Identifying productive working patterns at construction sites using BLE sensor networks

Abstract

Location tracking of workers and resources at construction sites has been continually researched to improve construction management. In this paper, Bluetooth low energy (BLE) device-based networks were used to monitor the movement and location of workers; this was followed by analysis of the location data to evaluate worker performance. The network uses a BLE tag as the “tracked” device. The system was implemented at a construction site. Measurement data shows it has a location accuracy in the range of 5–10 ​m depending on the positioning of the receiver gateway. The sensor network is suitable for implementation at a construction site to quantify productivity. The data was analysed with artificial neural networks to identify working patterns in correlation with the assigned area; a method is suggested to classify the location corresponding to maximum time spent by a worker.