東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

AI-empowered IoT communications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI-empowered IoT communications/ by Yulin Shao.
作者:	Shao, Yulin.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xvi, 342 p. :ill., digital ;24 cm.
內容註:	Chapter 1. Introduction -- Chapter 2. AI-Enhanced Feedback Communication for IoT -- Chapter 3. Semantic Communication for IoT -- Chapter 4. AI-Driven Multiple-Access for IoT -- Chapter 5. AI-Driven Network Management and Optimization for IoT -- Chapter 6. Future Trends and Challenges.
Contained By:	Springer Nature eBook
標題:	Internet of things. -
電子資源:	https://doi.org/10.1007/978-3-031-98816-5
ISBN:	9783031988165

AI-empowered IoT communications
Shao, Yulin.

AI-empowered IoT communications[electronic resource] /by Yulin Shao. - Cham :Springer Nature Switzerland :2025. - xvi, 342 p. :ill., digital ;24 cm. - Wireless networks,2366-1445. - Wireless networks..

Chapter 1. Introduction -- Chapter 2. AI-Enhanced Feedback Communication for IoT -- Chapter 3. Semantic Communication for IoT -- Chapter 4. AI-Driven Multiple-Access for IoT -- Chapter 5. AI-Driven Network Management and Optimization for IoT -- Chapter 6. Future Trends and Challenges.

This book presents a comprehensive framework for integrating Artificial Intelligence (AI) into Internet of Things (IoT) networks. It redefines communication paradigms by merging traditional data transmission with intelligent decision-making, adaptive feedback mechanisms, and semantic understanding. Beginning with foundational communication principles, the book progresses to advanced topics such as AI-enabled feedback coding, semantic representation, multi-agent learning for multiple access, and intelligent network control using deep reinforcement learning, graph neural networks, and large language models. A central theme of the book is how AI can unlock new dimensions of energy efficiency, scalability, and reliability across diverse IoT environments, from industrial automation and healthcare to smart cities and edge learning. Through practical case studies and in-depth technical discussions, it demonstrates how intelligent protocols enhance communication quality, minimize energy consumption, and coordinate large-scale distributed devices. The book concludes with a forward-looking examination of societal and ethical implications, addressing key challenges in managing intelligent IoT systems at scale. This book is intended for researchers, graduate students, and professionals in wireless communications, AI for networking, and IoT systems. System engineers and practitioners engaged in network optimization, industrial IoT, and smart city development will also find it a valuable resource.

ISBN: 9783031988165

Standard No.: 10.1007/978-3-031-98816-5doiSubjects--Topical Terms:

2057703
Internet of things.

LC Class. No.: TK5105.8857

Dewey Class. No.: 004.678

AI-empowered IoT communications
LDR:02801nmm a2200337 a 4500 001 2421967
003 DE-He213
005 20251025130411.0
006 m d
007 cr nn 008maaau
008 260505s2025 sz s 0 eng d
020 $a 9783031988165 $q (electronic bk.)
020 $a 9783031988158 $q (paper)
024 7 $a 10.1007/978-3-031-98816-5 $2 doi
035 $a 978-3-031-98816-5
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5105.8857
072 7 $a UKN $2 bicssc
072 7 $a COM043000 $2 bisacsh
072 7 $a UKN $2 thema
082 0 4 $a 004.678 $2 23
090 $a TK5105.8857 $b .S528 2025
100 1 $a Shao, Yulin. $3 3803414
245 1 0 $a AI-empowered IoT communications $h [electronic resource] / $c by Yulin Shao.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xvi, 342 p. : $b ill., digital ; $c 24 cm.
490 1 $a Wireless networks, $x 2366-1445
505 0 $a Chapter 1. Introduction -- Chapter 2. AI-Enhanced Feedback Communication for IoT -- Chapter 3. Semantic Communication for IoT -- Chapter 4. AI-Driven Multiple-Access for IoT -- Chapter 5. AI-Driven Network Management and Optimization for IoT -- Chapter 6. Future Trends and Challenges.
520 $a This book presents a comprehensive framework for integrating Artificial Intelligence (AI) into Internet of Things (IoT) networks. It redefines communication paradigms by merging traditional data transmission with intelligent decision-making, adaptive feedback mechanisms, and semantic understanding. Beginning with foundational communication principles, the book progresses to advanced topics such as AI-enabled feedback coding, semantic representation, multi-agent learning for multiple access, and intelligent network control using deep reinforcement learning, graph neural networks, and large language models. A central theme of the book is how AI can unlock new dimensions of energy efficiency, scalability, and reliability across diverse IoT environments, from industrial automation and healthcare to smart cities and edge learning. Through practical case studies and in-depth technical discussions, it demonstrates how intelligent protocols enhance communication quality, minimize energy consumption, and coordinate large-scale distributed devices. The book concludes with a forward-looking examination of societal and ethical implications, addressing key challenges in managing intelligent IoT systems at scale. This book is intended for researchers, graduate students, and professionals in wireless communications, AI for networking, and IoT systems. System engineers and practitioners engaged in network optimization, industrial IoT, and smart city development will also find it a valuable resource.
650 0 $a Internet of things. $3 2057703
650 0 $a Artificial intelligence. $3 516317
650 1 4 $a Computer Communication Networks. $3 775497
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Wireless and Mobile Communication. $3 3338159
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Wireless networks. $3 2162432
856 4 0 $u https://doi.org/10.1007/978-3-031-98816-5
950 $a Professional and Applied Computing (SpringerNature-12059)