Abstract
RFID technology is now widely used to identify, locate, track and monitor physical objects. However, the use of RFID technology in modern manufacturing has been limited because of the unreliability of RFID devices. In addition to this, where it is used, the technology is mostly deployed to be a substitute for manual inventory management. In this paper we present the Smart Factory, a modern factory infrastructure capable of monitoring each and every product part that moves across the factory during the entire production process. In order to overcome the reliability issues in RFID devices, we have built up a probabilistic model to assign probabilities to the RFID readers and to the product part detections. We also present a probability self-calibration algorithm that automatically adapts the probabilities of RFID readers to better reflect their performance at current instance of time.
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Hameed, B., Rashid, F., Dürr, F., Rothermel, K. (2012). Self-calibration of RFID Reader Probabilities in a Smart Real-Time Factory. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds) Pervasive Computing. Pervasive 2012. Lecture Notes in Computer Science, vol 7319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31205-2_16
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DOI: https://doi.org/10.1007/978-3-642-31205-2_16
Publisher Name: Springer, Berlin, Heidelberg
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