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Unsupervised detection of transitions at home by using BLE technology
dc.contributor.author | Montoliu Colás, Raul | |
dc.contributor.author | Sansano-Sansano, Emilio | |
dc.date.accessioned | 2022-07-22T07:07:46Z | |
dc.date.available | 2022-07-22T07:07:46Z | |
dc.date.issued | 2021-11 | |
dc.identifier.citation | R. Montoliu and E. Sansano-Sansano, "Unsupervised detection of transitions at home by using BLE technology," 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2021, pp. 1-8, doi: 10.1109/IPIN51156.2021.9662578 | ca_CA |
dc.identifier.uri | http://hdl.handle.net/10234/198636 | |
dc.description | Ponencia presentada en la 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 29 Nov.-2 Dec. 2021, Lloret de Mar (Spain) | ca_CA |
dc.description.abstract | This paper presents a set of unsupervised methods based on Bluetooth Low Energy (BLE) technology to obtain the position and transitions that users perform between the zones where they usually stay longer in their own homes. In particular, two different methods are studied to detect the user's position, the first based on proximity and the second based on fingerprinting techniques with self-training. The proposed methodology allows a very easy-to-use deployment by the user and with a very low economic cost. A set of experiments have been carried out to assess the performance of the proposed techniques presented in this paper, where a real user has captured data for several days at home. The results obtained show that the fingerprinting-based method is the most effective to accurately detect the user's position and the transitions performed between the different areas of interest at home. | ca_CA |
dc.format.extent | 8 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | IEEE | ca_CA |
dc.relation | Sistemas de posicionamiento local: enfoque holístico desde las teconologías base a la ciencia de datos para monitorización inteligente y no invasiva de personas (MICROCEBUS-UJI) | ca_CA |
dc.relation | Evaluación de la soledad y la calidad de vida de las personas mayores a través del uso de tecnologías de la información y las comunicaciones | ca_CA |
dc.relation | Evaluación para el pronóstico de deterioro cognitivo leve en las personas mayores y sobrecarga en las personas cuidadoras a través de las tecnologías de la información y las comunicaciones y la inteligencia artificial | ca_CA |
dc.relation.isPartOf | 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 9781665404020 | ca_CA |
dc.rights | © Copyright 2022 IEEE - All rights reserved. | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | ca_CA |
dc.subject | Indoor positioning | ca_CA |
dc.subject | Bluetooth Low Energy | ca_CA |
dc.subject | People monitoring at home | ca_CA |
dc.subject | Unsupervised methods | ca_CA |
dc.subject | E-health | ca_CA |
dc.title | Unsupervised detection of transitions at home by using BLE technology | ca_CA |
dc.type | info:eu-repo/semantics/conferenceObject | ca_CA |
dc.identifier.doi | 10.1109/IPIN51156.2021.9662578 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | https://ieeexplore.ieee.org/document/9662578 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
project.funder.name | Universitat Jaume I | ca_CA |
project.funder.name | Ministerio de Economía, Industria y Competitividad. Gobierno de España | ca_CA |
oaire.awardNumber | RTI2018- 095168-B-C53 | ca_CA |
oaire.awardNumber | AICO/2020/046 | ca_CA |
oaire.awardNumber | UJI-B2020-36 | ca_CA |
oaire.awardNumber | TEC2017-90808-REDT | ca_CA |