MétaCan
Menu
Back to cohort
Record W4226050301 · doi:10.1007/s10661-022-09825-9

Development of a sensor and measurement platform for water quality observations: design, sensor integration, 3D printing, and open-source hardware

2022· article· en· W4226050301 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

VenueEnvironmental Monitoring and Assessment · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsOpen source hardwareSoftwareComputer scienceComputer hardwareEmbedded systemModular designData loggerEngineeringOperating systemOpen source

Abstract

fetched live from OpenAlex

A measurement and development platform for collecting water quality data (the WaterWatcher) was developed. The platform includes sensors to measure turbidity, total dissolved solids (TDS), and water temperature as variables that are often collected to assess water quality. The design is extensible for research and monitoring purposes, and all the design files are provided under open-source permissive licenses for further development. System design and operation are discussed for illustrative purposes. A block diagram indicates elements of mechanical, electrical, and software design for this system. The mechanical assembly used to house circuit boards and sensors is designed using 3D printing for rapid prototyping. The electronic circuit board acts as a carrier for an Arduino 32-bit microcontroller board and an associated cellular module along with a GPS for geolocation of water quality measurements. The cellular module permits data transfer for Internet of Things (IoT) functionality. System operation is set up using a command line interface (CLI) and C + + code that allows for calibration coefficients and human-readable transfer functions to be defined so that sensor voltages are related to physical quantities. Data are cached on a secure digital (SD) card for backup. The circuit was calibrated, and system operation assessed by deployment on an urban reservoir. Biogeochemical cycles were identified in the collected data using spectrogram and semivariogram analyses to validate system operation. As a system with hardware and software released under an open source license, the WaterWatcher platform reduces the time and effort required to build and deploy low-cost water quality measurement sensors and provides an example of the basic hardware design that can be used for measurements of water quality.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.158
GPT teacher head0.318
Teacher spread0.160 · 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