Design and Implementation of an IoT‑Based Air Quality Monitoring

and Control System

Anist A., Mohammed Afrideen Ismail A. and Muralikrishnan K.

Department of Electronics and Communication Engineering, St. Joseph’s Institute of Technology, Chennai, Tamil Nadu,

India

Keywords: Air Quality Monitoring, Gas Detection, Real‑Time Alerts, Air Purification, Hazardous Gas Management,

Environmental Safety, Health Improvement.

Abstract: Air pollution is a serious threat to public health and environmental sustainability, particularly in industries

and confined areas where poisonous gases have the potential to aggregate. The current systems of air-quality

monitoring are costly and do not provide real-time intervention. To overcome this, we intend to implement a

low-cost and automated air-quality monitoring and purification system incorporating MQ2 and MQ7 gas

sensors, ESP8266, an LCD, a buzzer, and an air purifier. The novelty of this work comes from the fact that it

cannot only sense dangerous gases in real time but also act upon it immediately by triggering an air purifier,

thus taking a proactive stance towards air-quality control. The system incorporates an L293D motor driver

for driving and is powered with a low-power supply, which makes it very effective on an economical scale.

By allowing for early detection and rapid mitigation, this system promotes safety and adds to an indoor

environment that is healthier, providing a sensible solution for industrial, laboratory, and residential use.

1 INTRODUCTION

Air quality is a key factor determining human health

and environmental sustainability, especially in

regions where toxic gases can build up to harmful

concentrations. The growing number of air pollution

events and the related risks to human health

underscore the necessity for efficient and cost-

effective air quality monitoring systems. This project

presents a (N. Hossein Motlagh et al.,2023) complete

system intended to monitor and enhance air quality

utilizing MQ2 and MQ7 gas sensors, a buzzer, and an

air purifier. The project seeks to counter the

difficulties with poor air quality, particularly in

sensitive areas like industrial establishments,

laboratories, and indoors, where the buildup of unsafe

gases can result in major health and safety hazards.

The system uses gas detection technology and

sophisticated integrated circuits for real-time

detection and prompt response against deterioration

in air quality. The MQ2 sensor is commonly used (D.

Iskandaryan et al. 2023) to detect different gases,

including carbon monoxide, methane, and LPG. To

complement this, the MQ7 sensor is carbon monoxide

specific, being colorless and odorless but highly

toxic. Both offer sufficient protection for the majority

of the dangerous gases that could be anticipated in the

region being monitored, and with their assistance, the

system is able to rapidly identify the presence of

potential air quality dangers.

When gas levels surpass specified safety limits,

the system sounds a buzzer to warn occupants or

concerned authorities. This instant (R. Purbakawaca

et al. 2022) warning allows appropriate measures to

be taken in a timely manner to avoid possible damage.

In addition, the system has a built-in air purifier that

automatically kicks in to counteract the presence of

toxic gases. This anticipatory measure not only

enhances air quality but also curtails the effects of

long-term exposure to toxicants, which can cause

critical health problems such as respiratory illnesses

and cardiovascular disorders.

The design of the system will be minimalist and

cost-effective, hence general-purpose. In particular,

the system will be based around the ESP8266

microcontroller, which is handling data gathered and

the (L. Miasayedava et al. 2023) functionality of the

system. Real-time data from gas sensors will be

projected on an LCD display such that users are

immediately aware of the air quality status. The

power supply unit will guarantee consistent

operation, whereas the L293D motor driver will

A., A., A., M. A. I. and K., M.

Design and Implementation of an IoT-Based Air Quality Monitoring and Control System.

