Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems
- 296 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- About the Editors
- List of Contributors
- 1 Artificial intelligence and IoT: Challenges and future directions for data-driven system
- 2 Cloud computing in AI-based data-driven systems: Opportunities and challenges
- 3 Study on the detection of potato diseases using deep learning network
- 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 Data-driven early detection of livestock diseases using IoT-enabled smart collars
- 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
- Index