Evolution and Advances in Computing Technologies for Industry 6.0 : Technology, Practices, and Challenges

This book provides a comprehensive exploration of Industry 6.0, which marks the convergence of intelligent systems, machine learning (ML), deep learning, and human–robot collaboration (HRC) in various sectors. It focuses on how these technologies enable businesses to harness insights from vast datasets, optimize operations, forecast maintenance requirements, and mitigate outages. In this comprehensive book, the authors cover the major aspects of Industry 6.0, including the latest advances in technology, new applications, and the many challenges that accompany the process that is changing it. This book acts as a compass, guiding readers through the labyrinth of Industry 6.0, revealing the complex interactions between technologies, new applications, innovations, and business ecosystems. From a multidisciplinary perspective, the book explores the far‑reaching impact of Industry 6.0 on the business world, revealing its potential to increase productivity, improve decision‑making, and open new opportunities for development.

• Discusses the transformative impact of Industry 6.0 driven by the convergence of artificial intelligence (AI), ML, and the industrial internet of things (IIoT) in manufacturing
• Explores the transformative potential of HRC in modern manufacturing, emphasizing the ability of HRC to boost productivity, flexibility, and safety
• Compares several service models in cloud computing, with a focus on private, public, and community cloud deployment methods
• Presents information about autism spectrum disorder (ASD) in children and the advanced technology of convolutional neural networks used to detect autism in children
• Describes the accurate diagnosis of Alzheimer’s disease through integrating state‑of‑the‑art technologies, especially deep learning
• Focuses on digital adaptation in India’s agricultural sector, especially Uttar Pradesh, highlighting challenges and prospects
• Presents a visionary leap into Agriculture 6.0, where technology and tradition converge for sustainable farming solutions
• Provides the mitigation strategies for climate change over multiple locations
• Explores the transformative impact of recent computational intelligence advancements in vehicle surveillance and recognition, particularly through CCTV analysis
• Focuses on the exploration and development of a supply chain network design (SCND) model of milk products

This book will be of interest to researchers, academics, practitioners, technology providers, undergraduate and postgraduate students, scholars, consultants, advisors, and doctors. It can be used by undergraduate and postgraduate students pursuing Industry 6.0 programs in computer science and engineering across the globe.

C. Kishor Kumar Reddy is Associate Professor at the Department of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has research and teaching experience of more than ten years. He has published more than 60 research papers in national and international conferences, book chapters, and journals indexed by SCIE, Scopus, and others. He is the author of two textbooks and seven co‑edited books. His research areas include atmospheric sciences, meteorology, healthcare, intelligent systems, machine learning, and deep learning.

Srinath Doss is Professor and Dean in the Faculty of Engineering and Technology, Botho University, responsible for the Botswana, Lesotho, Eswatini, Namibia, and Ghana campuses. He has written several books, published more than 80 papers in international journals, and attended several prestigious conferences. He serves as an editorial member and reviewer for reputed international journals and as an advisory member for various prestigious conferences. Professor Srinath is a Member of IAENG and an Associate Member of UACEE.

Surbhi Bhatia Khan holds a doctorate in computer science and engineering in machine learning and social media analytics. She is listed in the top 2% of researchers released by Stanford University, USA. She earned project management Professional Certification from the reputed Project Management Institute, USA. She teaches in the Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester, United Kingdom. She holds a research position at the Lebanese American University. She also enjoys an Adjunct Professor position at Shoolini University, Himachal Pradesh, India. She has more than 12 years of academic and teaching experience at different universities. She has published 150+ papers in many reputed journals in high‑indexed outlets. She has 12 international patents from India, Australia, and the USA. She has written 2 books and edited 15 books. She is working on research projects with UKRI, the Deanship of Scientific Research, the Ministry of Education from Saudi Arabia, and India. She is a Senior Member of IEEE, a Member of IEEE Young Professionals, and ACM. She has chaired several international conferences and workshops and has delivered more than 20 invited and keynote talks across the globe. She serves as an Academic Editor, Associate Editor, and Guest Editor with many reputed journals. She is the awardee of the Research Excellence Award given by King Faisal University, Saudi Arabia, in 2021. Her areas of interest include artificial intelligence, medical imaging, deep learning, machine learning, and data science.

Abdulmajeed Alqhatani is Assistant Professor at Najran University, Saudi Arabia, and the Director of Research and Graduate Studies in the Department of Information Systems, Saudi Arabia. He earned a PhD in computing and information systems at the University of North Carolina at Charlotte, USA, in 2021. His research interests include usable security and privacy, internet of things (IoT) applications in a smart city, business intelligence, and data analytics. Dr. Alqhatani’s publications appear in various academic journals and conferences, including IEEE Sensors Journal and the CHI Conference on Human Factors in Computing Systems.