The last decade has witnessed unprecedented changes in the technologies and processes involved in the construction industry. The philosophies associated with Industry 4.0 now reverberate in construction 4.0. Digitalization and interconnectivity in the cyber-physical systems of the sector are at the heart of such transformation. Construction 4.0 brings to the table a plethora of technologies and associated processes over the construction project lifecycle. The current study performs a state-of-art literature review to summarize the knowledge advancement in construction 4.0. A layered conceptualization spanning across project lifecycle utilizing the people-process-technology dimensions is presented to summarize the current understanding of Construction 4.0. The cyber-physical space is classified into the physical, digital tool, data, and core data security and interoperability layers. The inter-layer and intra-layer interactions and information flows are then conceptualized based on the extant literature, including the human interaction and interventions. The people-process-technology dimensions were discussed across the project lifecycle through interactions in these layers. It is observed that Construction 4.0 is set to be driven by data creation, data flow, data transformation, and data storage across the project lifecycle to ensure a collaborative environment across the stakeholders who interact and associate with different layers of Construction 4.0. The article finally presents challenges with the current formulations and explores ways to further our knowledge in the area.
Construction safety is a matter of great concern for practitioners and researchers worldwide. Even after risk assessments have been conducted and adequate controls have been implemented, workers are still subject to safety hazards in construction work environments. The need for personal protective equipment (PPE) is important in this context. Automatic and real-time detection of the non-compliance of workers in using PPE is an important concern. Developments in the field of computer vision and data analytics, especially using deep learning algorithms have the potential to address this challenge in construction. This study developed a framework to sense in real-time, the safety compliance of construction workers with respect to PPE, which is intended to be integrated into the safety workflow of an organization. The study makes use of the Convolutional Neural Networks model, which was developed by applying transfer learning to a base version of the YOLOv3 deep learning network. Taking into account the presence of hardhat and safety jackets, the model predicts compliance in four categories such as NOT SAFE, SAFE, NoHardHat, and NoJacket. A data set of 2,509 images was collected from video recordings from several construction sites and this web-based collection was used to train the model. The model reported an F1 score of 0.96 with an average precision and recall rate at 96% on the test data set. Once a non "SAFE" category is detected by the model, an alarm and a timestamped report are also incorporated to enable a real-time integration and adoption on the construction sites. Overall, the study provides evidence on the feasibility and utility of computer vision-based techniques in automating the safety-related compliance processes at construction sites.
PurposeStrong and independent judiciary symbolizes transparency and impartiality in the dispute resolution process. However, litigation is often time-consuming and affects the working relationship between the disputants. In the construction context, where projects typically have a short life span of three to four years, dispute resolution through litigation induces unaffordable process delays. Despite the inherent challenges associated with litigation, it is observed that disputing parties resort to litigation. This behavior, called the litigation dilemma, ostensibly appears counterintuitive to rational decision-making.Design/methodology/approachThe study identifies 35 “decision to litigate” (DTL)-triggers from a review of the literature and court cases followed by expert interviews and groups them into thematic research domains using Exploratory Factor Analysis (EFA) followed by Confirmatory Factor Analysis (CFA).FindingsDTL studies in construction stands benefited through interdisciplinary research. “Presumptuous decision-making,” “construction project characteristics,” “milieu influence,” “interest in amicable resolution,” “positional focus” and “opportunism” are the six focus areas to decode the DTL in construction.Research limitations/implicationsThe study identifies factors that consolidate the knowledge from various fields with the substantive experience of construction professionals from across the world to help understand the dynamics behind the DTL in the context of contract-linked disputes in construction.Originality/valueThe findings from the domains of law, behavior, sociology and economics can help understand the above dilemma in the context of contractual disputes in construction. However, studies that explore the “decision to litigate” (DTL) contractual disputes in construction are limited, providing a vast scope for further research. The current study addresses a part of this gap.
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