Arecanut Yield Disease Forecast using IoT and MachineLearning

DOI

No DOI

Published In

Volume 1, Issue 2 (2021)

Published Online

March-April 2021

Pages

06-08

Article Type

Research Article

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A general slump in the plant items region is obvious from the ongoing deficiency and nonattendance of food supplies. A huge support for this lack is the characteristic improvement of disorders in key harvests. A critical improvement is subsequently expected in this field for avoiding these issues from here on out. This progression is supposed to develop the organization tasks of different positions in agrarian ventures. A genuine suggestion of the meaning of disease assumption and regular components ought to be done to the less careful farmers. To address these challenges, we have proposed a disease assumption system that contemplates temperature (°C), humidity(%), rainfall(cm), wind flow(m/s) and soil clamminess (%) around the region of gather and encouraged a model to predict the occasion of disease. This structure will give information before the occasion of sickness by looking at different associations among environmentalfactors.