Self-Powered Multi-Port UHF RFID Tag-Based-Sensor
Bibliographic record
Abstract
In this paper, multi-port UHF RFID tag-based sensor for wireless identification and sensing applications is presented. Two RFID chips, one with attached sensor and the other without, are incorporated in a single tag antenna with two excitation ports. The chip with the integrated sensor (sensor port) transmits a signal impacted by the sensed temperature or humidity, while the other RFID chip serves as the reference signal (reference port) transmitter in the sensing process. The proposed tag-based sensor is fabricated and experimentally evaluated. The measured results demonstrate that the sensed data can be extracted using a commercial RFID reader by recording and comparing the difference in the reader output power required to power up the reference port and the power required to power the sensor ports. To improve the reading range of the proposed sensor, a dual-port solar powered RFID sensor is also presented. The reading range of the sensor is increased by two times compared to a similar prototype without solar energy harvesting. The experimental evaluation demonstrates that the proposed tag-based sensor can be easily integrated with a resistive humidity or temperature sensor for a low-cost solution to detect the heat or humidity exposure of sensitive items for several applications such as supply chains and construction structures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".