Frontiers in Advanced Computing and Emerging Intelligent Technologies: Proceedings of FACEIT-2026: 63 (Learning and Analytics in Intelligent Systems, 63) - Tapa dura

Sinopsis

This book presents rigorously peer-reviewed contributions that capture the latest advances in intelligent computing systems and scalable computational infrastructures, offering practical solutions to real-world challenges across domains such as healthcare, cybersecurity, smart systems, and data-driven decision-making. It provides readers with a consolidated view of how modern computing paradigms and intelligent technologies are converging to address complex, dynamic, and large-scale problems.

This book adopts a dual perspective by integrating advanced computing methodologies with emerging intelligent technologies, enabling a holistic understanding of both system-level innovations and intelligent application development. Unlike traditional collections that treat these domains independently, this book highlights their interdependence through contributions spanning distributed systems, cloud and edge computing, optimization techniques, and software engineering, alongside artificial intelligence, machine learning, computer vision, and data science.

The contributions included in this book are selected from the International Conference on Frontiers in Advanced Computing and Emerging Intelligent Technologies (FACEIT 2026), hosted by the Department of Computer Science and Engineering, National Institute of Technology Warangal, India, during July 10–11, 2026. The conference served as a platform for researchers, academicians, and industry practitioners to present innovative research, exchange ideas, and foster collaborations in cutting-edge areas of computing and intelligent systems. All papers underwent a rigorous peer-review process to ensure high academic quality and relevance.

The scope of the book is broad and interdisciplinary, covering topics such as cyber-physical systems, vehicular networks, secure communication protocols, intelligent optimization, and scalable data processing frameworks, as well as applications in sentiment analysis, recommender systems, fairness-aware machine learning, and multimodal perception. A significant portion of the work is dedicated to healthcare and biomedical intelligence, including medical imaging, disease prediction, clinical decision systems, and bioinformatics, reflecting the growing importance of AI-driven solutions in critical domains. Additionally, contributions on explainable AI, bias mitigation, and trustworthy systems emphasize responsible and ethical deployment of intelligent technologies.

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