
handle: 11589/228341
In this paper an insight on innovative implementation strategies and operative Information and Communication Technologies (ICT) regarding Intelligent Buildings (IBs) is provided. Data-driven knowledge extraction and re-usage can be a valid source of information to study the whole building life-cycle as a process to optimize. Today, new challenges can be provided thanks to ICT and Internet of Things (IoT) paradigms that allow big data to be stored, processed and analysed. This approach is still not deeply applied in construction engineering fields. In order to analyse the related literature, first a framework to describe the IB technological environment is proposed. Second, the literature is reviewed according to this framework and focusing on ICT tools and implementation aspects for the whole building life-cycle. To the best of our knowledge, there isn't yet a survey focusing on innovative operative tools adopted in the development of the ICT technological layer of IB. The reviewed literature is discussed by identifying implemented technologies and related ICT tools and classifying applications in building life-cycle. Finally, critical aspects are singled out and opportunities for future developments in the field of IBs are outlined.
Big data; Building information modelling; Building life-cycle; Intelligent building; Internet of things; Natural language processing; Semantic technologies
Big data; Building information modelling; Building life-cycle; Intelligent building; Internet of things; Natural language processing; Semantic technologies
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
