A State-of-the-Art Review and Bibliometric Analysis on the Smart Preservation of Heritages
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
The preservation of heritage buildings is a crucial endeavour for countries worldwide. This study presents a comprehensive bibliometric analysis of the latest trends in smart applications for heritage building preservation within the context of Industry 4.0 and Industry 5.0, covering the period of 2020–2024. A total of 216 peer-reviewed journal articles obtained from the Scopus database were subjected to analysis using RStudio and VOSviewer. The methodology was based on a dual analysis, including surface-level examination and in-depth exploration. Consequently, a new conceptual framework is presented for achieving smart preservation of heritages. It is structured based on two pillars: the physical methods pillar, including smart devices and smart processes, and the digital methods pillar, involving smart technologies and environments. Also, the results revealed that the dominant portion of literature publications (61%) emphasize specific topics such as interoperability, monitoring, data management, and documentation. However, training and community engagement represent an insufficient fraction (2–6%), and more research is needed in the future. This paper concludes by discussing a future innovative vision for policy and industry through urging policymakers to promote interoperability standards; address data security; and fund innovative, low-cost technologies, as well as advocating the industry sectors for public engagement, sustainable preservation, and prioritizing skill development programs and workforce.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.018 |
| 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) | 0.000 | 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