MétaCan
Menu
Back to cohort
Record W2985555676

EPC Gen-2 UHF RFID Tags with Low-power CMOS Temperature Sensor Suitable For Gas Applications

2016· article· en· W2985555676 on OpenAlexaff
Mohamed Zgaren, Saqib Mohamad, Abbes Amira, Mohamad Sawan

Bibliographic record

VenueIEEE International NEWCAS Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsUltra high frequencyEnvelope detectorAmplitude-shift keyingElectronic engineeringElectrical engineeringCMOSSensor nodeComputer scienceEngineeringBit error ratePhase-shift keyingChannel (broadcasting)WirelessTelecommunicationsKey distribution in wireless sensor networks
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.014
GPT teacher head0.234
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueIEEE International NEWCAS ConferenceSame topicEnergy Harvesting in Wireless NetworksFrench-language works237,207