Ingeniería SolidariaResearch文章。https://doi.org/10.16925/2357-6014.2023.03.03 1印度Lovely Professional University电子邮件:bhuvanpuri1199@gmail.com ORCID: https://orcid.org/0000-0002-3098-7892 2印度Lovely Professional University电子邮件:rameshwar.20345@lpu.co.in ORCID: https://orcid.org/0000-0002-5369-7433物联网、人工智能和区块链在农业中的作用综述;基于文本挖掘方法的作物病害检测

IF 0.4 Q4 ENGINEERING, MULTIDISCIPLINARY Ingenieria Solidaria Pub Date : 2023-09-15 DOI:10.16925/2357-6014.2023.03.03
Bhuvan Puri, Rameshwar Cambow
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引用次数: 0

摘要

引言:本文是2023年在印度旁遮普的Lovely Professional大学进行的一项综述调查的结果,该调查名为“物联网、人工智能和区块链在农业和使用文本挖掘方法进行作物病害检测中的作用”。问题:农业是对许多国家的经济做出重大贡献的关键产业。农作物病害是阻碍农业发展的问题之一。目的:利用机器学习、深度学习、图像处理方法、物联网和区块链技术,本研究总结了过去几年在各种作物疾病识别方面所做的研究。方法:采用文本挖掘技术,从已发表的论文中提取相关信息,并预测以下未来技术,以早期发现作物病害。结果:本文还涵盖了各种问题、挑战和潜在的解决方案。它还强调了用于识别作物病害的广泛工具。结论:本文有助于通过文本挖掘方法提取有价值的关键词,并为另一位研究者创建路线图。创意:运用词云、词频等文本挖掘可视化技术提取关键词。限制:文献调查仅涵盖2023年2月之前发表的文献;随着更多研究的发表,它可以得到扩展。
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Ingeniería SolidariaResearch article. https://doi.org/10.16925/2357-6014.2023.03.03 1 Lovely Professional University, India Email: bhuvanpuri1199@gmail.com ORCID: https://orcid.org/0000-0002-3098-7892 2 Lovely Professional University, India Email: rameshwar.20345@lpu.co.in ORCID: https://orcid.org/0000-0002-5369-7433 A review on the role of IoT, ai, and blockchain in agriculture & crop diseases detection using a text mining approach
Introduction: This paper is the outcome of a review survey, “Role of IoT, AI and blockchain in agriculture and crop disease detection using a text mining approach,” done at Lovely Professional University in Punjab, India, in 2023. Problem: Agriculture is a crucial industry that contributes significantly to the economies of many nations. Crop diseases are one of the issues that create a barrier to agricultural development. Objective: Using machine learning, deep learning, image processing methods, the Internet of Things, and blockchain technology, this study provides a current summary of research done over the past years on disease identfication of various crops. Methodology: The text mining technique is applied to extract the related information from published papers and predict the following futuristic technologies to detect crop diseases early. Results: This paper also covers the various issues, challenges, and potential solutions. It also emphasizes the wide range of tools available for identifying crop diseases. Conclusion: This paper helps to extract valuable keywords through a text-mining approach and create a roadmap for another researcher. Originality: Applied text mining visualization techniques, such as word cloud and word frequency, to extract the keywords. Limitation: The literature survey only covers literature published prior to February 2023; it can be extended with more studies published soon.
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Ingenieria Solidaria
Ingenieria Solidaria ENGINEERING, MULTIDISCIPLINARY-
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