A Recommendation-based Proposal for Improving Energy Efficiency in Housing
[EN]75% of buildings in the EU are not designed according to any energy efficiency code and around 45%of the world’s energy is used in the residential sector. This is why one of Europe’s biggest energy challenges is to include consumers at the heart of the energy system. The aim of this work is to d...
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/144155 |
| Acceso en línea: | http://hdl.handle.net/10366/144155 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial Intelligence Energy Efficiency Machine Learning Recommending System 1203.04 Inteligencia Artificial 3322.01 Distribución de la Energía |
| Sumario: | [EN]75% of buildings in the EU are not designed according to any energy efficiency code and around 45%of the world’s energy is used in the residential sector. This is why one of Europe’s biggest energy challenges is to include consumers at the heart of the energy system. The aim of this work is to develop a solution to a problem of such magnitude: to create a system of personalised recommendations to each consumer that contributes to improving the energy efficiency of their home. The data will be obtained from sensorized homes in Salamanca. Some examples of possible recommendations are reducing the temperature of the thermostat, change the time at which the house is ventilated and raise the blinds at a certain time. The system developed is capable of providing these recommendations correctly an-d efficiently. |
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