Crop Field Protection from Animals Using Convolutional Neural Networks

Animals such as buffaloes, cows, goats, birds, and others have caused agricultural damage in recent years, resulting in significant losses for farmers. Farmers are unable to safeguard entire fields or remain on the field 24 hours a day to do so. As a result, we suggest an automated crop security system that will protect crops from animal attacks. We can train a system utilising datasets that can automatically filter photos and identify animals using Convolutional Neural Network (CNN) architectures. When an animal is discovered in the field, it emits an alarm sound. This sound irritates the animal, and it flees.