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Record W4415861910 · doi:10.54536/ajise.v4i3.5703

Design & construction of a flood detection system with SMS Alert

2025· article· W4415861910 on OpenAlexaff
Ogechukwu Tammy Ibeama, Michael Warebi Godwin

Bibliographic record

VenueAmerican Journal of Innovation in Science and Engineering · 2025
Typearticle
Language
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsArduinoGSMMicroprocessorShort Message ServiceMicrocontrollerLiquid-crystal displayFlood mythEncryptionWork (physics)

Abstract

fetched live from OpenAlex

This project involves the design and construction of a flood detection system with SMS alert. The system is made up of a 9V DC battery for power supply, water level measuring sensors, a programmable microcontroller, a GSM module, an SD card module for data storage, and a liquid crystal display (LCD) to display the status of the system. The project utilized affordable embedded system components to provide timely flood alert text messages to residents and relevant authorities. The Global System for Mobile Communications (GSM) module is used for sending the mobile text message while the Arduino Nano microprocessor is used to read the input from the water level sensor unit and calculate the height of water. The water level sensor/measuring device in this work was designed using resistors and the principle of water conductivity. The design analysis and simulation was done with proteus and Arduino IDE software. The system was tested using salt water and the output at different water level was obtained.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.235
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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