Air pollution has become a critical global concern due to rapid urbanization and industrialization, posing severe risks to environmental and public health. Effective indoor air quality monitoring systems (IAQMSs) are essential for accurately assessing pollutant levels, identifying sources, and implementing timely mitigation strategies. This paper presents a comprehensive review of recent advancements and challenges in IAQMSs, focusing on emerging techniques and technologies that enhance environmental and human health. The study explores the evolution of IAQ monitoring, emphasizing Internet of Things (IoT)–based solutions for real‐time data acquisition and analysis. Advanced communication technologies such as Wi‐Fi, Zigbee, and LoRa are evaluated for their efficiency and applicability in indoor environments. The review highlights key challenges, including sensor calibration, integration with renewable energy systems, and data reliability, and critically examines the suitability of low‐cost sensors for consumer and large‐scale applications, considering durability and performance under variable indoor conditions. Furthermore, the integration of sustainable energy solutions, such as photovoltaic solar panels and rechargeable batteries, is discussed for uninterrupted operation. The paper also investigates the role of artificial intelligence (AI) including machine learning and deep learning techniques in enhancing predictive capabilities, sensor stability, and operational efficiency. Covering literature published between 2019 and 2025, this review synthesizes current knowledge to inform the design, deployment, and future development of next‐generation indoor air monitoring systems, offering actionable insights for researchers, policymakers, and public health practitioners.
Ahmed et al. (Thu,) studied this question.
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