E-Agronomy: Smart irrigation decision making system using Machine learning in Precision Agriculture

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Suresh P, Aswathy RH, Jeeva kumar VK, Gowtham R, Gopalakrishnan.T

Abstract

Agriculture is the backbone for a developing country like India, and there is a vast need to maintain the agricultural property. Precise agriculture is a significant contribution to the economic and agricultural welfare of countries across the globe. Effective utilization of agricultural land and irrigation guaranteeing food safety. This proposed decision-making system proposes nursing the Internet of Things (IoT) and micro litre-based agriculture system. This system will assist farmers or agriculturists in maintaining a proper irrigation schedule, leading to solid root development with minimizing water loss. IoT technology and Machine Learning (ML) for the prediction will change sensible farming and increase their overall yield with minimum water. The smart irrigation decision-making system designed using a decision tree algorithm, which trains the system using the gathered soil and methodological parameters to decide the amount of water to irrigate.


 

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