Blockchain, a peer-to-peer, controlled, distributed database structure, has the potential to profoundly affect current business transactions in the construction industry through smart contracts, cryptocurrencies, and reliable asset tracking. The construction industry is often criticized for being slow in embracing emerging techno-logies and not effectively diffusing them through its supply chains. Often, the extensive fragmentation, traditional procurement structures, destructive competition, lack of collaboration and transparency, low-profit margins, and human resources are shown as the main culprits for this. As blockchain technology makes its presence felt strongly in many other industries like finance and banking, this study investigates the preparation of construction supply chains for blockchain technology through an explorative analysis. Empirical data for the study were collected through semi-structured interviews with 17 subject experts. Alongside presenting a strengths, weaknesses, opportunities, and threats analysis (SWOT), the study exhibits the requirements for and steps toward a construction supply structure facilitated by blockchain technology.

In the wide context of facility management, several processes, such as operations, maintenance, retrofitting, and renovations, ensure that buildings comply with the principles of efficiency, cost-effectiveness, and indoor comfort. Apart from ordinary operation, facility management is responsible for the renovation of and long-term performance improvement of building facilities. In such a scenario, the cyber–physical system (CPS) paradigm with holonic architecture, which is the focus of this study, can successfully guide the operation management and long-term refurbishment processes of buildings. Analogous to the manufacturing field, the developed CPS maximizes holons’ self-configuration and self-organization and overall throughput effectiveness metrics to detect the best corrective actions toward system improvements. Consequently, suggestions and lessons learned from the evaluation of building efficiency are redirected to the building information model. Hence, the digital model acts as a repository of currently available equipment for operations management and the history of diagnoses that support decision-making during the maintenance, retrofitting, and renovation processes. Evidently, the repeated detection of a specific issue, which is unaffected by operations management, should be considered an opportunity to act and enhance the performances of existing building components. Similar to a goods-producing industry, the building management system developed in this study applies the aforementioned methodology to provide services related to indoor comfort and building health. This approach indicates that a method for automatic real-time diagnosis is tested in a case study consisting of a multi-use and large public building. The current paper, which is an extended version of the one presented in the Creative Construction Conference 2018, deepens the decision support tool and the supervision policy. Moreover, the developed system is contextualized by providing an example of use case and highlighting the step forward in the field of smart buildings.

Construction is considered among the most dangerous industries and is responsible for a large portion of total worker fatalities. A construction worker has a probability of 1-in-200 of dying on the job during a 45-year career, mainly due to fires, falls, and being struck by or caught between objects. Hence, employers must ensure their workers wear personal protective equipment (PPE), in particular hardhats, if they are at risk of falling, being struck by falling objects, hitting their heads on static objects, or coming in proximity to electrical hazards. However, monitoring the presence and proper use of hardhats becomes inefficient when safety officers must survey large areas and a considerable number of workers. Using images captured from indoor jobsites, this paper evaluates existing computer vision techniques, namely object detection and color-based segmentation tools, used to rapidly detect if workers are wearing hardhats. Experiments are conducted and the results highlight the potential of cascade classifiers, in particular, to accurately, precisely, and rapidly detect hardhats under different scenarios and for repetitive runs, and the potential of color-based segmentation to eliminate false detections.

The construction sites of mega construction projects (MCP) often have numerous participants with interfacing work within a highly complex system. It is critical how to realize collaborative work and information sharing among such participants. The information and communication technologies (ICTs) provides a technical guarantee for solving this problem. Existing research has been achieved the partial processes digitization of construction site, but certain problems still exist: 1)information perception of the construction site is passive. 2) common collaboration and coordination problems in the construction industry have not been addressed. The emerging trends of ICTs have resulted in the integration of various computer technologies such as CPS, BIM, big data, and cloud computing into construction process, which would changes behavioral and management mode of construction sites. These new ICTs have been applied successfully in MCP, in particular, Hong Kong-Zhuhai-Macao Bridge project. A new management mode of construction sites is inspired by these case. In this paper, a new management mode of construction site for MCP has been proposed, namely, smart construction site. The ultimate goal of smart construction site is to accomplish safe, efficient and high-quality construction. This study put forward the conceptual framework for smart construction site, and have identified three key elements of smart construction site, including information support platform, collaboration work, and intelligent construction management. A case study on Hong Kong-Zhuhai-Macao Bridge project work as an evidence to support the practicability of the proposed mode. Significant contributions of this study is to propose a new management mode for MCP in construction industry, which would enrich the body of knowledge or the construction management community. Future research should be dedicated to further explore the potential of smart construction site in MCP management.

Over the last two decades, construction contractors have been gradually making more investments in construction equipment to meet their needs associated with increasing volumes of construction projects. At present, from an operational perspective, almost all contractors pay more attention to maintaining their equipment fleets in well-sustained workable conditions and having a high accessibility of the necessary equipment pieces. However, such an approach alone is not enough to maintain an efficient and sustainable business. In particular, for large-scale construction companies that operate in multiple sites in the U.S. or overseas, the problem extends to an optimal allocation of available equipment. Given the current state of the construction industry in the U.S., this problem can be solved by geographically locating equipment pieces and then wisely re-allocating them among projects. Identifying equipment pieces geographically is a relatively easy task. The difficulty arises when informed decision-making is required for equipment allocation among job sites. The actual allocation of equipment should be both economically feasible and technologically preferable. To help in informed decision-making, an optimization model is developed as a mixed integer program. This model is formed based on a previously successfully developed decision-support model for construction equipment selection. The proposed model incorporates logical strategies of supply chain management to optimally select construction equipment for any construction site while taking into account the costs, availability, and transportation-related issues as constraints. The model benefits those responsible for informed decision-making for construction equipment selection and allocation. It also benefits the owners of construction companies, owing to its cost-minimization objective.

Current construction engineering management suffers numerous challenges in terms of the trust, information sharing, and process automation. Blockchain which is a decentralised transaction and data management technology, has attracted increasing interests from both academic and industrial aspects since 2008. However, most of the existing research and practices are focused on the blockchain itself (i.e. technical challenges and limitations) or its applications in the finance service sector (i.e. Bitcoin). This paper aims to investigate the potential of applying blockchain technology in the construction sector. Three types of blockchain-enabled applications are proposed to improve the current processes of contract management, supply chain management, and equipment leasing, respectively. Challenges of blockchain implementation are also discussed in this paper.