Evidence map›Paper›PMID 37630114›Full record

ArticleMicromachines2023

Three-Dimensional Printed Biomimetic Robotic Fish for Dynamic Monitoring of Water Quality in Aquaculture.

Xiaojun Chen, Dejin Li, Deyun Mo, Zaifu Cui, Xin Li, Haishan Lian, Manfeng Gong

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 27% of its field
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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

7 authors at 1 institution in 1 country.

Xiaojun ChenSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Dejin LiSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Deyun MoSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Zaifu CuiSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Xin LiSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Haishan LianSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Manfeng GongSchool of Mechanical and Electronic Engineering, Lingnan Normal University, Zhanjiang 524048, China.
Lingnan Normal University · CN

Funding

Guangdong Basic and Applied Basic Research Foundation 2022A1515011108National Natural Science Foundation of China 52005239Science and Technology Planning Project of Zhanjiang :2021A05235, 2020A01044
6 · The paper itself

Abstract

The extensive water pollution caused by production activities is a key issue that needs to be addressed in the aquaculture industry. The dynamic monitoring of water quality is essential for understanding water quality and the growth of fish fry. Here, a low-cost, low-noise, real-time monitoring and automatic feedback biomimetic robotic fish was proposed for the dynamic monitoring of multiple water quality parameters in aquaculture. The biomimetic robotic fish achieved a faster swimming speed and more stable posture control at a swing angular velocity of 16 rad/s by using simulation analysis. A fast swimming speed (0.4 m/s) was achieved through the control of double-jointed pectoral and caudal fins, exhibiting various types of movements, such as straight swimming, obstacle avoidance, turning, diving, and surfacing. As a demonstration of application, bionic robotic fish were placed in a lake for on-site water sampling and parameter detection. The relative average deviations in water quality parameters, such as water temperature, acidity and alkalinity, and turbidity, were 1.25%, 0.07%, and 0.94%, respectively, meeting the accuracy requirements for water quality parameter detection. In the future, bionic robotic fish are beneficial for monitoring water quality, fish populations, and behaviors, improving the efficiency and productivity of aquaculture, and also providing interesting tools and technologies for science education and ocean exploration.

Indexed as

3D printingbionic robotic fishwater quality detection

Identifiers

PMID37630114
PMCPMC10456635
OpenAlexW4385738270

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.