Reconfigurable self-calibrated multi-sensing RFID-based platform
Bibliographic record
Abstract
This paper concerns an RFID tag platform using an integrated temperature sensor and external pressure sensor targeted for the Electronics Product Code (EPC) Gen-2 standard operating in the 902-928 MHz ISM band. The developed system is part of a low-cost wireless sensors network node. This work demonstrates the study, development, and troubleshooting of battery-assisted sensing platform compliant to the RFID standard electronic product code Gen-2. Two main scenarios are tested to connect the sensors; passive and semi-passive tags. The two architectures allow collecting data based on either the RFID reader command or a signal processing program to save the sensing data using the integrated circuit memory. Temperature and pressure measurements are performed based on the integrated and external sensors combined in the RFID circuit board. Besides the fully integrated temperature sensor with a sensing precision of 0.5 C over the target temperature range, external pressure sensor is connected to provide a flexible way for additional sensors interfacing. Sensor are connected to a single system as the design is intended for a reconfigurable self-calibrated multi-sensing platform. The proposed sensing tags are fully verified through measurements.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.002 | 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".