Convergence of deep learning and internet of things : [electronic resource] / computing and technology [edited by] T. Kavitha, G. Senbagavalli, Deepika Koundal, Yanhui Guo, Deepak Jain.
- 其他作者：
- 其他題名：
- Advances in computational intelligence and robotics (ACIR) book series.
- 出版： Hershey, Pennsylvania : IGI Global 2023.
- 叢書名： Advances in computational intelligence and robotics (ACIR) book series
- 主題： Internet of things. , Deep learning (Machine learning) , Convergence (Telecommunication) , Electronic books.
- ISBN： 9781668462775 (electronic bk.) 、 1668462753 、 9781668462751
- URL：
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- 一般註：Includes bibliographical references and index. Chapter 1. Intelligent devices, device management, and device security for cloud platforms -- Chapter 2. Intelligent broker design for IoT using a multi-cloud environment -- Chapter 3. Deep learning-based intelligent sensing in IoT -- Chapter 4. Deep learning-enabled edge computing and IoT -- Chapter 5. Distributed deep learning for IoT -- Chapter 6. Approaches for detecting and predicting attacks based on deep and reinforcement learning to improve information security -- Chapter 7. Enhancing quality of service in internet of things: deep learning approach and its challenges -- Chapter 8. Edge computing in intelligent IoT -- Chapter 9. Edge AI-based crowd counting application for public transport stops -- Chapter 10. Patient behavioral analysis with smart healthcare and IoT -- Chapter 11. Deep learning neural networks for online monitoring of the combustion process from flame colour in thermal power plants -- Chapter 12. Analysis of political and ideological systems in education with lightweight deep learning -- Chapter 13. Comparative analysis of feature selection methods for detection of Android malware -- Chapter 14. Applications of internet of things with deep learning. 112年度臺灣學術電子書暨資料庫聯盟採購
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讀者標籤：
- 系統號： 000306537 | 機讀編目格式
館藏資訊
Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.
摘要註
"For those interested in design and building intelligent Internet of Things, this research book offers solutions with the state-of-the-art and novel approaches for the IoT problems and challenges from a deep learning perspective"--
