EPC Gen-2 UHF RFID Tags with Low-power CMOS Temperature Sensor Suitable For Gas Applications
Bibliographic record
Abstract
This paper presents a passive RFID tag with an embedded temperature sensor intended for the EPC Gen-2 protocol operating in the 902–928 MHz ISM band. The design is implemented as a node of a low cost temperature sensors network. The system is powered by a remote power through the RF energy received from the reader in order to create autonomous temperature measurement micro systems. The temperature sensor is based on ring oscillator using CMOS thyristor delay element. The energy recovery and power distribution unit of the RFID tag provides different supply voltages in order to optimize the performance and the power consumption of each building block. Amplitude Shift Keying (ASK) modulation architecture is adopted for Radio Frequency (RF) link which uses an envelope detector and non-coherent demodulation technique. For the temperature sensor, Low power operation is achieved by eliminating the use of power hungry Analog to Digital Converters (ADCs) at the sensor output. The design architecture is fully compliant to the EPC Gen-2 standard. The error in temperature sensing is around −1.8°C/+1°C, with a resolution of 0.3°C. The RFID tag achieves a sensitivity of −11 dBm with an input data rate up to 200 kbps from 1.8V. 0.5Vwas used as supply voltage for the temperature sensor to ensure the low power consumption as well as robustness. The proposed UHF RFID tag is implemented and simulated in 0.18µmCMOS process.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".