A Graphic-based Data Mining Approach in RFID Sensor Networks

Abstract

As the wide use of radio frequency identification (RFID) technology, such wireless sensor network has created enormous data in supply chain management, manufacturing sites, retailor sections, as well as health care domain. In order to discovery the invaluable information and knowledge from such massive RFID data, this paper introduces a data mining approach based on graphic theory to pick out the useful information and knowledge from logistics RFID data. This approach considers the complex relationship of different RFID data and uses graphic model to build up the logistics path. That means the logistics information stored in RFID data is converted by graphic diagram, which could be mined by the proposed approach over OLAP. The inquiry efficiency has been greatly improved through experimental results. © 2014 SERSC.