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Advancing edge artificial intelligence : (Record no. 141986)

MARC details
000 -LEADER
fixed length control field 02133nam a22002537a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260807152528.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260807s2024 |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788770041027
040 ## - CATALOGING SOURCE
Transcribing agency PK-LaUMT
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number ADV-
245 00 - TITLE STATEMENT
Title Advancing edge artificial intelligence :
Remainder of title system contexts /
Statement of responsibility, etc edited by Ovidiu Vermesan and Dave Marples
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc London :
Name of publisher, distributor, etc River Publishers,
Date of publication, distribution, etc 2024
300 ## - PHYSICAL DESCRIPTION
Extent xxv, 232 p.
490 ## - SERIES STATEMENT
Series statement River Publishers series in communications and networking
500 ## - GENERAL NOTE
General note Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc The intersection of AI, the Internet of Things (IoT) and edge computing has kindled the edge AI revolution that promises to redefine how we perceive and interact with the physical world through intelligent devices. Edge AI moves intelligence from the network centre to the devices at its edge, entrusting these endpoints to analyse data locally, make decisions, and provide real-time responses. Recent advances in power-efficient high-performance embedded silicon make edge AI a viable proposition, albeit one requiring new distributed architectures and novel design concepts. Moving decision-making closer to the edge makes responses faster and systems more reliable, while the constant pressure to reduce network bandwidth demand and the need to contain spiralling data storage and operations costs help justify the engineering investment necessary to embrace this new paradigm. Moving to decentralised operation opens the door to a multitude of novel applications, covering immersive technologies and autonomous systems across fields as diverse as healthcare and industrial automation, personal assistance and prognostics, surgery, and process control. In the best tradition of systems engineering, the first stage of this transition process is understanding the application domain for edge AI deployment, the ""system context"".
546 ## - LANGUAGE NOTE
Language note Eng
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Edge computing
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Vermesan, Ovidiu
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Marples, Dave
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Home library Current library Date acquired Full call number Barcode Date last seen Price effective from Koha item type
      UMT Main Campus UMT Main Campus 2026-08-07 006.31 ADV- 153714 2026-08-07 2026-08-07 Books