Digital Agronomist — drones for monitoring and managing crop conditions

Client

A large agricultural company cultivating extensive farmland. The client name is not disclosed under confidentiality terms.

Goal

Build a system for rapid crop monitoring and early problem detection to reduce crop losses and optimize spending on irrigation and fertilizers.

Challenge

A shortage of qualified agronomists and large field areas led to untimely irrigation and fertilization, late detection of plant diseases, and annual yield losses.

Solution

A “digital agronomist” system was developed combining an unmanned aerial platform, spectral imaging, and AI analytics for automated monitoring of crop health.

UAV with a spectral NIR camera

A specialized drone for agricultural monitoring.

NIR camera for spectral vegetation analysis.

Early detection of stress zones and hidden issues.

Fully autonomous flights.

AI-based image analysis

Automatic interpretation of spectral data.

Plant condition classification and disease detection.

Highlighting problem areas of the field.

Generating treatment recommendations.

UAV flight automation

AI-powered route planning.

Optimized coverage of large territories.

Reduced human factor.

Significant time savings.

Interactive crop map

Field map with risk zones.

Visualization of plant stress levels.

Heatmaps of moisture and nutrition.

Clear recommendations for the agronomist.

Result

Reduced crop losses

Issues are detected at early stages, before visual signs appear.

Cost optimization

Lower spending on irrigation, fertilizers, and chemicals through targeted treatment.

Higher agronomist productivity

One specialist can oversee 5–7× more area.

Faster decision-making

The agronomist receives ready-to-use recommendations without manual data analysis.

Conclusion

The “digital agronomist” system enabled a shift to proactive yield management. Using UAVs with spectral imaging and AI analytics reduced costs, improved crop quality, and made crop management more precise and predictable.