Shanu Sharma | Akateeminen Kirjakauppa

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.