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Record W4410220378 · doi:10.62951/repeater.v3i2.407

Rancang Bangun Pengembangan Robot Pembersih Sampah Berbasis Internet of Thing (IOT) Untuk Pemantauan dan Pengontrolan Jarak Jauh.

2025· article· en· W4410220378 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRepeater · 2025
Typearticle
Languageen
FieldComputer Science
TopicIoT-based Control Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsComputer scienceInternet of ThingsWorld Wide Web

Abstract

fetched live from OpenAlex

The increasing waste problem requires innovative solutions that are efficient and sustainable. This study aims to design and build an Internet of Things (IoT) based garbage cleaning robot that can be monitored and controlled remotely. This system is designed by utilizing a microcontroller as the main brain, sensors to detect the presence of garbage, and an IoT-based communication module that allows monitoring and control of the robot via mobile devices or the web. Based on the results of the analysis and testing carried out, this study shows that the use of ESP8266 in the RC Trans Robot motor control with the Blynk application has succeeded in significantly increasing system efficiency. The system successfully responds to user input via a mobile application and can control the movement of the robot in real-time. The performance of the robot system controlled via a WiFi network shows good stability in various test scenarios. The robot can operate effectively within a distance that matches the range of the WiFi network, with fast control response and reliable communication.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.225
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it