Relative localization method of wet spot of grain using array of passive RFID tags

Noraini Azmi, Latifah Munirah Kamarudin*, Latifah Mohamed, Ammar Zakaria, Mohd Hafiz Fazalul Rahiman, Syed Muhammad Mamduh Syed Zakaria, David Lorater Ndzi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Radio Frequency Identification (RFID) enables a large number of object monitoring since semi/passive tags are independent of batteries. In our previous work, the possibility of using different wireless technologies such as Wireless Sensor Network (WSN), Wireless Local Area Network (WLAN) and Radio Frequency Identification (RFID) to determine the moisture content in rice was investigated. Finding from our previous work suggest that RFID can be used to determine the moisture content of rice. While numerous research have been conducted for moisture content of grain, however, to author's knowledge, there is only a few studies conducted on the localization of grain hostpot. Therefore, this study aims to investigate if the passive RFID array can be used to localize the location of the wet spot of grain. Prior, the experiment, a suitable setting for the RFID system were determined. In addition, a simple test was conducted to select a suitable operating frequency. From the investigation, the result indicates that only frequency channels 865, 866, 867, 868 and 869 MHz can detect all 30 tags. Meanwhile, frequency channel in the range 902 to 928 MHz detects 26 to 29 unique tags. Hence, 868 MHz was selected as the operating frequency throughout the experiment. The findings indicate that the RSSI value measured by the RFID reader decreased as the moisture of the sample increased when the tags were blocked by the sample placed at the designated location during the test.

Original languageEnglish
Article number012004
Number of pages8
JournalJournal of Physics: Conference Series
Volume2107
Issue number1
DOIs
Publication statusPublished - 1 Dec 2021
Event7th International Conference on Man Machine Systems, ICoMMS 2021 - Perlis, Virtual, Malaysia
Duration: 19 Oct 202120 Oct 2021

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