DOI: 10.5220/0013914100004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 4, pages

413-420

ISBN: 978-989-758-777-1

413

regulate the buzzer and air purifier for their smooth

integration into the system. Such air quality

monitoring system is especially useful in settings

where conventional ventilation techniques can be

inadequate or even unfeasible. In industrial buildings,

for example, the buildup (M. A. Zaidan et al., 2022)

of gases such as methane or carbon monoxide can

result in explosion risks or poisoning threats. In the

same way, laboratories that work with volatile

chemicals need to be constantly monitored to prevent

accidents to human personnel. Even in domestic

areas, where the use of LPG for cooking is prevalent,

a system like this can be an added security measure

by being able to sense gas leaks and ensuring a clean

indoor environment.

Aside from its direct advantages, this system is a

major breakthrough in solving the larger problem of

air quality management. Air pollution is a worldwide

pressing issue, responsible for causing millions (X.

Lin et al. 2022) of premature deaths every year and

fueling climate change. Through offering a

dependable and cost-effective means of monitoring

air quality around the clock, this system gives

individuals and organizations the ability to take

proactive action to safeguard human health and the

environment. The potential applications for this type

of system do not end at health and safety. The

compiled data incorporated into broader systems

might help go towards smart city initiatives that

facilitate the upkeep and regulation of urban air

quality. Such data would also be beneficial for

research into trying to comprehend trends of pollution

and find effective measures to mitigate it. In addition,

the modular construction of the system would make it

expandable at a later point, such as with the

installation of sensors to detect other sources of

pollutants or connecting it to a feature enabling long-

distance control and monitoring.

The suggested system for air quality monitoring

provides an effective and worthwhile solution (Y.

Cao et al 2024) to air quality problems facing vital

locations. By taking advantage of sophisticated

sensor technology, real-time processing, and

automated response systems, it enables safety and

healthier environments. Its cost-effectiveness and

versatility render it applicable to a broad variety of

uses, from factories to homes, leading to a safer,

healthier, and more sustainable world. This project

emphasizes the need for the incorporation of

technology into environmental management, laying

the ground for innovations that ensure both human

welfare and the globe.

This work is organized as Section II presenting a

review of the literature survey. Section III describes

the methodology, highlighting its key features and

functionality. Section IV discusses the results,

analysing the system's effectiveness. Lastly, Section

V concludes with the main findings and explores

future implications.

2 LITERATURE SURVEY

Air quality monitoring is a heavily researched

subject due to pollution causing health and

environmental issues. Study mentions the systems

that can detect toxic gases and pollutants in different

environments, such as industrial, urban and

residential. These systems are primarily used to

provide real-time data to monitor air quality and

increase awareness about possible hazards. Studies

suggest that detection of air pollutants, since most of

these pollutants are harmful in the long term,

including carbon monoxide, methane, particulate

matter (PM), etc. Attention should be paid to

detection when the concentration of air pollutants in

the environment is low or air pollutant particles are

ineffective, to avoid long-term irreversible effects.

The development of affordable and reliable solutions

has been a key emphasis, to foster widespread

adoption and accessibility.

And the research suggests ways to reduce the

harmful effects of air pollution on human health and

the environment. Recent scientific publications have

focused on new approaches to recognize toxic

pollution and monitor air quality smartly (G. A.

López-Ramírez and A. Aragón-Zavala, 2023) in real

time. These indicate the need for a monitoring system

to mitigate the risk from toxic exposure and to ensure

compliance with tolerable limits. However, there is

potential for increased pollution in laboratories,

industries, and urban areas with thick human

collections where these monitoring systems are

useful. Air quality solutions that are good, make good

air make for good spaces that are good for health and

the environment.

The study explore approach to detecting and

mitigating air pollution in areas that matter. Research

centers on systems which (S. Al-Eidi, et al. 2023)

continuously monitor the presence of harmful agents

such as carbon monoxide, methane, and particulate

matter to provide health hazards. They are intended

to warn people promptly and promote interventions

to prevent exposure to toxic gases. Such systems will

thus inevitably have more interest in the practical use

of monitoring solutions in, for example, factories,

urban spaces, or residential areas. The study

highlights the need for continuous monitoring to

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

414

combat pollution problems and improve public health

and the environment.

