Technological Advancements in Data Processing for Next Generation Intelligent Systems presents an in-depth exploration of cutting-edge data processing technologies that drive the development of next-generation intelligent systems in the context of the digital transformation era. This comprehensive book delves into the role data plays as a critical asset for organizations across diverse industries, and how recent technological breakthroughs have unlocked unprecedented potential for handling vast data volumes and real-time analysis.

The book begins by providing a thorough overview of novel technologies such as artificial intelligence (AI) or machine learning (ML), edge computing, federated learning, quantum computing, and more. These revolutionary technologies, when integrated with big data frameworks, in-memory computing, and AI/ML algorithms, have transformed data processing capabilities, enabling the creation of intelligent systems that fuel innovation, optimize operations, and deliver personalized experiences. The ultimate aim of this integration is to empower devices with the ability to make autonomous intelligent decisions, maximizing computing power.

Emphasizing the development of highly efficient next-generation intelligent systems, the book focuses on various architectural approaches for data processing. The emphasis rests on real-time analysis, faster decision-making, enhanced privacy, and efficient processing of large data volumes. Future trends are explored, with an eye on achieving pervasive and fine-grained intelligence through optimized data processing methods for sensing data.

This book serves as a valuable resource for research scholars, academicians, and industry professionals working towards the future advancement of optimized intelligent systems and intelligent data processing approaches. The chapters encompass a wide range of topics, including architecture and frameworks for intelligent systems, applications in diverse domains, cloud-based solutions, quantum processing, federated learning, in-memory data processing, real-time stream processing, trustworthy AI for Internet of Things (IoT) sensory data, and more. The integration of blockchain technology for IoT sensory data management and architectural considerations for data processing technologies are extensively discussed, making this an important resource for anyone interested in next generation intelligent systems.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Artificial Intelligence
Autonomous Vehicles
Big Data Frameworks
Cloud-Based Solutions
Contextual Awareness
Data Processing
Data Security
Digital Transformation
Drones
Edge Computing
Explainable AI
Federated Learning
In-Memory Computing
Intelligent Systems
IoT Integration
Next Generation Intelligent Systems
Performance Optimization Approaches
Quantum Computing
Real-Time Analysis
Robotics
Technological Advancements

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Editor/Author Biographies

Shanu Sharma is an Assistant Professor in the Department of Computer Science & Engineering, ABES Engineering College, Ghaziabad (Affiliated to A.K.T University, Lucknow). She has a PhD from Amity University Uttar Pradesh and M.Tech (Intelligent Systems) from IIIT Allahabad. She has 13+ years of teaching and research experience and taught various courses at the graduate and under graduate level such as Image Processing, Data Mining, Machine Learning, Data Science, Data Structures, Analysis and Design of Algorithms, and Compiler Design. Her research areas include Cognitive Computing, Computer Vision, Pattern Recognition, and Machine Learning. She has published 40+ research papers in renowned Conferences and Journals and is currently associated with various reputed International Conferences and journals as a Reviewer. She has edited various special issues in Scopus indexed journals published by IGI Global, and Bentham Science. She has edited five books with renowned publishers such as Springer, IGI, CRC Press, and River Publishers. She is a senior member of IEEE and also an active member of other professional societies like ACM, Soft Computing Research Society (SCRS), EUSFLAT, and IAENG.

Ayushi Prakash is a Professor in the Department of Computer Science and Engineering at Ajay Kumar Garg Engineering College Ghaziabad, Dr. A.P.J. Abdul Kalam Technical University Uttar Pradesh. She received her Ph.D. in Computer Science and Engineering from Dr. K. N. Modi University, Rajasthan, received a M.Tech. degree from the AKTU State University of Uttar Pradesh & B.Tech. degree from Dr. R.M.L Awadh University, Uttar Pradesh. Her research interests span both Information retrieval and AI ML. Much of her work has been on improving the understanding and performance of search engine optimization, mainly through the application of data mining, statistics, and performance evaluation. She has received many best paper awards in international conferences. She has contributed to many International Conferences as an organizer, advisor, session chair, and reviewer. She has more than 40 research papers in renowned national and international journals and conferences and published many patents, chapters and research articles. She is the founding Chair of NGO (Prayatna Fikar Kal Ki). She is the member of National Advisory Board of Sports Academy Association of India. Dr. Prakash is an editor of 2 books and editing 1 forthcoming book. Prof. Prakash, is a professional member of IEEE and IAEPT.

Vijayan Sugumaran is Distinguished Professor of Management Information Systems and Chair of the Decision and Information Sciences department at Oakland University. He is also Co-Director of the Center for Data Science and Big Data Analytics at Oakland University. He received his Ph.D. in Information Technology from George Mason University, Fairfax, Virginia, USA. Over the years he has taught courses at the Graduate and Undergraduate level in Object-Oriented Systems Development, C++, Java, Javascript, Database Management Systems and Data Warehouses, Advanced Databases and Big Data Management, Deep Learning and Text Analytics, Systems Analysis and Design, Electronic Commerce, and Introduction to MIS. His research interests are in the areas of Big Data Analytics, Business Intelligence, Ontologies and Semantic Web, Intelligent Agent and Multi-Agent Systems, Component Based Software Development, Knowledge-Based Systems, and Data & Information Modeling. He has published over 275 peer-reviewed articles in Journals, Conferences, and Books. He has edited twenty books. His recent publications have appeared in Information Systems Research, ACM Transactions on Database Systems, IEEE Transactions on Engineering Management, IEEE Transactions on Big Data, IEEE Transactions on Education, IEEE software, Communications of the ACM, Healthcare Management Science, Data and Knowledge Engineering, The DATABASE for Advances in Information Systems, Information Systems Journal, and Journal of Information Systems and E-Business Management. He is also the editor-in-chief of the International Journal of Intelligent Information Technologies and also serves on the editorial board of eight other journals. He was the Program Co-Chair for the International Conference on Applications of Natural Language to Information Systems (NLDB 2008, NLDB 2013, NLDB 2016, NLDB 2019, and NLDB 2023). He was also the Chair of Intelligent Information Systems track for the Information Resources Management Association International Conference (IRMA 2001, 2002, 2005 - 2007) and the Intelligent Agent and Multi-Agent Systems in Business mini-track for Americas Conference on Information Systems (AMCIS 1999 - 2023). He served as Program Co-Chair for the 14th Workshop on E-Business (WeB2015), 29th Australasian Conference on Information Systems (ACIS 2018), 14th Annual Conference of Midwest Association for Information Systems (MWAIS 2019), 5th IEEE International Conference on Big Data Service and Applications (BDS 2019), and 2022 Midwest Decision Sciences Institute Annual Conference (MWDSI 2022). He also served as Chair of the E-Commerce track for Decision Science Institute’s Annual Conference, 2004. He was the Information Technology Coordinator for the Decision Sciences Institute from 2007 to 2010. He also regularly serves as a program committee member for numerous national and international conferences.

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