Crop Yield Prediction based on Indian Agriculture using Machine Learning
Product Description
Aim:
To be precise and accurate in predicting crop yield and deliver the end user with proper recommendations about required fertilizer ratio based on soil parameters.
Abstract
India is the land of agriculture and it is the major source of economy.70% of Indian population directly relies on agriculture. The common problem existing among the young Indian farmers is to choose the right crop based on the soil requirements. Due to this, they face a serious setback in productivity. Our work proposes to help farmers determine the soil quality by doing analysis on its various parameters and to suggest crops based on the results obtained using data mining approach. The system uses the Classification algorithm of Random Forest to improve the efficiency of Crop Recommendation System. The system maps the soil and crop data to predict the list of suitable crops for the soil and it also provides the information about nutrients which are deficient in soil for the particular crop. Hence it leaves upon the user to decide on the crop to be sown. Thus, the system helps to provide knowledge to the dilettante farmers.
Proposed system
The proposed system obtains the soil and crop parameters and maps those to list the suitable crops. It passes the various inputs to the controller which uses the Random Forest Algorithm for classification. The proposed system provides easy accessibility to the users. They are also easy to use and understand by the dilettante farmers. It improves the visualization and understandability.
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The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days
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The Delivery time for Hardware
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Mini Projects: Software Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- UML Diagrams
- SRS
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The
Delivery time for software Miniprojects is 2 -3 working days.
Mini Projects - Hardware includes
- Demo Video
- Abstract
- PPT
- Datasheets
- Circuit Diagrams
- Source Code
- Screen Shots & Photos
- Software Links
- Reference Papers
- Full Project Documentation
- Online
support
The Delivery time for Hardware Mini projects is 7-8 working days.
