concerns is

Air Pollution, due to its adverse impact on human health and

environmental quality. This research paper presents the design and implementation of a Real-Time Air Quality Monitoring

System measuring the Air Quality Index (AQI) using sensors such as MQ135, PM2.5, and DHT11. The ESP8266

microcontroller is used to collect and analyze data. The system is built to provide local display via LCD and remote display

through a web dashboard interface. The system has buzzer alerts for local alert generation when AQI thresholds are crossed, and

alert messages are generated simultaneously in the web interface. The system uses the HTTP protocol for communication and let

the users download CSV files to access the previous air quality data history. The proposed model aims to develop a low-cost, real-

time sensing Air Quality Monitor using widely available microcontrollers and sensors to bring awareness to every individual

about the harmful living environment.

Index Terms—Air Pollution, Air Quality Index (AQI), Sensors, Microcontroller, HTTP, CSV, ESP32

I. Introduction

When harmful substances including particulates and bio- logical molecules are introduced into the Earth’s atmosphere, it leads to

Air Pollution. It may cause diseases and allergies which adversely affect human health, leading to respiratory diseases such as

cardio-vascular problems and other long-term complications. It is harmful to other living organisms as well and it also affects

food crops and damages the environment. Human activities such as smoking, and the use of cleaning agents in the home

containing harmful chemicals and dust leads to air pollution. Therefore, monitoring air quality is not just a necessity for

regulatory compliance, but a vital measure to protect health and promote sustainable living.

Traditional air quality monitoring is mainly large, expensive and stationary systems that are used by governments or specialized

institutions. However, these systems are not easily accessible to the public, and they often lack real-time feedback

*All authors have equal contribution. for localized environments such as homes, offices, or small communities. To address these

limitations, this report focuses on developing a low-cost, compact and real-time air quality monitoring system using IoT

technology (Internet of Things). This proposed system uses a wireless network of low-cost sensors and hardware components

along with the necessary software to effectively monitor the quality of air in a confined close space.

The quality of air is captured using various sensors that are integrated into the system. The MQ135 sensor detects harmful gases

such as ammonia, nitrogen oxide, alcohol, and smoke that contribute to poor air quality. Particulate matter, which is among

the most dangerous pollutants due to its ability to penetrate the lungs, is measured using PM2.5 sensors. In addition,

temperature and humidity levels are monitored using DHT11 sensors. These sensors provide crucial data about the components of

air which significantly influence the dispersion and impact of pollutants. The ESP8266 microcontroller is used as the heart of the

system. It processes the sensor data and hosts the web server for the dashboard interface. The outcome of the processed data is the

Air Quality Index (AQI) value, which is a standard metric to measure air quality levels.

When air quality reaches dangerous levels, the buzzer provides an immediate auditory alert for users when AQI thresholds are

crossed, while a JHD 162A LCDs real-time data locally. The system includes a web dashboard built with HTML, CSS, and

JavaScript to extend usability and accessibil- ity. This dashboard fetches real-time data from the ESP8266 over HTTP and

displays it. When air quality thresholds are crossed, users can view live AQI, temperature, and humidity readings and receive

alerts.

The system is designed to provide actionable information on air quality for localized environments such as homes, offices, or

small communities. In addition, it seeks to cre- ate an efficient and user-friendly solution by leveraging IoT technology to

deliver real-time feedback, empowering users

to make informed decisions about their environment. It also highlights the potential of IoT technology in solving real-world

problems, paving the way for more advanced and personalized environmental monitoring solutions in the future.

Related Work

Several studies have explored IoT-based air quality monitor- ing. Hossain et al. [1] developed a low-cost IoT device using

ESP8266 and Atmega328 for real-time air quality monitoring, providing local alerts but lacking advanced web-based visu-

alization. Sahoo et al. [2] proposed an industrial air quality monitoring system using IoT, integrating multiple sensors but

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue III, March 2025

www.ijltemas.in Page 152

requiring extensive cloud-based data processing. Kayes et al. [3] designed a platform incorporating ESP32 with real- time AQI

calculations and web dashboard integration. Our proposed system improves upon these by integrating real- time data

visualization, web-based alerts, and optimized sensor calibration which enhances the system accuracy and response time.

thresholds, different actions are taken. If AQI is below 50, the green LED is activated, indicating safe air quality. If AQI falls

between 50 and 100, the system triggers a blue LED as a ventilation alert. When AQI exceeds 100, the system generates an

alert, activates a buzzer, and turns on the red LED to indicate hazardous conditions. The alert remains active until acknowledged,

ensuring prompt user intervention. This automated response mechanism improves the assessment of air quality and promotes

timely corrective measures.

