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  • 标题:IoT Framework for Smart Irrigation using Machine Learning Technique
  • 本地全文:下载
  • 作者:Ramya, S. ; Swetha, A.M. ; Doraipandian, Manivannan
  • 期刊名称:Journal of Computer Science
  • 印刷版ISSN:1549-3636
  • 出版年度:2020
  • 卷号:16
  • 期号:3
  • 页码:355-363
  • DOI:10.3844/jcssp.2020.355.363
  • 出版社:Science Publications
  • 摘要:The scarcity of freshwater around the world is becoming a serious issue, so there is a dire need to come up with a solution for effective utilization of water resources. Basically, agriculture depends on monsoon which is not a sufficient water source. The Internet of Things (IoT) and Machine Learning (ML) based smart irrigation system is employed in the field of agriculture to overcome the problem of water resource management. In this work, a smart irrigation system is proposed to predict the irrigation requirement of the field using several environmental parameters along with weather forecasting that assists the growth of the crop. This system proposes the idea of training the ensemble method in ML using the collected real-time data to make an optimized decision. This prediction model helps in reducing the traditional irrigation methods, thereby conserving water, labor and plant nutrients. This system provides a low-cost prototype model with advanced technological features with a fully functional system and the observed results are optimal with 90% accuracy..
  • 关键词:Ensemble; Evapotranspiration; Irrigation Management
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