Challenges in the data collection for diagnostics of smart buildings

Abstract

The rise of smart buildings, i.e. buildings equipped with latest technology and built according to cutting-edge architectural advances, implies increased buildings’ complexity. For this reason, both new and retrofitted buildings are often susceptible to new and unforeseen faults, whose timely detection and servicing can significantly affect buildings performance. Many Fault Detection and Diagnosis (FDD) methods are data-driven, where the quality of collected data can significantly affect the accuracy of results. However, data collection for FDD of buildings is a challenging task as needed data is not typically readily available. In this paper we focus on the data collection for FDD of smart buildings. This forms the motivation of this paper, i.e. to identify the challenges that relate to data collection processes for FDD of buildings, as well as propose workarounds of how to tackle the more important ones. Furthermore, we also look into how new technologies can be useful for this goal.