Artificial intelligence for the management of water projects and the management of water resources: A bibliographical analysis
Bibliographic record
Abstract
This bibliographical review gives us a clear and summarized analysis of the management tools for a water infrastructure construction project and, a tool that allows the management of water resources through the application of everything analyzed and compiled in scientific articles obtained from the Scopus database and after that it was analyzed using the VOSviewer tool, which has the complexity of analyzing a large amount of data. This analysis was carried out from the appearance of the first related investigations until the year 2023, analysis graphs were obtained from representative levels of the words “artificial intelligence”, “project management” of “construction” and “water” resource with greater interest in the analysis. The results obtained allowed us to understand the great variety of technological tools that are available today to be able to manage the construction of a project through artificial intelligence and its components that work together, likewise the application of these tools is carried out by countries as well as the United States. The United States and China are the ones that represent the greatest interest in these investigations, however this contribution is minimal to be able to generate effective solutions since each project presents its particular characteristics that technology has to adapt to. The future of these projects was also analyzed, such as the management of water resources through intelligent technologies that allow the preservation, care and maintenance of water resources, in addition to this, it is emphasized that worldwide there are already problems of droughts, lack of water resources and shortages of water in some countries. This research has the purpose of an overview for decision-making in the execution of the project at the water level and after the management of the water resource, it is important to apply these tools for their different advantages and carry it out to large-scale works in Peru subsidized by the Peruvian state since they are the most responsible for ensuring the care, maintenance and preservation of water resources.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.034 | 0.052 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".