AI Platform Architecture
This section provides detailed documentation of the Trifork AI Platform architecture for the YPF Unmanned Aerial Monitoring Service.
Architecture Overview
┌─────────────────────────────────────────────────────────────────────┐
│ ENTERPRISE INTEGRATION │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ SAP PM │ │ Genetec │ │ RTIC │ │
│ │ Work Orders │ │ Security │ │ Dashboards │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────────────────────┘
│
┌─────────────────────────────────────────────────────────────────────┐
│ TRIFORK AI PLATFORM │
│ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ Application Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ Alert │ │ Event │ │ API │ │ │
│ │ │ Manager │ │ Manager │ │ Gateway │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ AI/ML Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ Triton │ │ Correlation │ │ Confidence │ │ │
│ │ │ Inference │ │ Engine │ │ Scoring │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ Data Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ PostGIS │ │ InfluxDB │ │ Object │ │ │
│ │ │ Digital Twin │ │ Time Series │ │ Storage │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ Ingestion Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ FlightHub │ │ Sensor │ │ Message │ │ │
│ │ │ Ingestion │ │ Pipeline │ │ Queue │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────┘
│
┌─────────────────────────────────────────────────────────────────────┐
│ DJI FLIGHTHUB 2 │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Flight Ops │ │ Mission │ │ Media │ │
│ │ Control │ │ Planning │ │ Storage │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────────────────────┘
AI Inference Pipeline
The vision AI ensemble processes drone imagery through a multi-stage pipeline:
Multi-Sensor Correlation Engine
Signals from multiple sensors are correlated to increase detection confidence:
Technology Stack
| Layer | Component | Technology |
|---|---|---|
| Inference | Model Serving | NVIDIA Triton Inference Server |
| Vision AI | Object Detection | GroundingDINO |
| Vision AI | Segmentation | SAM2 |
| Vision AI | OCR | AWS Rekognition |
| Geospatial | Digital Twin | PostGIS |
| Time Series | Telemetry | InfluxDB |
| Storage | Media | S3-compatible object store |
| Messaging | Events | RabbitMQ / Kafka |
| API | Gateway | FastAPI / Kong |
Design Principles
1. Multi-Sensor Intelligence
The platform correlates signals across sensor modalities:
- Single sensor detection provides baseline capability
- Correlation across 2+ sensors increases confidence
- Geospatial context links detections to assets
- Historical comparison identifies anomalies
2. Human-in-Loop
AI provides recommendations, humans make decisions:
- Confidence scores on all detections
- Operator validation workflow
- Feedback loop for model improvement
- Override capability for edge cases
3. Phased Accuracy
Models improve through operational feedback:
- Phase 1: Baseline data collection
- Phase 2: Initial heuristics with validation
- Phase 3: Correlation refinement
- Phase 4: Production accuracy targets
4. Graceful Degradation
System operates with partial data:
- Individual sensor failures don't block detection
- Reduced confidence without correlation
- Automatic fallback to available sensors
- Manual override capabilities
Security Architecture
| Layer | Protection |
|---|---|
| Network | VPC isolation, security groups |
| Data Transit | TLS 1.2+ encryption |
| Data at Rest | AES-256 encryption |
| Access | RBAC, OAuth 2.0 |
| Audit | Complete activity logging |
Deployment Options
| Option | Description | Use Case |
|---|---|---|
| Cloud | AWS/Azure hosted | Primary deployment |
| Hybrid | Cloud + edge processing | Low-latency requirements |
| On-Premise | Customer data center | Data sovereignty |