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Integrative Use of IoT and Deep Learning for Agricultural Applications

机译:集中利用物联网和农业应用深度学习

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Agriculture is the backbone of Indian economy. Most of the population of the country is directly or indirectly dependent on agriculture. Technology can improve agricultural outcomes. In this modern era, there is a major drift in agricultural methods from traditional approaches. Recent advancements in technology have had a great impact on agriculture and it has been established that IoT can be used in farming to enhance quality of agriculture. Evolution of Machine Learning (ML), Deep Learning (DL) and Internet of Things (IoT) has gathered attention of researchers to apply these techniques in fields like agriculture. It helps farmers to increase the productivity of their land so the worldwide demand for food can be fulfilled. This paper highlights various farming problems that can be solved using the synergistic application of deep learning and IoT. In this paper, previous work done with these technologies is discussed. Moreover, we have presented a comparison between Deep Learning and Machine Learning, with specific focus on the complete process of applying Deep Learning on agriculture data to make predictions for agricultural applications.
机译:农业是印度经济的骨干。该国的大多数人口直接或间接依赖于农业。技术可以改善农业成果。在这个现代化的时代,来自传统方法的农业方法的重大漂移。技术的最新进步对农业产生了很大影响,并建立了可用于提高农业质量的农业资源。机器学习的演变(ML),深度学习(DL)和物联网(IOT)已经收集了研究人员的注意,以在农业等领域应用这些技术。它有助于农民增加其土地的生产力,因此可以实现全球对食物的需求。本文突出了可以使用深度学习和物联网协同应用来解决的各种农业问题。在本文中,讨论了使用这些技术完成的以前的工作。此外,我们展示了深度学习和机器学习之间的比较,特别关注了对农业数据应用深度学习的完整过程,以使农业应用预测。

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