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Record W4415359992 · doi:10.59934/jaiea.v5i1.1574

Optimization of the Automatic Bell System of STMIK Kaputama with Time Control Based on Smartphone Using Nodemcu

2025· article· W4415359992 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

VenueJournal of Artificial Intelligence and Engineering Applications (JAIEA) · 2025
Typearticle
Language
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsFlexibility (engineering)SoftwareScheduleClass (philosophy)Real-time operating systemControl systemReal-time Control SystemThe Internet

Abstract

fetched live from OpenAlex

This research aims to design and implement an Internet of Things (IoT)-based automatic bell system integrated with a smartphone using the ESP32 microcontroller. The background of this study is the limitation of the previous automatic bell system at STMIK Kaputama, which had unclear sound quality and lacked flexibility in scheduling. The developed system utilizes the RTC DS3231 for time management, the DFPlayer Mini for audio playback, and the Blynk application as a remote control interface. The research method includes hardware design, software development, and system functionality testing The results show that the system operates according to the class schedule with clearer sound output, can be controlled via a smartphone, and supports the concept of an efficient and modem smart campus. Therefore, this system can be an effective solution to optimize the time management of academic activities on campus.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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