{"id":25759,"date":"2019-04-05T10:12:55","date_gmt":"2019-04-05T08:12:55","guid":{"rendered":"https:\/\/www.ita.es\/proyecto\/cosmos\/"},"modified":"2023-11-30T09:09:10","modified_gmt":"2023-11-30T08:09:10","slug":"cosmos","status":"publish","type":"proyecto","link":"https:\/\/www.ita.es\/en\/project\/cosmos\/","title":{"rendered":"COSMOS"},"content":{"rendered":"\r\n
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\n 01 Project name:<\/strong>\n <\/p>\n\n\n\n

COSMOS <\/p>\n\n\n\n

\n 02 Summary:<\/strong>\n <\/p>\n\n\n\n

Platform\nof Cloud-based Energy Demand Forecasting based on Machine\nLearning and Big Data<\/p>\n\n\n\n

\n 03 General data:<\/strong>\n <\/p>\n\n\n\n

Description: Collaboration Challenges 2017 – COSMOS<\/p>\n\n\n\n

Number of\nDossier: RTC-2017-6289-3<\/p>\n\n\n\n

Date of\ngrant: 04\/12\/2018<\/p>\n\n\n\n

Dates of\nexecution: 01\/06\/2018 – 30\/05\/2020<\/p>\n\n\n\n

\n 04 Technical information on the project and objectives:<\/strong>\n <\/p>\n\n\n\n

The objective\nof COSMOS is the development of a Big Data technology platform unique in the world.\nthe market, allowing the collection and processing of massive amounts of data\ncollected for its subsequent transformation into intelligence, which will allow to\noptimize energy efficiency decision making, by means of\nof making advanced forecasts about demand forecasting\nenergy consumption. To this end, a model must be designed for forecasting the\ndemand for energy consumption that can be dynamically adapted to changing\nin consumption automatically.<\/p>\n\n\n\n

The\nforecasting of energy consumption demand will mean that the energy consumption of the\nmarketing companies a determining factor in optimizing the quality of their products.\ndecision making. However, this is a process that requires the\nand processing of huge amounts of data, so that most of the data is\nThe sector’s companies do not have the tools, capacity, or the ability to\nmethod to be able to make this prediction. This situation of lack of\ntechnology in the marketplace causes these marketing companies to incur\nin severe deviations at the time of making the energy purchase offers, which\nimpact on the cost overrun for the end consumer.<\/p>\n\n\n\n

Currently\nthere is an important technological gap in the sector, due to the non-existence of\nof available technologies that take advantage of the benefits of Big Data and Cloud\nComputing to increase energy efficiency.<\/p>\n\n\n\n

Among the\nobjectives are to promote technological development, innovation, and a\nquality research.<\/p>\n\n\n\n

\n 05 Project leader and partners:<\/strong>\n <\/p>\n\n\n\n

– TECHNOLOGY\nSISTEMAS Y APLICACIONES SL (TECSISA, as project leader)<\/p>\n\n\n\n

– ASIC XXI<\/p>\n\n\n\n

– ITAINNOVA<\/p>\n\n\n\n

\n 06 FPC Program:<\/strong>\n <\/p>\n\n\n\n

Challenges Collaboration 2017. Funded by: Ministry of Science, Innovation and Universities- State Research Agency\/ COSMOS (RTC-2017-6289-3).<\/p>\n\n\n\n

\n 07 General and specific budget:<\/strong>\n <\/p>\n\n\n\n

Budget\nbankable: 925,854.8<\/p>\n\n\n\n

Budget\nITAINNOVA fundable: 139750<\/p>\n\n\n\n

\n 08 General and specific subsidies and financing:<\/strong>\n <\/p>\n\n\n\n

Subsidy\nproject total: 139750<\/p>\n\n\n\n

Loan\ntotal project: 314890.8<\/p>\n\n\n\n

Grant to ITAINNOVA: 139750<\/p>\n\n\n\n

LOGOS<\/p>\n\n\n\n

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