A Hybrid VLC/RF Parking Automation System
Bibliographic record
Abstract
This paper proposes an innovative and integrated parking automation system based on visible light communication (VLC) and radio frequency (RF) wireless technologies. The VLC and RF are used for vehicle-to-infrastructure communication, infrastructure-to-vehicle communication, indoor localization, and wireless mesh networks. For VLC we have utilized the vehicle’s headlight and parking COB bulb-based VLC transmitters and optical receivers that are installed on the parking gate barrier and the roof of the vehicle. Digital pulse interval modulation (DPIM) is used as an anisochronous modulation scheme in VLC-based transactions. The client-server interface and parking’s central processing unit are implemented using the ParkLight software package consisting of an Android application, Django-based web, and LabVIEW PC-based applications. We have introduced a VLC-based two-factor authentication and charging payment systems for installation at the gate barrier. An experimental evaluation of the proposed system is conducted under both day and night conditions in terms of optical interference cancelation, angular displacement, and the transmission link range. The proposed system is successfully demonstrated by achieving a bit error rate (BER) of less than 10-4over a 5 m link range.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".