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

Cited by 12 publications

(2 citation statements)

References 34 publications

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“…The Plaster platform rounds out the stack is an open-source platform for testing various IoT metadata classification strategies (Koh et al, 2018). The BRICK schema continues to be developed to incorporate new types of data including occupants (Chamari et al, 2022;Luo et al, 2022) and building information models (BIM). There are also crucial discussion forming around the convergence of BIM and geographic information systems (GIS) (Zhu and Wu, 2022).…”

Section: Data Convergence Technologiesmentioning

confidence: 99%

Transformational IoT sensing for air pollution and thermal exposures

Pantelic

Nazarian

Miller

et al. 2022

Front. Built Environ.

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Cities today encounter significant challenges pertaining to urbanization and population growth, resource availability, and climate change. Concurrently, unparalleled datasets are generated through Internet of Things (IoT) sensing implemented at urban, building, and personal scales that serve as a potential tool for understanding and overcoming these issues. Focusing on air pollution and thermal exposure challenges in cities, we reviewed and summarized the literature on IoT environmental sensing on urban, building, and human scales, presenting the first integrated assessment of IoT solutions from the data convergence perspective on all three scales. We identified that there is a lack of guidance on what to measure, where to measure, how frequently to measure, and standards for the acceptable measurement quality on all scales of application. The current literature review identified a significant disconnect between applications on each scale. Currently, the research primarily considers urban, building, and personal scale in isolation, leading to significant data underutilization. We addressed the scientific and technological challenges and opportunities related to data convergence across scales and detailed future directions of IoT sensing along with short- and long-term research and engineering needs. IoT application on a personal scale and integration of information on all scales opens up the possibility of developing personal thermal comfort and exposure models. The development of personal models is a vital promising area that offers significant advancements in understanding the relationship between environment and people that requires significant further research.

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Section: Data Convergence Technologiesmentioning

confidence: 99%

Transformational IoT sensing for air pollution and thermal exposures

Pantelic

Nazarian

Miller

et al. 2022

Front. Built Environ.

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“…Semantic interoperability has shown to be an effective tool for improving building operation in general. Until recently, opportunities to improve interactions between the building systems and building occupants have been unaddressed by existing semantic metadata schemas [7,8].…”

Section: Introduction 11 Background and Motivationmentioning

confidence: 99%

Occupant-centric metadata paradigms for comfort optimization in buildings

Bradford,

Coleman,

Meggers

2023

J. Phys.: Conf. Ser.

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Three decades of building performance standards have resulted in a meaningful reduction in energy consumption in commercial buildings, but limited improvement in thermal comfort has been observed. ASHRAE Standard 55, the primary reference used to design and operate “comfortable” buildings, specifies six thermodynamic factors that must be addressed to provide comfort in a space. In practice, survey data reports only a small percentage of buildings are considered satisfactory by occupants. We perform a literature review to demonstrate that the range of each of the six thermodynamic dimensions of comfort can be observed well outside of the applicability of ASHRAE 55 in real buildings. The typical practice of modulating air temperature (Ta ) is shown to result in frequent occupant dissatisfaction. We posit that to be able to more consistently operate within a given “comfort zone” in a wider range of thermodynamic environments, we must embed within building systems higher-dimensional, occupant-centric parameters. To understand if two popular metadata schemas, Project Haystack and Brick Schema, are equipped to support higher-dimensional control paradigms, we (1) define a model, measure, manipulate (M3) evaluation criteria, which we (2) apply to each of the above schemas to determine if they can be used to codify closed-loop control for a given set of thermodynamic dimensions of comfort. We conclude that recent extensions to the Brick Schema provide much of the background necessary to codify closed control loops in six dimensions, and that Project Haystack requires a greater expansion.

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