Planning for sustainable cities by estimating building occupancy with mobile phones
Author(s)
Barbour, Edward; Davila, Carlos Cerezo; Gupta, Siddharth; Reinhart, Christoph; Kaur, Jasleen; Gonzalez, Marta C.; ... Show more Show less
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Accurate occupancy is crucial for planning for sustainable buildings. Using massive, passively-collected mobile phone data, we introduce a novel framework to estimate building occupancy at unprecedented scale. We show that, at urban-scale, occupancy differs widely from current estimates based on building types. For commercial buildings, we find typical occupancy rates are 5 times lower than current assumptions imply, while for residential buildings occupancy rates vary widely by neighborhood. Our mobile phone based occupancy estimates are integrated with a state-of-the-art urban building energy model to understand their impact on energy use predictions. Depending on the assumed relationship between occupancy and internal building loads, we find energy consumption which differs by +1% to −15% for residential buildings and by −4% to −21% for commercial buildings, compared to standard methods. This highlights a need for new occupancy-to-load models which can be applied at urban-scale to the diverse set of city building types. ©2019
Date issued
2019-08Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology. Sustainable Design LabJournal
Nature communications
Publisher
Springer Science and Business Media LLC
Citation
Barbour, Edward, et al., "Planning for sustainable cities by estimating building occupancy with mobile phones." Nature communications 10 (2019): no. 3736 doi 10.1038/S41467-019-11685-W ©2019 Author(s)
Version: Final published version
ISSN
2041-1723