{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:06:52Z","timestamp":1760234812974,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T00:00:00Z","timestamp":1623628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>At present, capacity control in indoor spaces is critical in the current situation in which we are living in, due to the pandemic. In this work, we propose a new solution using machine learning techniques with BLE technology. This study presents a real experiment in a university environment and we study three different prediction models using machine learning techniques\u2014specifically, logistic regression, decision trees and artificial neural networks. As a conclusion, the study shows that machine learning techniques, in particular decision trees, together with BLE technology, provide a solution to the problem. The contribution of this research work shows that the prediction model obtained is capable of detecting when the COVID capacity of an enclosed space is exceeded. In addition, it ensures that no false negatives are produced, i.e., all the people inside the laboratory will be correctly counted.<\/jats:p>","DOI":"10.3390\/jsan10020035","type":"journal-article","created":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T22:26:01Z","timestamp":1623709561000},"page":"35","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Capacity Control in Indoor Spaces Using Machine Learning Techniques Together with BLE Technology"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6280-7852","authenticated-orcid":false,"given":"M. Encarnaci\u00f3n","family":"Beato Guti\u00e9rrez","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, Universidad Pontificia de Salamanca, 37002 Salamanca, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3934-0291","authenticated-orcid":false,"given":"Montserrat Mateos","family":"S\u00e1nchez","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universidad Pontificia de Salamanca, 37002 Salamanca, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0503-9134","authenticated-orcid":false,"given":"Roberto","family":"Berj\u00f3n Gallinas","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universidad Pontificia de Salamanca, 37002 Salamanca, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7204-4414","authenticated-orcid":false,"given":"Ana M.","family":"Fermoso Garc\u00eda","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universidad Pontificia de Salamanca, 37002 Salamanca, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1145\/128756.128759","article-title":"The active badge location system","volume":"10","author":"Want","year":"1992","journal-title":"ACM Trans. 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