基于机器学习和物联网的智能农业

Shamili Srimani Pendyala
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引用次数: 0

摘要

必须提供的粮食数量正受到印度日益恶化的农业状况的影响。许多印度农民已经把注意力从农业转移到其他行业。这项研究是有用的,因为它评估了选择作物、种植作物、发现杂草和密切关注系统的替代方法。所有这些因素加起来构成了一个生产性产出,但它们受到诸如缺乏工人和不利的环境条件等因素的阻碍。这项研究从多个角度研究了该系统,主要关注图像处理、人工智能、机器学习和物联网。这项研究包括对当前框架与最新框架的比较。
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Smart Farming based on Machine Learning and IOT
The quantity of food that must be provided is being affected by the progressively deteriorating state of India’s agricultural industry. Many Indian farmers have shifted their focus away from farming and into other industries. This research is useful because it evaluates alternative approaches to selecting crops, planting them, spotting weeds, and keeping tabs on the system. All of these factors add up to a productive output, but they are hampered by things like a lack of workers and unfavorable environmental conditions. This research looked at the system from multiple angles, primarily focusing on image processing, artificial intelligence,machine learning and the internet of things. The research includes a comparison of the current framework with its most up-to-date counterpart.
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