Air quality monitoring for human health and

environmental safety has focused on real-time

pollution assessment research. In studies (H. A. D.

Nguyen and Q. P. Ha et al.2022) the evaluation of a

system to analyze (N. Liu et al. 2022) and even

perform early intervention against exposure to toxic

pollutants was performed. Issues resulting in

accumulation of dangerous gases in industrial and

urban areas lead research to emphasize the

importance of continuous monitoring in such areas.

Because on this matter, efficient solutions link to

raising awareness of pollution levels and nurturing

approaches to maintain air quality standards at safe

levels. It has been observed for the monitoring

system to minimize health related hazards due to

pollution and support the endeavor of environmental

management.

The work addresses the need for reliable

solutions to identify and control air pollution. Studies

focus on monitoring systems designed to assess

pollutant levels in real-time and provide actionable

(C. Liu et al. 2023) data for intervention. Researchers

emphasize the importance of monitoring air quality in

environments with elevated risks, such as urban areas,

workplaces, and laboratories. Monitoring systems

play a vital role in identifying pollution trends and

implementing safety measures to minimize health

risks. Research demonstrates that air quality

monitoring supports long-term sustainability goals by

mitigating environmental and health impacts caused

by air pollution.

The work has been one of the widely studied

systems because of the growing concern about

pollution and its health effects. Research has been

carried out to show different approaches in

identifying the pollutants, for instance, carbon

monoxide (L. Pang et al 2023), volatile organic

compounds, and particulate matter, that pose serious

risks. Systems intended for real-time monitoring are

assessed regarding their potential contribution toward

better security of the public and the environment.

Emphasis is based on deployment in high-risk areas,

such as urban centers and industrial zones.

The study has emphasized the need for

identification and mitigation in areas where air

quality is such that health and safety are affected. The

studies (S. Berkani et al. 2023) are directed towards

real-time systems that offer the capability for

pollutant detection and provide insights into

actionable information for the prevention of harm.

Applications are industrial, urban, and residential,

where air quality monitoring is important as part of

complying with the set standards of safety. The

literature highlights monitoring can raise awareness

of risks due to pollution and allow timely

intervention. Contributing to this research are efforts

toward lessening health issues related to pollution and

increasing sustainability across different settings.

The paper assesses creative strategies for

pollution control (G. Ramirez-Espinosa et al. 2024)

and the related hazards. Research focuses on systems

built to constantly monitor air quality and send alerts

for prompt intervention. Applications range from

industrial to urban and residential environments,

focusing on detecting noxious pollutants in order to

mitigate health risks. However, reliable data are

needed to implement safety measures and promote

effective air quality management. These initiatives

are part of a larger environmental framework, as

tracking systems inform approaches to reducing

pollution and improving human health.

This research explores management strategies in

order to prevent and identify pollution in public

health and safety hotspots. These studies emphasize

systems that can measure pollutant levels in real

time, providing the necessary data for people to act.

These fields are particularly relevant in high-risk

environments, such as industrial facilities and urban

centers where pollution exposure is higher. To

mitigate toxic pollutant emissions and air

contamination, research stresses the need for

ongoing monitoring. Thanks to them we have safer

environments and more strong efforts in

sustainability.

Pollution is a longstanding problem that is

becoming more challenging to manage; the research

reported here focuses on both real-time detection and

mitigation of the impact. Research focuses on

applications that detect contaminants in various

settings such as industrial properties, city areas, and

residences (E. I. Fernández et al. 2024). The

researchers underscore the value of ongoing

monitoring in both awareness of air quality

challenges and in enabling preventative actions. Such

systems promote health and safety by minimizing

exposure to hazardous materials. This study

highlights how monitoring and compliance is a major

means of ensuring adherence to these standards to

drive long-term efforts to prevent the detrimental

effects of pollution on human health and the

ecosystem.

