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Data-Oriented Algorithm for Real-Time Estimation of Flow Rates and Flow Directions in a Water Distribution Network

hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorDUMORA, Christophe
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorAUBER, David
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorBIGOT, Jérémie
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorCOUALLIER, Vincent
hal.structure.identifierCentre recherche et développement [LyRE]
dc.contributor.authorLECLERC, Cyril
dc.date.accessioned2024-04-04T03:05:24Z
dc.date.available2024-04-04T03:05:24Z
dc.date.created2018-06-07
dc.date.issued2018-07-17
dc.date.conference2018-07-17
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193242
dc.description.abstractEnThe aim of this paper is to present how data collected from a water distribution network (WDN) can be used to reconstruct flow rate and flow direction all over the network to enhance knowledge and detection of unforeseen events. The methodological approach consists in modeling the WDN and all available sensor data related to the management of such a network in the form of a flow network graph G = (V, E, s, t, c), with V a set of nodes, E a set of edges whose elements are ordered pairs of distinct nodes, s a source node, t a sink node and c a capacity function on edges. Our objective is to reconstruct a real-valued function f(u,v):VxV => ℝ on all the edges E in VxV from partial observations on a small number of nodes V = {1, ..., n}. This reconstruction method consists in a data-driven Ford-Fulkerson maximum-flow problem in a multi-source, multi-sink context using a constrained bidirectional breadth-first search based on Edmonds-Karp method. The innovative approach is its application in the context of smart cities to operate from sensor data, structural data from a geographical information system (GIS) and consumption estimates.
dc.language.isoen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/
dc.subject.enGraph theory
dc.subject.enmaximum flow problem
dc.subject.endata driven
dc.subject.ensensors
dc.subject.enInternet of Things
dc.subject.enwater distribution network
dc.title.enData-Oriented Algorithm for Real-Time Estimation of Flow Rates and Flow Directions in a Water Distribution Network
dc.typeCommunication dans un congrès
dc.subject.halMathématiques [math]/Statistiques [math.ST]
dc.subject.halInformatique [cs]/Recherche d'information [cs.IR]
dc.subject.halInformatique [cs]/Algorithme et structure de données [cs.DS]
dc.identifier.arxiv1807.10147
bordeaux.page273
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleMulti Conference on Computer Science and Information Systems
bordeaux.countryES
bordeaux.conference.cityMadrid
bordeaux.peerReviewedoui
hal.identifierhal-01847858
hal.version1
hal.invitednon
hal.proceedingsnon
hal.conference.end2018-07-19
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01847858v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2018-07-17&rft.spage=273&rft.epage=273&rft.au=DUMORA,%20Christophe&AUBER,%20David&BIGOT,%20J%C3%A9r%C3%A9mie&COUALLIER,%20Vincent&LECLERC,%20Cyril&rft.genre=unknown


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