Page 855 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

2 Use Case Description

2�1 Description

Divine Farmer Agricultural AI Model is trained on massive agricultural production data to Agriculture 4.11: Smart
address current challenges in agricultural practices, including over-reliance on individual
experience, shortage of technical personnel, and difficulties in promoting advanced agricultural
technologies. It provides practitioners with intelligent agricultural services such as agricultural
Q&A, pest and disease identification and prevention, and agricultural product price analysis
and forecasting.

Agricultural Q&A: Acts as an intelligent agricultural assistant, offering planting guidance,
farming recommendations, and technical knowledge through interactive Q&A. Eliminates
geographical and temporal constraints, significantly improving the coverage and efficiency of
agricultural technical services. Effectively resolves issues such as low agricultural informatization
levels, limited service coverage, and inconvenient access to information.

Pest and Disease Identification and Prevention: Rapidly and accurately identifies pest and
disease types from user-uploaded images (accuracy rate exceeding 86%). Generates targeted
prevention and treatment plans, providing precise and scientific management tools for
agricultural production. Protects crop health and ensures sustainable growth.

Agricultural Product Price Analysis and Forecasting: Delivers price analysis and market trend
predictions through natural language Q&A. Helps users better grasp market dynamics, optimize
resource allocation, and enhance the efficiency and profitability of the agricultural supply chain.

Related information about our model:

Agricultural technology assistant: Q&A accuracy rate of over 90%. Disease and pest identification
and prevention: Supports the identification of over 20 types of crops, 70 types of pests, and
136 types of diseases, with an accuracy rate of over 85%. Analysis and Trend Prediction of
Agricultural Product Prices: The predicted data covers 441 types of agricultural products from
34 categories across 31 provinces, 141 cities, and 219 farmer's markets, with an accuracy rate
of over 46% in predicting price trends.

2�2 Benefits of the use case

Alleviate rural poverty by providing farmers with precise cultivation guidance and market price
forecasts. This helps optimize farming practices, increase yields, and boost income through
informed decisions on sowing, irrigation, and harvesting.

Support food security through early pest and disease detection, minimizing crop losses
and ensuring stable food supplies. The model enables timely interventions with advanced
monitoring and alert systems.

Improve health outcomes by reducing reliance on chemical pesticides, thereby lowering
harmful residues in food and limiting health risks for both farmers and consumers.

Bridge the technological gap in underdeveloped regions by offering equal access to smart
farming tools and agricultural knowledge, helping reduce rural-urban disparities and promoting
inclusive development.

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