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Delicato. a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024. aXIII, 388 p. 65 illus., 51 illus. in color.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aInternet of Things, Technology, Communications and Computing,x2199-10810 aPart 1 Architecture, Systems, and Services -- Chapter 1 Modeling, Simulating, and Evaluating Complex End-to-End Edge Intelligence Systems -- Chapter 2 Exploring Edge AI Inference in Heterogeneous Environments: Requirements, Challenges, and Solutions -- Chapter 3 Artificial Intelligence Enabled Edge Computing: Necessity of Next Generation Future Computing System -- Chapter 4 Artificial Intelligence-based IoT-Edge Environment for Industry 5.0 -- Chapter 5 Service Provisioning at the Edge: An AI Approach based on Policies -- Chapter 6 Unsupervised Time Series Anomaly Detection for Edge Computing Applications - A Review -- Part 2 Security and Privacy paradigm -- Chapter 7 Secure, Trusted, Privacy-Protected Data Exchange in an Edge-Cloud Continuum Environment -- Chapter 8 Security, Privacy, Trust and Provenance issues in Internet of Things based Edge Environment -- Chapter 9 Secure Neural Network Inference for Edge Intelligence: Implications of Bandwidth and Energy Constraints -- Part 3 Applications -- Chapter 10 Internet of Things in Intelligent Transportation Systems -- Chapter 11 IoT- Driven Analytics and Edge Intelligence in Autonomous Navigation Systems -- Chapter 12 Edge-AI for Monitoring Air Pollution from Urban Waste Incineration : A Survey -- Chapter 13 Enabling Artificial Intelligence on IoT Edge: Smart Approaches and Solutions for Providing Remote Dental and Medical Services. aThis book explores fundamental and advanced concepts related to the AI-enabled Edge Technology paradigm, also known as Edge Intelligence, within the framework of the Internet of Things (IoT). Expanding the application of Edge computing is increasingly necessary. This can involve exploring automated, intelligent computational learning theorems, and ANN-oriented, trustworthy machine learning perspectives to enhance computational intelligence. The book functions as a valuable resource for professionals in the sector and also acts as a comprehensive learning tool for newcomers in the field of AI-enabled Edge Technologies and their applications, covering both fundamental and advanced concepts. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable IoT edge-cloud ecosystem and to implement cyber-physical pervasive infrastructure solutions. The book will help readers understand the design architecture and AI algorithms and learn analytics through IoT edge, device-edge and the state-of-the-art in cloud-IoT countermeasures. The book is a valuable reference for anyone doing undergraduate or postgraduate studies, conducting research, or working in the computer science, information technology, electronics engineering, and complicated mathematical modeling domains. Serves as a manual for both basic and advanced aspects in edge-enabled technologies; Explores intelligent object identification and object discovery through the edge computing ecosystem; Addresses the complete functional framework and knowledge hierarchy for edge computing and IoT edge. 0aTelecommunication. 0aSignal processing. 0aApplication software.14aCommunications Engineering, Networks.24aDigital and Analog Signal Processing.24aComputer and Information Systems Applications.1 aPal, Souvik.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9750511 aSavaglio, Claudio.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9672631 aMinerva, Roberto.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9781901 aDelicato, Flávia C.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9781912 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303158387208iPrinted edition:z978303158389608iPrinted edition:z9783031583902 0aInternet of Things, Technology, Communications and Computing,x2199-108196590940uhttps://doi.org/10.1007/978-3-031-58388-9 aZDB-2-ENG aZDB-2-SXE c60486d60486