Current practices and infrastructure for open data based research on occupant-centric design and operation of buildings

Many new tools for improving the design and operation of buildings try to realize the potential of big data. In particular, data is an important element for occupant-centric design and operation as occupants’ presence and actions are affected by a high degree of uncertainty and, hence, are hard to model in general. For such research, data handling is an important challenge, and following an open science paradigm based on open data can increase efficiency and transparency of scientific work. This article reviews current practices and infrastructure for open data-driven research on occupant-centric design and operation of buildings. In particular, it covers related work on open data in general and for the built environment in particular, presents survey results for existing scientific practices, reviews technical solutions for handling data and metadata, discusses ethics and privacy protection and analyses principles for the sharing of open data. In summary, this study establishes the status quo and presents an outlook on future work for methods and infrastructures to support the open data community within the built environment

Modeling occupant behavior in buildings

In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents is systematically constructed, and, using bibliometric analysis techniques, the scientific production and landscape are described. The initial literature screening identified more than 750 studies, out of which 278 publications were selected. They provide an overarching view of the development of OPA modeling methods. The research field has evolved from longitudinal collaborative efforts since the late 1970s and, so far, covers diverse building typologies mostly concentrated in a few climate zones. The modeling approaches in the selected literature are grouped into three categories (rule-based models, stochastic OPA modeling, and data-driven methods) for modeling occupancy-related target functions and a set of occupants’ actions (window, solar shading, electric lighting, thermostat adjustment, clothing adjustment and appliance use). The explanatory modeling is conventionally based on the model-based paradigm where occupant behavior is assumed to be stochastic, while the data-driven paradigm has found wide applications for the predictive modeling of OPA, applicable to control systems. The lack of established standard evaluation protocols was identified as a scientifically important yet rarely addressed research question. In addition, machine learning and deep learning are emerging in recent years as promising methods to address OPA modeling in real-world applications