Automated Fertilizer Spraying System for Purple Eggplant Plants Based on IoT at STMIK KAPUTAMA
Bibliographic record
Abstract
The purple eggplant plant (Solanum melongena L) is a high-value vegetable crop that requires proper fertilization to support optimal growth. However, the manual fertilization methods currently in use are often inefficient and inaccurate, leading to fertilizer waste and suboptimal harvest yields. This study developed an automatic fertilizer spraying system based on the Internet of Things (IoT) using a NodeMCU ESP8266 microcontroller and soil moisture sensors to monitor soil conditions in real-time. The system is equipped with an RTC module and the Blynk app to automatically adjust fertilizer application based on soil moisture levels between 50% and 60%. Test results demonstrate that the system can efficiently activate the pump when moisture drops below the minimum threshold and deactivate it when moisture reaches the maximum threshold. Implementing this system improves fertilizer efficiency compared to manual methods and facilitates remote control, thereby supporting increased productivity and the development of purple eggplant farming.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".