The application of Artificial Neural Networks (ANNs) to discriminate tag actions in UHF-RFID gate is presented in this paper. By exploiting Received Signal Strength Indicator values acquired in a real experimental scenario, a multi-layer perceptron neural network is trained to distinguish among tags incoming, outgoing or passing the RFID gate. A 99% accuracy can be obtained in tag classification by employing only one reader antenna and independently from tag orientation and typology.
UHF-RFID smart gate: Tag action classifier by artificial neural networks
Buffi, A.;D'Andrea, Eleonora;Lazzerini, B.;Nepa, P.
2017-01-01
Abstract
The application of Artificial Neural Networks (ANNs) to discriminate tag actions in UHF-RFID gate is presented in this paper. By exploiting Received Signal Strength Indicator values acquired in a real experimental scenario, a multi-layer perceptron neural network is trained to distinguish among tags incoming, outgoing or passing the RFID gate. A 99% accuracy can be obtained in tag classification by employing only one reader antenna and independently from tag orientation and typology.File in questo prodotto:
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