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1 – 3 of 3Abdelhamid Hati and Amina Abdessemed-Foufa
The protection of industrial heritage emerged as a major concern when those buildings and installations representative of the industry, became at risk. North Africa, considered…
Abstract
Purpose
The protection of industrial heritage emerged as a major concern when those buildings and installations representative of the industry, became at risk. North Africa, considered the geographical gateway to European countries, experienced enormous industrial activity during the French colonial era. Industrial buildings such as the flour mills, were built during this era of colonial rule. Today, a lack of legislation concerning industrial heritage has left this type of buildings with no protection, leading this paper to a preservation process. The aim of this paper is to locate and identify the flour mills of the 19th and 20th centuries in Algeria.
Design/methodology/approach
This research consists of cross-referencing data from archived documents against the geographical location.
Findings
The results obtained are the first step in the process of preservation. The success of this research can be summarized as follows: identification of 88.46% of the flour mills in Algeria by means of the inventory data collected, and their location, with the use of a crisp logic, the remaining 9.62% with the use of fuzzy logic by the attribution of a “fuzzy radius” with a total localization and identification of 98.08%.
Originality/value
The use of both crisp (Boolean) and fuzzy logic as part of the geographical localization method.
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Keywords
Jantanee Dumrak and Seyed Ashkan Zarghami
The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers…
Abstract
Purpose
The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers a classification scheme that specifies different categories of AI tools, as applied to the field of LCM to support various principles of LCM.
Design/methodology/approach
This research adopts the systematic literature review (SLR) process, which consists of five consecutive steps: planning, searching, screening, extraction and synthesis and reporting. As a supplement to SLR, a bibliometric analysis is performed to examine the quantity and citation impact of the reviewed papers.
Findings
In this paper, seven key areas related to the principles of LCM for which AI tools have been used are identified. The findings of this research clarify how AI can assist in bolstering the practice of LCM. Further, this article presents directions for the future evolution of AI tools in LCM based on the current emerging trends.
Practical implications
This paper advances the LCM systems by offering a lens through which construction managers can better understand key concepts in the linkage of AI to LCM.
Originality/value
This research offers a new classification scheme that allows researchers to properly recall, identify and group various applications of AI categories in the construction industry based on various principles of LCM. In addition, this study provides a source of references for researchers in the LCM discipline, which advances knowledge and facilitates theory development in the field.
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Peyman Jafary, Davood Shojaei, Abbas Rajabifard and Tuan Ngo
Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different…
Abstract
Purpose
Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.
Design/methodology/approach
This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.
Findings
Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.
Originality/value
This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.
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