The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0. Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving carsHighlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domainsDiscusses important topics such as the Internet of robotic things, cloud…mehr
The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0. Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving carsHighlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domainsDiscusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical roboticsExplains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0 The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.
Dr C Kishor Kumar Reddy is currently an Associate Professor in the Department of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has more than 10 years of research and teaching experience. He has published more than 50 research papers in national and international conferences, book chapters, and journals indexed by Scopus and others. He is an author for two textbooks and two co-edited books. He acted as the special session chair for Springer FICTA 2020, 2022, SCI 2021, INDIA 2022, and IEEE ICCSEA 2020 conferences. He is the corresponding editor of AMSE 2021 conference, published by IoP Science JPCS. He is a member of ISTE, CSI, IAENG, UACEE, and IACSIT. Dr P R Anisha, TEDx Speaker, is currently working as Associate Professor in the Department of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. She has nine plus years of teaching experience. She earned her PhD from K L University, Guntur, India. Her areas of interest include Artificial Intelligence, Machine Learning, and Image Processing. She has 35 + research articles published in international conferences and journals. She has co-authored two books titled Introduction to C and C++ programming. She has acted as the special session chair for international conferences for Springer including INDIA 2019, 2022, SCI 2021, FICTA 2020, 2022 besides the IEEE conference ICCSEA 2020. She is a member of ACM and IAENG professional bodies. Dr Samiya Khan is an alumna of the University of Delhi, India and completed her PhD in Computer Science from Jamia Millia Islamia, India. Currently, she is a Lecturer in Computer Science at the University of Greenwich, United Kingdom. Previously, she served as a postdoctoral research fellow at the University of Wolverhampton, United Kingdom. She has contributed more than 30 research papers and her publications extend across journal articles and book chapters in high impact publications of international repute. She has also presented her research at reputed international conferences. She has served as Associate Editor of Scientific India Magazine and reviewer for many reputed journals and conferences such as IEEE Transactions on Emerging Trends in Computing and Information Processing and Management, Elsevier. She is a regular contributor to magazines with many articles published in CSI Communications and Scientific India. Besides this, she has co-edited two books published by reputed publishers such as Springer and Elsevier and is also the author of a textbook titled Big Data and Analytics . Dr Khan's expertise spans across data science, Artificial Intelligence, edge computing, and the Internet of Things (IoT) with demonstrated experience in the development of heterogeneous systems. Her research interests include the use of Artificial Intelligence for the development of descriptive, diagnostic, predictive, and prescriptive healthcare applications. Dr Marlia Mohd Hanafiah is a Professor and Head of the Centre for Tropical Climate Change System, Institute of Climate Change, The National University of Malaysia, Malaysia. Her areas of research expertise include Life Cycle Impact Assessment (LCA) and Environmental Foot printing of Green Materials and Energy, Environmental Engineering, Wastewater Treatment & Water Management, and Green Technology and Sustainability. She has 15 plus years of academic teaching experience and more than 170 publications in reputed journals and online book chapter contributions (indexed by SCI, SCIE, SSCI, Scopus, DBLP). She received research grant and consultation (as project leader and team member) of more than RM 7 million. Dr Lavanya Pamulaparty has been working as Professor and Head of the Department of Computer Science and Engineering in the Methodist College of Engineering and Technology since 2010. She earned her BE degree in Computer Science and Engineering from KITS, Nagpur University. She earned her MTech in Software Engineering from Jawaharlal Nehru and Technological University (JNTUH), Hyderabad and Doctorate degree from JNTUH, Hyderabad, in the area of Data Mining. She has over 21 years of experience in the field of academic research and technological education. She has published 20 papers in various international and national journals and IEEE international/national conferences and two patents. Her papers are indexed in Scopus and SCI. Her areas of interest include Artificial Intelligence and Machine Learning. She is IEEE, CSI, and ISTE life members. She has organized international conferences including ICPET-2016, 2018, and ICAISC-2022. Dr R Madana Mohana is a senior member of IEEE and a Professor in the Department of IT at the Chaitanya Bharathi Institute of Technology, Hyderabad, India. He has more than 18 years of teaching experience. He earned his PhD with a Machine Learning specialization. He has published more than 50 research articles in various peer-reviewed journals and conferences. He is a life member of ISTE and fellow of IETE. He has organized various conferences, workshops, and delivered keynote addresses.
Inhaltsangabe
1. From Industry 4.0 to Industry 5.0. 2. Assessing the Impact of Industry 5.0 on Sustainability Strategies. 3. Digital Industrial Revolution: From Sustainability Perspective. 4. Machine Learning for Supply Chain Management in Industrial 4.0 Era: A Bibliometric Analytics. 5. Transforming Industry 5.0: Real-Time Monitoring and Decision-Making with IIoT. 6. Sustainable Transformation: Energy Efficiency and Renewable Energy in Industry 5.0. 7. A study of Cloud of Things enabled Machine learning based Smart health monitoring system. 8. Lung Cancer Classification using CNN: Addressing Class Imbalance and Model Performance Analysis. 9. Water Quality forecasting using Deep Learning: Astudy of the Brahmaputra Basin. 10. Multimodal Fusion Techniques for Enhanced Fake News Detection: A Robustly Optimized BERT and Vision Transformer Approach.
1. From Industry 4.0 to Industry 5.0. 2. Assessing the Impact of Industry 5.0 on Sustainability Strategies. 3. Digital Industrial Revolution: From Sustainability Perspective. 4. Machine Learning for Supply Chain Management in Industrial 4.0 Era: A Bibliometric Analytics. 5. Transforming Industry 5.0: Real-Time Monitoring and Decision-Making with IIoT. 6. Sustainable Transformation: Energy Efficiency and Renewable Energy in Industry 5.0. 7. A study of Cloud of Things enabled Machine learning based Smart health monitoring system. 8. Lung Cancer Classification using CNN: Addressing Class Imbalance and Model Performance Analysis. 9. Water Quality forecasting using Deep Learning: Astudy of the Brahmaputra Basin. 10. Multimodal Fusion Techniques for Enhanced Fake News Detection: A Robustly Optimized BERT and Vision Transformer Approach.
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