Overview
Multi-agent agriculture systems enable precision farming at scale. Agent teams monitor crops via satellite and drone imagery, predict yields, detect pests and diseases, and optimize resource usage—maximizing yields while minimizing inputs and environmental impact.
Architecture
Farm Data → Crop Monitoring Agent → Crop Health Maps
↓
Weather Analysis Agent → Weather Insights
↓
Pest Detection Agent → Pest Alerts
↓
Irrigation Agent → Irrigation Schedule
↓
Yield Prediction Agent → Yield Forecasts
↓
Harvest Planning Agent → Harvest Plan
Agent Roles
Crop Monitoring Agent
- Analyzes satellite and drone imagery
- Tracks crop health indices (NDVI, etc.)
- Identifies stressed areas
- Monitors growth stages
Weather Analysis Agent
- Forecasts local weather conditions
- Predicts frost and extreme events
- Analyzes precipitation patterns
- Recommends weather-based actions
Pest Detection Agent
- Identifies pest and disease signs
- Predicts pest outbreaks
- Recommends treatment options
- Tracks treatment effectiveness
Irrigation Agent
- Monitors soil moisture levels
- Calculates crop water needs
- Optimizes irrigation schedules
- Manages water resources
Yield Prediction Agent
- Forecasts crop yields
- Tracks yield by field zone
- Identifies yield-limiting factors
- Supports harvest planning
Harvest Planning Agent
- Optimizes harvest timing
- Coordinates equipment and labor
- Manages logistics
- Tracks harvest progress
Equipment Agent
- Monitors equipment health
- Schedules maintenance
- Optimizes equipment usage
- Tracks fuel and inputs
Market Agent
- Tracks commodity prices
- Recommends sell timing
- Analyzes market trends
- Manages contracts
Precision Agriculture Data
Data Sources:
├── Satellite imagery
├── Drone surveys
├── IoT sensors
│ ├── Soil moisture
│ ├── Weather stations
│ └── Equipment telemetry
├── Historical yield maps
└── Market data
Analysis Outputs:
├── Variable rate prescription maps
├── Pest/disease alerts
├── Irrigation schedules
├── Yield predictions
└── Harvest recommendations
Pest Detection Pipeline
Imagery Analysis → Anomaly Detection → Classification
↓
Pest/Disease Identification
↓
Treatment Recommendation
↓
Application Planning
Real-World Results
Commercial Farms:
- 15-25% reduction in water usage
- 20% reduction in pesticide application
- 10-15% yield improvement
- Better resource allocation
Key Patterns
- Monitoring Pattern: Continuous crop surveillance
- Prediction Pattern: Weather and yield forecasting
- Optimization Pattern: Resource usage optimization
- Alert Pattern: Early warning for pests and diseases