Research Article Open Access

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

Santhi Balachandran1, Sourna Lakshmi1 and Nithya Rajendran1
  • 1 SASTRA Deemed University, India
Journal of Computer Science
Volume 16 No. 4, 2020, 576-582

DOI: https://doi.org/10.3844/jcssp.2020.576.582

Submitted On: 15 July 2019 Published On: 15 April 2020

How to Cite: 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

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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Keywords

  • Hyperspectral
  • Fuzzy Logic
  • Smart Farming