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This paper proposes a novel interconnected financial management system based on Hyperledger fabric and chaincode solutions to address endemic problems with financial management practices adopted within construction projects. Increasingly complex construction projects have necessitated a corresponding evolvement of financial management tools and systems to augment security and control. A decentralised financial management system is introduced to deal with all financial tasks across various construction stages using blockchain technology. Under different delivery approaches and payment methods, the proposed system enables parties to record/invoke their transactions safely and automatically, with no third party involvement. Moreover, the proposed approach allows non-owner parties to control remaining financial rights during the Defects Liability Period (DLP) automatically through a pre-agreed endorsement policy. The proposed system is tested on a real-life case project, where results corroborate its ability and workability in providing a secure and scalable platform for all project parties. • This paper provides a secure and interconnected financial system for construction projects • The proposed financial solution-based Hyperledger fabric deal with payment issues during the whole project lifecycle • The proposed 'Proof Of Concept' enables all parties to invoke their transactions through an integrated platform • The endorsement policy in this system prevents the misuse of the DLP by the client to withhold contractors' duties [ABSTRACT FROM AUTHOR]

While unavoidable, inspections, progress monitoring, and comparing as-planned with as-built conditions in construction projects do not readily add tangible intrinsic value to the end-users. In large-scale construction projects, the process of monitoring the implementation of every single part of buildings and reflecting them on the BIM models can become highly labour intensive and error-prone, due to the vast amount of data produced in the form of schedules, reports and photo logs. In order to address the mentioned methodological and technical gap, this paper presents a framework and a proof of concept prototype for on-demand automated simulation of construction projects, integrating some cutting edge IT solutions, namely image processing, machine learning, BIM and Virtual Reality. This study utilised the Unity game engine to integrate data from the original BIM models and the as-built images, which were processed via various computer vision techniques. These methods include object recognition and semantic segmentation for identifying different structural elements through supervised training in order to superimpose the real world images on the as-planned model. The proposed framework leads to an automated update of the 3D virtual environment with states of the construction site. This framework empowers project managers and stockholders with an advanced decision-making tool, highlighting the inconsistencies in an effective manner. This paper contributes to body knowledge by providing a technical exemplar for the integration of ML and image processing approaches with immersive and interactive BIM interfaces, the algorithms and program codes of which can help replicability of these approaches by other scholars. • This study proposed a framework for automated real-time simulation of the construction projects. • Feasibility of integrating real-world images with BIM and virtual world models is proven. • The algorithm is developed for splicing site and BIM data through image semantic segmentation and BIM virtual photogrammetry. • Exploration of BIM-led deep learning provides a method for reinforcement learning through spatial inference. • The paper contributes to the BIM and Deep learning communications and supports emerging convergent reality literature. [ABSTRACT FROM AUTHOR]

Concrete pouring represents a major critical path activity that is often affected by design limitations, structural considerations and on-site operational constraints. As such, meticulous planning is required to ensure that both the aesthetic and structural integrity of joints between cast in-situ components is achieved. Failure to adequately plan concrete pouring could lead to structural defects, construction rework or structural instability, all having major financial implications. Given the inherent complexity of large-scale construction projects, the 'manual planning' of concrete pouring is a challenging task and prone to human errors. Against this backdrop, this study developed 4D Building Information Management (BIM) approach to facilitate automated concrete joint positioning solution (as a proof of concept) for design professionals and contractors. The study first developed structural model in Revit, then extracted spatial information regarding all construction joints and linked them to dynamic Microsoft (MS) Excel and Matlab spreadsheets using integration facilitated by Dynamo software. Midspan points of each beam as well as floor perimeter information were gathered via codes developed in MS Excel macros. Based on the Excel outputs, Matlab programming was used to determine best concreating starting points and directions, and daily allowed concrete volume, considering limitations due to cold joints. These information were then pushed back to Revit via Dynamo in order to develop daily concrete scheduling. The developed automated programme framework offers a cost-effective and accurate methodology to address the limitations and inefficiencies of traditional methods of designing construction joints and planning pours. This framework extends the body of knowledge by introducing innovative solutions to integrate structural design considerations, constructional procedures and operational aspects for mitigating human error, and providing a novel, yet technically sound, basis for further application of BIM in structural engineering. • A prototype integrating 4D BIM applications were developed to facilitates real-time concrete joint layout planning. • The system improves integration of structural design process and eases decision making prior construction phase. • The system helps reducing structural damages caused by operational shortfalls and supply-chain issues. • The paper contributes to 4D BIM literature by integrating operational data with design considerations to leverage efficiency. • Paper discussed how the system can be improved by adopting machine learning, sensors, and data science techniques. [ABSTRACT FROM AUTHOR]

Accurate quantification and detailed classification of construction waste are paramount to improving their management. Over the last decades, various quantification models have been developed to measure, manage, and report construction waste generation. A detailed understanding of those models is essential to explore their applications across the life-cycle stages of a built asset. Existing reviews primarily focused on analysing the functions of quantification methodologies, but the digital and information standards to automate the quantification process are under-explored in the existing literature. A review is adopted to analyse papers published from 2012 to 2022. Out of 279 articles retrieved, 71 papers meeting the eligibility criteria were included. A critical analysis of the models indicates that unified data structure, standard information, life-cycle approach and interoperability between the BIM and waste knowledge bases are vital to automate and reinforce the quantification efficiency. Based on the review findings, a conceptual framework is developed to demonstrate the quantification workflow for building projects. The outcomes from the review will facilitate researchers to identify the prevailing gaps and enhance the waste quantification system to meet digital construction demands. [Display omitted] • Key factors influencing WQ in the construction setting are reviewed. • Significant limitations associated with current CW quantification systems are highlighted. • Future research directions to enhance and automate CW quantification process are recommended. • A BIM-assisted CW quantification and classification framework is proposed. [ABSTRACT FROM AUTHOR]

Blockchain technology (BT) can execute transactions verifiable and permanently, which can help foster the idea of embracing sustainability pillars within industries. Therefore, BT holds considerable promise for the industrial and service sectors; however, its implementation during the procurement stage in a sustainable construction project (SCP) is a bottleneck because of inherent and unknown barriers. Though some attempts on the identification of these barriers have been carried out, the literature lacks a thorough investigation into the relationships and inner dependencies among the related barriers within the realm of SCP. Thus, a novel combination of fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) and social network analysis (FDSNA) is proposed in this paper to fill this gap; FDSNA uncovers causal relationships among leading barriers that impede the adoption of BT within an SCP, and it determines the most critical barriers by modeling their complex interrelationships in related intricate environments. The obtained results suggest "inadequacies in implementing block chain-based policies" and "unawareness and resistance to BT among customers" as the most significant barriers, and "technology immaturity," "market uncertainty and competition," and "technology accessibility" are identified as the most critical. These results present managers and governmental bodies with an inclusive picture regarding the major obstructions to the successful implementation of BT, and it is expected to open avenues to accrue benefits from such leading-edge technologies at a greater pace. [Display omitted] • Barriers to blockchain technology in sustainable construction projects are identified. • The cause-and-effect relationships among the identified barriers are unraveled. • The most critical barriers are determined by modeling their complex interrelationships. • The lack of sagacious policies and end-user's unawareness are the most significant barriers. • Technology immaturity, market uncertainty, and accessibility are the most critical barriers. [ABSTRACT FROM AUTHOR]