Crop Recommendation System

A ML and DL based website that recommends the optimum crop to grow based on the soil composition and atmospheric conditions.

Motivation

• One of the key elements influencing a nation's economic development is the agriculture sector.
• In nations like India, the majority of the population relies on agriculture for a living.
• New technologies like machine learning and deep learning are being used in agriculture as it gets increasingly automated.
• Farmers will be able to increase productivity and maximise their harvest with the help of this techniques.
• One of the most crucial elements of precision and automated agriculture is crop suggestion. Numerous variables are taken into account while recommending crops.
• Farmers often don't know which crops to grow.
• In this project, we aim to build such a website in which farmers will giveninput on the soil composition of the field and the climatic condition of the area. Based on several parameters, the website will suggest which crop will be most suitable according to the given inputs by the farmer with the help of artificial neural network.

Features

• Interactive User Interface
• Easily accessible
• Works on all type of devices
• Supports multiple language
• Has high accuracy rate
• Quick processing
• Result can be understood easily
• User Friendly
• Supports vast variety of crops

Dataset Used

• Crop Recommendation System (Custom built)

Tools and Technologies used

• Python
• HTML5
• CSS3
• JavaScript
• Matplotlib
• Pandas
• Tensorflow
• Keras
• Flask
• Numpy

Output

--> Language : English

--> Language : Hindi

--> Language : Gujarati

Conclusion

To conclude, this project aims at developing a highly accurate crop recommendation system. For recommendation of the crop this system will use a neural network which is developed from the scratch. The system takes the input from farmers such as Nitrogen , Phosphorus, Potassium, Rainfall, Temperature, Pressure, and pH level. This system will help farmers to harvest proper crops according to the soil composition and atmospheric conditions of their field. This will take farmers one step closer to precision and automated farming. It will help farmers in getting greater yield for their products and by getting a good amount of profit from their crops. Thus it will make farming more efficient by helping farmers in getting better yield for their harvest.