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Conceptual Design of a Single Rotor Unmanned Aerial Vehicle for Water Health Monitoring

2025· article· W7152423210 on OpenAlexafffund
Miguel Juarez Monroy, Afshin Rahimi

Bibliographic record

Venuenot available
Typearticle
Language
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsUniversity of Windsor
FundersMitacs
KeywordsConceptual designConceptual modelRotor (electric)Work (physics)

Abstract

fetched live from OpenAlex

Algae blooms pose significant risks to both human and animal health, necessitating effective monitoring strategies. This paper presents a novel conceptual design of a Single Rotor Unmanned Aerial Vehicle (SRUAV) tailored for water health monitoring. commercial-off-the-shelf (COTS) components and 3D printing technology, the SRUAV is designed to collect water samples from Lake Erie, addressing the specific requirements of the Great Lakes Institute for Environmental Research (GLIER) at the University of Windsor. The modular, thrust-controlled SRUAV, weighing 1.5 kg, offers a flight time of 25 minutes and vertical take-off and landing capabilities. This design aims to enhance the efficiency and reduce the costs associated with routine water sampling and monitoring procedures. The paper details the design process, mission profile, and initial sizing, highlighting the advantages of SRUAVs in environmental monitoring applications.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
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
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.087
GPT teacher head0.310
Teacher spread0.222 · 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 teacher head, not a consensus.

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 routes2
Has abstractyes

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