How AVQS Works
A 4-phase autonomous visual quality system
The 4 Phases
1
PERCEPTION (Weeks 1-8)
What: YOLO-based defect detection on your production line
- Train on your factory's specific defects
- Deploy to edge devices (Jetson, RPi)
- Real-time detection (<50ms latency)
- 99.2% accuracy on validation set
Deliverable: Working prototype detecting defects in real-time
2
COGNITION (Weeks 9-14)
What: AI agents that reason about defects and decide actions
- AI agents analyze defect type and severity
- N8N workflows automate decisions
- LLM-based reasoning (Claude/GPT)
- Sensor fusion (camera + IoT data)
Deliverable: Intelligent agent that reasons about defects
3
IOT LAYER (Weeks 15-20)
What: Unified data pipeline connecting all systems
- MQTT broker for sensor data
- Edge gateway integration
- Real-time data aggregation
- Factory network topology
Deliverable: Reliable sensor fusion pipeline
4
ACTION (Weeks 21-26)
What: Automated response to defects
- PLC/SCADA integration (Modbus, OPC-UA)
- Automated triggers (reject, stop, alert)
- Quality report generation
- Maintenance ticket creation
Deliverable: Full autonomous loop
Technology Stack
Computer Vision
YOLOv8, PyTorch, TensorRT, ONNX for edge deployment
AI Agents
Claude API, OpenAI, LangChain for intelligent reasoning
Automation
N8N workflows, MQTT, Kafka for real-time processing
Integration
Modbus, OPC-UA, PLC/SCADA for factory systems