The study has attracted much attention following

an increasing concern about pollution and its

consequences on health and safety. To detect

pollutants (F. Naz et al., 2023) and evaluate air

quality at places that are critical, the research answers

Design and Implementation of an IoT-Based Air Quality Monitoring and Control System

415

certain solutions. These are done to provide real-

time monitoring that enables the collection of credible

data at all times to facilitate early intervention to

prevent exposure to harmful substances. This has

applications for industrial output and urban,

residential groups that experience significant

pollution. Overall, these studies confirm that such

systems can turn back the tides of pollution, ensure

the continuation and improvement of public health,

and provide reinforcement for general goals around

sustainability.

The research evaluates the effectiveness of

systems designed to address pollution in high-risk

areas. Studies highlight real-time monitoring

solutions that provide data on pollutant levels and

enable proactive responses to deteriorating air

quality. Key applications (J. Pellegrino et al. 2025)

include industrial zones, urban environments, and

laboratories, where exposure to harmful substances

must be minimized. Continuous monitoring is

recognized for its role in improving safety and

compliance with health standards. The literature

emphasizes that air quality monitoring not only

protects human health but also supports

environmental management efforts aimed at reducing

pollution's long-term impacts.

The work is geared toward solving the challenges

arising from pollution. The studies have focused on

the detection and analysis of pollutants (F. Gandino

et al. 2023) to ensure a safe and healthy environment.

Additionally, real-time systems are called for in light

of their ability to provide exact and timely data that

aids in quick interventions in the most needed

locations. The applications vary from urban areas to

industrial settings where pollution is likely to be high.

Researchers also express that air quality monitoring

ensures awareness, reduction of health risks, and

sustainability that help in creating healthier and

greener communities.

The work addresses the urgent need for effective

pollution management systems. Research focuses on

solutions capable of detecting (M. A. Zaidan et al.,

2023) harmful pollutants and providing real-time

insights into air quality. Studies underline the

significance of monitoring in environments where

health risks are heightened, such as industrial

facilities and urban centers. These systems facilitate

timely actions to mitigate exposure to toxic

substances, ensuring compliance with safety

regulations. Research demonstrates that air quality

monitoring plays a vital role in improving public

health outcomes and advancing broader efforts to

reduce pollution's impact on the environment.

3 METHODOLOGY

Air pollution is one of the significant health and

environmental hazards, particularly in enclosed

spaces where toxic gases can accumulate. These

hazards must be contained, requiring efficient air-

quality monitor and improvement system. Traditional

monitoring systems are passive and costly, which

leads to a lack of adaptability. This paper describes

an inexpensive way of monitoring and purifying air

quality using MQ2 and MQ7 gas sensors, an

ESP8266 microcontroller, a buzzer and an air

purifier. The system acts not only by detecting toxic

gases in real time but also by applying immediate

corrective actions. This is a preventive measure that

moves air quality into the management phase and

makes it safe and sustainable under various

conditions. Figure 1 shows the block diagram.

Figure 1: Block Diagram.

3.1 System Architecture

It consists of some hardware, which are combined to

map the air quality and to clean it. Both the MQ2 and

MQ7 identify the gas components like carbon

monoxide, methane and LPG, while the MQ7 only

identifies carbon monoxide. Real-time sensor data is

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

416

written in the ESP8266 microcontroller and used to

determine if gas concentrations are above specific

thresholds or not. If unsafe levels are detected, an

alarm buzzer sounds, and the air purifier is activated.

The LCD screen shows constant air quality

information for real-time monitoring. A stable power

supply powers all elements of the system, ensuring

continuous operation of the air purification units

when needed.

