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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 12

Position Papers of the 2017 Federated Conference on Computer Science and Information Systems

Utilising Latent Data in Smart Buildings: A Process Model to Collect, Analyse and Make Building Data Accessible for Smart Industries


DOI: http://dx.doi.org/10.15439/2017F545

Citation: Position Papers of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 12, pages 195201 ()

Full text

Abstract. Smart buildings are embedded with large amounts of latent data from different sources, e.g. IoT devices, sensors, and the like. Integration of this latent data with the buildings information can highly impact efficiency of the services provided by various industries, e.g. facility management companies, utility companies, smart commerce, and so forth. To manage buildings information, diverse technologies such as Building Information Modelling (BIM) technology have been developed and changed the traditional approaches. Notwithstanding a plethora of research in this area, potential users of this information, such as facility management companies, are still unable to fully benefit from the building information. This is due to the fact that various information and data have been heterogeneously scattered across various sources. To overcome this challenge, this research follows the design science approach to propose a process model to enable facility management industry to access the integration of buildings information with live data. The presented process model is introduced thoroughly by explaining the required steps to collect and integrate and preserve the integrated information and data. The evaluation of the process model was undertaken via the employment of a focus group session with the construction professionals, the IoT experts, and the data analysts. Also, this paper elaborates on two industrial use-cases to demonstrate how having access to the building information effectively affects the other industries. The outcome of this research provides an open access to the integration of building information and live data for diverse range of users.


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