Investigating the Barriers to Applying the Internet-of-Things-Based Technologies to Construction Site Safety Management.

The utilization of Internet-of-Things (IoT)-based technologies in the construction industry has recently grabbed the attention of numerous researchers and practitioners. Despite the improvements made to automate this industry using IoT-based technologies, there are several barriers to the further utilization of these leading-edge technologies. A review of the literature revealed that it lacks research focusing on the obstacles to the application of these technologies in Construction Site Safety Management (CSSM). Accordingly, the aim of this research was to identify and analyze the barriers impeding the use of such technologies in the CSSM context. To this end, initially, the extant literature was reviewed extensively and nine experts were interviewed, which led to the identification of 18 barriers. Then, the fuzzy Delphi method (FDM) was used to calculate the importance weights of the identified barriers and prioritize them through the lenses of competent experts in Hong Kong. Following this, the findings were validated using semi-structured interviews. The findings showed that the barriers related to "productivity reduction due to wearable sensors", "the need for technical training", and "the need for continuous monitoring" were the most significant, while "limitations on hardware and software and lack of standardization in efforts," "the need for proper light for smooth functionality", and "safety hazards" were the least important barriers. The obtained findings not only give new insight to academics, but also provide practical guidelines for the stakeholders at the forefront by enabling them to focus on the key barriers to the implementation of IoT-based technologies in CSSM.

Multi-stage network-based two-type cost minimization for the reverse logistics management of inert construction waste.

The growing concerns for achieving sustainability has gained much attention from waste management experts with particular focus on reverse logistics, as it supports concepts like circular economy, material recovery, and improved environmental performances. This paper describes a multi-stage network-based model to minimize the overall cost for the reverse logistics management of inert construction waste across its entire life cycle. This model takes a unique two-type costing approach to overcome the ambiguities and deficiencies existing in previous models. Type-I cost refers to the facility-based costing (FBC) and Type-II cost refers to non-facility based costing (NFBC). The mixed-integer linear programming technique is applied using the LINGO software. A case study of construction waste management in Hong Kong is conducted to validate the developed model, which includes waste generation point as the starting node, public fill reception facility and recycling facility as an intermediate node, and landfill as an ending node. The result shows about 24% reduction in the total cost compared to the base case. Furthermore, to evaluate the impact of uncertainties on the cost parameters, a detailed scenario based sensitivity analysis is conducted. The optimal result shows that the larger portion of total cost come from the NFBC component. Therefore, NFBC is critical in defining the overall reverse logistics network and thus, should be given more emphasis in the design of an effective construction waste management system.