Technologies for the acquisition, storage and mining of big data are increasingly affecting the Architecture, Engineering and Construction (AEC) industry, modifying the way buildings are conceived and developed. Indeed, they will be no longer designed and managed only as financial products, but also as service providers to support the needs of the occupants. This is a great challenge in the building sector, that is experiencing a period of various (r)evolution concerning products, technologies and processes. This research defines a digitally enabled framework for operating cognitive buildings, presenting a case study by which it has been possible to analyze how information collected during operations could inform end-users (i.e. administrators, owners, facility managers and occupants) about the behavior of both buildings and occupants. Focusing on building in-use stages, advantages in tracking the behavior of occupants and in satisfying the needs of users should be derived through the availability of real-time information, i.e. collected by sensors. In this way, not only the behavior of users could be taken into account, but also predicted performance could be correlated with real measurement and, consequently, the building performance gap should be estimated and filled. A connection between as-designed virtual models (resulted from a BIM – Building Information Modeling – process) and as-delivered physical assets (monitored in real-time, i.e. through BMS – Building Management Systems) could be established to explore how BIM practices and technologies could improve a data-driven asset management, by enriching building information in operation. The results should allow pointing out how data and information gathered along building life cycle could provide services to users.

Exploiting Internet of Things and Building Information Modeling Framework for Management of Cognitive Buildings

PASINI, DANIELA;MASTROLEMBO VENTURA, SILVIA;CIRIBINI, ANGELO LUIGI CAMIL
2016

Abstract

Technologies for the acquisition, storage and mining of big data are increasingly affecting the Architecture, Engineering and Construction (AEC) industry, modifying the way buildings are conceived and developed. Indeed, they will be no longer designed and managed only as financial products, but also as service providers to support the needs of the occupants. This is a great challenge in the building sector, that is experiencing a period of various (r)evolution concerning products, technologies and processes. This research defines a digitally enabled framework for operating cognitive buildings, presenting a case study by which it has been possible to analyze how information collected during operations could inform end-users (i.e. administrators, owners, facility managers and occupants) about the behavior of both buildings and occupants. Focusing on building in-use stages, advantages in tracking the behavior of occupants and in satisfying the needs of users should be derived through the availability of real-time information, i.e. collected by sensors. In this way, not only the behavior of users could be taken into account, but also predicted performance could be correlated with real measurement and, consequently, the building performance gap should be estimated and filled. A connection between as-designed virtual models (resulted from a BIM – Building Information Modeling – process) and as-delivered physical assets (monitored in real-time, i.e. through BMS – Building Management Systems) could be established to explore how BIM practices and technologies could improve a data-driven asset management, by enriching building information in operation. The results should allow pointing out how data and information gathered along building life cycle could provide services to users.
2016 IEEE International Smart Cities Conference (ISC2) Proceedings - Improving the citizens quality of life
978-1-5090-1845-1
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1014765
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