Intelligent High-Level RFID Event Transformation Utilising Non-Monotonic Reasoning

Abstract

Radio Frequency Identification technology utilises radio communication between tags and readers to automatically recognise large amounts of items reducing cost in both time and effort. Although there is a wide array of applications which RFID may be applied to, there are several issues that hinder the adoption of the technology into various commercial sectors. One of these problems is that the data recorded by readers are becoming increasingly difficult to decipher in its raw form resulting in complex spatio-temporal aspects. To counter the effects of this issue, we have proposed a concept that employs Clausal Defeasible Logic Non-Monotonic Reasoning to correctly identify a high-level event. From our experimental evaluation, we have shown that our approach surpasses the state-of-the-art probabilistic method in both identifying events and limiting false-positive anomalies into the data set.