... surface. Spalling shows surface material breaking away from a brick face with rough edges. Vegetation shows plant growth emerging from mortar joints between bricks. Machine learning (ML) has transformed structural inspection by automating defect analysis in 360° imagery (Humpe, 2020). Three key...

...Hung P. Thach; Long D. Nguyen; Viet Thanh Nguyen Purpose This study aims to develop machine learning ( ML ) models to predict the sufficiency rating ( SR ) of bridges, thereby supporting decision-making in infrastructure management, including repair, maintenance and reconstruction. Design...

...Sachin Venu Jaya; Adolf Acquaye; Malik Khalfan; Vikas Swarnakar; Mutasem El Fadel Purpose This study aims to address critical sustainability challenges in modular construction by developing a predictive machine learning ( ML ) framework to estimate off-cut material waste and associated carbon...

... influence, interacts with organizational culture to promote technological innovation (Lam et al., 2021). In addition, the use of advanced analytical techniques, like machine learning and topic modeling, in this context remains limited (Li et al., 2021b). Therefore, in this study, we...

...Mohammad Nafe Assafi; Jun Wang; Junfeng Ma; Joshua Cotton Purpose Identifying hazards in construction sites is essential for ensuring safety. This study aims to propose a machine learning-based approach to identify the most effective set of eye-tracking features for assessing hazard identification...

... of research efforts on predicting the number of bidders with only a handful of studies over the past decades, which mainly focused on statistical distribution of the number of bidders. This study aims to provide a new perspective of predicting the number of bidders using machine learning (ML) algorithms...

...Wiput Tuvayanond; Viroon Kamchoom; Lapyote Prasittisopin Purpose This paper aims to clarify the efficient process of the machine learning algorithms implemented in the ready-mix concrete (RMC) onsite. It proposes innovative machine learning algorithms in terms of preciseness and computation time...

... Construction defects Machine learning Data mining Simulation Digitalization The residential building sector plays a vital role in the economic growth and development of a country. National Housing Finance and Investment Corporation (2020) report showed that the residential building construction...

... the potential for improving the accuracy of cost forecasts for buildings using machine learning techniques and large data sets. Design/methodology/approach The Australian State of Victoria Building Authority data sets, which comprise various parameters such as cost of the buildings, materials used, gross...

...Farouq Sammour; Heba Alkailani; Ghaleb J. Sweis; Rateb J. Sweis; Wasan Maaitah; Abdulla Alashkar Purpose Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms...

...Ilker Karadag; Orkan Zeynel Güzelci; Sema Alaçam Purpose This study aims to present a twofold machine learning (ML) model, namely, EDU-AI, and its implementation in educational buildings. The specific focus is on classroom layout design, which is investigated regarding implementation of ML...

... of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different...

... the path for technologies, such as electrification. The research also aims to explore the impact of automation on electromobility in earthmoving applications. Design/methodology/approach This paper adopts a multi-objective simulation-based optimization approach using machine learning in earthmoving...

... by finding the competency factors required by them. Hence, this study aims to identify the characteristics of competent project managers by expert opinion method and to evaluate their competency level by a questionnaire survey to develop a prediction model using a supervised machine learning approach via...

... developed for this particular purpose, and are therefore used to train and assess the performance of various machine-learning classifiers. Findings A promising result of up to 88% accuracy level for activity recognition was achieved by using an artificial neural network classifier. Nonetheless, special...

... Construction safety Health and safety Machine learning Image-based methods Roofing industry In the construction industry, roofers suffered from the highest rate of fall fatalities [ Center for Construction Research and Training (CPWR), 2016 ]. According to [ Center for Construction Research...