Lean construction methods have demonstrated potential to improve construction productivity. For example, the location-based management system and the last planner system have increased the reliability of planning and control in construction production. However, these benefits are often reduced because of inaccurate manual data collection. To alleviate these problems, technologies for automated monitoring of workers have been developed to identify site events in chaotic environments. This paper aims to investigate whether a Bluetooth low-energy-based real-time indoor positioning system can monitor task progress from workers’ presence. Our findings suggest that the proposed system is a feasible solution for monitoring task-level progress when there are explicit dependencies between tasks. This method could automatically detect task start and finish times and estimate the hours required to complete a task. This enables the measurement of waste hidden inside tasks, which allows for interventions for improving flows and eliminating waste.

Improved productivity and the elimination of waste are key goals for lean methods in construction production control. One such lean method is a kit-based logistics management in which task-based materials are delivered just-in-time and aligned with assembly operations on-site. Digital platforms could enable a situational awareness of work and material flows, potentially increasing the benefit and applicability of kitting. The aim of the current research is to utilize a real-time indoor tracking of material and labor flows to evaluate an assembly kit–based management of construction projects. We propose a linked data framework to connect labor, material, and scheduling information to integrate heterogenous data. The contribution of the study is threefold: first, a feasible method is developed to enable real-time detection of work and material flows inside the building for logistics management purposes. Second, several key performance indicators for effective evaluation of kit-based production flow in construction are provided, which allows management to tackle root causes of problems and to enhance timely and productive logistic solutions. Thirdly, by applying the linked data method, the study introduces a novel approach to integrate heterogenous data from both indoor tracking and schedules.

The interest in production control has increased over recent years, especially among lean construction practitioners. Despite of advanced planning and control methods, the data of on-site processes are still typically collected manually. At the same time, technology has been developed to the point where it is possible to remotely locate people, equipment and products in supply chains. Therefore, how to obtain and manage data in construction based on real time tracking is critical to change production control to a more real-time and less laborious process. The availability of real-time, location-based data, opens possibilities to revolutionize production control. This paper proposes a prototype of an intelligent system for real time production control on construction site, defining the types of the tracking data, and investigating the utility of them. The prototype combines Bluetooth and WIFI network as connection methods, and locates resources and their movements in real-time, which can be used as a reference to explore proper solution on construction projects and potentially improve production efficiency, sustainability and management of workers.

The construction jobsites are highly dynamic environments involved with labor-intensive and manual tasks that suffer from inefficiency and mis-management. To remedy these issues, production control within the scope of lean construction has been a hot topic in academia and industry. To this end, we have developed a real-time coordination-based tracking system using low-cost Bluetooth Low Energy beacons. This system is implemented according to the trilateration method in order to acquire the real-time location of resources and movement trajectory in the construction jobsites. The prototype is tested and implemented in the real construction site in China. The results show that the implemented tracking system can be used in the construction sites depending on the accuracy level required in the project.