GrowRight – Intelligent Crop Prediction for Smarter FarmingL
The project GrowRight aims to develop an intelligent software system that leverages data-driven insights
to recommend the most suitable crops for cultivation.
It analyzes key environmental factors such as Nitrogen (N), Phosphorus (P), Potassium (K) levels,
soil temperature, humidity, pH, rainfall, and crop types to provide smart recommendations that help farmers maximize yields and optimize resources.
The knowledge and insights gained through the GrowRight project can be utilized by agricultural researchers, policymakers, and stakeholders to advance the understanding of crop-environment interactions and inform the development of evidence-based agricultural strategies.
GrowRight transforms farming by offering intelligent crop recommendations based on key environmental factors.
It helps farmers maximize yields and optimize resource use.
This promotes sustainable and efficient agricultural practices.
About the Data
- N (Nitrogen): Essential for plant growth and yield.
- P (Phosphorous): Vital for root development and energy transfer.
- K (Potassium): Important for water regulation and disease resistance.
- Temperature: Average soil temperatures for optimal bioactivity range from 50 to 75°F.
- Humidity: Influences plant transpiration and disease risk.
- pH: Indicates soil acidity or alkalinity (Acidic: pH<7, Neutral: pH=7, Basic: pH>7).
- Rainfall: Total precipitation, crucial for crop selection.
- Label: Crop type (e.g., Rice, Maize, Chickpea, Banana, Mango, Cotton, Coffee, and more).
Machine Learning Approach
- Data Visualization & Analysis: Univariate, bivariate, and multivariate analysis to understand relationships and trends.
- Model Building: Implementation of Artificial Neural Network (ANN) using TensorFlow for crop prediction.
- Model Evaluation: Rigorous performance assessment to ensure high accuracy and reliability.
- Prediction Engine: Suggests the best crop based on user-provided soil and environmental parameters.