RFID Localization Using Angle of Arrival Cluster Forming
Why this work is in the frame
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Bibliographic record
Abstract
Radio Frequency IDentification (RFID) has been increasingly used to identify and track objects automatically. RFID has also been used to localize tagged objects. Several RFID localization schemes have been proposed in the literature; some of these schemes estimate the distance between the tag and the reader using the Received Signal Strength Index (RSSI). From a theoretical point of view, RSSI is an excellent approach to estimate the distance between a sender and a receiver. However, our experiments show that there are many factors that influence the RSSI value substantially and that, in turn, has a negative effect on the accuracy of the estimated distance. Another approach that has been recently proposed is utilizing transmission power control from the reader side. Our experiments show that power control results are more stable and accurate than RSSI results. In this paper, we present a test-bed comparison between the power control and the RSSI distance estimation approaches for active RFID tags. We also present the Angle of arrival Cluster Forming (ACF) localization scheme that uses both the angle of arrival of the tag's signal and the reader's transmission power control to localize active tags. Our experiments show that ACF is very accurate in estimating the location of active RFID tags.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it