Enhanced Trajectory Estimation Method for RTLS in Port Logistics Environment

Abstract

As logistics has grown dramatically, container port terminals become heavily congested in the loading, unloading, and processing of containers into and out of port terminals currently. So, there is a growing need for a design of a location-based smart port terminal. In port terminals, especially, valuable time can be saved by recognizing precisely where the nearest available containers or mobile equipment can be found. A real time locating system (RTLS) is a novel technology which estimates and tracks mobile objects and personal. However, RTLSs in port terminals are likely to include a large of uncertainty, and could not find the location of assets because they can be easily damaged by malicious materials such as steel and water. This paper proposes an enhanced trajectory estimation method for the RTLS in port logistics environment. Basically, the RTLS for the port terminal estimates the location of mobile equipment which includes a large of packet loss and uncertainties. The proposed method corrects inaccurate location information and mitigates uncertainties occurred by the RTLS by adopting interpolation and the Kalman filter. In addition, this paper includes an instance of the RTLS for the port terminal and presents experimental results to prove the superiority of the proposed method.