Smart Agriculture Drone and Edge AI Crop Health Monitoring

In the era of precision agriculture, OneData empowers agri businesses with a complete Smart Agriculture Drone and Edge-AI Crop Health Monitoring platform that brings together unmanned aerial vehicles, IoT sensors, edge computing and cloud analytics. This end-to-end solution enables farms to monitor crop health dynamically, detect emerging issues, and optimise input usage for higher yield and environmental sustainability.

Drone & Sensor Integration

OneData links multispectral drone cameras flying over fields with IoT-connected soil sensors to gather rich data on plant health and soil conditions. Edge computing is enabled via AWS Greengrass and SageMaker Edge so that initial processing and anomaly detection happen on-site, reducing latency and dependency on continuous connectivity.

Edge AI & Cloud Analytics

At the edge, SageMaker Edge handles trained models that detect stressed plants, early pest infestation or nutrient deficiency. Processed data and telemetry stream to AWS Timestream for time-series storage and trend analysis, and AWS Rekognition supports image-based detection of crop anomalies or pest damage. The cloud then aggregates and visualises the data across fields and seasons.

Use Cases

• Precision agriculture: Monitor large-scale fields to optimise water, fertiliser and pesticide use.

• Crop mapping: Generate high-resolution maps of crop vigor, stress zones, yield potential.

• Pest and disease detection: Identify pest-infestation patterns or disease onset early through drone imagery and sensor data.

• Yield prediction: Based on combined multispectral, soil and historical data, predict yield and drive decision-making for harvest planning or market timing.

Benefits

• Optimised pesticide/fertiliser use: By precisely targeting input only where needed, cost and environmental waste are reduced.

• Higher crop yield: Early detection of stress and corrective action increases productivity.

• Reduced water/fertiliser usage: Smart irrigation and input application reduce operational and environmental costs.

• Sustainability & profitability: Better resource efficiency leads to improved margins and sustainable practices.

• Scalable analytics: The edge-to-cloud architecture supports farms of varying sizes, from small holdings to enterprise agriculture business.