A Global Building Occupant Behavior Database

Bing Dong*, Yapan Liu, Wei Mu, Zixin Jiang, Pratik Pandey, Tianzhen Hong, Bjarne Olesen, Thomas Lawrence, Zheng O’Neil, Clinton Andrews, Elie Azar, Karol Bandurski, Ronita Bardhan, Mateus Bavaresco, Christiane Berger, Jane Burry, Salvatore Carlucci, Karin Chvatal, Marilena De Simone, Silvia ErbaNan Gao, Lindsay T. Graham, Camila Grassi, Rishee Jain, Sanjay Kumar, Mikkel Kjærgaard, Sepideh Korsavi, Jared Langevin, Zhengrong Li, Aleksandra Lipczynska, Ardeshir Mahdavi, Jeetika Malik, Max Marschall, Zoltan Nagy, Leticia Neves, William O’Brien, Song Pan, June Young Park, Ilaria Pigliautile, Cristina Piselli, Anna Laura Pisello, Hamed Nabizadeh Rafsanjani, Ricardo Forgiarini Rupp, Flora Salim, Stefano Schiavon, Jens Schwee, Andrew Sonta, Marianne Touchie, Andreas Wagner, Sinead Walsh, Zhe Wang, David M. Webber, Da Yan, Paolo Zangheri, Jingsi Zhang, Xiang Zhou, Xin Zhou

*Kontaktforfatter

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

53 Citationer (Scopus)
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Abstract

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.
OriginalsprogEngelsk
Artikelnummer369
TidsskriftScientific Data
Vol/bind9
Udgave nummer1
ISSN2052-4463
DOI
StatusUdgivet - 28 jun. 2022

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© 2022. The Author(s).

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