Table 2

Diverse applications of DL, based on the latest research in AEC industry

nReferencesYearApplications
1Alawadhi and Yan (2021) 2021Presented a concept for a hybrid system that uses BIM and hyperrealistic rendering for DL to synthesize data sets for training a neural network for object recognition in photographs, with the goal of building object recognition in photographs
2Chang et al. (2019) 2019By applying DL and BIM to indoor positioning, we were able to develop a sound-based method
3Chen and Demachi (2021) 2021The combination of DL-based object detection and individual detection using geometric relationships analysis resulted in a novel solution for identifying improper use of personal protective equipment
4Hou et al. (2021a) 2021Identified relevant gaps, challenges and future work on DL-based applications for safety management in the AEC industry
5Kim and Lee (2020) 2020With reference images and a deep-learning model, this paper describes a stochastic approach for identifying and appending interior design style information to a design document
6Marzouk and Zaher (2020) 2020DL was used to present a methodology for exploitation of artificial intelligence in facility management using DL
7Ma et al. (2020) 2020With DL, a methodology for generating synthetic point clouds from 3D BIM models was demonstrated and discussed
8Perez-Perez et al. (2021) 2021Presented an end-to-end DL method, Scan2BIM-NET, for semantically segmenting the structural, architectural and mechanical components present in point cloud data, as well as experimental results demonstrating the method's effectiveness
9Wu et al. (2020) 2020DL and NLP techniques were used to develop a method for screening patents related to information and communications technology (ICT) in construction
10Xue and Zhang (2021) 2021It was proposed that a part-of-speech (POS) tagger tailored to building codes be developed, which would be empowered by DL and transformative rules
11Zhong et al. (2020a) 2020In order to improve the efficiency and effectiveness of retrieving queries pertaining to building regulations, a robust end-to-end methodology was developed that integrates information retrieval with a DL model of natural language processing (NLP) (NLP)

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