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Crop Prediction Using Machine Learning

About

This project helps to predict the suitable crop and its price according to the air humidity, soil moisture, soil pH and rainfall.

Working

  1. Data Collation At first the Air humidity, Air temperature, Soil moisture, Soil pH and the GPS sensor modules are integrated with the NodeMCU platform into a portable kit. This kit is installed in the farm to gather the respective data of the soil. The data gathered is transferred in real time to firebase database for storage and further processing.
  2. The atmospheric humidity, temperature, soil moisture, soil pH are sent as it is to the database. The latitude and longitude sent by the GPS module is retrieved in the form of which state they fall under. This enables us to collect the rainfall of that place in the previous year.
  3. Data Processing Using Machine Learning -> Crop Prediction -> Price Prediction

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Crop Prediction Using Machine Learning

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