Design and implementation of fertilizer recommendation system for farmers

作     者：Usha Kiruthika, S. Kanaga Suba Raja, S. Ronak, S.R. Rengarajen, S. Ravindran, P. 

作者机构：Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Easwari Engineering College Chennai India 

出 版 物：《Test Engineering and Management》 

年 卷 期：2020年第83卷

页      面：8840-8849页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

基　　金：This work was supported by TNSCST student project scheme   Government of Tamil nadu 

主　　题：Learning algorithms 

摘      要：India is an agrarian nation. But creating a profitable yield for the farmer in each crop cycle is becoming a major challenge on various factors. Picking the reasonable fertilizer for the land and yield is an important and basic part of agriculture. Deciding the supplement levels in soil utilizing lab hardware can be restrictively costly, particularly in developing nations. The current frameworks on deciding soil nutrient substance and proposal for fertilizer isn t sufficiently proficient efficient enough. This paper introduces a compelling technique for estimation of nutrient dimension in soil and suggestion for appropriate fertilizer. The proposed methodologies comprise of four stages: soil analysis, data pre-processing, data analysis and Recommendation. The soil sample is analyzed using an IoT based device utilizing NPK sensor with two electrodes are set to calculate collect the NPK ratio of the soil nutrient and for pre-processing, the data gathered from sensors are figured into correct dataset and machine learning algorithm is utilized to recognize the reasonable fertilizer. This venture is extremely valuable to farmer to pick the right fertilizer toward the start of product cycle and amplify the yield. © 2020 Mattingley Publishing. All rights reserved.