SOIL NUTRIENT PREDICTION SYSTEM USING MACHINE LEARNING

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  Prototype of IoT-Enabled Soil Nutrients Prediction, Crop Suggestion and Fertilizer Recommendation System using Machine Learning Approach

Inspiration agricultural practices with the help of modern computer science technologies have great scope. The invention disclosed in the patent, helps the farmers to know about their soil fertility, crops which can be grown and fertilizers or nutrients required for their land will be valuable inputs for them. Too much or too little fertilizers may harm the soil, so the right amount of fertilization is also important.

What it does IoT-Enabled Soil Nutrients Prediction, Crop Suggestion and Fertilizer Recommendation System using Machine Learning Approach

How we built it fertilizer to be used , we use input parameters like N,P,K temperature, humidity,moisture and soil type and also crop to be grown. Fertilizer prediction process begins with the loading of the external fertilizers datasets.

Challenges we ran into implementing a central processing unit with the use of meachine learing technology can offer us all the information we need the challenge in implemting this system

Accomplishments that we're proud of The data relating to the soil nutrition are collected from soil testing historical data which provides general crop data. The major crops like wheat, rice, bajra, maize and jowar and minor crops like pulses, gram, jute, cotton, groundnut, barley, ragi, mustard, sugarcane, sesame, and sunflower are considered in the model.

What we learned about machine learning algorithms and creating ml models which will be efficient for future use

What's next for SOIL NUTRIENT PREDICTION SYSTEM USING MACHINE LEARNING

has proposed a crop prediction system which performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production

Built With

• database.com
• iot
• machine-learning