Evidence map›Paper›PMID 38339568›Full record

ArticleSensors (Basel, Switzerland)2024

Effect of Light-Emitting Grid Panel on Indoor Aquaculture for Measuring Fish Growth.

Nguyen Ngoc Huynh, Myoungjae Jun, Hieyong Jeong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Nguyen Ngoc HuynhDepartment of Artificial Intelligence Convergence, Chonnam National University, Gwangju 61186, Republic of Korea.ORCID 0009-0008-1525-7171
Myoungjae JunDepartment of Artificial Intelligence Convergence, Chonnam National University, Gwangju 61186, Republic of Korea.ORCID 0000-0002-8666-9068
Hieyong JeongDepartment of Artificial Intelligence Convergence, Chonnam National University, Gwangju 61186, Republic of Korea.ORCID 0000-0002-8135-8252

Funding

Ministry of Oceans and Fisheries, Korea 20220596
6 · The paper itself

Abstract

This study is related to Smart Aqua Farm, which combines artificial intelligence (AI) and Internet of things (IoT) technology. This study aimed to monitor fish growth in indoor aquaculture while automatically measuring the average size and area in real time. Automatic fish size measurement technology is one of the essential elements for unmanned aquaculture. Under the condition of labor shortage, operators have much fatigue because they use a primitive method that samples the size and weight of fish just before fish shipment and measures them directly by humans. When this kind of process is automated, the operator's fatigue can be significantly reduced. Above all, after measuring the fish growth, predicting the final fish shipment date is possible by estimating how much feed and time are required until the fish becomes the desired size. In this study, a video camera and a developed light-emitting grid panel were installed in indoor aquaculture to acquire images of fish, and the size measurement of a mock-up fish was implemented using the proposed method.

Indexed as

AquacultureArtificial IntelligenceAnimalsComputer SystemsFishesHumansTechnologyaquaculturedeep learningfish growth, size, and length estimationsegmentation

Identifiers

PMID38339568
PMCPMC10857074

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.