Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems (Intelligent Data-driven Systems and Artificial Intelligence)

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Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems (Intelligent Data-driven Systems and Artificial Intelligence)

  • ウェブストア価格 ¥34,945(本体¥31,769)
  • CRC Press(2024/07発売)
  • 外貨定価 US$ 170.00
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  • ポイント 1,585pt
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  • 製本 Hardcover:ハードカバー版/ページ数 284 p.
  • 言語 ENG
  • 商品コード 9781032548173
  • DDC分類 006.3

Full Description

This book comprehensively discusses the role of cloud computing in artificial intelligence‑based data‑driven systems and hybrid cloud computing for large data‑driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides Internet of Things‑based frameworks and advanced computing techniques to deal with online/virtual systems.

This book:

• Covers the aspects of security, authentication, and prediction for data‑driven systems in heterogeneous environments.

• Provides data‑driven frameworks in combination with the Internet of Things, artificial intelligence, and computing to provide critical insights and decision‑making for real‑time problems.

• Showcases deep learning‑based computer vision algorithms for enhanced pattern detection in different domains based on data‑centric approaches.

• Examines the role of the Internet of Things and machine learning algorithms for data‑driven systems.

• Highlights the applications of data‑driven systems and cloud computing in enhancing network performance.

This book is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, and computer science engineering.

Contents

1. Artificial Intelligence & IoT: Challenges and Future Directions for Data Driven System. 2. Cloud Computing in AI-based Data-Driven Systems: Opportunities and Challenges. 3. Study on Detection of Potato Diseases using Deep Learning Network and Image Segmentation. 4. Leveraging Cloud Computing for Efficient AI-Based Data-Driven Systems. 5. Analyzing and contrasting the outcomes of performance-based plagiarism detection methods. 6. Machine Learning Algorithms for Data Driven Systems in IoT. 7. Improving Classification Accuracy of Diabetes Mellitus Prediction using Ensemble Techniques. 8. Machine learning Models for IoT Botnet attack Detection. 9. Blockchain-based identity authentication for Internet of Things systems: A comprehensive survey. 10. Connected Healthcare: The Impact of Internet of Things on Medical Services: Merits, Limitations, Future Insights, Case Studies, and Open Research Questions. 11. IoT-Enabled Smart Farming Systems using Data Analytics and Machine Learning: An empirical study of livestock monitoring. 12. Exploring the Performance Improvement and Skill Set Transformations in Sheet Metal Operations through Digital Technology. 13. Crowd-Sourced Based Emergency Response on the Internet of Vehicles (IOV): Harnessing Strengths and Limitations.

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