FACILITY RFID LOCALIZATION SYSTEM BASED ON ARTIFICIAL NEURAL NETWORKS
DOI:
https://doi.org/10.23055/ijietap.2011.18.1.381Keywords:
radio frequency identification, inventory location systems, artificial neural networks, interferenceAbstract
Radio frequency identification (RFID) technology is used for asset tracking due to its accuracy and speed. RFID tracking systems are being used to locate tagged objects in indoor environments, however; reliability is low due to interferences. To overcome this limitation, artificial neural networks (ANNs) can be used to determining a device’s location in the proximity of interference. This research presents a proof of concept to an industrial application of using ANNs as an RFID localization algorithm when objects are subjected to metallic and human interference. To prove this concept, random samples are collected using the received signal strength indication (RSSI) values from passive RFID readers and antennas. The test results show that ANNs can determine the location of a passive RFID tag accurately in the presence of noise and shows that data preprocessing techniques can improve the predictive capabilities of the ANN-RFID localization algorithm.
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