AI-based Applications for Sanitary Environmental Engineering

Growth in demand for clean water, waste reduction, and environmental safety has driven innovation in sanitary-environmental engineering. Conventional process control and process monitoring systems can fail to adequately control the variation and data density of contemporary environmental systems. The emergence of digital technology, including sensors, the Internet of Things (IoT), and big data, has led to the generation of new opportunities. Artificial Intelligence (AI) has enabled the optimization of treatment processes and the prediction of environmental risks in a manner never previously experienced. The fact that it can be integrated into sanitary and environmental systems represents a significant shift, enabling the dynamic and adaptive management of water, air, and waste systems in real world situations.

The purpose of this Research Topic is to explore the possibilities of enhancing environmental safety and human health through the application of more sophisticated modeling and intelligent regulation of sanitary-environmental systems, utilizing AI. Particularly, the collection will highlight the state-of-the-art and cutting-edge examples of using AI in wastewater treatment, solid waste management, environmental surveillance, and resource recovery. A combination of AI-based tools and conventional engineering knowledge will help researchers implement more efficient, predictive, and resilient environmental infrastructures. We also aim to showcase research on the responsible use of AI to support environmental decisions, the provisions of data governance, and sustainability evaluation. Ultimately, this Research Topic aims to bridge the gap between various fields, thereby facilitating the implementation of AI as a stimulus for next-generation environmental engineering.

We welcome original research, reviews, mini-reviews, data reports, and perspectives that explore AI-based approaches in sanitary-environmental engineering. The areas of interest are, but not limited to:

• AI-based process management and optimization of wastewater and waste treatment processes (e.g., anaerobic digestion) and solid waste management;
• Methods for resource recovery, a circular economy plan, and life-cycle assessment (LCA);
• Resilient sanitary environmental infrastructure;
• Monitoring of emerging contaminants and pathogens (e.g., PFAS, microplastics, SARS-CoV-2) in wastewater using predictive models;
• Digital Twin-based environmental systems, a combination of AI and IoT, remote sensing;
• AI and air quality (e.g., control of odor emissions);
• Environmental policies and solutions for the integration of AI systems.

The authors are encouraged to present studies characterized by a combination of innovative methodology and practical application to real-life environmental problems or sustainability-focused views.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: artificial intelligence, wastewater treatment, waste management, environmental monitoring, resource recovery, digital twins, predictive modelling, emerging contaminants, pathogens

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.