Data Analytics for Smart Infrastructure - Wang, Yang; Li, Zhidong; Liang, Bin; - Prospero Internet Bookshop

 
Product details:

ISBN13:9781032754154
ISBN10:103275415X
Binding:Paperback
No. of pages:184 pages
Size:234x156 mm
Language:English
Illustrations: 81 Illustrations, black & white; 13 Halftones, black & white; 68 Line drawings, black & white; 23 Tables, black & white
700
Category:

Data Analytics for Smart Infrastructure

Asset Management and Network Performance
 
Edition number: 1
Publisher: CRC Press
Date of Publication:
 
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Short description:

This book presents, for the first time, data analytics for smart infrastructures. The authors draw on over a decade?s experience working with industry and demonstrating the capabilities of data analytics for infrastructure and asset management. 

Long description:

This book presents, for the first time, data analytics for smart infrastructures. The authors draw on over a decade?s experience working with industry and demonstrating the capabilities of data analytics for infrastructure and asset management.  


The volume gives data-driven solutions to cover critical capabilities for infrastructure and asset management across three domains: 1) situation awareness 2) predictive analytics and 3) decision support. The reader will gain from various data analytic techniques including anomaly detection, performance evaluation, failure prediction, trend analysis, asset prioritization, smart sensing and real-time/online systems. These data analytic techniques are vital to solving problems in infrastructure and asset management. The reader will benefit from case studies drawn from critical infrastructures such as water management, structural health monitoring and rail networks.  


This groundbreaking work will be essential reading for those studying and practicing analytics in the context of smart infrastructure.  



" ?Data Analytics for Smart Infrastructure? is an indispensable resource for researchers, engineers, and even asset managers. The book's focus on data analytics for smart infrastructure will be of significant benefit to professionals seeking to expand their knowledge and skills in the use of analytics techniques. "


-Professor Changsheng XuChinese Academy of Sciences


 


" ?Data Science for Smart Infrastructure? is an indispensable resource that empowers professionals to harness the power of data analytics in infrastructure and asset management practices. With insightful case studies, this book showcases the transformative potential of data-driven solutions in optimizing infrastructure operations and management." 


-Professor Dikai LiuUniversity of Technology Sydney 


 


This book is essential for navigating the complexities of modern infrastructure management. With a focus on real-world applications and advanced techniques, it equips readers with the knowledge to optimise infrastructure and asset management through data analytics. A must-read for anyone seeking to harness the power of data for critical infrastructure systems. 


-Professor Lei WangUniversity of Wollongong 


 


The book is a comprehensive exploration of data analytics for smart infrastructure, offering invaluable insights into enhancing situation awareness, predictive analytics, and decision support. Covering a range of data-driven solutions with practical applications, from service gap identification to real-time system implementation, it's an indispensable resource for professionals and researchers. 


 -Professor Zhiyong WangUniversity of Sydney

Table of Contents:

1. AI Empowering Infrastructure: the Road to Smartness  2. Asset anomaly identification - damage detection in structural health monitoring  3. Network performance evaluation - Delay Propagation on Large Scale Railway Systems  4. Network Status Monitoring - Signal Aspect Detection for Railway Networks  5. Underground Vessel: Water Pipe Failure Prediction  6. Long-Term Prediction of Water Supply Networks Condition  7. Service Demand Prediction - passenger flow  8. Prioritising Risk Assets for Infrastructure Maintenance  9. Adapting dynamic behavior evolution in structural health monitoring  10. Smart Sensing and Preventative Maintenance