System Overview

Block Diagram of the System

Fig. 1 shows the block diagram of the proposed system. The hardware consists of an ESP8266 microcontroller, which collects

real-time environmental data from multiple sensors, including temperature, humidity, dust concentration, and gas levels. The

DHT11 sensor measures temperature and humidity, while the MQ135 (gas sensor) and PM2.5 (dust sensor) detect air quality and

particulate matter levels. To achieve real-time monitoring, data is displayed on a LCD screen, and for remote access, the ESP8266

transmits sensor data to a web-based dashboard that provides live updates, analytics, and threshold alerts.

Fig. 1. Overview of the proposed air quality monitoring system.

Flow of Control

Fig.2 depicts the flowchart which illustrates the decision- making process of the air quality monitoring system. The system begins

by collecting real-time sensor data from various environmental sensors. The collected input is transmitted to the ESP module,

where it is processed to compute the equivalent value of the Air Quality Index (AQI), based on predefined

Fig. 2. Flowchart of the system.

II. Methodology

Data Acquisition

The data is continuously collected by the system from multiple sensors to monitor environmental conditions and air quality in real

time.

MQ135 Gas Sensor: The concentration of smoke, harm- ful gases such as ammonia, nitrogen oxides are measured by

this sensor. The output of this sensor is analog signals proportional to the intensity of detected pollutants, providing essential data

for air quality analysis.

PM2.5 Sensor: The fine particulate matter, focusing on particles smaller than 2.5 microns, is detected by PM2.5 sensors.

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

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Digital output ensures precise monitoring, which is a critical component in evaluating pollution levels.

DHT11 Sensor: The temperature and humidity levels recorded by DHT11 are sent as a digital signal to the ESP8266

microcontroller. This information helps to contextualize air quality trends with environmental conditions.

Real-time data update: The data is updated every two seconds for continuous and real-time monitoring of environ- mental

changes.

The integration of multiple sensors with the ESP8266 en- ables efficient data processing, ensuring that all parameters are

accurately recorded and analyzed. These sensors work together to give a detailed view of air quality, helping users understand their

environment with actionable insights in real time. With continuous data updates, the system ensures accurate and reliable

monitoring.

Data Processing

After gathering data, the ESP8266 analyzes it to extract meaningful information, including the calculation of the Air Quality

Index (AQI) value for an accurate assessment of air quality.

Threshold Declaration

The AQI values are compared by the system against prede- fined thresholds to categorize the quality of air into ”Good”,

”Moderate”, ”Poor”, and ”Hazardous”. Trigger alerts and web dashboard updates are based on the above classification, which

ensure that users receive actionable insights. Based on general air quality guidelines and environmental standards, predefined

threshold values are selected. These threshold values act as reference points to determine safe and harmful levels of

environmental conditions:

Temperature Threshold (26.0°C): The temperature threshold is set to 26.0°C, which is derived from comfort levels used in

home or office environments. When temperature exceeds the given limit, it results into affecting both air quality and personal well-

being.

Humidity Threshold (70%): Based on general recom- mendations for indoor environments, the optimal percentage for

humidity is 70% or less. High humidity levels (above 70%) are often associated with discomfort and can increase the risk of mold

growth and other environmental issues.

MQ135 Gas Sensor Threshold (100): The MQ135 gas sensor is set at a threshold value of 100, following general air quality

standards for gases such as ammonia, nitrogen oxides, and carbon dioxide. When this level is exceeded, it indicates rise in

pollution and a decline in overall air quality.

PM2.5 Sensor Threshold (500): The 500 threshold for PM2.5 levels is set on the basis of air quality standards es- tablished by

environmental health organizations. Levels above this threshold indicate dangerous air quality due to high concentrations of fine

particulate matter, which can lead to significant health risks.

These thresholds help to determine whether the air quality is within acceptable limits and allow the system to trigger alerts when

certain environmental conditions are exceeded.

Overall AQI Calculation

The final AQI value is calculated by combining the individ- ual components of the air. The PM2.5 data is given a weight of 60%,

the MQ135 data is weighted at 30%, and the DHT11 data is given a smaller weight of 10%. This weighted sum is used to

calculate the final AQI value, which is used to classify the quality of air as Good, Moderate, Poor, or Hazardous.

AQI

(0.6

pm25AQI)

(0.3

mq135AQI)

+(0.1

dht11AQI)

Data Transmission and Visualization

The processed AQI data is displayed both locally and remotely.

Local LCD Display: The JHD 162A LCD presents real- time readings for on-site monitoring.

