Case study on application of wireless ultra-wideband technology for tracking equipment on a congested site
Bibliographic record
Abstract
Construction sites are well known for their dynamic and challenging working environment. Several researchers are investigating the application of various Real-time Location Systems (RTLSs) for improving the safety and productivity of construction projects. When integrated with real-time data analysis systems, RTLS can contribute to making the construction environment smarter and safer by identifying safety hazards and inefficient resource configurations. Previous research shows that the Ultra-Wideband (UWB) technology, an emerging type of RTLS, is suitable for the identification and tracking of construction resources. However, the prevalent form of UWB application requires a set of data cables for data communication and a set of timing cables that aids in the estimation of location. This requirement limits the use of the technology in construction sites, especially for outdoor tracking, since the cable connections can pose safety and logistical challenges. In the wireless application of UWB, the wireless bridges substitute the data cables and the timing cables are entirely removed. While the use of wireless UWB is investigated for indoor application in previous studies, the setting is not tested for the application in outdoor projects. This paper presents a case study on the application of the wireless UWB on an outdoor construction site. The case study was conducted for tracking the equipment on a building reconstruction project in downtown Vancouver. Special ready-to-install panels that contained all the required hardware components for a single sensor were designed to facilitate the installation of UWB on the site. The setting and installation of the wireless UWB is proven to be successful under the harsh construction site conditions. It is demonstrated that the designed UWB system configuration has a great potential for making the system logistically practical and user-friendly for outdoor tracking of construction equipment and assets. By highlighting the limitations of the system in the current set-up, the case study also helped pinpoint the areas of attention for further improvement of the system's performance in terms of accuracy and update rate.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".