Crop-Wise Precision Farming with Integration of ML and IoT

The smart crop recommendation system is becoming more and more important as global population growth puts pressure on food production systems. IoT-based smart garden systems are gaining popularity. When watering systems are tracked and controlled using sensors, an easy-to-use program is offered to display the data that has been gathered. In order to give farmers access to real-time crop data, the article describes a novel crop recommendation system that combines IoT devices like the Arduino Nano Board, ESP32 Board, NPK Sensor, and capacitive soil moisture sensor with ML models like the random forest regressor, decision tree, and logistic regressor. By employing real-time data and analysis, the suggested technique can assist farmers in reaching their precision farming objectives by assisting them in determining when to apply water, herbicides, and fertilizer.