Development of a UAV-RFID Platform for Construction Resource Localization

Abstract

Even though location data of construction resources, such as materials,

heavy machinery, and workers, is one of the most critical keys to understand the context of the construction site, most sites still rely on human-oriented observations to localize the resources. As one of the techniques for collecting location data, Radio Frequency Identification(RFID) technology has been extensively studied

and widely used. However, RFID requires multiple readers or a lot of

manpower for location data acquisition because the RFID receiver is fixed or carried by a human with a GPS device. It is inefficient and infeasible in terms of time and cost in complex or large-scale construction sites. To address the issue, the aim of this study is to overcome the limitations of current approaches by proposing a localization method based on UAV-RFID integrated p latform. With the Received Signal Strength Index (RSSI) of RFID and UAV flight log acquired by flying the integrated platform, we applied machine learning and deep learning techniques to localize the location of RFID tags. The method estimates the location of tags with high accuracy and acceptable error range. With this proposed method, we have demonstrated the feasibility of the UAV RFID integrated platform the or construction site.