Autonomous drone surveillance that detects crop disease and wildfire threats in real-time using advanced computer vision — protecting your harvest before damage spreads.
Detects fire and smoke signatures from aerial footage with sub-2-second latency. Automatically uploads evidence to the cloud and triggers real-time alerts with GPS coordinates.
Scans aerial imagery row-by-row to identify early signs of crop disease. Classifies infection type and severity, logs GPS coordinates, and sends an instant photo report.
Every detection is pinned to exact coordinates on your farm map, so you know precisely where to act.
Evidence photos auto-upload to Firebase Storage the moment a threat crosses the confidence threshold.
Full detection timeline with timestamps, severity scores, and image URLs in real-time Firestore.
JPG, PNG up to 20MB — field photos, aerial shots
AI
Upload an image and click Analyze
to see AI detection results here.
Autonomous drone flies pre-set routes over your farmland continuously
Camera streams real-time footage at 30fps to onboard processor
YOLOv8 models analyze every frame for fire, smoke, and disease
Detections log to Firestore with GPS coordinates and evidence photo
Farmer gets real-time notification with location map and severity score
The AgroDrone AI mobile experience is being prepared for a more reliable field release. Until launch, the web demo remains available for testing the connected AI models.
Every fire alert and disease hotspot pinned in real-time on Google Maps.
Notified within seconds of any detection, with photo evidence and severity score.
Complete detection timeline with filters by date, type, and GPS location.
Firebase Auth with role-based access. Your farm data stays yours.
Android packaging, field testing, and model response checks are in progress before the public release.
Your observations are training data. Every note helps us build smarter AI.
We're actively collecting real-world feedback to refine our fire detection and disease classification models. Notes you submit may be reviewed by our team and used to improve model accuracy. No personal information is required.
Your feedback helps us push our models further.
We review every note to improve accuracy.