Evidence map›Paper›PMID 40917292›Full record

ArticleHardwareX2025

Programmable automated low-cost IoT water sampler.

Emmanuel Deleon, Ansley J Brown, Jakob Ladow, Erik Wardle, Troy Bauder

Abstract read
In one paragraph

Article in HardwareX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Emmanuel DeleonColorado State University, Department of Soil and Crop Sciences, Agricultural Water Quality Program, 1170 Campus Delivery, Fort Collins, CO 80523-1170, USA.
Ansley J BrownColorado State University, Department of Soil and Crop Sciences, Agricultural Water Quality Program, 1170 Campus Delivery, Fort Collins, CO 80523-1170, USA.
Jakob LadowColorado State University, Department of Soil and Crop Sciences, Agricultural Water Quality Program, 1170 Campus Delivery, Fort Collins, CO 80523-1170, USA.
Erik WardleColorado State University, Department of Soil and Crop Sciences, Agricultural Water Quality Program, 1170 Campus Delivery, Fort Collins, CO 80523-1170, USA.
Troy BauderColorado State University, Department of Soil and Crop Sciences, Agricultural Water Quality Program, 1170 Campus Delivery, Fort Collins, CO 80523-1170, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water quality management is a critical environmental challenge for water resource managers in agriculture and other sectors due to pollution from contaminants like nitrogen and phosphorus. This pollution degrades ecosystems in waterways worldwide. Environmental pollutant mitigation methods rely heavily on the ability of managers to monitor water quality, often by collecting water samples (either by manual or automated methods) and sending them out for analyte characterization by a laboratory. Traditional automated samplers are often prohibitively expensive and/or complex, hindering effective water resource management across different contexts. Conversely, manual collection methods require more time and labor, but provide less data (i.e., a single point in time as opposed to a composite sample from multiple time points). Addressing this, the Colorado State University Agricultural Water Quality Program created a low-cost, automated water sampler (LCS) leveraging Internet of Things (IoT) technology that enables near-real-time, edge-of-field water monitoring. The LCS stands out for its affordability, simplicity, and real-time data provision, offering a practical tool for water resource managers seeking to monitor WQ. Furthermore, comparing LCS water quality and quantity data shows promising agreement, indicating that the device is a reasonable substitute for practical applications.

Indexed as

AutomationEnvironmentInternet of ThingsWater monitoringWater sampler

Identifiers

PMID40917292
PMCPMC12410521

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.