{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:58:22Z","timestamp":1760237902672,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2020,6,30]],"date-time":"2020-06-30T00:00:00Z","timestamp":1593475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Science and Innovation and the European Regional Development Fund","award":["DPI2015-69891-C2-1-R\/2-R"],"award-info":[{"award-number":["DPI2015-69891-C2-1-R\/2-R"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The understanding of the nature and structure of energy use in large buildings is vital for defining novel energy and climate change strategies. The advances on metering technology and low-cost devices make it possible to form a submetering network, which measures the main supply and other intermediate points providing information of the behavior of different areas. However, an analysis by means of classical techniques can lead to wrong conclusions if the load is not balanced. This paper proposes the use of a deep convolutional autoencoder to reconstruct the whole consumption measured by the submeters using the learnt features in order to analyze the behavior of different building areas. The display of weights and information of the latent space provided by the autoencoder allows us to obtain precise details of the influence of each area in the whole building consumption and its dependence on external factors such as temperature. A submetering network is deployed in the Le\u00f3n University Hospital building in order to test the proposed methodology. The results show different correlations between environmental variables and building areas and indicate that areas can be grouped depending on their function in the building performance. Furthermore, this approach is able to provide discernible results in the presence of large differences with respect to the consumption ranges of the different areas, unlike conventional approaches where the influence of smaller areas is usually hidden.<\/jats:p>","DOI":"10.3390\/s20133665","type":"journal-article","created":{"date-parts":[[2020,6,30]],"date-time":"2020-06-30T09:36:04Z","timestamp":1593509764000},"page":"3665","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Feature Extraction from Building Submetering Networks Using Deep Learning"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2762-6949","authenticated-orcid":false,"given":"Antonio","family":"Mor\u00e1n","sequence":"first","affiliation":[{"name":"Grupo de Investigaci\u00f3n en Supervisi\u00f3n, Control y Automatizaci\u00f3n de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial, Inform\u00e1tica y Aeroespacial, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24007 Le\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3467-4938","authenticated-orcid":false,"given":"Seraf\u00edn","family":"Alonso","sequence":"additional","affiliation":[{"name":"Grupo de Investigaci\u00f3n en Supervisi\u00f3n, Control y Automatizaci\u00f3n de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial, Inform\u00e1tica y Aeroespacial, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24007 Le\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2173-3364","authenticated-orcid":false,"given":"Daniel","family":"P\u00e9rez","sequence":"additional","affiliation":[{"name":"Grupo de Investigaci\u00f3n en Supervisi\u00f3n, Control y Automatizaci\u00f3n de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial, Inform\u00e1tica y Aeroespacial, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24007 Le\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1563-1556","authenticated-orcid":false,"given":"Miguel A.","family":"Prada","sequence":"additional","affiliation":[{"name":"Grupo de Investigaci\u00f3n en Supervisi\u00f3n, Control y Automatizaci\u00f3n de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial, Inform\u00e1tica y Aeroespacial, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24007 Le\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9023-0341","authenticated-orcid":false,"given":"Juan Jos\u00e9","family":"Fuertes","sequence":"additional","affiliation":[{"name":"Grupo de Investigaci\u00f3n en Supervisi\u00f3n, Control y Automatizaci\u00f3n de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial, Inform\u00e1tica y Aeroespacial, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24007 Le\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3921-1599","authenticated-orcid":false,"given":"Manuel","family":"Dom\u00ednguez","sequence":"additional","affiliation":[{"name":"Grupo de Investigaci\u00f3n en Supervisi\u00f3n, Control y Automatizaci\u00f3n de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial, Inform\u00e1tica y Aeroespacial, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24007 Le\u00f3n, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.enbuild.2018.08.040","article-title":"Review of 10 years research on building energy performance gap: Life-cycle and stakeholder perspectives","volume":"178","author":"Zou","year":"2018","journal-title":"Energy Build."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Santamouris, M. (2019). Chapter 2\u2014Energy Consumption and Environmental Quality of the Building Sector. 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