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An IoT sensor network to model occupancy profiles for energy usage simulation tools

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)
1 Descargas (Pure)

Resumen

The development of IoT devices has allowed to install large amounts of sensors in different environments. Consequently, monitoring small houses and entire buildings has become possible. In addition, buildings are one of the biggest energy consumers, so the monitoring of the energy waste, and its sources, is gaining attention. Human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, thus being able to easily monitor such behaviour will bring greater insight in the building usage. In this paper, an IoT sensor network is proposed to model occupancy profiles at room level. Such measurement of users’ behaviour along with additional information such as temperature or humidity can be used to develop strategies to save energy, especially regarding heating, ventilating and airconditioning (HVAC) systems. The proposed equipment has been gathering data for some months in a workplace containing several meeting rooms. Four of those rooms were monitored and later analysed to test the validity of the proposed approach. The results show that it is possible to obtain occupancy profiles by using simple IoT equipment.
Idioma originalInglés
Título de la publicación alojadaunknown
EditorialIEEE
Páginas1-6
Número de páginas6
ISBN (versión digital)9781538664513
ISBN (versión impresa)978-1-5386-6452-0
DOI
EstadoPublicada - 13 nov 2018
Evento2018 Global Internet of Things Summit, GIoTS 2018 - Bilbao, Espana
Duración: 4 jun 20187 jun 2018

Serie de la publicación

Nombre2018 Global Internet of Things Summit, GIoTS 2018

Conferencia

Conferencia2018 Global Internet of Things Summit, GIoTS 2018
País/TerritorioEspana
CiudadBilbao
Período4/06/187/06/18

Palabras clave

  • Behaviour modelling
  • Data analysis
  • IoT
  • Occupancy profiles
  • Sensor networks
  • Smart building

Project and Funding Information

  • Funding Info
  • Unai Saralegui is grateful to the Tecnalia Research & Innovation_x000D_ Foundation for funding through a PhD fellowship._x000D_ Olatz Arbelaitz and Javier Muguerza’s research was partially_x000D_ supported by the Department of Education, Universities and_x000D_ Research of the Basque Government under Grant IT980-_x000D_ 16 and by the Ministry of Economy and Competitiveness_x000D_ of the Spanish Government and the European Regional_x000D_ Development fund- ERFD (PhysComp project, TIN2017-_x000D_ 85409-P).

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