3.2 Sensor Calibration

Because MQ2 and MQ7 are gas sensors, they need

calibration to make sure the output gas concentration

is accurate. Each sensor must be subjected to known

concentrations of gases to determine its baseline

resistance. These sensors operate on the principle

that the resistance across them changes when they are

exposed to different gas species. Sensor output is

taken in a controlled environment to prepare a

calibration curve. This calibration data is stored in

the ESP8266 microcontroller and is used to convert

sensor output to actual gas concentration

measurements. Proper calibration ensures the

accuracy of the system, avoiding false-positive

readings and enabling accurate monitoring of

damaging gas levels in real-time air-quality

monitoring applications.

3.3 Data Collection

In this phase, the ESP8266 microcontroller keeps

taking data from the calibrated MQ2 and MQ7

sensors. It reads sensor readings at intervals and

compares it with a predefined safety limit. The

system logs gas concentration readings, tracking air-

quality trends over time. An LCD display reads data

out for real-time visualization, allowing feedback

right away. In necessary areas, the data extracted can

also be transmitted without wires for monitoring

purposes. This real-time air-quality awareness assists

in the rapid intervention of mitigating harmful health

effects of prolonged exposures to toxic gases and

ongoing data collection.

3.4 Threshold Detection and Alert

Mechanism

Threshold concentrations of gas must be defined

beforehand from safety standards and also from

sensor calibration data. If the values read by the

sensors exceed the defined parameters, an alert

mechanism is activated by the system. The buzzer is

a noise alarm that informs members of the household

that something is wrong. Simultaneously, an LED

light indicator on top of the LCD display provides a

visual alert. This two-tier warning array ensures

users detect air-quality issues right away. As long as

gas levels are above the safety threshold, the alert

system remains active. Such alerts, when coupled

with each other, help improve safety by providing

early warnings and allowing timely action to avoid

exposure to hazardous gases.

3.5 Automatic Air Purification System

The air purifier is automatically powered on if gas

levels are over safety thresholds. The L293D motor

driver is employed for motor control to ensure

effective operation. The purifier is kept on until the

sensors are able to detect safe levels of air quality.

Automation minimizes human interaction and

ensures a consistent reaction to worsening air quality.

The purification system ensures the elimination of

toxic gases, making the indoor environment safer.

With automatic purification integrated into the

system, it not only monitors air pollution but also its

effect, providing a complete solution to air-quality

enhancement.

3.6 Communication and Power

Management

The ESP8266 microcontroller allows for wireless

connectivity, which makes remote monitoring

features available if required. The system is able to

send real-time air-quality data to a cloud platform,

which makes it easy for users to monitor

environmental conditions remotely. The power

management unit ensures stable voltage regulation to

all components, thus eliminating power variations

that might impair sensor accuracy. The system is

powered to run on low power, thus it is ideal for

round-the-clock monitoring in industrial, laboratory,

or home environments. Efficient power management

maximizes the operational life of the system and

guarantees stable performance, even in power-

constrained or varying supply environments.

3.7 Testing and Validation

The system is thoroughly tested to assess its accuracy,

response time, and efficiency under actual operating

conditions. Sensors are subjected to testing in

industrial environments, laboratories, and enclosed

spaces to evaluate their dependability under diverse

atmospheric conditions. The system's performance in

accurately measuring gas concentrations and

Design and Implementation of an IoT-Based Air Quality Monitoring and Control System

417

initiating proper alerts is tested against reference air-

quality monitoring equipment. Performance

parameters like response time, false alarm rate, and

purification efficiency are examined. The ultimate

implementation makes sure that the system is reliable

and able to give good air-quality monitoring and

improvement in real-world applications.

4 RESULT AND DISCUSSION

The proposed air-quality monitoring system was

tested under varying environmental conditions to

evaluate its performance in detecting toxic gases and

improving indoor air quality. For accurate detection

of carbon monoxide, methane, and LPG, the MQ2

and MQ7 sensors were calibrated with standard

concentrations of gases. The time response of the

system was determined by activating the sensors

under a particular concentration of gases and counting

how long it took to turn on the buzzer and air purifier.

