Sustainable Smart Cities: IoT-Driven Green Infrastructure for Particulate Matter Reduction

Abstract

Speedy urbanization has exacerbated environmental issues, primarily air pollution through particulate matter (PM), which greatly endangers people's health and urban ecosystems. This paper presents a comprehensive review of how Internet of Things (IoT) technology, when integrated with green infrastructure, can support the development of sustainable smart cities and PM level reduction. It begins by setting forth the definition of smart and sustainable city development based on the role of PM (as PM2.5 and PM10) in aggravating air quality. Subsequently, the review reviews IoT-driven air quality monitoring systems emphasizing technologies such as low-cost sensors, LPWAN, 5G, edge computing, and AI-based analytics. Concurrently, the study reviews green infrastructure strategies—green roofs, walls, and city greenery—that are nature-based solutions to PM capturing and mitigation. The interaction between IoT and ecosystems is developed in depth, with examples like smart irrigation, environmental observation, and decision-making systems. Global case studies from cities like Singapore, Amsterdam, and Barcelona provide real-world implementation and advantages, for instance, improved air quality, public health, and cost reductions. The paper also identifies significant technical, ecological, and socio-political challenges like sensor accuracy, temporal variability, policy harmonization, and privacy concerns. Lastly, it outlines potential research avenues like leveraging digital twins, bio-IoT, and transdisciplinary approaches to enhance resilience and sustainability. The findings emphasize strongly the unavoidable need to integrate IoT with green infrastructure to accelerate holistic, data-driven, and sustainable urbanization.