Artificial Intelligence in Air Pollution
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Air".
Deadline for manuscript submissions: closed (15 March 2024)
Special Issue Editor
Interests: machine learning; neural networks and artificial intelligence; air pollution; particulate matter
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) has been increasingly applied in air pollution research and management in recent years. It has the potential to improve our understanding of the sources and effects of air pollution, and to support the development of more effective strategies for reducing air pollution and its impacts on human health and the environment.
AI techniques such as machine learning and deep learning can analyze large volumes of air quality data from various sources, such as sensors, satellites, and models, to identify patterns and correlations that may not be visible to human experts. AI can also help to develop predictive models that can forecast air pollution levels and its impacts on human health, which can be used to inform policy decisions and public health interventions.
Furthermore, AI can be used to optimize pollution control strategies and improve the efficiency of environmental monitoring and management systems. For example, AI can be used to control traffic flow in cities to reduce emissions, or to optimize the operation of industrial facilities to minimize pollution.
Guest Editor
Prof. Dr. Marco Antonio Aceves-Fernandez
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- airborne pollution
- machine learning
- neural networks
- deep learning
- environmental monitoring
- air quality
- pollution control
- data analytics
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