Convergence of Artificial Intelligence and the Internet of Things (Internet of Things) (2020)

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Convergence of Artificial Intelligence and the Internet of Things (Internet of Things) (2020)

  • オンデマンド(OD/POD)版です。キャンセルは承れません。
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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 439 p.
  • 言語 ENG
  • 商品コード 9783030449094
  • DDC分類 006.3

Full Description

This book gathers recent research work on emerging Artificial Intelligence (AI) methods for processing and storing data generated by cloud-based Internet of Things (IoT) infrastructures. Major topics covered include the analysis and development of AI-powered mechanisms in future IoT applications and architectures. Further, the book addresses new technological developments, current research trends, and industry needs. Presenting case studies, experience and evaluation reports, and best practices in utilizing AI applications in IoT networks, it strikes a good balance between theoretical and practical issues. It also provides technical/scientific information on various aspects of AI technologies, ranging from basic concepts to research grade material, including future directions. 

The book is intended for researchers, practitioners, engineers and scientists involved in the design and development of protocols and AI applications for IoT-related devices. As the book covers a wide range of mobile applications and scenarios where IoT technologies can be applied, it also offers an essential introduction to the field.

Contents

Fog Computing: Data Analytics for Time-Sensitive Applications.- Medical Image Watermarking in Four Levels Decomposition of DWT Using Multiple Wavelets in IoT Emergence.- Optimised Statistical Model Updates in Distributed Intelligence Environments.- Intelligent Vehicular Networking Protocols.- Towards Ubiquitous Privacy Decision Support:Machine Prediction of Privacy Decisions in IoT.- Energy-Efficient Design of Data Center Spaces in the Era of IoT Exploiting the Concept of Digital Twins.- In-network Machine Learning Predictive Analytics: A Swarm Intelligence Approach.- Machine Learning Techniques for Wireless-Powered Ambient Backscatter communications.- Processing Systems for Deep Learning Inference on Edge Devices.- Power Domain based Multiple Access for IoT Deployment: Two-way Transmission Mode and Performance Analysis. 

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