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Planning for sustainable cities by estimating building occupancy with mobile phones

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journal contribution
posted on 28.08.2019 by Edward Barbour, Carlos Cerezo Davila, Siddharth Gupta, Christoph Reinhart, Jasleen Kaur, Marta C González
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.

Funding

Centre for Complex Engineering Systems at MIT-KACST

MIT Energy Initiative

Philips Lighting

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Nature Communications

Volume

10

Publisher

Springer Nature

Version

VoR (Version of Record)

Rights holder

© The Authors

Acceptance date

24/07/2019

Publication date

2019-08-19

Copyright date

2019

eISSN

2041-1723

Language

en

Depositor

Dr Edward Barbour

Article number

3736

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