A design and implementation of a cloud-integrated IoT framework for real-time urban air quality monitoring

Authors

  • Sheila Maria Muniz * Municipal Secretary of Education of Jijoca de Jericoacoara, 62598-000 Jijoca de Jeric., CE, Brazil. https://orcid.org/0000-0002-4210-1497
  • Isametova Madina Esdauletova Satbayev University, 050000 Almaty, Kazakhstan.

https://doi.org/10.22105/sci.v2i4.49

Abstract

The rapid urbanization of cities worldwide has led to a significant increase in air pollution, posing severe health risks to urban residents. High costs, limited coverage, and lack of real-time capabilities often limit traditional air quality monitoring methods. This paper proposes a novel IoT-based Air Pollution Monitoring System (APMIoT) designed to accurately track and evaluate urban air quality. The system utilizes a Raspberry Pi Pico W with wireless capabilities and multiple sensors to monitor Particulate Matter (PM), Carbon Dioxide (CO₂), Total Volatile Organic Compounds (TVOCs), humidity, temperature, and GPS location. The APMIoT modules transmit real-time data to a cloud-based platform, which manages data collection, visualization, and analysis from a distributed network of APMIoT sensors across urban spaces. The system leverages FreeRTOS for modular programming, facilitating efficient and independent processing and data transmission.

Keywords:

IoT monitoring, Air quality monitoring, Measuring algorithms, APMIoT

References

  1. [1] Malleswari, S., & Mohana, T. K. (2022). Air pollution monitoring system using IoT devices. Materials today: proceedings, 51, 1147–1150. https://doi.org/10.1016/j.matpr.2021.07.114
  2. [2] Shahid, S., Brown, D. J., Wright, P., Khasawneh, A. M., Taylor, B., & Kaiwartya, O. (2025). Innovations in air quality monitoring: Sensors, IoT and future research. Sensors, 25(7), 2070. https://doi.org/10.3390/s25072070
  3. [3] Gololo, M. G. D., Nyathi, C. W., Boateng, L., Nkadimeng, E. K., Mckenzie, R. P., Atif, I., … & Mellado, B. (2024). Review of IoT systems for air quality measurements based on LTE/4G and lora communications. IoT, 5(4), 711–729. https://doi.org/10.3390/iot5040032
  4. [4] Munera, D., Aguirre, J., & Gomez, N. G. (2021). IoT-based air quality monitoring systems for smart cities: A systematic mapping study. International journal of electrical and computer engineering, 11(4), 3470–3482. 10.11591/ijece.v11i4.pp3470-3482
  5. [5] Gueye, A., Drame, M. S., & Niang, S. A. A. (2024). A low-cost IoT-based real-time pollution monitoring system using ESP8266 NodeMCU. Measurement and control, 00202940241306690. https://doi.org/10.1177/00202940241306690
  6. [6] Buelvas, J., Múnera, D., Tobón V, D. P., Aguirre, J., & Gaviria, N. (2023). Data quality in IoT-based air quality monitoring systems: A systematic mapping study. Water, air, & soil pollution, 234(4), 248. https://doi.org/10.1007/s11270-023-06127-9
  7. [7] Karnati, H. (2023). IoT-based air quality monitoring system with machine learning for accurate and real-time data analysis. https://arxiv.org/abs/2307.00580
  8. [8] Aserkar, A. A., Godla, S. R., Baker El-Ebiary, Y. A., & Naga Ramesh, J. V. (2024). Real-time air quality monitoring in smart cities using IoT-enabled advanced optical sensors. International journal of advanced computer science & applications, 15(4). https://doi.org/10.14569/ijacsa.2024.0150487
  9. [9] Gadekar, M. C. S. (2022). Air quality index (AQI) basics. International journal of research publication and reviews, 3(1), 805–807. https://www.researchgate.net/profile/Deepak-Gadekar/publication/378975308_Air_Quality_Index_AQI_Basics/links/65f47d15286738732d4d458e/Air-Quality-Index-AQI-Basics.pdf
  10. [10] De Vito, S., Massera, E., Piga, M., Martinotto, L., & Di Francia, G. (2008). On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario. Sensors and actuators b: chemical, 129(2), 750–757. https://doi.org/10.1016/j.snb.2007.09.060
  11. [11] Nguyen, H., Nguyen, K., Sridharan, S., & Fookes, C. (2023). Aerial-ground person re-id. 2023 IEEE international conference on multimedia and expo (ICME) (pp. 2585–2590). IEEE. https://doi.org/10.1109/ICME55011.2023.00440
  12. [12] Nalakurthi, N. V. S. R., Abimbola, I., Ahmed, T., Anton, I., Riaz, K., Ibrahim, Q., … & Gharbia, S. (2024). Challenges and opportunities in calibrating low-cost environmental sensors. Sensors, 24(11), 3650. https://doi.org/10.3390/s24113650
  13. [13] Karagulian, F., Barbiere, M., Kotsev, A., Spinelle, L., Gerboles, M., Lagler, F., … & Borowiak, A. (2019). Review of the performance of low-cost sensors for air quality monitoring. Atmosphere, 10(9), 506. https://doi.org/10.3390/atmos10090506
  14. [14] Garcia, A., Saez, Y., Harris, I., Huang, X., & Collado, E. (2025). Advancements in air quality monitoring: A systematic review of IoT-based air quality monitoring and AI technologies. Artificial intelligence review, 58(9), 275. https://doi.org/10.1007/s10462-025-11277-9

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Published

2025-12-20

Issue

Vol. 2 No. 4 (2025): Smart City Insights

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Articles

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How to Cite

Muniz, S. M., & Esdauletova, I. M. (2025). A design and implementation of a cloud-integrated IoT framework for real-time urban air quality monitoring. Smart City Insights, 2(4), 197-204. https://doi.org/10.22105/sci.v2i4.49

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