Αποτελέσματα Αναζήτησης
Visual sensing AI can analyze and interpret this data to: track crop health; make accurate yield predictions. detect crop malnutrition much faster than humans; AI models can inform farmers of specific problem areas so that they can take immediate action.
15 Φεβ 2024 · Key findings reveal that AI significantly improves the accuracy and efficiency of demand forecasting and supply chain operations in agriculture. AI technologies, including machine learning...
1 Μαρ 2024 · Predictive analytics is a powerful tool that empowers farmers to optimize their energy usage and make informed decisions in agriculture. By analyzing data from diverse sources, predictive analytics offers valuable insights on crop selection, optimal planting times, appropriate fertilizers, irrigation schedules, and pest or disease management.
1 Ιουλ 2024 · This review study provides an overview of AI applications in agriculture, focusing on its applications to predict and monitor crop growth rate and yield, climate change and weather patterns,...
1 Μαρ 2023 · Predictive analytics, robotics, uncrewed aerial vehicles, and autonomous farm vehicles are some of the popular applications of AI in agriculture. Crop protection, weather forecasting, farm machinery automation, and livestock growth monitoring are examples of agricultural applications where AI has been successfully implemented.
Predictive analytics, integral to intelligent farming, aid farmers in strategic decision-making about crop production, storage, optimal marketing techniques, and risk mitigation.
23 Φεβ 2023 · This work presents extensive research on the latest application of AI in agriculture to alleviate problems in the seven main agriculture domains identified: crop management, water management, soil management, fertirrigation, crop prediction, crop classification, disease, and pest management.