These readings showed that the sensors could

measure gas concentration from about 5 to 10

seconds, and the interval depended on the type and

concentration of gas.

For assessing system performance, gas

concentration levels were measured before and after

switching on the air purifier. Under a controlled

setting with high carbon monoxide concentrations,

the air purifier lowered concentrations by about 40%

in 10 minutes, indicating its performance in

enhancing air quality. Similar decreases were

witnessed for methane and LPG but with varying

efficiency depending on the initial concentration

levels. The real-time monitoring function offered

constant updates on air quality condition, showing

gas concentration values on the LCD display. The

sensors' precision was tested using a comparison

against a reference gas analyzer. It was found that the

reading deviations were within ±5%, demonstrating

that the envisioned system is not far from what is

required to provide accurate, real-time analysis.

Minor disparities were, however, found with the

sensors operated in mixed-gas environments,

suggesting potential issues of cross-sensitivity. Such

a limitation poses the necessity to apply sensor fusion

methods to allow for greater confidence in multi-gas

detection settings.

From figure 2, one of the key features of the

analysis was the performance of the buzzer alarm

system. The system actuated the buzzer instantly once

gas levels exceeded specified safety levels, warning

residents in a matter of seconds. This feature

facilitates a quick reaction to dangerous gas buildup,

preventing possible health harm. The purifier

activation by the system automatically on the basis of

gas concentration levels also relieved the need for

human intervention.

Figure 2: Simulated Output.

The system was also subjected to various

environmental tests, including fluctuating

temperatures and humidity. In results, very high

humidity values were found to slightly impact

response times of the sensors, introducing minor

delays into detection. Regardless, overall

functionality of the system was not hindered, thus

demonstrating its adaptability in any environment. In

addition, the use of algorithms for temperature and

humidity compensation might further improve

performance of the sensors under changing

environments.

A cost comparison was done to evaluate the new

system against traditional air-quality monitoring

systems. The implementation cost was much less than

commercial gas analyzers, and hence this system is a

cost-effective option for industrial and domestic use.

The ESP8266-based wireless connectivity also

provides scope for future development, such as IoT-

based monitoring and remote access. Practically, the

system was deployed in a sealed room with

intermittent exposure to cooking gas and vehicle

exhaust. Around-the-clock monitoring for a week

showed trends of gas buildup, with peak

concentrations during certain times of the day. These

data can be used for predictive maintenance so that

proactive actions are taken before air quality becomes

hazardous.

Overall, the findings confirm the system's ability

in delivering real-time gas detection, instant alerts,

and efficient air purification. Although the system

works efficiently under normal conditions, further

refinements, including adaptive filtering algorithms

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

418

and sophisticated data analytics, may further enhance

its accuracy and efficiency.

5 CONCLUSIONS

The patent successfully demonstrates a low-cost, real-

time air-quality monitoring and enhancement system

that reports gas concentrations and activates an air

purifier from delayed gas concentrations in remote

areas by means of MQ2 and MQ7 (gas) sensors using

ESP8266 microcontroller, buzzer, and air purifier. It

is capable of detecting hazardous gases such as

carbon monoxide, methane, and LPG, and issue an

immediate warning via a buzzer while activating an

air purifier automatically to avoid potential threats.

These elements together create a self-sustaining

system that ensures more security against indoor time

in industrial, laboratory, and dwelling places. Years

of experience have been built on experiences, we

carried out experiments to ensure the system can

detect and react to dangerous gas concentration

within only a few seconds since detected, to assure

prompt actions. Under performance in background

gas environment, slight error (< 5% in average

relative to commercial gas analysers) was recorded

within the acceptable limit of accuracy from the data

of these sensors. The system was effective in

achieving a reduction of concentrations of carbon

monoxide, methane, and LPG, justifying its use

towards the mitigation of air pollution. The buzzer

alarm system did its job well, warning residents, or

the authorities if necessary, if gas levels exceeded the

safety limits.

