Sustainable Low–Cost Air Pollution Monitors and Air Quality

Dear Colleagues,

Sustainable development is the core value of human society in creating a better future for living. The UN set the 17 Sustainable Development Goals (SDGs) for its country members to practice and collaborate on globally. Among others, air quality improvement has been the major climate action in facilitating an equilibrium between industrial development and human health. To augment the coverage of air quality monitoring regions, low-cost and low-power sensors have been deployed at a large scale to offer a substantial analysis of air quality. The huge number of participating organizations and citizens further promote the research with citizen science to improve air quality. For the past decade, artificial intelligence (AI) has made great progress in diverse fields. The applications of AI, especially deep learning, seep into every piece of air quality to reach a sustainable future. We anticipate a great opportunity to explore promising computational approaches for low-cost sensors and air quality analysis.

The purpose of the Special Issue is to call attention to the marriage between “computational approaches” and “low-cost sensors and air quality” and to boost the synergy between the two streams. The publication of our Special Issue will position itself at the sustainability frontier for promoting low-cost sensors and air quality.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Low–cost air pollution monitors;
• Air quality forecast;
• Air quality spatiotemporal analysis;
• Sustainability and air quality IoT;
• Sustainability and human health;
• Big data mining for air quality;
• Machine learning and artificial intelligence for air quality analysis;
• Heuristic and metaheuristic for air quality analysis;
• Operation and maintenance for air quality IoT.

I look forward to receiving your contributions.

Prof. Dr. Pengyeng Yin
Guest Editor

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• low-cost air monitoring sensors
• air quality
• IoT
• artificial intelligence
• computational approaches
• spatiotemporal analysis
• air quality forecast