Advancements and Frameworks in IoT-Based Air Pollution Monitoring Systems

The Internet of Things (IoT) has emerged as a key technology for scalable, real-time environmental monitoring, addressing the growing global challenge of air pollution. This review synthesizes findings from more than twenty major deployments across urban, industrial and smart-city environments, including implementations from Hindustan Institute of Technology [1], Sathyabama Institute [2], Taiwan’s integrated governance framework [3], the Bulgarian Academy of Sciences [4] and low-cost deployments in developing regions. Comparative analysis spans sensing hardware, communication technologies (WiFi, LTE/4G, LoRa), cloud architectures, machine learning integration and field performance. Results indicate significant improvements in spatial coverage, real-time responsiveness and data-driven governance, while highlighting persistent challenges in sensor calibration, cybersecurity and long-term reliability. Emerging advances in edge intelligence, spectral sensing, federated learning and hybrid communication architectures are examined as pathways toward next-generation environmental monitoring. This consolidated review provides a structured framework for scalable, resilient and policy-integrated IoT air-quality monitoring systems.

IoT, air pollution monitoring, environmental sensors, real-time data, machine learning, smart cities, sustainability, cloud computing

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