Data-Centric Structural Health Monitoring: Mechanical, Aerospace and Complex Infrastructure Systems

Mohammad Noori; Fuh Gwo Yuan; Ehsan Noroozinejad Farsangi

doi:10.1515/9783110791426

Data-Centric Structural Health Monitoring: Mechanical, Aerospace and Complex Infrastructure Systems

Mohammad Noori (Editor), Fuh Gwo Yuan (Editor), Ehsan Noroozinejad Farsangi (Editor)

Research output: Book/Research Report › Edited Book › peer-review

Abstract

This book introduces the latest developments in data-centric engineering, including different artificial intelligence and machine learning approaches, as well as their wide range of applications for long-term monitoring and health assessment of mechanical, aerospace and complex infrastructure systems. Leading scholars in the field demonstrate these emerging techniques assure the longevity of engineered systems and predict their life cycles. "¢ Presents a data-centric approach to structural engineering. "¢ Covers the applications of AI and Machine Learning to infrastructure sustainability. "¢ Features leading scholars worldwide.

Original language	English
Place of Publication	Germany
Publisher	Walter de Gruyter
Number of pages	263
ISBN (Electronic)	9783110791426
ISBN (Print)	9783110791273
DOIs	https://doi.org/10.1515/9783110791426
Publication status	Published - 4 Sept 2023
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2023 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved.

Keywords

Artificial Intelligence
Data Analysis
Data-Centric Engineering
Machine Learning
Sustainability

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1515/9783110791426

Cite this

@book{466071ef38ad485993f66b766b7af507,

title = "Data-Centric Structural Health Monitoring: Mechanical, Aerospace and Complex Infrastructure Systems",

abstract = "This book introduces the latest developments in data-centric engineering, including different artificial intelligence and machine learning approaches, as well as their wide range of applications for long-term monitoring and health assessment of mechanical, aerospace and complex infrastructure systems. Leading scholars in the field demonstrate these emerging techniques assure the longevity of engineered systems and predict their life cycles. {"}¢ Presents a data-centric approach to structural engineering. {"}¢ Covers the applications of AI and Machine Learning to infrastructure sustainability. {"}¢ Features leading scholars worldwide.",

keywords = "Artificial Intelligence, Data Analysis, Data-Centric Engineering, Machine Learning, Sustainability",

editor = "Mohammad Noori and Yuan, {Fuh Gwo} and Farsangi, {Ehsan Noroozinejad}",

year = "2023",

month = sep,

day = "4",

doi = "10.1515/9783110791426",

language = "English",

isbn = "9783110791273",

publisher = "Walter de Gruyter",

}

TY - BOOK

T1 - Data-Centric Structural Health Monitoring: Mechanical, Aerospace and Complex Infrastructure Systems

A2 - Noori, Mohammad

A2 - Yuan, Fuh Gwo

A2 - Farsangi, Ehsan Noroozinejad

PY - 2023/9/4

Y1 - 2023/9/4

N2 - This book introduces the latest developments in data-centric engineering, including different artificial intelligence and machine learning approaches, as well as their wide range of applications for long-term monitoring and health assessment of mechanical, aerospace and complex infrastructure systems. Leading scholars in the field demonstrate these emerging techniques assure the longevity of engineered systems and predict their life cycles. "¢ Presents a data-centric approach to structural engineering. "¢ Covers the applications of AI and Machine Learning to infrastructure sustainability. "¢ Features leading scholars worldwide.

AB - This book introduces the latest developments in data-centric engineering, including different artificial intelligence and machine learning approaches, as well as their wide range of applications for long-term monitoring and health assessment of mechanical, aerospace and complex infrastructure systems. Leading scholars in the field demonstrate these emerging techniques assure the longevity of engineered systems and predict their life cycles. "¢ Presents a data-centric approach to structural engineering. "¢ Covers the applications of AI and Machine Learning to infrastructure sustainability. "¢ Features leading scholars worldwide.

KW - Artificial Intelligence

KW - Data Analysis

KW - Data-Centric Engineering

KW - Machine Learning

KW - Sustainability

UR - http://www.scopus.com/inward/record.url?scp=85171604755&partnerID=8YFLogxK

U2 - 10.1515/9783110791426

DO - 10.1515/9783110791426

M3 - Edited Book

SN - 9783110791273

BT - Data-Centric Structural Health Monitoring: Mechanical, Aerospace and Complex Infrastructure Systems

PB - Walter de Gruyter

CY - Germany

ER -

Data-Centric Structural Health Monitoring: Mechanical, Aerospace and Complex Infrastructure Systems

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this