Industrial revolution and smart farming: a critical analysis of research components in Industry 4.0

Isha Batra, Chetan Sharma, Arun Malik, Shamneesh Sharma, Mahender Singh Kaswan, J. Garza‐Reyes
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Abstract

PurposeThe domains of Industry 4.0 and Smart Farming encompass the application of digitization, automation, and data-driven decision-making principles to revolutionize conventional sectors. The intersection of these two fields has numerous opportunities for industry, society, science, technology and research. Relatively, this intersection is new, and still, many grey areas need to be identified. This research is a step toward identifying research areas and current trends.Design/methodology/approachThe present study examines prevailing research patterns and prospective research prospects within Industry 4.0 and Smart Farming. This is accomplished by utilizing the Latent Dirichlet Allocation (LDA) methodology applied to the data procured from the Scopus database.FindingsBy examining the available literature extensively, the researchers have successfully discovered and developed three separate research questions. The questions mentioned above were afterward examined with great attention to detail after using LDA on the dataset. The paper highlights a notable finding on the lack of existing scholarly research in the examined combined field. The existing database consists of a restricted collection of 51 scholarly papers. Nevertheless, the forthcoming terrain harbors immense possibilities for exploration and offers a plethora of prospects for additional investigation and cerebral evaluation.Research limitations/implicationsThis study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.Practical implicationsThe paper proposes that the incorporation of Industry 4.0 technology into agricultural operations can enhance efficiency, production and sustainability. Furthermore, it highlights the significance of creating user-friendly solutions specifically tailored for farmers and companies. The study indicates that the implementation of supportive legislative frameworks, incentive programmes and resource conservation methods might encourage the adoption of smart agricultural technologies, resulting in the adoption of more sustainable practices.Social implicationsThis study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.Originality/valueBased on a thorough examination of existing literature, it has been established that there is a lack of research specifically focusing on the convergence of Industry 4.0 and Smart Farming. However, notable progress has been achieved in the field of seclusion. To date, the provided dataset has not been subjected to analysis using the LDA technique by any researcher.
工业革命与智能农业:对工业 4.0 研究内容的批判性分析
目的 "工业 4.0 "和 "智能农业 "领域包括应用数字化、自动化和数据驱动决策原则来彻底改变传统行业。这两个领域的交叉为工业、社会、科学、技术和研究带来了众多机遇。相对而言,这两个领域的交叉还是新生事物,仍有许多灰色地带需要识别。本研究是确定研究领域和当前趋势的一个步骤。本研究探讨了工业 4.0 和智能农业领域的现有研究模式和前瞻性研究前景。通过对现有文献进行广泛研究,研究人员成功地发现并提出了三个独立的研究问题。在对数据集使用 LDA 方法后,研究人员对上述问题进行了细致的研究。本文强调了一个值得注意的发现,即在所研究的综合领域缺乏现有的学术研究。现有数据库只收集了 51 篇学术论文。尽管如此,即将到来的领域蕴藏着巨大的探索可能性,并为更多的调查和脑力评估提供了大量前景。所提出的方法可帮助农业从业人员实施工业 4.0 技术。此外,它还可以为技术开发人员提供创新咨询,并促进技术转让。有关监管框架、激励计划和资源保护的研究可帮助政策制定者和政府机构。此外,本文还强调了为农民和企业量身定制用户友好型解决方案的重要性。研究表明,实施支持性立法框架、激励计划和资源保护方法可能会鼓励采用智能农业技术,从而采用更具可持续性的做法。所提出的方法可帮助农业从业人员实施工业 4.0 技术。此外,它还可以为技术开发人员提供创新咨询,促进技术转让。对监管框架、激励计划和资源保护的研究可能有助于政策制定者和政府机构。原创性/价值基于对现有文献的深入研究,已经确定缺乏专门针对工业 4.0 和智能农业融合的研究。不过,在隐蔽领域已经取得了显著进展。迄今为止,还没有任何研究人员使用 LDA 技术对所提供的数据集进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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