By being able to eliminate harmful gases sans the

need for human intervention, the automated air

purification process adds a valuable practicality to the

system. Tests under different environmental

conditions, such as temperature and humidity

fluctuations, showed small differences in

performance but the overall functionality of the

system was not impacted. The work also emphasizes

the system’s cost-effectiveness compared to

commercial gas analyzers, making it a potentially

low-cost solution for long-term air-quality

monitoring. Despite its efficiency, the study

acknowledges its flaws; for instance, the sensors are

cross-sensitive and have low responses in mixed

gases, with slight delays in over-high humidity.

These issues can be addressed with further

refinements, for example sensor fusion techniques

and adaptive calibration schemes. IoT-enabled

remote health monitoring and predictive analytics

integration can even more adapt the system, making

it responsive and intelligent.

Its future applications involve optimizing air-

quality management through high-accuracy machine

learning models for anticipating gas build-up trends

and process-based optimization of air cleansing

activities. Further, the system is implementable for

intelligent home automation with optimal

environment management. Additionally, integrating

energy-saving hardware in its setup will ensure the

possibility of long-term field deployment while

utilizing negligible amounts of power. The research

offers an all-around, result-driven method of air-

quality monitoring and improvement. Through real-

time gas detection, instant alarm, and active

purification, the system helps provide a healthier and

safer indoor atmosphere. The results confirm its real-

world application and open the door to further

developments in smart air-quality management.

REFERENCES

C. Liu, G. Pan, D. Song and H. Wei, "Air Quality Index

Forecasting via Genetic Algorithm-Based Improved

Extreme Learning Machine," in IEEE Access, vol. 11,

pp. 67086-67097, 2023, doi:

10.1109/ACCESS.2023.3291146.

D. Iskandaryan, F. Ramos and S. Trilles, "Graph Neural

Network for Air Quality Prediction: A Case Study in

Madrid," in IEEE Access, vol. 11, pp. 2729-2742, 2023,

doi: 10.1109/ACCESS.2023.3234214.

E. I. Fernández, A. J. J. Valera and J. T. F. Breis,

"Improving Air Quality Zoning Through Deep

Learning and Hyperlocal Measurements," in IEEE

Access, vol. 12, pp. 38700-38716, 2024, doi:

10.1109/ACCESS.2024.3374208.

F. Naz et al., "Comparative Analysis of Deep Learning and

Statistical Models for Air Pollutants Prediction in

Urban Areas," in IEEE Access, vol. 11, pp. 64016-

64025, 2023, doi: 10.1109/ACCESS.2023.3289153.

F. Gandino, P. Chiavassa and R. Ferrero, "Measuring

Particulate Matter: An Investigation on Sensor

Technology, Particle Size, Monitoring Site," in IEEE

Access, vol. 11, pp. 108761-108774, 2023, doi:

10.1109/ACCESS.2023.3319092.

G. A. López-Ramírez and A. Aragón-Zavala, "Wireless

Sensor Networks for Water Quality Monitoring: A

Comprehensive Review," in IEEE Access, vol. 11, pp.

95120-95142, 2023, doi:

10.1109/ACCESS.2023.3308905.

G. Ramirez-Espinosa, P. Chiavassa, E. Giusto, S. Quer, B.

Montrucchio and M. Rebaudengo, "Improving Data

Quality of Low-Cost Light-Scattering PM Sensors:

Toward Automatic Air Quality Monitoring in Urban

Environments," in IEEE Internet of Things Journal, vol.

Design and Implementation of an IoT-Based Air Quality Monitoring and Control System

419

11, no. 17, pp. 28409-28420, 1 Sept.1, 2024, doi:

10.1109/JIOT.2024.3405623.

H. A. D. Nguyen and Q. P. Ha, "Wireless Sensor Network

Dependable Monitoring for Urban Air Quality," in

IEEE Access, vol. 10, pp. 40051-40062, 2022, doi:

10.1109/ACCESS.2022.3166904.

