One example of how AI can be used in agriculture is livestock monitoring. With accurate annotated data and machine learning, AI can record animal data, monitor their activities, and analyze their health, leading to more precise and efficient cattle farming.
AI can also be used to help farmers make informed decisions about when to harvest their crops. The ripening process for different types of fruits and vegetables varies, and there is always a risk of disease and insects infecting the crops before they are harvested. With AI, farmers can make informed decisions about when to harvest and when to take precautionary measures to reduce these risks.
Another application of AI in agriculture is aerial crop
analysis. Using drones, aerial imagery, and AI, farmers can
keep track of their crops, analyze their growth, identify
infected crops, and determine the areas that need spraying,
helping to maximize their harvests.
Overall, AI and machine learning can provide valuable tools
for the agriculture industry, helping to increase
productivity and efficiency and supporting farmers in their
work.