@article{34710,
  keywords = {Mobility, Sensors, Big data, Occupant behavior, Machine learning, Energy modeling, Urban data, Energy in buildings, Energy in cities},
  author = {Flora D Salim and Bing Dong and Mohamed Ouf and Qi Wang and Ilaria Pigliautile and Xuyuan Kang and Tianzhen Hong and Wenbo Wu and Yapan Liu and Shakila Khan Rumi and Mohammad Saiedur Rahaman and Jingjing An and Hengfang Deng and Wei Shao and Jakub Dziedzic and Fisayo Caleb Sangogboye and Mikkel Baun Kjærgaard and Meng Kong and Claudia Fabiani and Anna Laura Pisello and Da Yan},
  title = {Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey},
  abstract = {<p>The proliferation of urban sensing, IoT, and big data in cities provides unprecedented opportunities for a deeper understanding of occupant behaviour and energy usage patterns at the urban scale. This enables data-driven building and energy models to capture the urban dynamics, specifically the intrinsic occupant and energy use behavioural profiles that are not usually considered in traditional models. Although there are related reviews, none investigated urban data for use in modelling occupant behaviour and energy use at multiple scales, from buildings to neighbourhood to city. This survey paper aims to fill this gap by providing a critical summary and analysis of the works reported in the literature. We present the different sources of occupant-centric urban data that are useful for data-driven modelling and categorise the range of applications and recent data-driven modelling techniques for urban behaviour and energy modelling, along with the traditional stochastic and simulation-based approaches. Finally, we present a set of recommendations for future directions in data-driven modelling of occupant behaviour and energy in buildings at the urban scale.</p>},
  year = {2020},
  journal = {Building and Environment},
  volume = {183},
  pages = {106964},
  month = {10/2020},
  issn = {03601323},
  doi = {10.1016/j.buildenv.2020.106964},
  language = {eng},
}