Internet of Things – ICIOT 2024

9th International Conference, Held as Part of the Services Conference Federation, SCF 2024, Bangkok, Thailand, November 16-19, 2024, Proceedings

AvShunli Zhang,Liang-Jie Zhang

Häftad, Engelska, 2024

Del 15427 i serien Lecture Notes in Computer Science

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Beskrivning

This book constitutes the refereed proceedings of the 9th International Conference on Internet of Things – ICIOT 2024, held as part of the Services Conference Federation, SCF 2024, in Bangkok, Thailand, during November 16-19, 2024.The 9 full papers presented in this volume were carefully reviewed and selected from 16 submissions. These papers focus on current research in various aspects of IOT technologies and applications, including sensors and other types of sensing devices, wired and wireless networks, platforms and tools, data processing/visualization/analysis and integration engines.

Produktinformation

Utgivningsdatum:2024-11-17
Mått:155 x 235 x 9 mm
Vikt:236 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:134
Förlag:Springer International Publishing AG
ISBN:9783031770029

Utforska kategorier

Hårdvara inom Data och IT
IT-säkerhet inom Data och IT
Nätverk och kommunikation inom Data och IT

Innehållsförteckning

.- Design an AutoCar Kit for Project-Based Learning in Autonomous Vehicle Programming for University Students..- Research and Application of Distributed Energy Storage Monitoring System Based on Plug-And-Play Protocols..- Long-Term Traffic Congestion Detection Method Based on Speed-Threshold..- Application of Digital Exhibition and Preservation of Intangible Cultural Heritage via Holographic Real-Time Cloud Broadcasting..- Node Pressure Prediction by Aggregating Long-Range Information..- Novel Technology for IoT Charging Battery..- Optimizing Target Coverage in Wireless Sensor Networks: A Hybrid Differential Evolution and Simulated Annealing-Based Approach..- Research on Automatic Detection and Early Warning of Epilepsy in Electroencephalogram Signals..- Cross-Scale Bilevel Aggregation for Multi-Exposure Fusion via Conditional Generative Adversarial Network.