Digital Twins and ESG
Informazioni su questo ebook
Digital Twins and ESG introduces the dynamic world of ESG practices, emphasizing the pivotal role technology plays in shaping and advancing sustainability goals. It introduces readers to the multifaceted world of Digital Twin technology, offering a comprehensive understanding of its historical development and diverse applications across industries. This volume will intricately examine the integration of Digital Twins in ESG metrics and reporting frameworks. Artificial intelligence, machine learning, and blockchain technologies are also discussed as key enablers for achieving ESG goals, providing readers with a glimpse into the potential advancements and breakthroughs that lie ahead. Through detailed analyses and case studies, readers will gain insights into how Digital Twins enhance data collection, monitoring, and reporting, elevating transparency and accountability. Digital Twins and ESG serves as a rallying call, urging businesses to embrace Digital Twins as an integral component of their ESG strategies, ultimately paving the way for a more sustainable and responsible future.
Informazioni sull'autore
Surajit Mondal, PhD is teaching at the University of Petroleum and Energy Studies. He has published eight books, over 50 international research articles as an author or co-author, and 85 patents, 20 of which were granted. His research interests include optimization of renewable energy, biofuels, and solar thermal technologies.
Adesh Kumar, PhD is an associate professor in the Department of Electrical and Electronics Engineering at the University of Petroleum and Energy Studies with over 15 years of experience. He has published five books and over 100 research papers in international journals and conferences in addition to chairing over 200 conference sessions. His research interests include embedded systems, digital image processing, and telecommunications.
Mudassir Khan, PhD is a postdoctoral fellow at Multimedia University and a co-supervisor for Postgraduate Studies at Lincoln University College with over 13 years of experience. He has published over 80 research articles and more than 10 editorial books and authored four books, inspiring many in technology and education. His research interests include big data, deep learning, and AI, particularly in medical imaging.
