Smart farming, also known as precision agriculture, is the practice of using technology and data analysis to optimize agricultural production. It involves the use of sensors, drones, GPS mapping, and other technologies to collect and analyze data on crop yields, weather patterns, soil conditions, and other factors that can affect crop growth.
By leveraging this data, farmers can make more informed decisions about when to plant, fertilize, irrigate, and harvest crops, and can even tailor their approach to specific areas of their fields. This can help to increase efficiency, reduce waste, and ultimately improve crop yields and profitability.
Crop recommendation is the process of providing farmers with advice on which crops to grow based on various factors such as soil quality, climate, market demand, and profitability. Crop recommendation systems use data and models to provide farmers with tailored advice on which crops are most suitable for their specific farm conditions.
A fertilizer recommendator is a tool or system that helps farmers to determine the optimal fertilizer application rates for their crops. It takes into account various factors such as soil type, soil fertility, crop type, and growth stage to provide tailored recommendations for fertilizer application.
| Functionality | Technologies |
|---|---|
| Backend | Django, REST API |
| ML Algorithms | GaussianNb, Naive Bayes, Logistic Regression |
| Database | Mysql |
| Frontend | REACT JS |