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Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles
dc.contributor.author | Saralegui Vallejo, Unai | |
dc.contributor.author | Antón, Miguel Ángel | |
dc.contributor.author | Arbelaiz Gallego, Olatz | |
dc.contributor.author | Muguerza Rivero, Javier Francisco | |
dc.date.accessioned | 2019-03-29T14:08:43Z | |
dc.date.available | 2019-03-29T14:08:43Z | |
dc.date.issued | 2019-01-02 | |
dc.identifier.citation | Sensors 19(2) : (2019) // Article ID 353 | es_ES |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10810/32222 | |
dc.description.abstract | The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies. | es_ES |
dc.description.sponsorship | This work was partially supported by the Department of Education, Universities and Research of the Basque Government (ADIAN research group, grant IT980-16) and by the Ministry of Economy and Competitiveness of the Spanish Government and the European Regional Development fund- ERDF (PhysComp project, TIN2017-85409-P). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/TIN2017-85409-P | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | buildings | es_ES |
dc.subject | ambient intelligence | es_ES |
dc.subject | occupancy detection | es_ES |
dc.subject | behaviour modelling | es_ES |
dc.subject | sensor networks | es_ES |
dc.subject | smart meeting room | es_ES |
dc.subject | Internet of Things (IoT) | es_ES |
dc.subject | energy management-system | es_ES |
dc.subject | iot | es_ES |
dc.subject | methodologies | es_ES |
dc.subject | technologies | es_ES |
dc.subject | behavior | es_ES |
dc.subject | design | es_ES |
dc.subject | zigbee | es_ES |
dc.title | Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0). | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/19/2/353 | es_ES |
dc.identifier.doi | 10.3390/s19020353 | |
dc.departamentoes | Arquitectura y Tecnología de Computadores | es_ES |
dc.departamentoeu | Konputagailuen Arkitektura eta Teknologia | es_ES |