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- W4387237384 abstract "One of the principle types of the revenue in India is framing. Creation of the harvests in the agribusiness depends on the different types of boundaries like temperature, moisture, downpour, and so forth which differ regularly, and human cannot control them. In the fields of agribusiness likewise relies on some of the elements such as bug, illness, composts, and so forth which depends on controlling by giving appropriate treatment to the crops. Pesticides can expand usefulness of the harvests, however, additionally influences on the human wellbeing. So, the fundamental point for discussion in the paper is to deploy farming drome for the splashing fields with pesticides. The utilization of pesticides in horticulture is vital to agribusiness, and it will be so natural on the off chance using machine learning (ML). ML is a moving innovation, and it makes a difference in assembling the precision and gives answers for the harvest yield issue. ML gives better opportunities to loosen up, measure, furthermore, comprehend the information escalated expectation conditions. In this paper, we will talk about an engineering dependent on drome and behaviors different ideas of ML for Internet of things (IoT) based on agriculture framework." @default.
- W4387237384 created "2023-10-02" @default.
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- W4387237384 date "2023-01-01" @default.
- W4387237384 modified "2023-10-16" @default.
- W4387237384 title "An Architecture on Drome Agriculture IoT Using Machine Learning" @default.
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- W4387237384 doi "https://doi.org/10.1007/978-981-99-2746-3_63" @default.
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