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TechnicalIot Data Integration Patterns
IoT Data Integration Patterns for Industrial Digital Twins
Technical guide to integrating IoT data with digital twin platforms. Covers BACnet, Modbus, OPC-UA, MQTT protocols and best practices for real-time data mapping.
Industrial IoT Protocol Landscape
| Protocol | Use Case | Data Type | Typical Latency |
|---|---|---|---|
| BACnet | Building automation | Points, schedules | 1-5s |
| Modbus | Industrial sensors | Registers | 100ms-1s |
| OPC-UA | Manufacturing | Complex objects | 10-100ms |
| MQTT | Edge IoT | Messages | 10-50ms |
| REST API | Enterprise systems | JSON/XML | 100ms-5s |
Data Mapping Architecture
The key challenge is mapping heterogeneous IoT data to 3D model elements:
- Device Registry — Catalog all sensors and their metadata
- Semantic Mapping — Link sensor IDs to 3D model element IDs
- Transformation — Unit conversion, aggregation, derived metrics
- Binding — Real-time data overlay on digital twin objects
- Alerting — Threshold-based and AI anomaly detection
DataMesh FactVerse's Data Fusion Service (DFS) provides a configuration-driven approach where data mappings are defined via CSV templates, eliminating the need for custom integration code.