Applications of Blockchain and Computational Intelligence in Environmental Sustainability (Hardcover)

The book explores the complex correlation between blockchain technology and sustainability, demonstrating the potential of cutting-edge computational intelligence methods to address critical environmental and societal challenges. It provides a comprehensive analysis of the most recent developments in research, innovative approaches to design, and real-world implementations, establishing a strategic plan for the incorporation of blockchain technology into environmentally friendly solutions.

Features:

• Focuses on the intersection of blockchain technology, computational intelligence, and sustainability.
• Covers international regulatory landscapes and ethical considerations.
• Emphasizes real-world applications such as supply chain management systems and smart energy networks.
• Offers concrete examples of how these technologies contribute to sustainability.
• Provides insight into how new technologies are transforming health informatics.

This book is aimed at graduate students and researchers in computer engineering and environmental sustainability.

Dr. Hamed Taherdoost is an award-winning leader in research and development, renowned for his impactful contributions to both industry and academia. He is the founder of Hamta Business Corporation, Associate Professor Meritorious and Chair of RSAC at University Canada West, and Director of R&D at Q Minded. With over 20 years of experience spanning global companies in Cyprus, the UK, Malta, Iran, Malaysia, and Canada, Dr. Taherdoost has led innovative projects across sectors such as healthcare, transportation, oil and gas, and IT. In academia, he has taught across Southeast Asia, the Middle East, Europe, and North America since 2009, and is actively engaged in editorial and advisory roles for prestigious journals and conferences. A prolific author with over 300 scientific publications, he has been repeatedly recognized as one of the world’s top 2% scientists by Stanford-Elsevier and is among the top 10 SSRN Business Authors (2021-2024). Dr. Taherdoost is currently Editor of the Routledge Book Series Mastering Academic Excellence: Research, Teaching, Learning, and Publishing and serves on multiple international editorial boards. His professional affiliations include senior memberships in IEEE and the International Federation for Information Processing (IFIP) TC 11.

Dr. Mohsen Saeedi is a Professor of Sustainability at the University of Canada West. With over 20 years of experience in academia, Dr. Saeedi specializes in sustainability, environmental management, and technology, having contributed to both research and curriculum development in Canada and Iran. He has served in prominent roles, including Dean of the School of Civil Engineering at the Iran University of Science and Technology. Dr. Saeedi's research spans sustainable development and environmental pollution, environmental management, and management systems, with numerous publications in peer-reviewed journals. He also serves as an associate editor for international sustainability-focused journals. As an editor of this book, Dr. Saeedi brings his expertise to the intersection of blockchain technology and sustainable practices.

Dr. Aydin Shishegaran is Lecturer at IU International University of Applied Sciences and another institute in Germany. He got his first Ph.D. in 2022 from Iran University Science and Technology and his second PhD accepted in 2024 at Bauhaus University Weimar. Since, he has published over pre-reviewed papers in high-ranked journals and have 798 citations and has also reviewed 265 manuscripts for high ranked-journals. He is editor in journal of mechatronics and artificial intelligence in engineering since 2020. Furthermore, in 2021, he is a guest editor in Sustainability in MDPI. In 2020, he published a new MCDA method for sustainable evaluation. In 2023, 2023, and 2024, he published four new ML methods in high-ranked journal, which one of them is the most cited paper in computers and structures.