An Overview on Detemining Fish Population using Image and Acoustic Approaches

B. B. Rao, J. Keerthana, C. Raghavendra, Kushi Sarangamath, Mallikarjuna
{"title":"An Overview on Detemining Fish Population using Image and Acoustic Approaches","authors":"B. B. Rao, J. Keerthana, C. Raghavendra, Kushi Sarangamath, Mallikarjuna","doi":"10.1109/ICDSIS55133.2022.9915953","DOIUrl":null,"url":null,"abstract":"India is indeed the world’s third largest producer of fish, with the aquaculture sector accounting for roughly 68 percent of the country’s total fish production. Aquaculture accounts for 1.07 percent of the country’s GDP. By 2025, India is anticipated to require 1.6 crore tonnes of fisheries. However, due to abrupt regional climatic conditions, aquatic productivity has reduced in recent situations. In intensive aquaculture, the quantity of fish in a shoal can provide useful information for the design of smart manufacturing management systems. Traditional artificial sampling and manual testing of aquatic life are not only difficult, arduous, and time - intensive, but they also put strain on the fish because it is a disruptive contact method that impacts fish well-being and health. This study reports on a review of an automatic fish counting system based on appropriate and dependable technology that can assist farmers in real-time, reliable and lossless fish population counts to address the aforementioned difficulties.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"351 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSIS55133.2022.9915953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

India is indeed the world’s third largest producer of fish, with the aquaculture sector accounting for roughly 68 percent of the country’s total fish production. Aquaculture accounts for 1.07 percent of the country’s GDP. By 2025, India is anticipated to require 1.6 crore tonnes of fisheries. However, due to abrupt regional climatic conditions, aquatic productivity has reduced in recent situations. In intensive aquaculture, the quantity of fish in a shoal can provide useful information for the design of smart manufacturing management systems. Traditional artificial sampling and manual testing of aquatic life are not only difficult, arduous, and time - intensive, but they also put strain on the fish because it is a disruptive contact method that impacts fish well-being and health. This study reports on a review of an automatic fish counting system based on appropriate and dependable technology that can assist farmers in real-time, reliable and lossless fish population counts to address the aforementioned difficulties.
利用图像和声学方法确定鱼类种群的研究综述
印度确实是世界第三大鱼类生产国,水产养殖部门约占该国鱼类总产量的68%。水产养殖占该国国内生产总值的1.07%。到2025年,印度预计将需要160万吨渔业资源。然而,由于区域气候条件的突变,在最近的情况下,水生生产力有所下降。在集约化养殖中,鱼群的数量可以为智能制造管理系统的设计提供有用的信息。传统的水生生物人工采样和人工测试不仅困难、费力、耗时,而且由于这种破坏性的接触方法会影响鱼类的健康和健康,也给鱼类带来了压力。本研究报告了一种基于适当和可靠技术的鱼类自动计数系统的审查,该系统可以帮助农民实时、可靠和无损地进行鱼类种群计数,以解决上述困难。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信