Computer Vision―The Frontier of Modern Environmental Diagnostics: A Review

IF 0.6 Q3 MULTIDISCIPLINARY SCIENCES Pertanika Journal of Science and Technology Pub Date : 2024-07-16 DOI:10.47836/pjst.32.4.08
Anna Sergeyevna Olkova, Evgeniya Vladimirovna Tovstik
{"title":"Computer Vision―The Frontier of Modern Environmental Diagnostics: A Review","authors":"Anna Sergeyevna Olkova, Evgeniya Vladimirovna Tovstik","doi":"10.47836/pjst.32.4.08","DOIUrl":null,"url":null,"abstract":"Computer vision (CV), in combination with various sensors and image analysis algorithms, is a frontier direction in diagnosing the state of the environment and its biogenic and abiogenic objects. The work generalizes scientific achievements and identifies scientific and technical problems in this area of research based on the conceptual system of analysis on the time axis: from implemented achievements as part of the past and present to original new solutions—the future. Our work gives an idea of three areas of application of CV in diagnosing the state of the environment: phenotype recognition in digital images, monitoring of living and abiogenic objects, and development of new methods for identifying pollution and its consequences. The advantages of CV, which can be attributed to scientific achievements in this field of research, are shown: an increase in the volume of analyzed samples, simultaneous analysis of several parameters of the object of observation, and leveling of subjective evaluation factors. The main CV problems currently solved are the accuracy of diagnostics and changing quality of the survey, identification of the object of analysis with minimal operator participation, simultaneous monitoring of objects of different quality, and development of software and hardware systems with CV. A promising direction for the future is to combine the capabilities of CV and artificial intelligence. Thus, the review can be useful for specialists in environmental sciences and scientists working in interdisciplinary fields.","PeriodicalId":46234,"journal":{"name":"Pertanika Journal of Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pertanika Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47836/pjst.32.4.08","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Computer vision (CV), in combination with various sensors and image analysis algorithms, is a frontier direction in diagnosing the state of the environment and its biogenic and abiogenic objects. The work generalizes scientific achievements and identifies scientific and technical problems in this area of research based on the conceptual system of analysis on the time axis: from implemented achievements as part of the past and present to original new solutions—the future. Our work gives an idea of three areas of application of CV in diagnosing the state of the environment: phenotype recognition in digital images, monitoring of living and abiogenic objects, and development of new methods for identifying pollution and its consequences. The advantages of CV, which can be attributed to scientific achievements in this field of research, are shown: an increase in the volume of analyzed samples, simultaneous analysis of several parameters of the object of observation, and leveling of subjective evaluation factors. The main CV problems currently solved are the accuracy of diagnostics and changing quality of the survey, identification of the object of analysis with minimal operator participation, simultaneous monitoring of objects of different quality, and development of software and hardware systems with CV. A promising direction for the future is to combine the capabilities of CV and artificial intelligence. Thus, the review can be useful for specialists in environmental sciences and scientists working in interdisciplinary fields.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
计算机视觉--现代环境诊断的前沿:综述
计算机视觉(CV)与各种传感器和图像分析算法相结合,是诊断环境状态及其生物和非生物物体的前沿方向。我们的工作以时间轴为分析概念系统,概括了这一研究领域的科学成就并确定了科学和技术问题:从作为过去和现在一部分的已实施成就到原创的新解决方案--未来。我们的工作让人了解到计算机视觉在诊断环境状况方面的三个应用领域:数字图像中的表型识别、生物和非生物物体的监测以及识别污染及其后果的新方法的开发。在这一研究领域取得的科学成就体现了 CV 的优势:分析样本量的增加、同时分析观察对象的多个参数以及主观评价因素的平衡。目前已解决的主要 CV 问题有:诊断的准确性和调查质量的变化、在操作人员最少参与的情况下识别分析对象、同时监测不同质量的对象以及开发具有 CV 功能的软件和硬件系统。未来一个有前途的方向是将 CV 和人工智能的能力结合起来。因此,本综述对环境科学专家和从事跨学科领域工作的科学家很有帮助。
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 去求助
来源期刊
Pertanika Journal of Science and Technology
Pertanika Journal of Science and Technology MULTIDISCIPLINARY SCIENCES-
CiteScore
1.50
自引率
16.70%
发文量
178
期刊介绍: Pertanika Journal of Science and Technology aims to provide a forum for high quality research related to science and engineering research. Areas relevant to the scope of the journal include: bioinformatics, bioscience, biotechnology and bio-molecular sciences, chemistry, computer science, ecology, engineering, engineering design, environmental control and management, mathematics and statistics, medicine and health sciences, nanotechnology, physics, safety and emergency management, and related fields of study.
期刊最新文献
A Review on the Development of Microcarriers for Cell Culture Applications The Compatibility of Cement Bonded Fibreboard Through Dimensional Stability Analysis: A Review Bending Effects on Polyvinyl Alcohol Thin Film for Flexible Wearable Antenna Substrate Mesh Optimisation for General 3D Printed Objects with Cusp-Height Triangulation Approach The Riblet Short-Slot Coupler Using Substrate Integrated Waveguide (SIW) for High-frequency Applications
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1