Perceive
AI Disease Detection
A downward-facing aerial camera streams the canopy while multispectral sensing captures stress invisible to the eye. Frames are pre-processed on-board in real time.
Aerial cameraMultispectralGPS module
Fully Offline · Edge-First
Intelligence that lives on the drone
No internet. No cloud round-trips. No pilot. The complete perceive-analyze-decide-act loop runs on-board in a single flight pass.
System Architecture
The end-to-end intelligent pipeline
Four stages, one flight pass, zero cloud dependency.
Analyze
Severity Evaluation
A YOLO detection model, TensorRT-optimized for the Jetson Nano, localizes disease lesions and grades infection severity — all at the edge, mid-flight.
YOLOJetson NanoTensorRT
Decide
Crop-Specific Logic
A rule engine fuses model output with the active crop profile — severity thresholds, chemical limits, droplet parameters — and issues an explainable spray decision.
Rule engineCrop profilesSpray control
Act
Precision Spraying
Nozzles actuate only over infected zones, with intensity, droplet size and duration adapted to severity. Every event is GPS-tagged and logged for analytics.
Variable rateGPS loggingDashboard
Why Edge
Remote fields have no signal. Neither do we need one.
Cloud-based crop tools fail exactly where they're needed most. Nexcrop AI carries its full inference stack on-board, so detection latency is measured in milliseconds — not in the drive back to the farmhouse.
Real-time
On-device YOLO inference
Offline
Zero internet in the field
Adaptive
Severity-based spray rates
Traceable
GPS-tagged event logs
Roadmap
A 12-month phased execution plan
From dataset to field-validated system in six disciplined phases.
Months 0–2
Dataset Collection
Field data gathering, annotation and system design.
Months 2–4
Model Development
YOLO training, severity estimation and validation.
Months 4–6
Edge Deployment
Jetson Nano deployment with TensorRT optimization.
Months 6–8
Decision Intelligence
Spray logic and crop-specific control modules.
Months 8–10
System Integration
Full pipeline: detect, decide, act — end to end.
Months 10–12
Field Validation
Real-world trials, evaluation and final reporting.
Want the technical deep dive?
We'll walk your team through the model, the hardware and the field data.