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Research Article · Open access · Published 15 April 2020

Irrigation System Using Hyperspectral Data and Machnie Learning Techniques for Smart Agriculture

Santhi Balachandran1, Sourna Lakshmi1 & Nithya Rajendran1

Journal of Computer Science, Volume 16, Issue 4, pp. 576–582 · doi.org/10.3844/jcssp.2020.576.582

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Abstract

Water is the main resource for agriculture. Management of water in agricultural field is a challenging process. To manage the water content in the agricultural field, smart irrigation system has been proposed by using fuzzy based decision support system on Hyperspectral Image benchmark dataset. Hyperspectral images are the process of collected and processed the images from electromagnetic spectrum. Recent studies show that hyperspectral images are very accurate in collecting the soil moistures value. Dataset is collected in five-day field of campaign the soil is the type of clayey slit and it is non vegetation. Hyperspectral datasets which consist of range value between 454 to 598 nm. Value is gathered from the 285 hyperspectral snapshot camera recording images with 125 spectral bands with the spectral resolution of 4 nm. Experimental results of this method achieve the accuracy of 0.98. Hence the proposed method reduces the water wastage to an extent.

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Balachandran, S., Lakshmi, S. & Rajendran, N. (2020). Irrigation System Using Hyperspectral Data and Machnie Learning Techniques for Smart Agriculture. Journal of Computer Science, 16(4), 576–582. https://doi.org/10.3844/jcssp.2020.576.582

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Irrigation System Using Hyperspectral Data and Machnie Learning Techniques for Smart AgricultureJournal of Computer Science · Volume 16, Issue 4 · pp. 576–582 · CC BY 3.0Download