Today, the agriculture sector is becoming more efficient with the help of artificial intelligence-supported farming practices due to the development of technology. Artificial intelligence helps farmers make more accurate and efficient decisions by creating data analysis and prediction models in the agriculture sector.\n\nArtificial intelligence-supported farming applications help farmers make more accurate and efficient decisions by analyzing data collected by sensors, drones, robots, and other devices used in the agriculture sector. This data may include soil moisture levels, temperature, weather conditions, plant growth, and other factors.\n\nData analysis is one of the most important components of artificial intelligence-supported farming. Data is analyzed by artificial intelligence algorithms to provide information about plant diseases, pests, soil fertility, and other factors. This information helps farmers make more accurate and efficient decisions.\n\nPrediction models are another important component of artificial intelligence-supported farming. Prediction models are used to predict future events using past data. These models help farmers plan harvest timing, irrigation, fertilization, and other operations.\n\nArtificial intelligence-supported farming applications help farmers achieve more efficient and sustainable farming. These applications allow farmers to achieve higher yields with less water, fertilizer, and pesticides. Additionally, artificial intelligence-supported farming applications help reduce farmers' workload and enable them to work more efficiently.\n\nIn conclusion, artificial intelligence-supported farming is an important tool for increasing efficiency in the agriculture sector. Data analysis and prediction models help farmers make more accurate and efficient decisions. These applications enable farmers to achieve more sustainable farming and are a promising technology for the future of the agriculture sector.