Fusion of Pre/Post-RFID Correction Techniques to Reduce Anomalies

• Published in: Intelligent Sensor Networks pp. 529 - 566
• Main Authors: Darcy, Peter, Pupunwiwat, Prapassara, Stantic, Bela
• Format: Book Chapter
• Language: English
• Published: CRC Press 2013
• Edition: 1
• Subjects: Sensor Networks; Bayesian Network; Maximum Frame Size; Genetic Algorithm; BP Algorithm; Data Set; Interrogation Zone; RFID Data; RFID Reader; Cleaning Rate; NMR; RFID System; Tag Reply; Neural Network; Integrate RFID Technology; Training Algorithm; Nonmonotonic Reasoning; RFID Technology; Cognitive Wireless Sensor Networks; Slot Counter; RFID Tag; EPC Class; Successful Slot
• ISBN: 1138199745; 9781439892817; 1439892814; 9781138199743
• DOI: 10.1201/b14300-27

This chapter discusses the issues associated with anomalies present in captured Radio frequency identification (RFID) data and presented solutions to improve its integrity. RFID technology refers to the use of multiple tags being attached to various items that are scanned and recorded in a database. The process itself eliminates mundane tasks such as conducting manual inventory checking, counting or using a barcode scanner to count the items to be purchased at a supermarket checkout. RFID technology refers to the use of multiple tags being attached to various items that are scanned, recorded in a database. Modern integrations of this technology include baggage tracking at airports, pet owner identification, tagging objects in stores to enforce security by alerting management when an item has left the facility without the tag being deactivated. The middleware, also commonly known as the savant or edge systems, the layer at which the raw RFID readings are cleaned and filtered to make the data more application friendly.