Embedded visualizations in crane operation user interfaces for real-time assistance
Bibliographic record
Abstract
While crane operations are becoming increasingly complex, challenges remain in creating user interfaces (UIs) that effectively support real-time decision-making and situational awareness . This paper presents a comprehensive review and evaluation of visualizations used in crane operations, focusing on user interfaces designed to enhance operator performance and safety during lifts. Through a systematic review of existing literature, this paper synthesizes key trends, design principles, and technologies in crane UIs, with a particular emphasis on the role of embedded visualizations. A tailored UI evaluation model is developed, drawing from principles in human-computer interaction and Augmented Reality (AR) design realms, to assess the efficacy of these systems in real-time operations. This review also identifies key research gaps, including the need for empirical testing of individual visualizations and comprehensive UI configurations to better understand their impact on operator performance. Overall, this paper makes valuable contributions to the field by laying the groundwork for improving both the safety and productivity of crane operations through more effective, user-centered UIs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 teacher head, 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".