Technological Advancements in Data Processing for Next Generation Intelligent Systems

Technological Advancements in Data Processing for Next Generation Intelligent Systems

Release Date: March, 2024|Copyright: © 2024 |Pages: 357
DOI: 10.4018/979-8-3693-0968-1
ISBN13: 9798369309681|EISBN13: 9798369309698
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Description & Coverage
Description:

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 a B.Tech. degree from Dr. R.M.L Awadh University, and an M.Tech. from the AKTU State University of Uttar Pradesh at Lucknow. She received her Ph.D. in Computer Science and Engineering from Dr. K. N. Modi University. From 2010 to 2024, she also has a continuous contribution in the Training & Placement Department in Dr. A.P.J. Abdul Kalam Technical 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. Dr. Prakash is co-editor of3 upcoming book. Prof. Prakash, professional member of IEEE, professional lifetime member of Indgiants Association of Educators & Professional Trainers. She is the founding Chair & trustee of Prayatna Fikar Kal ki NGO. Wipro Certified Faculty for training program. 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.
Vijayan Sugumaran is Professor of Management Information Systems and Chair of the Department of Decision and Information Sciences at Oakland University, Rochester, Michigan, USA. He received his Ph.D in Information Technology from George Mason University, Fairfax, USA. His research interests are in the areas of Big Data Analytics, Ontologies and Semantic Web, Intelligent Agent and Multi-Agent Systems, and Component Based Development. He has published over 200 peer-reviewed articles in Journals, Conferences, and Books. He has edited twelve books and serves on the Editorial Board of eight journals. He has published in top-tier journals such as Information Systems Research, ACM Trans on Database Systems, IEEE Trans on Engineering Management, Communications of the ACM, and IEEE Software. He is the editor-in-chief of the International Journal of Intelligent Information Technologies. He is the Chair of the Intelligent Agent and Multi-Agent Systems mini-track for Americas Conference on Information Systems (AMCIS 1999 - 2019). He has served as the program co-chair for the International Conference on Applications of Natural Language to Information Systems (NLDB 2008, 2013, 2016, and 2019).
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