Artificial Intelligence for the Water-Energy-Food Nexus
- 1st Edition - December 1, 2025
- Imprint: Elsevier
- Editors: Shahryar Jafarinejad, Amir Shahirinia
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 4 0 1 9 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 4 0 2 0 - 8
Artificial Intelligence for the Water–Energy–Food Nexus considers the interrelationships among water, energy, and food, which are key to sustainable development and the p… Read more
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Artificial Intelligence for the Water–Energy–Food Nexus considers the interrelationships among water, energy, and food, which are key to sustainable development and the potential of artificial intelligence (AI) as a useful tool to facilitate research and development within and between these areas as well as the water–energy–food (WEF) nexus.
The first chapter introduces the WEF nexus concepts, assessment/analysis methodologies and tools, challenges, trends, and future perspectives. The second chapter summarizes AI applications to the water sector/industry with a focus on the importance, general applications, and real-world applications, as well as the challenges and future perspectives. The third chapter focuses on the application of AI techniques to the water and wastewater treatment systems, including treatment processes, urban drinking water systems, and integrated urban drainage systems. The fourth chapter explores the application of AI techniques to the nonrenewable and renewable energy systems, load monitoring, load demand forecasting, smart grids, energy optimization and process control, energy storage systems, and case studies and real-world applications, as well as the challenges in AI application to the energy industry and future directions. The application of AI techniques in the food industry in the areas of organoleptic properties, nutrition, toxicology, and food chemistry; biotechnology processes and microbiology security; food processing and manufacturing; conservation and storage conditions; supply chains, markets, and distribution; and food industry environments (circular economy, water, and energy management), as well as the challenges and opportunities are discussed in the fifth chapter. The final chapter reviews/presents the application of AI techniques to address problems associated with the WEF nexus. This book can be of interest to all those who are looking to understand and utilize AI techniques in the context of water, energy, food, and the WEF nexus, including researchers, advanced students, faculty, engineers, R&D, industry professionals, and policymakers.
- Provides an overview of the water–energy–food nexus, including concepts, assessment/analysis, challenges, trends, and future directions
- Explores the individual applications of AI techniques to the water, energy, and food sectors
- Highlights the application of AI to the water–energy–food nexus
Researchers, advanced students, and faculty in energy, environmental science, civil and environmental engineering, chemical engineering, mechanical engineering, agricultural science, biosystems engineering, sustainability, and other related disciplines
1. Introduction to the Water-Energy-Food Nexus: Concepts/Frameworks, Assessment, Challenges, and Trends
2. Introduction to Artificial Intelligence Techniques
3. Artificial Intelligence for the Water Sector/Industry
4. Artificial Intelligence for the Energy Sector/Industry
5. Artificial Intelligence for the Food Sector/Industry
6. Artificial Intelligence Application to the Water-Energy-Food Nexus
2. Introduction to Artificial Intelligence Techniques
3. Artificial Intelligence for the Water Sector/Industry
4. Artificial Intelligence for the Energy Sector/Industry
5. Artificial Intelligence for the Food Sector/Industry
6. Artificial Intelligence Application to the Water-Energy-Food Nexus
- Edition: 1
- Published: December 1, 2025
- Imprint: Elsevier
- Language: English
SJ
Shahryar Jafarinejad
Dr. Shahryar Jafarinejad is an Assistant Professor of Chemical Engineering at Tuskegee University (TU), United States, where he also serves as a faculty senate member since 2019. Before joining TU in 2018, he worked as a postdoctoral researcher at the University of California, Irvine. He has taught chemical engineering courses at TU, University of Tehran, and the College of Environment, and Technical and Vocational University (Iran), and supervised undergraduate and graduate students. He has published three books, several book chapters, and numerous peer-reviewed journal and conference papers, and has served as an editorial board member and reviewer of engineering journals. His research group focuses on green technologies and sustainable materials, energy and environment, and applying nanotechnology and modeling and simulation tools to solve problems in chemical and environmental engineering. He received the Henry C. McBay Faculty Research Fellowship from UNCF and the Outstanding Faculty Performance Award for Research and Teaching/Learning at TU in 2020 and 2022, respectively.
Affiliations and expertise
Assistant Professor, Chemical Engineering Department, College of Engineering, Tuskegee University, USAAS
Amir Shahirinia
Dr. Amir Shahirinia is an Associate Professor of Electrical and Computer Engineering at the University of the District of Columbia (UDC), Washington DC, United States. He is the Director of the Smart Grids and Artificial Intelligence Lab (SGAI) at UDC and serves as the Director of the Center of Excellence for Renewable Energy. A distinguished expert in the fields of electrical engineering and artificial intelligence, his research primarily focuses on integrating artificial intelligence in power systems, power electronics, and motor drives. He specializes in the optimal planning and operation of renewable energy grid integration systems (REGIS), with a particular emphasis on intelligent real-time control of these systems, as well as the application of robotics in the health monitoring of energy systems. Dr. Shahirinia has secured over $10 million in research funding from various esteemed organizations such as the National Science Foundation (NSF), the Department of Defense (DoD), the National Institute of Standards and Technology (NIST), and the DC Water Resources Research Institute (DCWRRI).
Affiliations and expertise
Associate Professor of Electrical and Computer Engineering, University of the District of Columbia (UDC), Washington DC, USA