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In recent years, information and sensing technologies have been applied to the construction industry to collect and provide rich information to facilitate decision making processes. One of the applications is using location data to support autonomous crane safety monitoring (e.g., collision avoidance and dangerous areas control). Several location-aware wireless technologies such as GPS (Global Positioning System), RFID (Radio-frequency identification), and Ultra-Wide Band sensors, have been proposed to provide location information for autonomous safety monitoring. However, previous studies indicated that imperfections (errors, uncertainty, and inconsistency) exist in the data collected from those sensors and the data imperfections have great impacts on autonomous safety monitoring system performance. This paper explores five computationally light-weight approaches to deal with the data imperfections …