VIDA Awarded Project - ISV007 - Implementing remote water monitoring in Holland
- Dec 29, 2020
- [email protected]
19 August 2019 / 09 December 2019
Nearly all industrial coffee machines, dishwashers, washing machines, ice machines etc. have water filters installed to soften water and avoid scale build up in the equipment. These filters need to be changed after a certain amount of water has been softened, depending on the water’s hardness and the type/size of filter. Service providers today often change them far too early, since no system exists for remotely monitoring the filters’ statuses. To solve this problem, the Flowplan Solution is making remote water monitoring in real time possible. This is done by utilizing flowmeters and our own Beam electronics box with integrated microprocessor and IoT radio transmission system. We measure each water flow event, and transmit it wirelessly to our cloud software platform, where data is collected and analysed. Based on all the data, we are able to precisely predict when the filters’ capacity is used up. This enables the service providers to intelligently plan their filter changes and thereby reduce driving, and most importantly, stop wasting half-used filters. The solution is working on solving a big issue in the food value chain. As these filters are so widely used, it is a huge waste of resources not to use them completely. By connecting the filters to the internet, we can reduce waste and driving drastically. An estimated 30 million water filters are installed in Europe alone, these filters are changed at least once per year and in extreme cases up to 50 times yearly. Estimating an average size of 5kg per filter and one change per year, and an increased utilization from 75% to 95%, results in a yearly saving of 30.000 tons of resin (polymer) in Europe alone. The collaboration with VIDA has been a big aid in opening up the possibilities for exploring the Dutch market for Flowplan.
Learn more: www.vidaproject.eu I I Follow us: @h2020vida
This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme, under Grant Agreement nº 777795.
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