10)

Web Dashboard: The ESP8266 transmits data to a web- based interface via HTTP requests. The dashboard, built using

HTML, CSS, and JavaScript, dynamically updates air quality readings every 2 seconds.

11)

Alert Mechanism: The system triggers a buzzer and flashes LED alerts when AQI level crosses hazardous thresh- olds. Data

Reference Index:

12)

Good Air Quality (AQI ≤ 50): When the AQI level is 50 or below, the system considers the air quality to be good. In this

case, the green LED is turned on to visually indicate that the air quality is safe.

13)

Moderate Air Quality (50

AQI ≤ 100): If the AQI

level is between 51 and 100, indicating moderate air quality, the

blue LED is activated. This provides a visual cue that air

quality is acceptable but could be improved.

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

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14)

Poor Air Quality (AQI

100): When the AQI level exceeds 100, the air quality is considered poor, and the red LED is

turned on. This alerts the user that air quality is harmful and should be addressed.

Additionally, if the AQI level exceeds 150, the air quality is considered ”very poor” and the buzzer is activated. This provides an

audible alert, which is especially useful in remote environments where visual cues may not be sufficient.

15)

System Implementation and Testing: The system is de- ployed in a real-world environment to evaluate its perfor- mance.

Sensor readings are compared with reference data from standard air quality monitoring stations to validate accuracy. Multiple test

cases are conducted under different environmen- tal conditions to assess system responsiveness, data reliability, and wireless

communication stability.

III. Result

The Air Quality Monitoring System successfully integrates multiple sensors to monitor and assess environmental condi- tions in

real-time. Throughout the project, the performance of the system was evaluated across several key parameters, including air

quality, temperature, humidity, and particulate matter, with outputs displayed on both hardware (LCD) and software (web

interface). To validate the system, sensor read- ings were compared with reference AQI data from a standard monitoring station.

Test Condition

Govt.

AQI

System

AQI

Error

(%)

Indoor(Low Pollution)

5.7%

Outdoor(Moderate

Pollution)

2.2%

Traffic Area(High

Pollution)

180

175

-2.8%

Real-Time Monitoring

The system efficiently collects and processes data from the MQ135 gas sensor, PM2.5 dust sensor and DHT11 temper- ature and

humidity sensor. Continuous data refresh ensures that readings are updated every two seconds, allowing real- time tracking of

environmental conditions. By integrating these sensors with the ESP8266 microcontroller, seamless data acquisition was achieved,

which is crucial for accurate air quality analysis.

AQI Calculation

The system successfully computes the Air Quality Index (AQI) by aggregating data from multiple sensors. Using pre- defined

thresholds, the AQI categorizes air quality into Good, Moderate, Poor, or Hazardous levels, providing users with a clear and

intuitive understanding of environmental condi- tions. In addition, a discomfort factor based on temperature and humidity is

considered which further contextualizes the AQI value, ensuring a more comprehensive assessment of air quality.

Alert System

An effective warning mechanism is implemented using color-coded LEDs and a buzzer to notify users of air quality conditions.

When AQI value crosses specific thresholds, the system triggers visual (LED) and audible (buzzer) alerts, ensuring immediate

awareness of deteriorating air quality. This real-time feedback enhances safety and allows users to take necessary precautions.

Web Interface

A user-friendly web dashboard enables remote monitoring of air quality data in real time. The dashboard dynamically updates

every two seconds, ensuring that users receive the latest sensor readings. Additional functionalities include data export in CSV

format, allowing users to store and analyze historical air quality data. The interface also features a memory reset function, which

ensures long-term system efficiency by clearing unnecessary stored data.

Data Storage and Retrieval

The system efficiently logs sensor readings along with timestamps, storing them in CSV format for easy retrieval and analysis.

The ability to download recorded data via the web interface enhances the user experience, enabling further evaluation of air

quality trends and patterns.

Calibration and Accuracy

Calibration played a critical role in ensuring accurate sensor readings. Threshold values were carefully chosen based on standard

air quality guidelines, allowing the system to cor- rectly classify air quality levels and trigger alerts as required. This calibration

process, combined with the precise sensor data, ensured that the system met the accuracy standards necessary for reliable air

quality monitoring.

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue III, March 2025

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IV. Conclusion

This paper presents an IoT-based air quality monitoring system using ESP8266 and real-time web visualization. The system

achieved an AQI calculation accuracy of ±2.5%, with a response time of 2 seconds. Compared to existing solutions, our

approach enhances efficient monitoring while maintaining affordability. Future work includes cloud-based data analytics, AI-

driven analysis of past trend, and expanded sensor integration for NO

and CO levels

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