FarmScenario is an AI-powered farming simulation that helps users explore crop selection, soil compatibility, water management, and farming scenarios through an interactive 3D environment.
The project aims to make agricultural knowledge more accessible by combining artificial intelligence with interactive visualization.
- AI Farming Assistant: Ask farming questions and receive AI-generated guidance.
- Interactive 3D Farm: Explore a visual farm environment that responds to farming settings.
- Crop Intelligence: Explore crop options and their suitability for different farming conditions.
- Soil Compatibility: Investigate how soil types affect crop selection.
- Water Management: Experiment with different water availability levels.
- Farm Scenarios: Compare normal conditions, drought, and drought with irrigation.
- AI Crop Diagnosis: Designed to help users investigate crop health using image-based analysis.
- Natural-Language Interaction: Explore farming settings using ordinary language.
- React
- Vite
- JavaScript
- React Three Fiber
- Three.js
- Node.js
- Express
- AI model APIs
- Select a crop and configure the farming conditions.
- Choose soil and water availability settings.
- Explore the farm in the interactive 3D environment.
- Ask the AI farming assistant for relevant guidance.
- Experiment with different scenarios to understand how changing conditions affect the farm.
FarmScenario aims to make agricultural technology more approachable, especially for learners and farmers who need accessible tools to explore crop and soil decisions.
The long-term vision is to develop the platform into a more comprehensive AI-assisted agricultural planning and simulation tool.
FarmScenario is under active development. Features and AI integrations are being tested and improved.
Developed for the Victoria VR AI Builder Hackathon 2026, FarmScenario explores how AI and interactive 3D experiences can help users understand agricultural scenarios.
- Node.js and npm
- An internet connection
- API keys for the AI providers configured by the project
Clone the repository:
git clone https://github.com/atorfaruk/farmscenario.git
cd farmscenario
npm installCreate a local .env file and configure the required AI provider API keys. Refer to the environment variables used in server.cjs. Never publish API keys or commit your .env file.
Start the development server using the scripts defined in package.json. Run the frontend and backend as required by the project configuration.
- Keep API keys private.
- Do not commit
.envfiles. - Validate API responses and handle provider failures safely.
- More realistic 3D crops and farm environments.
- Expanded crop and soil intelligence.
- Improved AI-powered crop diagnosis.
- More detailed irrigation and drought simulations.
- Better guidance for different farming regions.
No license has been specified yet.