Overview
This project is funded by Amrita Vishwa Vidyapeetham. The objective is to design and develop a Crop Prediction System using a Machine Learning algorithm (K-Means) in which farmers are helped with crop recommendations by knowing the type of soil and location, the intended time of sowing and the crop type. Implemented using PHP & MySQL.
Aim
To create software that provides crop recommendations for a place given its location, the intended date of sowing and the crop type for the Japanese terrain.
Key Functionalities
The growth of plants depends upon their location of sowing, time of sowing and the weather. The location of the farm will tell us about its soil composition and also the pests prevalent in the area. The location and time will together give us an idea about the weather in that location. All crops for proper growth have their own ideal soil nutrient compositions and pest resistance.
System Modules
- Interface creation for crop table management where farmers enter location details
- Database storing location, soil, nutrients, weather, crops, and pests data
- Prediction engine for best suitable crop based on stored data
- Web-based application for remote access