Development Octagonal in Concentric and Meander Line Slot Antennas for Optimal RFID Performance for Safety Food
Bibliographic record
Abstract
RFID technology, first utilized over half a century ago, is rapidly becoming an essential tool for enhancing the flow of information within supply chains and improving security in the agri-food industry.Contrary to the perception that RFID is already fully integrated and widely implemented, it has the potential to significantly enhance current supply chain processes.This study aimed to demonstrate the ongoing relevance of RFID technology, particularly in assessing the quality and freshness of fruits.To illustrate the application of RFID technology for quality assessment.The tag, designed and fabricated in this study, features an octagonal geometric shape with a PET substrate, measuring a minimum area of 1.83 cm².The proposed tag operates within a frequency range of 6.7 GHz to 11.8 GHz and can store approximately 127 bits of data.Simulations conducted indicate notable performance enhancements, particularly in its RCS response for evaluating mango quality.Furthermore, the article discusses the fundamental impedance-matching processes involved in the design of a meander line slot microstrip antenna tag.When the impedance of the antenna aligns with that of the integrated circuit (IC) chip, a significant portion of power is delivered to the antenna rather than being reflected back to the source.The article also provides insights into other important RFID IC chips and their characteristic impedances at 866 MHz within RFID systems, describing these chips using similar RC series circuits and considering the impact of resistance on the impedance in the communication output of RFID antennas.In conclusion simulation results are provided which prove that both of the proposed antenna designs exhibit the desired return loss and resonant frequency for UHF RFID systems.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".