Digital building management through Digital Twins and Data Science technologies

The management of buildings has been currently gaining momentum in the construction industry. Public and private organisations which deal with managing facilities are interested in and needy to use any means to run their business as best as possible. Indeed, the life cycle of buildings is distributed in an asymmetric way, where the longest part regards the operational phase, leading to a huge importance to this stage. Traditionally, buildings used to be managed by using paper-based documents, personal experience, and manual analysis approaches. This implied loss of data and separated data silos, insights potentially biased in favour of knowledge, and time-consuming tasks. With the advent of the fourth industrial revolution, technology has boosted the opportunities to exploit disruptive tools to effectively manage buildings in a digital way and data has been put in the centre of attention. Although the digital building management can be extremely useful to manage the usage of data, organisations need appropriate methods, tools and skills to handle it. Nevertheless, most of organisations are not ready or capable to embrace innovations and still use old and traditional practices, even if error-prone and less efficient. As a result, the digital building management is not conducted at a reasonable and effective level. In addition to it, not only the abundance of data might be problematic, but also its format, as data is often stored using unstructured formats, leading to the impossibility to effectively exploit it. This leads to the following research questions: What are the methods and technologies that can be exploited in order to improve the building management? How should they be implemented and applied to reach such result? To what extent is data exploitable for the building management enhancement? The manuscript aims to improve the management of buildings. The first research objective concerns implementing the BIM method, defining crucial FM system features and describing how to generate digital models to lay the foundation for an effective digital management of buildings. The second one focuses on proposing solutions for space and maintenance management exploiting innovative technologies and techniques, namely Digital Twins and text-mining algorithms, in order to improve the management of buildings. The outcome of this research is a series of guidelines, which both public and private organisations can use, for enhancing building management.