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Ensuring Energy Efficiency of Air Quality Monitoring Systems Based on Internet of Things Technology

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  • Krzysztof Przystupa

    (Department of Automation, Lublin University of Technology, Nadbystrzycka 38D, 20-618 Lublin, Poland)

  • Nataliya Bernatska

    (Department of Physical, Analytical and General Chemistry, Lviv Polytechnic National University, 79013 Lviv, Ukraine)

  • Elvira Dzhumelia

    (Department of Software, Lviv Polytechnic National University, 79013 Lviv, Ukraine)

  • Tomasz Drzymała

    (Faculty of Safety Engineering and Civil Protection, Fire University, 52/54 Słowackiego Street, 01-629 Warsaw, Poland)

  • Orest Kochan

    (Department of Information-Measuring Technologies, Lviv Polytechnic National University, 79013 Lviv, Ukraine
    School of Computer Science, Hubei University of Technology, Wuhan 430068, China)

Abstract

Air quality monitoring systems based on Internet of Things (IoT) technology are critical for addressing environmental and public health challenges, but their energy efficiency poses a significant challenge to their autonomous and scalable deployment. This study investigates strategies to enhance the energy efficiency of IoT-based air quality monitoring systems. A comprehensive analysis of sensor types, data transmission protocols, and system architectures was conducted, focusing on their energy consumption. An energy-efficient system was designed using the Smart Air sensor, Zigbee gateway, and Mini UPS, with its performance evaluated through daily energy consumption, backup operation time, and annual energy use. An integrated efficiency index (IEI) was introduced to compare sensor models based on functionality, energy efficiency, and cost. The proposed system achieves a daily energy consumption of 72 W·h, supports up to 10 h of autonomous operation during outages, and consumes 26.28 kW·h annually. The IEI analysis identified the Ajax LifeQuality as the most energy-efficient sensor, while Smart Air offers a cost-effective alternative with broader functionality. The proposed architecture and IEI provide a scalable and sustainable framework for IoT air quality monitoring, with potential applications in smart cities and residential settings. Future research should explore renewable energy integration and predictive energy management.

Suggested Citation

  • Krzysztof Przystupa & Nataliya Bernatska & Elvira Dzhumelia & Tomasz Drzymała & Orest Kochan, 2025. "Ensuring Energy Efficiency of Air Quality Monitoring Systems Based on Internet of Things Technology," Energies, MDPI, vol. 18(14), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3768-:d:1702891
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    References listed on IDEAS

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    1. Osama Alsamrai & Maria Dolores Redel-Macias & Sara Pinzi & M. P. Dorado, 2024. "A Systematic Review for Indoor and Outdoor Air Pollution Monitoring Systems Based on Internet of Things," Sustainability, MDPI, vol. 16(11), pages 1-21, May.
    2. Jarosław Brodny & Magdalena Tutak & Wieslaw Wes Grebski, 2025. "A Holistic Assessment of Sustainable Energy Security and the Efficiency of Policy Implementation in Emerging EU Economies: A Long-Term Perspective," Energies, MDPI, vol. 18(7), pages 1-38, April.
    3. Beatrice Faniyi & Zhenhua Luo, 2023. "A Physics-Based Modelling and Control of Greenhouse System Air Temperature Aided by IoT Technology," Energies, MDPI, vol. 16(6), pages 1-18, March.
    4. Daniel Icaza Alvarez & Fernando González-Ladrón-de-Guevara & Jorge Rojas Espinoza & David Borge-Diez & Santiago Pulla Galindo & Carlos Flores-Vázquez, 2025. "The Evolution of AI Applications in the Energy System Transition: A Bibliometric Analysis of Research Development, the Current State and Future Challenges," Energies, MDPI, vol. 18(6), pages 1-31, March.
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