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BIM-IoT-integrated Architectures as the Backbone of Cognitive Buildings: Current State and Future Directions
Published in Ibrahim Yitmen, BIM-enabled Cognitive Computing for Smart Built Environment, 2021
Ali Motamedi, Mehrzad Shahinmoghadam
In a broader sense, cognitive computing can be performed based on two main approaches, namely, data-driven and knowledge-based driven computing systems. Data-driven approaches, which work on a data-mining basis, enable the extraction of new knowledge from large building datasets. Different methods of this approach have been previously investigated in the context of building lifecycle management. Examples of such studies include the application of Artificial Neural Networks (ANN) for energy consumption (Yuce et al., 2014), indoor localization (Soltani et al., 2015), and occupant temperature-preference learning (Peng et al., 2019), Convolutional Neural Networks for textual building quality compliance data classification (Zhong et al., 2019), Support Vector Machines (SVM) for energy efficiency (Shabunko et al., 2014), association rule mining for building component fault diagnosis (Liu et al., 2020), and a combination of ANN and SVM for building component predictive maintenance (Cheng et al., 2020).
The new model for UNESCO’s WHNF
Published in Ahmad Baik, Heritage Building Information Modelling for Implementing UNESCO Procedures, 2020
With the purpose of providing a lifecycle approach in regards to a heritage building within the BIM environment, a Heritage Building Lifecycle Management (HBLM) system is put into place. The HBLM puts into practice the level 3 BIM method, which provides a highly efficient extended collaboration model referring to the Heritage Building Lifecycle Management (HBLM) plan and the heritage manufacturing industry’s best practice (Moriwaki, 2014).
Enhancing the quality of bid evaluation in government refurbishment projects
Published in Intelligent Buildings International, 2022
G. C. D. Alwis, B. A. K. S. Perera, S. D. Gallage, I. H. P. R. Indikatiya
When the operational stage of a building nears its end, the owner has to decide whether to demolish the building or refurbish it (Ali et al. 2009). However according to Oloke (2017), a decision to refurbish will depend on the condition of the building and the level of refurbishment required. The earliest definition of refurbishment is ‘extensive maintenance of buildings to take the current acceptable conditions’ (BSI 1974). RICS (2009) defined refurbishment as the extensive repair, renewal, and modification of a building. According to Ryu (2014), the refurbishment of a building is a combination of conversion, retrofitting, renovation, redevelopment, and conservation of the building. Sezer (2015) claims that refurbishment is an ‘alteration that avoids uncertainties of the existing buildings in a sustainable way’. Although refurbishment of a building was earlier a traditional process that enhanced the status of the building, it has now become a complex process incorporating new concepts, such as sustainability and building life cycle management (Gunawardhana and Karunasena 2014).