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Record W4387365312 · doi:10.59934/jaiea.v3i1.329

Monitoring The Temperature And Humidity Air In The Room Using A Sensor IOT-Based DHT-11

2023· article· en· W4387365312 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) · 2023
Typearticle
Languageen
FieldEngineering
TopicIoT-based Smart Home Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsHumidityEnvironmental scienceAir humidityInternet of ThingsAir temperatureAndroid (operating system)MeteorologyComputer scienceReal-time computingEmbedded systemOperating systemGeography

Abstract

fetched live from OpenAlex

Air is an important element in everyday life.Therefore the air must have quality so as not to have a negative impact on the body. Low air humidity can cause drying of the air membranes, and if the air humidity in a room is too high it can result in high growth of microorganisms. Abnormal humidity levels can become a respiratory problem and interfere with human health. The temperature and humidity monitoring device is designed based on the NodeMCU ESP8266 and the DHT-11 sensor to measure air temperature and humidity. This study aims to make it easier to know the temperature and humidity in real-time. A temperature and humidity monitoring tool based on NodeMCU ESP8266 is designed with a DHT-11 sensor to measure air temperature and humidity. temperature and humidity air monitoring results will then be sent via a wifi network connection and displayed on an Android smartphone.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.270
Teacher spread0.233 · 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