Extending the Brick schema to represent metadata of occupants

Luo, Na; Fierro, Gabe; Liu, Yapan; Dong, Bing; Hong, Tianzhen

doi:10.1016/j.autcon.2022.104307

Extending the Brick schema to represent metadata of occupants

Journal Article · Fri May 06 00:00:00 EDT 2022 · Automation in Construction

DOI:https://doi.org/10.1016/j.autcon.2022.104307· OSTI ID:1869801

Luo, Na; Fierro, Gabe; Liu, Yapan; Dong, Bing; Hong, Tianzhen

Here, energy-related behaviors of occupants constitute a key factor influencing building performance; accordingly, the measured occupant data can support the objective assessment of the indoor environment and energy performance of buildings, which can inform building design and operational decisions. Existing data schemas focus on metadata of sensors, meters, physical equipment, and IoT devices in buildings; however, they are limited in representing the metadata of occupant data, including occupants' presence in spaces, movement between spaces, interactions with building systems or IoT devices, and preference of indoor environmental needs. To address this gap, an extension to the widely adopted metadata schema, Brick, is proposed to represent the contextual, behavioral, and demographic information of occupants. The proposed extension includes four parts: (1) a new “Occupant” class to represent occupants' demography and energy related behavioral patterns, (2) new subclasses under the Equipment class to represent envelope system and personal thermal comfort devices, (3) new subclasses under the Point class to represent occupant sensing and status, and (4) new auxiliary properties for occupant interactable equipment to represent the level of controllability for each piece of equipment by occupants. The extension is implemented in the Brick schema and has been tested using multiple occupant datasets from the ASHRAE Global Occupant Database. The extension enables Brick schema to capture diverse types of occupant sensing data and their metadata for FAIR data research and applications.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: American Society of Heating, Refrigerating and Air-Conditioning Engineers; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: AC02-05CH11231; AC36-08GO28308; EE0008681

OSTI ID:: 1869801

Alternate ID(s):: OSTI ID: 1872741

Report Number(s):: NREL/JA-5500-82999; MainId:83772; UUID:ab563f82-63c3-49b1-b23c-7716a3c81c84; MainAdminID:64576

Journal Information:: Automation in Construction, Journal Name: Automation in Construction Vol. 139; ISSN 0926-5805

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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