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

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.

Lógica Fuzzy na Agricultura: Breve Histórico

“…Modelagem fuzzy do vigor das videiras a partir da coleta de dados na França para suportar melhorias nas práticas agrícolas voltadas a produtividade. (Balachandran et al, 2020) Irrigation system using hyperspectral data and machnie learning techniques for smart agriculture Geração de modelagem fuzzy e aprendizado de máquina para otimização de uso de água na irrigação usando sensoriamento de imagens hiperespectrais para leitura de umidade do solo (Cronin et al, 2020)…”