J. Pellegrino, H. Aziza, M. Guerin, P. Taranto, W.

Rahajandraibe and B. Ravelo, "Development of a

Multi-Sensor Mobile Device for Urban Air Quality

Monitoring at the Street Corner: The SMILE Project,"

in IEEE Access, doi: 10.1109/ACCESS.2025.3530145.

L. Miasayedava, J. Kaugerand and J. A. Tuhtan,

"Lightweight Open Data Assimilation of Pan-European

Urban Air Quality," in IEEE Access, vol. 11, pp.

84670-84688, 2023, doi:

10.1109/ACCESS.2023.3302348.

L. Pang, C. Luo and W. Pan, "Research on the Impact of

Indoor Control Quality Monitoring Based on Internet of

Things," in IEEE Access, vol. 11, pp. 139614-139627,

2023, doi: 10.1109/ACCESS.2023.3336706.

M. A. Zaidan et al., "Dense Air Quality Sensor Networks:

Validation, Analysis, and Benefits," in IEEE Sensors

Journal, vol. 22, no. 23, pp. 23507-23520, 1 Dec.1,

2022, doi: 10.1109/JSEN.2022.3216071.

M. A. Zaidan et al., "Intelligent Air Pollution Sensors

Calibration for Extreme Events and Drifts Monitoring,"

in IEEE Transactions on Industrial Informatics, vol. 19,

no. 2, pp. 1366-1379, Feb. 2023, doi:

10.1109/TII.2022.3151782.

N. Liu, X. Liu, P. -T. Lin, Y. Wang and L. Zhang,

"Enhanced Air Quality Inference via Multi-View

Learning with Mobile Sensing Memory," in IEEE

Access, vol. 10, pp. 36616-36628, 2022, doi:

10.1109/ACCESS.2022.3164506.

N. Hossein Motlagh et al., "Unmanned Aerial Vehicles for

Air Pollution Monitoring: A Survey," in IEEE Internet

of Things Journal, vol. 10, no. 24, pp. 21687-21704, 15

Dec.15, 2023, doi: 10.1109/JIOT.2023.3290508.

R. Purbakawaca, A. S. Yuwono, I. D. M. Subrata, Supandi

and H. Alatas, "Ambient Air Monitoring System with

Adaptive Performance Stability," in IEEE Access, vol.

10, pp. 120086-120105, 2022, doi:

10.1109/ACCESS.2022.3222329.

S. Al-Eidi, F. Amsaad, O. Darwish, Y. Tashtoush, A.

Alqahtani and N. Niveshitha, "Comparative Analysis

Study for Air Quality Prediction in Smart Cities Using

Regression Techniques," in IEEE Access, vol. 11, pp.

115140-115149, 2023, doi:

10.1109/ACCESS.2023.3323447.

S. Berkani, I. Gryech, M. Ghogho, B. Guermah and A.

Kobbane, "Data Driven Forecasting Models for Urban

Air Pollution: MoreAir Case Study," in IEEE Access,

vol. 11, pp. 133131-133142, 2023, doi:

10.1109/ACCESS.2023.3331565.

X. Lin, H. Wang, J. Guo and G. Mei, "A Deep Learning

Approach Using Graph Neural Networks for Anomaly

Detection in Air Quality Data Considering

Spatiotemporal Correlations," in IEEE Access, vol. 10,

pp. 94074-94088, 2022, doi:

10.1109/ACCESS.2022.3204284.

Y. Cao, D. Zhang, S. Ding, W. Zhong and C. Yan, "A

Hybrid Air Quality Prediction Model Based on

Empirical Mode Decomposition," in Tsinghua Science

and Technology, vol. 29, no. 1, pp. 99-111, February

2024, doi: 10.26599/TST.2022.9010060.

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

420