Space-Mate: Computational Modeling for Building and Occupant Cooperative Sustainable Performance

TitleSpace-Mate: Computational Modeling for Building and Occupant Cooperative Sustainable Performance
Publication TypeWorking Paper
AuthorsFruchter, R., F. Gray Rodriquez, and K. Law
Year of Publication2016
Date PublishedOct-2016

Building performance simulation tools model and predict building performance, but their accuracy is compromised by simplified simulated occupancy. Occupant behavior is complex yet energy modeling software represents it as deterministic and unchanging in hour-long periods of time, which leads to discrepancies between model results and measured performance. These discrepancies limit the use of the models both as a predictive tool and real time post occupancy evaluation of the building. The aim of this project is to: (1) define a computational modeling framework for building and occupant cooperative sustainable performance; (2) collect correlated occupant and building performance data sets in real time (3) develop a computational spatial-temporal-physiological occupant model and a preliminary prototype Space-Mate. Real-time occupant state and building performance data feeds will generate dynamic occupancy information for building energy performance simulation and building space adjustment to respond to the evolving occupant’s energy needs and provide feedback to the occupant for potential sustainable behavior changes. This report presents the outcomes of the first phase of the Space-Mate project that focused on: performing an extensive literature review, collecting and summarizing state-of-practice building data from CIFE industry partners, developing a building-occupant data collection protocol, deploying an IRB human subjects protocol, recruiting volunteer participants, and collecting signed consent forms from volunteers, identifying and instrumenting two spaces in the Y2E2 building at Stanford for building data collection, launching concurrent building and occupant data collection, developing preliminary data analytics and indicators using building space and occupant data towards a correlated building-occupant data set and co-simulation.

Keywordsbig data, Building performance simulation, co-simulation, data analytics, IoT, occupant behavior, spatial-temporal-physiological data, sustainable performance, visualization, wearable sensor technology
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Last modified Wed, 3 May, 2017 at 10:35