Bibliographic record
Abstract
The application spectrum of visible light communication (VLC) in navigation is steadily broadening, primarily fueled by its remarkable precision achievable in indoor environments. VLC has emerged as a superior alternative to traditional navigation systems like the commercial global positioning system (GPS), consistently delivering precise results. Despite its success in-doors, addressing the challenges posed by ambient light remains paramount, especially in outdoor scenarios where natural lighting conditions exhibit significant variability. This article explores the intricate relationship between ambient light and outdoor VLC technology for navigation, particularly when coupled with solid-state lighting technologies. These technologies are pivotal in ensuring precise localization in dynamic outdoor environments. Through the application of advanced simulation and modeling techniques, the endeavor is to quantify the impact of ambient light on outdoor VLC systems. This article uses appropriate methodologies to calculate the angular error for the Angle of Arrival and measure received energy across different seasons to comprehensively assess ambient light's influence on system performance. Furthermore, the tables and graphs in the paper facilitate a detailed analysis of sunlight effects, offering valuable insights to optimize the positioning of light transmitters and receivers for enhanced performance and reliability in real-world applications. The findings presented hold significant implications for advancing outdoor VLC technology, paving the way for more robust and effective navigation systems operating seamlessly in diverse environmental conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.019 |
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; both teacher heads agree on what is shown here.
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".