RF-Symmetry: Contactless Liquid Identification Using Two Symmetrically-Located COTS RFID Tag Arrays

Nowadays, liquid identification plays an important role in our daily lives, especially for security checks at railway stations or airports. Traditional identification technologies are either intrusive or expensive, so they are inconvenient to use. In this article, we use commercial off-the-shelf (COTS) RFID devices to design and implement a nonintrusive, contactless liquid identification system, and radio frequency (RF)-symmetry. Based on the symmetrical characteristics of refraction when RF signals travel through the cylindrical container, we use two symmetrically-located RFID tag arrays to receive RF signals which are transmitted by an RFID antenna. In order to effectively select the symmetrical tag pairs, we design a tag selection algorithm to select tags from two tag arrays. We design a specialized signal processing method to extract liquid features, and then use an extreme learning machine optimized by genetic algorithm (GA-ELM) to classify liquids. We build a prototype system of RF-symmetry, and through extensive experiments, we can find that RF-symmetry can achieve a high recognition accuracy (97.22%) on 12 different liquids. Moreover, the experiments also show that our system can effectively distinguish similar liquids such as coke and diet coke.