| Description |
1 online resource (xviii, 328 pages) |
| Series |
Advances in Computational Collective Intelligence |
| Contents |
I. Computational Intelligence: Edge AI Services1. Edge Computational Intelligence: Fundamentals, Trends, and ApplicationsShrikaant Kulkarni2. Securing IoT Services using Artificial Intelligence in Edge ComputingP. William1, Siddhartha Choubey, Abha Choubey, and Gurpreet Singh Chhabra3. Computational-Based Edge AI Services and ChallengesBharati AinapureII. Computational Intelligence: Edge AI security and Privacy4. Security and Privacy in Edge AI: Challenges and ConcernsRitu Sachdeva, Sandeep Gulia, and Vishal Prasad5. A Study of Edge Computing-Enabled Metaverse EcosystemPooja Kulkarni, Ashish Kulkarni, Shriprada Chaturbhuj6. Sustainable Communication-Efficient Edge AI: Algorithms and SystemsPradnya S. Mehta, Dattatray G. Takale, Sachin R. Sakhare, Parishit N. Mahalle, Sarita D. Sapkal, and Gopal B. DeshmukhIII. Computational Intelligence: Edge Computingand AI Applications7. Machine Learning-Based Hybrid Technique for Securing Edge ComputingP. William, Yogeesh. N, andPravin B. Khatkale8. A Study of Secure Deployment of Mobile Services in Edge ComputingP. William, Yogeesh. N, andPravin B. Khatkale9. AI-Enabled Novel Applications in Edge Computing for IoT ServicesIshita Dixit, Sonali Powar, and Kabir Kharade10. Application of Edge AI in BiomedicineOm M. Bagade, Priyanka E. Doke-Bagade, and Krushna S. WankhadeIV. Computational Intelligence: IoT Systems11. Artificial Intelligence and Soft Computing-Driven Evolutionary Computation Algorithms for Solving Unconstrained Nonlinear ProblemsPriyavada and Binay Kumar12. UAV-Enabled Mobile Edge Computing for IoT ApplicationsAlok Singh Kushwaha and Nagendra Kumar13. Internet of Things Enabled Software-Defined NetworksSantosh Kumar Sharma, Debendra Muduli, Sukant Kisoro Bisoy, Srikanta Kumar Mohapatra, Prakash Kumar Sarangi14. Smart and Sustainable Energy-Efficient Wireless Sensor Network : Design and TechniquesDattatray G. Takale, Parishit N. Mahalle, Piyush P. Gawali, Gopal B. Deshmukh, Chitrakant O. Banchhor, and Pradnya S. Mehta |
| Summary |
Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs and resilience from network failure, and the book explains the advantages of systems and applications using intelligent IoT devices that are at the edge of a network and close to users. It explains how to make most of edge and cloud computing as complementary technologies or used in isolation for extensive and widespread applications. The advancement in IoT devices, networking facilities, parallel computation and 5G, and robust infrastructure for generalized machine learning have made it possible to employ edge computational intelligence in diverse areas and in diverse ways. The book begins with chapters that cover Edge AI services on offer as compared to conventional systems. These are followed by chapters that discuss security and privacy issues encountered during the implementation and execution of edge AI and computing services The book concludes with chapters looking at applications spread across different areas of edge AI and edge computing and also at the role of computational intelligence in AI-driven IoT systems |
| Notes |
Shrikaant Kulkarni has 37 years of teaching and research experience at both undergraduate and postgraduate levels. Presently he is a Professor in the Department of Civil Engineering, Padm. Dr. V. B. Kolte College of Engineering, Malkapur, India. He has published over 60 research papers in national and international journals and conferences Jaiprakash Narain Dwivedi is currently working as an Associate Professor, ECE Department, University Institute of Engineering, Chandigarh University, Mohali, Punjab, India. His interest in research includes machine learning, artificial neural network, pattern recognition, classification, CNN, DNN, deep learning and signal processing. Dinda Pramanta is an Assistant Professor and a committee member of Mathematical-Data Science-AI Educational Program on Kyushu Institute of Information Sciences from 2021. His research interests include spiking neural networks, hardware, and AI for educational purposes. Yuichiro Tanaka is an Assistant Professor with Research Center for Neuromorphic AI Hardware, Kyushu Institute of Technology, Japan. His research interests include soft computing, neural networks, hardware, and home service robots. He is a member of IEEE and JNNS |
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Online resource; title from PDF title page (Taylor & Francis, viewed February 14, 2024) |
| Subject |
Artificial intelligence.
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Internet of things.
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artificial intelligence.
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COMPUTERS / Artificial Intelligence
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COMPUTERS / Data Processing / Parallel Processing
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| Form |
Electronic book
|
| Author |
Kulkarni, Shrikaant, editor.
|
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Dvivedī, Jayaprakāśa Nārāyaṇa, editor.
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Pramanta, Dinda, editor
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Tanaka, Yuichiro, editor
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| ISBN |
9781032650722 |
|
1032650729 |
|
9781003825142 |
|
1003825141 |
|
9781003825128 |
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1003825125 |
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