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Monitoring networked infrastructure with minimum data via sequential graph fourier transforms

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Wei, Zhuangkun, Pagani, Alessio and Guo, Weisi (2020) Monitoring networked infrastructure with minimum data via sequential graph fourier transforms. In: IEEE International Smart Cities Conference, Casablanca, Morocco, 14-17 Oct 2019. Published in: 2019 IEEE International Smart Cities Conference (ISC2) doi:10.1109/ISC246665.2019.9071735 ISSN 2687-8860.

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Official URL: https://doi.org/10.1109/ISC246665.2019.9071735

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Abstract

Many urban infrastructures contain complex dynamics embedded in spatial networks. Monitoring using Internet-of-Things (IoT) sensors is essential for ensuring safe operations. An open challenge is given an existing sensor network, where best to collect the minimum amount of representative data. Here, we consider an urban underground water distribution network (WDN) and the problem of contamination detection. Existing topology-based approaches link complex network (e.g. Laplacian spectra) to optimal sensing selections, but neglects the underpinning fluid dynamics. Alternative data-driven approaches such as compressed sensing (CS) offer limited data reduction.In this work, we introduce a principal component analysis based Graph Fourier Transform (PCA-GFT) method, which can recover the full networked signal from a dynamic subset of sensors. Specifically, at each time step, we are able to predict which sensors are needed for the next time step. We do so, by exploiting the spatial-time correlations of the WDN dynamics, as well as predicting the sensor set needed using sparse coefficients in the transformed domain. As such, we are able to significantly reduce the number of samples compared with CS approaches. The drawback lies in the computational complexity of a data collection point (DCP) updating the PCA-GFT operator at each time-step. The experimental results show that, on average, with nearly 40% of the sensors reported, the proposed PCA-GFT method is able to fully recover the networked dynamics.

Item Type: Conference Item (Paper)
Subjects: T Technology > TD Environmental technology. Sanitary engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): Internet of things, Smart water grids, Computer networks
Journal or Publication Title: 2019 IEEE International Smart Cities Conference (ISC2)
Publisher: IEEE
ISSN: 2687-8860
Official Date: 20 April 2020
Dates:
DateEvent
20 April 2020Published
7 August 2019Accepted
DOI: 10.1109/ISC246665.2019.9071735
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 21 August 2019
Date of first compliant Open Access: 21 August 2019
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
Lloyd’s Register Foundation’s ProgrammeAlan Turing Institutehttp://dx.doi.org/10.13039/100012338
EP/N510129/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/R041725/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
Conference Paper Type: Paper
Title of Event: IEEE International Smart Cities Conference
Type of Event: Conference
Location of Event: Casablanca, Morocco
Date(s) of Event: 14-17 Oct 2019
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