AI Agriculture
Artificial Intelligence (AI) in agriculture refers to using machine learning algorithms and other AI technologies to analyze data and make predictions and recommendations related to agricultural operations1. Farmers use AI for methods such as precision agriculture, which can monitor crop moisture, soil composition, and temperature in growing areas, enabling farmers to increase their yields by learning how to take care of their crops and determine the ideal amount of water or fertilizer to use. AI can provide farmers with real-time insights from their fields, allowing them to identify areas that need irrigation, fertilization, or pesticide treatment.
Artificial Intelligence (AI) can also help farmers reduce waste and improve sustainability by analyzing data on water usage, fertilizer application, and other resources, reducing waste and minimizing their environmental impact. AI has the ability to transform 21st century agriculture by increasing efficiency of time, labor, and resources, improving environmental sustainability, and making resource allocation “smarter”. AI has improved crop production and real-time monitoring, harvesting, processing, and marketing, saving the agriculture sector from different factors such as climate change, population growth, employment issues, and food safety.
Benefits

Data-based decisions

Cost savings







Automation impact

AI in Agriculture
globally 2023 -2030
($ Billion) AI in agriculture market
0
($ Billion) spending on AI Agriculture
0
Applications
Traditional farming involves various manual processes. Implementing AI models can have many advantages in this respect. By complementing already adopted technologies, an intelligent agriculture system can facilitate many tasks. AI can collect and process big data, while determining and initiating the best course of action. Here are some common use cases for AI in agriculture:
Crop and soil monitoring

Observing crop maturity

Hitting the Ground with Computer Vision

Finding bugs with code










Livestock health monitoring

Intelligent spraying

Automatic weeding

Intelligent pesticide application

Sorting harvested produce
