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Data analytics for smart infrastructure : asset management and network performance / Yang Wang, Zhidong Li, Ting Guo, Bin Liang, Hongda Tian, Fang Chen.

By: Publisher: Boca Raton, FL : CRC Press, 2025Edition: First editionDescription: xiii, 188p. illContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781032754154
Subject(s): DDC classification:
  • 307.1/416 23/eng/20241125
LOC classification:
  • TD 159.4 .W36
Summary: "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"-- Provided by publisher.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books NILE UNIVERSITY OF NIGERIA - MAIN LIBRARY TD 159.4 .W36 2025 (Browse shelf(Opens below)) Available 0199274
Books Books NILE UNIVERSITY OF NIGERIA - MAIN LIBRARY TD 159.4 .W36 2025 (Browse shelf(Opens below)) Available 0199275
Total holds: 0

Includes bibliographical references and index.

"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"-- Provided by publisher.

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