Creating household occupancy and energy behavioural profiles using national time use survey data

Jeong, Bongchan; Kim, Jungsoo; Dear, Richard de

doi:10.1016/j.enbuild.2021.111440

Cited by 16 publications

(3 citation statements)

References 24 publications

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“…As shown in previous studies, building performance are highly dependent on the occupant behavior (Ren and Yan 2014;McKenna et al 2015;Jeong et al 2021;Mitra et al 2021). Thus, the proposed occupancy model can influence the predictions of other occupant behaviors by accurately predicting the occupancy, and then influence the building performance simulation indirectly.…”

Section: Preliminary Applicationmentioning

confidence: 73%

Occupancy of rooms in urban residential buildings by users in cold areas of China

Dong

Sun

2022

Build. Simul.

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Occupancy is used to represent the movements and locations of users among various zones of buildings, and it is the basis of all other daily energy consumption behaviors. This study investigated eight families in cold areas of China based on occupancy measurements obtained in four main rooms, i.e., living room, bedroom, kitchen, and bathroom. In particular, we analyzed the duration of user occupancy and hourly mean occupancy, and characterized their regular and random features. According to the results, we developed an event-based occupancy model using an inhomogeneous Markov chain, where the rooms were modeled and daily events were divided into three categories according to their randomness. We established a new method for conversion between event characteristic parameters and a transition probability matrix, as well as an overlap avoidance method for active events. The model was then validated using real data. The results showed that the model performed well in terms of two evaluation criteria. The model should improve the accuracy of simulations of occupancy.

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Section: Preliminary Applicationmentioning

confidence: 73%

Occupancy of rooms in urban residential buildings by users in cold areas of China

Dong

Sun

2022

Build. Simul.

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“…Researchers have found a 41% difference between commonly accepted default occupancy schedules and the schedules they generated for residential buildings, although both schedules share similar patterns. Similarly, another study relied on a time use survey and census data to assess occupancy and behavioural information (Jeong et al, 2021). Researchers obtained information for household composition and occupant activities during different periods of the year.…”

Section: Prototypementioning

confidence: 99%

Proceedings of the 27th Conference on Computer Aided Architectural Design Research in Asia (CAADRIA) [Volume 2]

2022

CAADRIA Proceedings

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This paper discusses the design and development of scale masonry structures using robot arms, computer vision hardware and bespoke computational workflows. In parallel to the development of full-scale masonry solutions using a Cable Driven Parallel Robot (CDPR), a faster method for testing large numbers of brick elements is needed to verify buildability, mitigate collisions, and think differently about recycled materials during real-world construction activities. Additionally, by incorporating scanning and analysis technology, materials can be digitized, and their attributes translated into variables for placement within an intended structure.

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“…Furthermore, spatial variation also exists in time use. Several studies showed differences in the time use of occupants among countries, which revealed spatial variation existed in the time spent on OBs [9][10][11]. Esteban et al [12] found that OBs conducted by people are spatially varied in European countries, which cannot be effectively explained by economic or demographic differences.…”

Section: Introductionmentioning

confidence: 99%

Modeling of occupant behavior considering spatial variation: Geostatistical analysis and application based on American time use survey data

Yamaguchi

Torriti

et al. 2023

Energy and Buildings

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Creating household occupancy and energy behavioural profiles using national time use survey data

Cited by 16 publications

References 24 publications

Occupancy of rooms in urban residential buildings by users in cold areas of China

Occupancy of rooms in urban residential buildings by users in cold areas of China

Proceedings of the 27th Conference on Computer Aided Architectural Design Research in Asia (CAADRIA) [Volume 2]

Modeling of occupant behavior considering spatial variation: Geostatistical analysis and application based on American time use survey data

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