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Editore: Springer International Publishing AG, CH, 2023
ISBN 10: 3031289897 ISBN 13: 9783031289897
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ISBN 10: 3031289897 ISBN 13: 9783031289897
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Edge Computing and IoT: Systems, Management and Security | Third EAI International Conference, ICECI 2022, Virtual Event, December 13-14, 2022, Proceedings | Zhu Xiao (u. a.) | Taschenbuch | xi | Englisch | 2023 | Springer | EAN 9783031289897 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer Nature Switzerland, 2023
ISBN 10: 3031289897 ISBN 13: 9783031289897
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed post-conference proceedings of the Third International Conference on Edge Computing and IoT, ICECI 2022, held in December 13-14, 2022 in Changsha, China. Due to COVID-19 pandemic the conference was held virtually. The explosion of the big data generated by ubiquitous edge devices motivates the emergence of applying machine learning systems for edge computing and Internet of Things (IoT) services. Machine learning techniques are delivering a promising solution to the industry for building IoT systems and to make innovation at a rapid pace. The 22 full papers of ICECI 2022 were selected from 76 submissions and present results and ideas in the area of edge computing and IoT.
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Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Seiten: 336 | Sprache: Englisch | Produktart: Bücher | This book constitutes the refereed post-conference proceedings of the Third International Conference on Edge Computing and IoT, ICECI 2022, held in December 13-14, 2022 in Changsha, China. Due to COVID-19 pandemic the conference was held virtually. The explosion of the big data generated by ubiquitous edge devices motivates the emergence of applying machine learning systems for edge computing and Internet of Things (IoT) services. Machine learning techniques are delivering a promising solution to the industry for building IoT systems and to make innovation at a rapid pace. The 22 full papers of ICECI 2022 were selected from 76 submissions and present results and ideas in the area of edge computing and IoT.
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Nature Switzerland Mrz 2023, 2023
ISBN 10: 3031289897 ISBN 13: 9783031289897
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed post-conference proceedings of the Third International Conference on Edge Computing and IoT, ICECI 2022, held in December 13-14, 2022 in Changsha, China. Due to COVID-19 pandemic the conference was held virtually. The explosion of the big data generated by ubiquitous edge devices motivates the emergence of applying machine learning systems for edge computing and Internet of Things (IoT) services. Machine learning techniques are delivering a promising solution to the industry for building IoT systems and to make innovation at a rapid pace. The 22 full papers of ICECI 2022 were selected from 76 submissions and present results and ideas in the area of edge computing and IoT. 336 pp. Englisch.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Switzerland|Springer, 2023
ISBN 10: 3031289897 ISBN 13: 9783031289897
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed post-conference proceedings of the Third International Conference on Edge Computing and IoT, ICECI 2022, held in December 13-14, 2022 in Changsha, China. Due to COVID-19 pandemic the conference was held virtually. The .
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Springer Mär 2023, 2023
ISBN 10: 3031289897 ISBN 13: 9783031289897
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Models and methods for data management in IoT.- Forecasting the Temperature of BEV Battery Pack based on Field Testing Data.- The Data Exchange Protocol over Multi-chain BlockchainUsing Zero-knowledge Proof.- A Hybrid Task Offloading and Service Cache Scheme for Vehicular Edge Computing.- On Enhancing Transmission Performance for IoV Based on Improved Greedy Algorithm.- Precise Segmentation on Poly-Yolo, YoloV5 and FCN.- Adaptive approaches to manage energy consumption and security of systems.- Research on DAG Based Consensus Mechanism for Adjustable Load Metering Data.- A Detection and Information Processing Model based on an Automatic Mechanism for Tax Payment Control in Developing Countries.- IEC-FOF: An Industrial Electricity Consumption Forecasting and Optimization Framework.- Demons Hidden in the Light: Unrestricted Adversarial Illumination Attacks.- Edge Intelligence Based Garbage Classification Detection Method.- Mobile computing in wireless networks.- Evaluation of Higher Education System.- Defense Mechanisms against Audio Adversarial Attacks: Recent Advances and Future Directions.- An Empirical Study of Worldwide Plastic Waste Mitigation.- Prediction for Surface Subsidence of Shield Construction in Water-Rich Sand Egg Stratum Based on Edge Intelligence.- Highly Accurate Dynamic Gesture Recognition Method Based on Edge Intelligence.- Distributed computing in IOT.- Edge Intelligence Based Garbage Classification Detection Method.- Adversarial Example Attacks in Internet of Things (IoT).- Training Node Screening in Decentralized Trusted Federated Learning.- Exploration and Practice of Course Homework Metaverse Based on Extended Reality under Edge Computing.- Federated Learning Based User Scheduling for Real-Time Multimedia Tasks in EdgeDevices.- A Co-caching Strategy for Edges Based on Federated Learning and Regional Prevalence.- LSTM-DAM: Malicious Network Traffic Prediction for Cloud Manufacturing System.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 336 pp. Englisch.