Development of a web-based module for automatic electrical energy management on an animal farm for a resilient electrical system
Bibliographic record
Abstract
Guaranteeing a reliable service to consumers, while reducing power interruptions and minimising environmental impact, is one of the main challenges facing rural electricity distribution. Poor energy quality has a negative impact on production efficiency. For this reason, an automatic module controlling electrical energy from the approved distributor, solar energy and biogas, as well as internal farm parameters, has been developed to help achieve resilient energy. The device consists of an Arduino Mega board, sensors, actuators, clock and wifi modules and a web application for seamless communication between the farmer and the farm. Initial tests on the prototype revealed a minimum efficiency of 90.28% for all units. Laboratory tests showed that the module is able to communicate almost instantaneously with the farmer. It was concluded that the use of this module can seriously limit the variation of electrical energy on a farm and contribute effectively to its resilience. It therefore considerably reduces the environmental pollution caused by farms around the world and increases livestock production.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".