LEADER 05415nam 22005775 450 001 9911066006803321 005 20260216120419.0 010 $a3-032-09090-3 024 7 $a10.1007/978-3-032-09090-4 035 $a(MiAaPQ)EBC32552652 035 $a(Au-PeEL)EBL32552652 035 $a(CKB)45344631500041 035 $a(OCoLC)1574115778 035 $a(DE-He213)978-3-032-09090-4 035 $a(EXLCZ)9945344631500041 100 $a20260216d2026 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLearning-Driven Data Fabrics for Sustainability $eCloud-to-Thing Continuum Solutions for Global Challenges /$fedited by Prithi Samuel, Daniel Arockiam, Balamurugan Balusamy, Liza Macasukit Gernal, Chander Prabha 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (378 pages) 225 1 $aSustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development,$x3005-1770 311 08$a3-032-09089-X 327 $a1. Learning-Driven Data Fabric Evolution: A Thorough Overview -- 2. Cloud-to-Thing Continuum: Connecting IoT Devices and Cloud Infrastructures -- 3. Advances and Considerations for Machine Learning Integration in Data Fabric -- 4. Data Interoperability: Enabling Smooth Cross-Platform Communication -- 5. Security Issues in Data Fabric Driven by Learning -- 6. Scalability Considerations: Fulfilling the Increasing Data Requirements -- 7. Dynamics of Edge Computing in the Cloud-To-Thing Continuum -- 8. Learning-Driven Data Fabric: Innovations and Applications for Real-Time Insights -- 9. Psychological Resilience in Data-Driven Workflows -- 10. Learning-Driven Data Fabric Innovations: Current Advancements -- 11. Adaptive Data Fabric: Flexible Adaptation to Changing Circumstances -- 12. Human-Machine Cooperation in Data Fabric Driven by Learning -- 13. Privacy-Preserving Data Fabric: Judging Between Confidentiality and Utility -- 14. Learning-Driven Data Fabric Governance: Standards and Regulatory Compliance -- 15. Human-Machine Synergy in Learning-Driven Data Fabrics. 330 $aThis book explores the distinct problems, trends, and future trajectories for constructing cohesive, sustainable data infrastructures that correspond with the United Nations Sustainable Development Goals (SDGs). In the contemporary digital ecosystem, the amalgamation of data across diverse platforms and environments?from cloud to edge to IoT?has become imperative for fostering creativity, sustainability, and efficiency. ?Learning-Driven Data Fabric for Sustainable Cloud-to-Thing Continuum? examines the optimization of integration through sophisticated data fabrics enhanced by machine learning and AI. This book initiates its exploration by analyzing the fundamental concepts of a learning-driven data fabric that integrates cloud and IoT ecosystems, facilitating real-time decision-making and minimizing energy consumption. It offers comprehensive insights into how intelligent data management throughout the cloud-to-thing continuum may be utilized to enhance resource efficiency, facilitate smart city planning, and promote advancements in sectors such as healthcare, transportation, and agriculture. This book emphasizes how data fabrics may advance objectives related to affordable and clean energy (SDG 7), industrial innovation (SDG 9), and sustainable cities and communities (SDG 11), with sustainability as its central theme. This book illustrates how learning-driven data architectures are revolutionizing businesses and tackling global challenges through real-world case studies and upcoming trends. Subjects encompass edge computing, real-time data analytics, safe data transmission, and the reduction of carbon footprints via effective data processing. This study examines how data fabrics might alleviate the risks associated with cyberattacks and data breaches, while ensuring regulatory compliance and fostering sustainable, ethical AI operations. This book offers a detailed framework for utilizing data fabric technologies to create sustainable, safe, and intelligent cloud-to-thing ecosystems, regardless of whether you are a data scientist, IoT specialist, cloud architect, or policymaker. This book promotes data-driven decision-making throughout the infrastructure, enabling organizations to design scalable and sustainable solutions that advance global development objectives. 410 0$aSustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development,$x3005-1770 606 $aSustainability 606 $aInternet of things 606 $aArtificial intelligence 606 $aSustainability 606 $aInternet of Things 606 $aArtificial Intelligence 615 0$aSustainability. 615 0$aInternet of things. 615 0$aArtificial intelligence. 615 14$aSustainability. 615 24$aInternet of Things. 615 24$aArtificial Intelligence. 676 $a304.2 700 $aSamuel$b Prithi$01770114 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911066006803321 996 $aLearning-Driven Data Fabrics for Sustainability$94547652 997 $aUNINA