Abstract
Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches.
Highlights
In many applications such as manufacturing, distribution logistics, access control, and healthcare, the ability to uniquely identify, real-time product track, locate and monitor individual objects is indispensable for efficient business processes and inventory visibility
A typical radio-frequency identification (RFID) system consists of a transponder, which is attached to the object to be identified, an interrogator that creates an RF field for detecting radio waves, the middleware and a backend database system for maintaining expanded information on the objects and other associated information
We model an RFID system with multiple readers and tags
Summary
In many applications such as manufacturing, distribution logistics, access control, and healthcare, the ability to uniquely identify, real-time product track, locate and monitor individual objects is indispensable for efficient business processes and inventory visibility. The use of radio-frequency identification (RFID) technology has simplified the process of identifying, tracking, locating and monitoring objects in many applications. A typical RFID system consists of a transponder (i.e., tag), which is attached to the object to be identified, an interrogator (i.e., reader) that creates an RF field for detecting radio waves, the middleware and a backend database system for maintaining expanded information on the objects and other associated information. The middleware collects and processes the readings from readers for the use of enterprise applications and enterprise database. The process such as filtering and aggregation transform raw data into meaningful information for the application. Relative to both active and semi-active tags, passive tags are very cheap and they are widely used in very large quantities in many applications such as supply chain management
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