The escalating levels of air pollution in urban environments have become a significant public health concern, necessitating the development of efficient, real-time monitoring systems. Traditional air quality monitoring infrastructures are often expensive, spatially limited, and lack the ability to provide continuous data feedback for proactive decision-making. With the advent of the Internet of Things (IoT), it is now feasible to design low-cost, scalable, and intelligent air quality monitoring solutions tailored for smart cities. This paper explores the development and deployment of IoT-based real-time air quality monitoring systems, emphasizing sensor integration, edge computing, wireless communication protocols, and cloud-based data analytics. We propose a comprehensive architecture combining embedded sensing units with real-time data transmission and analytics capabilities. The system is tested in a metropolitan area, demonstrating its efficacy in capturing particulate matter (PM2.5, PM10), nitrogen dioxide (NO₂), carbon monoxide (CO), and volatile organic compounds (VOCs). The results show improved spatial-temporal resolution and immediate feedback mechanisms, enabling authorities and citizens to take timely action. This research underlines the critical role of IoT in building environmentally responsive and health-conscious urban ecosystems.
Ramesh Prajapati (Wed,) studied this question.