› Forums › General › News (General) › processes two billion data points each year for Spanish water utility
Tagged: UseCase_G14, Utility_V8, Water_O5
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May 4, 2019 at 5:03 am #30660
#News(General) [ via IoTForIndiaGroup ]
The Global Omnium Group is one of Spain’s largest water utilities, with a large share of the water-related service market, it manages more than 400 municipalities, from small towns to large cities. Altogether, it serves more than one million customers.
Tiresias is a big data remote readout platform suitable for any sensorisation, but optimised for large meter parks with a large amount of information being produced. It uses a fixed communications network, through issuers, concentrators and repeaters, communicating with the networks and protocols of the main meter manufacturers; iCurrently, the Tiresias environment in Global Omnium receives information from more than 700,000 water meters adding up to two billion annual data points, while displaying a highly efficient data intake. As with the big data information system, the data intake is a crucial point to ensure the quality of the results obtained after treatment. Tiresias incorporates deep learning algorithms to efficiently reconstruct the information that may have been lost in the transmission.
The incorporated algorithm and its machine learning capabilities allow Tiresias to obtain individual consumption patterns of each client and, relating them to variables such as the use of water, socio-economic and geographical environment and other factors, extrapolate the known consumption patterns to users who do not yet have meters with remote-reading capabilities – smart metering.
Ears, go-aigua’s system for intelligent management of water distribution, collaborates with Tiresias in the evaluation of hydraulic performance of sectors or complete networks, and also in the identification of leaks in the distribution network itself. The forecast of the water demand that Tiresias calculates allows Linkwatt to apply its advanced algorithms of both hydraulic and energy cost optimisation of the production of water, optimising the cost of potabilisation in the treatment plants.
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