Rancang Bangun Alat Pendeteksi dan Pengusir Hama Tanaman Kangkung menggunakan Sensor Pir dan Cairan Peptisida Berbasis Internet Of Things (IOT)
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
This research aims to design and build a tool for detecting and repelling pests on kale plants using Passive Infrared (PIR) sensors and Internet of Things (IoT) based pesticide liquid which can be controlled via the Telegram application. This system works by detecting the movement of pests using a PIR sensor, which then activates the mechanism for automatically spraying pesticide liquid to repel pests. Users can monitor and control this tool in real-time via Telegram, providing flexibility in plant monitoring. Data from sensors is sent to the IoT platform and integrated with Telegram to provide remote notifications and control. Test results show that this tool can detect the presence of pests with high accuracy and is effective in repelling pests from the kale plant area. It is hoped that the implementation of this tool can help farmers maintain the quality and quantity of their kale harvest in a more efficient and environmentally friendly manner.
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 | 0.000 | 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) | 0.001 | 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