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Arecanut Crop Disease Prediction using IoT and Machine Learning
Publication year - 2020
Publication title -
journal of science and technolgy
Language(s) - English
Resource type - Journals
ISSN - 2456-5660
DOI - 10.46243/jst.2020.v5.i3.pp160-165
Subject(s) - scarcity , agriculture , field (mathematics) , agricultural engineering , computer science , natural resource economics , business , risk analysis (engineering) , economics , engineering , geography , mathematics , archaeology , pure mathematics , microeconomics
A prevailing recession in the agricultural goods sector is evident from the present scarcity and lack offood supplies. A major reason for this scarcity is the inherent growth of diseases in essential crops. A majordevelopment is thus required in this field for avoiding these problems in the future. This development is intended tosimplify the management tasks of different roles in agricultural industries. A proper intimation of the importance ofdisease prediction and environmental factors must be done to the less aware farmers. To address these challenges,we have proposed a disease prediction system that takes into consideration temperature (°C), humidity(%),rainfall(cm), wind flow(m/s) and soil moisture (%) around the region of crop and developed a model to predict theoccurrence of disease. This system will provide information prior to the occurrence of disease by analyzing differentrelationships among environmental factors.

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