Structural Integrity Management with Unmanned Aerial Vehicles: State- of-the-Art Review and Outlook
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the last decade, Unmanned Aerial Vehicles (UAVs) have been used for monitoring construction and operation of civil infrastructure, as well as industrial facilities and power plants. Their operational simplicity along with time-and-cost-related benefits have already rendered them attractive for structural surveying. Nevertheless, the field of UAV research currently lacks a targeted employment of UAVs for Structural Integrity Management (SIM) and Structural Health Monitoring (SHM). This paper provides an overview about actual developments of UAV technologies, breakthroughs in sensor technologies, SHM andValue of Information analysis, the latter being oriented to facilitate an efficiency assessment of precision and cost dependent information. Relevant literature, as well as research and industrial projects, integrating UAVs and SHM are described and assessed, while monitoring strategies, advanced technologies and related algorithms are discussed with a view to achieving increased Value of UAV-based SHM Information.
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.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it