Implementation of Smart Farming using ML and IoT

Authors

  • Gopal Krishna Shyam, Arun Kumar B, Niranjan S, Rajkumar S, Santhosh Kumar S

Abstract

The Main Aim of this project is to boost the potency of the Agriculture sector. Different weather parameters area unit taken into thought with that the simplest appropriate crop to be fully grown area unit foreseen with the assistance of supervised learning like call Tree Classifier, Regression, SVM. Facilitate of various sensors, the soil and part conditions area unit determined and transferred to machine learning algorithmic program and analysis present itself. The only answer to {the current} downside is sensible agriculture by modernizing the current ancient strategies of agriculture. Hence the project aims at creating fashionable agriculture victimization automation and IoT technologies victimization raspberry pi and machine learning. With the assistance of IoT alongside Machine Learning within the field of agriculture. Will area unit able to increase the yield of the crops and during this system even we tend to are intimating the farmer regarding natural disasters so he can take safety preventative measures. . The result of crop prediction is given through a mobile app and the intimation of natural disaster is given through normal sms so it would be user friendly.

 Keywords: SVM, Regression, Decision tree classifier, Raspberry pi, Sensor, Android app.

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Published

2020-05-12

Issue

Section

Articles