PROJECTS
Energymate
We are not different from you. We believe in a responsible and transparent use of energy. We offer you an easy way to take control of your energy consumption, in plain language, with no small print and above all an space where you can share and gain knowledge for a more informed use of your energy.
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ENERGYMATE: Experimental development for an application that provides the user with their electricity consumption in natural language format and suggests opportunities to adapt their behavior to the prices of the electricity schedule.
With the main objective of:
“Provide customers with relevant information about their electricity consumption habits through the use of natural language, in an innovative service, being able to be different and thus seeking, loyalty and strengthening relationships with them”
Project subsidized by:
Weldingmate
WELDINGMATE: Software solution capable of monitoring the welding activities carried out in the equipment.
With the main objective of:
“Carry out traceability of welding procedures, from the materials used, through the welders involved and the processes that are carried out, to the traceability of the non-destructive tests performed on welding and equipment (visual inspection, liquids penetrants, inspection of magnetic particles, ultrasound…) ”
Project subsidized by:
Disaggregation of electrical consumption
Big Data platform with application of Artificial Intelligence models for the disaggregation of electrical consumptions, from time series of high frequency electric meters in Industry 4.0 environments.
With the main objetive of:
Big Data platform with application of Artificial Intelligence models for the disaggregation of electrical consumptions, from time series of high frequency electric meters in Industry 4.0 environments.With the main objective of:“Obtain a large amount of data (Big Data) of electrical consumption through high frequency electrical meters and use them by disaggregating them, applying Non-Intrusive Load Monitoring – NILM techniques to generate some models based on Artificial Intelligence evaluating their result, both for the detection of consumption elements as for the connection / disconnection of these (start and stop) ”
Project subsidized by:
