Advanced Computing and AI for Sustainable Environment, Energy, and Smart Manufacturing

AI-Driven Sustainability Across Environment, Energy, and Industry
1. Auflage 2026
ISBN: 978-1-041-34029-4
Verlag: Taylor & Francis Ltd

Buch, Englisch, 640 Seiten, Format (B × H): 210 mm x 280 mm

This book presents a comprehensive exploration of cutting-edge research and innovations driving sustainability across energy, environment, materials, and intelligent systems. Bringing together multidisciplinary perspectives, the book highlights how advanced physics, chemistry, artificial intelligence, data science, and manufacturing technologies are shaping a greener, more resilient future.

The book is organized into thematic tracks covering energy conversion and storage, environmental and atmospheric physics, green and sustainable chemistry, materials chemistry for energy and environment, mathematical modeling and simulation, data science, AI and IoT for sustainability, and advanced manufacturing. It features state-of-the-art studies on renewable energy systems, smart grids, climate and environmental monitoring, sustainable materials and composites, green nanotechnology, and next-generation coatings. Significant emphasis is placed on AI-driven modeling, machine learning, digital twins, and IoT frameworks for optimizing resource use, enhancing healthcare, agriculture, cybersecurity, and smart infrastructure. The contributions collectively demonstrate how computational intelligence and advanced materials enable efficient energy management, environmental protection, and circular-economy practices, supported by experimental, analytical, and simulation-based findings.

This book is intended for researchers, academicians, postgraduate students, and industry professionals working in sustainability, energy systems, materials science, environmental engineering, artificial intelligence, and applied computational sciences, as well as policymakers seeking research-driven insights for sustainable development.

Zielgruppe

Academic and Undergraduate Core

Autoren/Hrsg.

Singh, Harvinder

Kaushal, Priyanka

Kaur, Sarabjeet

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Sozialwissenschaften Politikwissenschaft Regierungspolitik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Wirtschaftswissenschaften Volkswirtschaftslehre Internationale Wirtschaft Entwicklungsökonomie & Emerging Markets
• Geowissenschaften Umweltwissenschaften Nachhaltigkeit
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Energie- & Versorgungswirtschaft
• Naturwissenschaften Physik Mechanik Energie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur

Inhaltsverzeichnis

1. Energy Conversion and Storage Physics 2. Environmental and Atmospheric Physics 3. Green and Sustainable Chemistry 4. Materials Chemistry for Energy and Environment 5. Mathematical Modeling and Simulation in Sustainability 6. Data Science and Computational Mathematics 7. Artificial Intelligence and IoT for Sustainability 8. Advanced Manufacturing and Materials

Über Autor(innen)

Harvinder Singh is an experienced academic and researcher, currently serving as an Associate Professor at CEC-CGC Landran, Mohali. His areas of expertise include sustainability, environmental engineering, and renewable energy systems, with a strong focus on interdisciplinary solutions for global environmental challenges. Singh has actively contributed to numerous international conferences and research collaborations and has several publications in reputed peer-reviewed journals. As the editor of this volume, Singh brings his academic leadership and commitment to advancing knowledge in sustainable development and innovative environmental practices.

Priyanka Kaushal is a Professor of Mathematics at Chandigarh Engineering College, CGC Landran. With over a decade of academic and research experience, she holds a Ph.D. in Applied Mathematics from I.K. Gujral Punjab Technical University. Her research interests include computational mathematics, steganography, fog computing, and image processing. She has actively guided student research and organized national academic events. Kaushal was honored with the Best Researcher Award in Mathematics at the Universal Innovators Leadership Awards (UILA 2021). She is recognized for her dedication to teaching, innovation in applied mathematics, and significant contributions to interdisciplinary academic development.

Sarbjeet Kaur is an Assistant Professor in the Department of Applied Sciences at CGC College Engineering, CGC Landran. Holding a Ph.D. in Applied Sciences, she brings over a decade of experience in teaching and research. Her expertise spans applied mathematics, computational modeling, and interdisciplinary applications in engineering contexts. Kaur actively mentors undergraduate and postgraduate students, guiding them through research projects and publications. She plays a pivotal role in organizing academic events, workshops, and faculty development programs at CGC Landran. Known for her commitment to enhancing both academic rigor and student success, Kaur contributes meaningfully to the college’s research culture and curriculum innovation.