Evolution and Advances in Computing Technologies for Industry 6.0
Technology, Practices, and Challenges
Herausgeber: Alqhatani, Abdulmajeed; Bhatia Khan, Surbhi; Doss, Srinath; Reddy, C. Kishor Kumar
Evolution and Advances in Computing Technologies for Industry 6.0
Technology, Practices, and Challenges
Herausgeber: Alqhatani, Abdulmajeed; Bhatia Khan, Surbhi; Doss, Srinath; Reddy, C. Kishor Kumar
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Explores the evolution from Industry 4.0 to the cutting-edge Industry 6.0, offering insights into the integration of next-generation computing, including IoT, AI, machine learning, deep learning, edge computing and quantum computing.
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Explores the evolution from Industry 4.0 to the cutting-edge Industry 6.0, offering insights into the integration of next-generation computing, including IoT, AI, machine learning, deep learning, edge computing and quantum computing.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 392
- Erscheinungstermin: 19. November 2024
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032823041
- ISBN-10: 1032823046
- Artikelnr.: 70770648
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 392
- Erscheinungstermin: 19. November 2024
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032823041
- ISBN-10: 1032823046
- Artikelnr.: 70770648
Dr C Kishor Kumar Reddy, currently working as Associate Professor, Dept. of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has research and teaching experience of more than 10 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 an author for 2 text books and 7 co-edited books. His research areas include: Atmospheric Sciences, Meteorology, Healthcare, Intelligent Systems, Machine Learning and Deep learning. Prof. Srinath Doss is the Professor and Dean in the Faculty of Engineering and Technology, Botho University, responsible for Botswana, Lesotho, Eswatini, Namibia and Ghana Campuses. He has written good number of books and 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 an advisory member for various prestigious conferences. Prof. Srinath is member of IAENG and Associate Member in UACEE. Surbhi Bhatia Khan is doctorate in Computer Science and Engineering in machine learning and social media analytics. She is listed in the top 2% researchers released by the Stanford University, USA. She earned Project management Professional Certification from reputed Project Management Institute, USA. She is currently working in the Department of Data Science, School of Science, Engineering and environment, University of Salford, Manchester, United Kingdom. She holds research positions Lebanese American University. She also enjoys adjunct professor position from Shoolini University, Himachal Pradesh, India. She has more than 12 years of academic and teaching experience in different universities. She has published 150+ papers in many reputed journals in high indexed outlets. She has around 12 international patents from India, Australia and USA. She has successfully authored 2 books and edited 15 books. She is working in the research projects with UKRI, Deanship of Scientific Research, 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 over 20 invited and keynote talks across the globe. She is serving as an Academic editor, Associate Editor and Guest editor in many reputed journals. She is the awardee of the Research Excellence award given by King Faisal University, Saudi Arabia in 2021. Her area of interests are AI, Medical Imaging, Deep learning, Machine learning, and Data science. Abdulmajeed Alqhatani is currently an Assistant Professor at Najran University, Saudi Arabia, and is also serving as the Director of Research and Graduate Studies in the Department of Information Systems. He completed his Ph.D. in Computing and Information Systems from the University of North Carolina at Charlotte, United States in 2021. His research interests include Usable Security & Privacy, 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
1. Empowering the Factory of the Future: Integrating Artificial
Intelligence, Machine Learning, and IOT Innovations in Industry 6.0. 2.
Human-Robot Collaboration Analyzing the Challenges and Opportunities of
Integrating Soft Computing Algorithms in Manufacturing Environments. 3. An
Overview of Cloud Computing: Paradigm, Technologies, and Application. 4.
Autism Spectrum Disorder Classification in Children Using Deep Learning
Approaches in Healthcare 6.0. 5. Exploring Neurodegenerative Progression:
Healthcare 6.0 Insights using Sustainable Convolutional Neural Networks. 6.
Digital Adaptation in Agricultural Sector: Challenges and Prospects in
Uttar Pradesh; India. 7. Next-Gen Agriculture 6.0, A Smart Solutions
Pioneering the Future of Farming. 8. Review of Study of Biochemical Water
Parameters for Prediction and Analysis of Quality of Water using Machine
Learning Techniques in Industry 6.0. 9. Climate Change Mitigation
Strategies using Convolutional Neural Networks over Multiple Locations. 10.
Driving Sustainable Practices in Industry 6.0: A Study on Article Detection
with Fuzzy Wuzzy and Supervised Machine Learning Algorithms. 11. Evolution
of Computational Intelligence for Vehicle Surveillance and Recognition in
Industry 6.0: Recent Innovations, Practices, and Challenges. 12. Piecewise
Mixed Integer Non-Linear Optimization for Supply Chain Network Design
(SCND) Model: Confirmation through Cluster Analysis. 13. Integrated
Multi-Item Multi-Echelon Supply Chain Model: A Mixed Integer Heuristic
Approach.
