See what the field sees.
DEMETER is our computer vision artilect for crop health: disease detection, pest identification, and yield-critical diagnostics at the edge.
Vision in the field
DEMETER is the computer vision AI (image and video object detection) specialised in agriculture within the Vertex ecosystem. It runs on Vertex edge nodes and fixed ground cameras, analysing streams in real time.
Trained on proprietary and augmented datasets, the model delivers high precision in varied conditions. Detections and confidence scores are streamed to Vertex for logging, smart alerts, and downstream automation.
Detections
DEMETER powers the visual intelligence layer: from fire and frost to disease and intrusion.
Disease detection
Multi-class | Real-time
Identifies fungal, bacterial, and viral signatures on leaves and stems (e.g. Septoria, rust, powdery mildew, fungal leaf spots, fruit rot) with minimal latency for field deployment.
Pest identification
Object detection | Taxonomy
Detects and classifies pest species to support integrated pest management and reduce broad-spectrum treatments.
Fire, frost, intrusion
Smoke | Flame | Human | Animal
Smoke and flame detection for early fire alerts; frost detection for viticulture and crops; human and animal intrusion detection for security and authority alerts.
Irrigation defects
Stress indicators
Detects irrigation defects and water-stress indicators before they impact yield, enabling targeted interventions.
Vertex integration
Rust backend | Telemetry
Streams detections and confidence scores to Vertex for logging, alerts, parcel health mapping, and downstream automation.
Use cases by sector
Concrete applications of DEMETER across cereals, viticulture, fruit farming, and arboriculture.
Cereals
Cryptogamic disease detection: Septoria, rust, powdery mildew on leaves and stems for early treatment decisions.
Viticulture
Frost detection to trigger protection measures and limit damage to vines.
Fruit farming
Identification of fruit rot and fungal development on fruit for quality and yield management.
Arboriculture
Fungal disease detection via leaf spot analysis for targeted interventions.