RFID smart data analysis for reading discrimination and direction detection

The objective of the paper is twofold: on the one hand, to propose an algorithm capable of discriminating unwanted and cross RFID readings coming from different readers in a dense-reader environment. On the other one, a methodology is proposed in order to detect the direction of the movement of the tagged goods. The typical environment in which these algorithms can be profitably implemented is a RFID-enabled warehouse; in fact, in such scenario many readers are usually installed in closed proximity, each one monitoring a specific dock door. Many tagged items are simultaneously loaded and unloaded from trucks, thus a reliable algorithm capable of reducing interferences and detecting directions without the need for hard metal shields can make the RFID system more reliable and the deploy easier. Design, methodology, approach: The proposed methodology has been developed and tested on raw RFID data coming from a couple of RFID readers installed in a lab in order to simulate a couple of dock doors; each reader is equipped with an array of 52 antennas facing different directions under different angles. A dummy pallet composed of cardboard boxes, apparel products and RFID tags has been passed under one reader in different directions, and resulting data from both readers has been processed. Different pallet configurations and speeds, reader settings and reading parameters have been tested, and different algorithms have been developed to analyse raw data. Findings: by simulating a real-world environment, test results give a direct insight of performances to be expected from the proposed algorithms under real use cases. The reliability of the proposed methodologies, defined as the correct detection of the direction of each tag and the elimination of cross readings, is very high, being more than 90%.