Intelligence, Machine Learning, and IOT Innovations in Industry 6.0. 2.
Human-Robot Collaboration Analyzing the Challenges and Opportunities of
Integrating Soft Computing Algorithms in Manufacturing Environments. 3. An
Overview of Cloud Computing: Paradigm, Technologies, and Application. 4.
Autism Spectrum Disorder Classification in Children Using Deep Learning
Approaches in Healthcare 6.0. 5. Exploring Neurodegenerative Progression:
Healthcare 6.0 Insights using Sustainable Convolutional Neural Networks. 6.
Digital Adaptation in Agricultural Sector: Challenges and Prospects in
Uttar Pradesh; India. 7. Next-Gen Agriculture 6.0, A Smart Solutions
Pioneering the Future of Farming. 8. Review of Study of Biochemical Water
Parameters for Prediction and Analysis of Quality of Water using Machine
Learning Techniques in Industry 6.0. 9. Climate Change Mitigation
Strategies using Convolutional Neural Networks over Multiple Locations. 10.
Driving Sustainable Practices in Industry 6.0: A Study on Article Detection
with Fuzzy Wuzzy and Supervised Machine Learning Algorithms. 11. Evolution
of Computational Intelligence for Vehicle Surveillance and Recognition in
Industry 6.0: Recent Innovations, Practices, and Challenges. 12. Piecewise
Mixed Integer Non-Linear Optimization for Supply Chain Network Design
(SCND) Model: Confirmation through Cluster Analysis. 13. Integrated
Multi-Item Multi-Echelon Supply Chain Model: A Mixed Integer Heuristic
Approach.
1. Empowering the Factory of the Future: Integrating Artificial
Intelligence, Machine Learning, and IOT Innovations in Industry 6.0. 2.
Human-Robot Collaboration Analyzing the Challenges and Opportunities of
Integrating Soft Computing Algorithms in Manufacturing Environments. 3. An
Overview of Cloud Computing: Paradigm, Technologies, and Application. 4.
Autism Spectrum Disorder Classification in Children Using Deep Learning
Approaches in Healthcare 6.0. 5. Exploring Neurodegenerative Progression:
Healthcare 6.0 Insights using Sustainable Convolutional Neural Networks. 6.
Digital Adaptation in Agricultural Sector: Challenges and Prospects in
Uttar Pradesh; India. 7. Next-Gen Agriculture 6.0, A Smart Solutions
Pioneering the Future of Farming. 8. Review of Study of Biochemical Water
Parameters for Prediction and Analysis of Quality of Water using Machine
Learning Techniques in Industry 6.0. 9. Climate Change Mitigation
Strategies using Convolutional Neural Networks over Multiple Locations. 10.
Driving Sustainable Practices in Industry 6.0: A Study on Article Detection
with Fuzzy Wuzzy and Supervised Machine Learning Algorithms. 11. Evolution
of Computational Intelligence for Vehicle Surveillance and Recognition in
Industry 6.0: Recent Innovations, Practices, and Challenges. 12. Piecewise
Mixed Integer Non-Linear Optimization for Supply Chain Network Design
(SCND) Model: Confirmation through Cluster Analysis. 13. Integrated
Multi-Item Multi-Echelon Supply Chain Model: A Mixed Integer Heuristic
Approach.
Intelligence, Machine Learning, and IOT Innovations in Industry 6.0. 2.
Human-Robot Collaboration Analyzing the Challenges and Opportunities of
Integrating Soft Computing Algorithms in Manufacturing Environments. 3. An
Overview of Cloud Computing: Paradigm, Technologies, and Application. 4.
Autism Spectrum Disorder Classification in Children Using Deep Learning
Approaches in Healthcare 6.0. 5. Exploring Neurodegenerative Progression:
Healthcare 6.0 Insights using Sustainable Convolutional Neural Networks. 6.
Digital Adaptation in Agricultural Sector: Challenges and Prospects in
Uttar Pradesh; India. 7. Next-Gen Agriculture 6.0, A Smart Solutions
Pioneering the Future of Farming. 8. Review of Study of Biochemical Water
Parameters for Prediction and Analysis of Quality of Water using Machine
Learning Techniques in Industry 6.0. 9. Climate Change Mitigation
Strategies using Convolutional Neural Networks over Multiple Locations. 10.
Driving Sustainable Practices in Industry 6.0: A Study on Article Detection
with Fuzzy Wuzzy and Supervised Machine Learning Algorithms. 11. Evolution
of Computational Intelligence for Vehicle Surveillance and Recognition in
Industry 6.0: Recent Innovations, Practices, and Challenges. 12. Piecewise
Mixed Integer Non-Linear Optimization for Supply Chain Network Design
(SCND) Model: Confirmation through Cluster Analysis. 13. Integrated
Multi-Item Multi-Echelon Supply Chain Model: A Mixed Integer Heuristic
Approach.