Evidence map›Paper›PMID 30484049›Full record

ArticleEnvironmental science and pollution research international2019

Camera sensor-based contamination detection for water environment monitoring.

Yong Wang, Xufan Zhang, Jun Chen, Zhuo Cheng, Dianhong Wang

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2019. 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. Review
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.

Yong WangSchool of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, 430074, China. wy112708@163.com.ORCID http://orcid.org/0000-0003-2642-5210
Xufan ZhangSchool of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, 430074, China.
Jun ChenSchool of Automation, China University of Geosciences, Wuhan, 430074, China.
Zhuo ChengSchool of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, 430074, China.
Dianhong WangSchool of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, 430074, China.

Funding

National Natural Science Foundation of China 61771436
6 · The paper itself

Abstract

Water environment monitoring is of great importance to human health, ecosystem sustainability, and water transport. Unlike traditional water quality monitoring problems, this paper focuses on visual perception of water environment. We first introduce the development of a customized aquatic sensor node equipped with an embedded camera sensor. Based on this platform, we present an efficient and holistic contamination detection approach, which can automatically adapt to the detection of floating debris in dynamic waters or the identification of salient regions in static waters. Our approach is specifically designed based on compressed sensing theory to give full consideration to the unique challenges in water environment and the resource constraints on sensor nodes. Both laboratory and field experiments demonstrate the proposed method can fast and accurately detect various types of water pollutants and is a better choice for camera sensor-based water environment monitoring compared with other methods.

Indexed as

EcosystemEnvironmental MonitoringPhotographyWater Pollutants, ChemicalWater QualityWater Pollutants, ChemicalCamera sensorCompressed sensingContamination detectionEnvironmental monitoring

Identifiers

PMID30484049

What OpenQuestion holds

Textmetadata
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.