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Low-Cost Open Source IoT-Based SCADA System for a BTS Site Using ESP32 and Arduino IoT Cloud

2021· article· en· W4206213829 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIoT-based Smart Home Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsArduinoCloud computingSCADAComputer scienceInternet of ThingsEmbedded systemDashboardModbusTransceiverOpen sourceElectrical engineeringOperating systemEngineeringWirelessDatabaseSoftware

Abstract

fetched live from OpenAlex

A low-cost open source IoT-based SCADA system for a rural BTS site using ESP32 and Arduino IoT Cloud is presented in this work. Current, voltage, temperature, and humidity sensors are programmed to measure relevant parameters of interest, and the measured Data is processed and parsed to the Arduino IoT Cloud via a Wi-Fi network communication channel. A widget-based dashboard is created on the Arduino IoT Cloud to monitor and control the system. A mobile application is also deployed to aid remote monitoring and control as well. LEDs are used to implement a high temperature and low voltage control logic. A prototype is used to demonstrate this as an illustration of what is obtainable in a Base Transceiver Station (BTS), where the voltage must be within a specific value (48 V) and the temperature within an acceptable value too.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.236
Teacher spread0.217 · 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

Quick stats

Citations33
Published2021
Admission routes1
Has abstractyes

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