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A new step towards pressure transient cl...

Thames Water has developed a novel solution for understanding pressure transients in clean water networks. By applying machine-learning techniques on high-resolution pressure data from Syrinix PipeMinder-S (PM-S) devices, the Innovation team at Thames Water have been able to classify a majority of transients as normal network operations, and highlight unusual pressure events worthy of further […]

Energy visualisation at the Smart Water ...

Dr. Esther Goya and Dr. Johannes Andersen from Thames Water presented at the 6th annual Smart Water System Conference that took place in London on the 24th and 25th of April   Organised by SMI, the conference discussed the challenges and new developments of the implementation of smart meters as well as the value of […]

Leak-detecting smart meters are putting ...

Thames Water has been installing the water industry’s latest smart meter technology in the borough since May 2016 as part of its capital-wide metering programme to help save water. So far, 15,165 smart meters have been installed in Haringey, with thousands more expected to be fitted over the next year. Early results show customers who […]

Multivariate data mining for estimating ...

Multivariate data mining for estimating the rate of discoloration material accumulation in drinking water distribution systemss Author: Mounce, S. R., Blokker, E. J. M., Husband, S. P., Furnass, W. R., Schaap, P. G., Boxall, J. B. Full Paper         Abstract:  Particulate material accumulates over time as cohesive layers on internal pipeline surfaces […]

Bounds on water quality sensor network p...

Bounds on water quality sensor network performance from design choices and practical considerations Author: P. van Thienen, B. de Graaf, J. Hoogterp, J. van Summeren, A. Vogelaar Full Paper         Abstract:  Bounds of limitations on traditional approaches to optimal water quality sensor placement in drinking water distribution networks, oriented towards obtaining information […]

Automated feature recognition in CFPD an...

Automated feature recognition in CFPD analyses of DMA or supply area flow data Author: Peter van Thienen and Ina Vertommen Full Paper         Abstract:  The recently introduced comparison of flow pattern distributions (CFPD) method for the identification, quantification and interpretation of anomalies in district metered areas (DMAs) or supply area flow time […]

 
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