AI for Smart Infrastructure: UWB + BLE Hybrid Embedded Systems for Sub-Meter Precision RTLS
Introduction: The Challenge of Mixed-Precision Tracking
Modern facilities, such as manufacturing floors and hospitals, require varying degrees of asset tracking precision. Certain workflows need sub-meter accuracy (e.g., operating theatres), while the rest of the facility requires low-cost tags and long battery life. Single-technology solutions were either too expensive or too inaccurate, demanding a specialized smart infrastructure solution for IoT product engineering.
Solution Overview: Edge AI Embedded Systems for Hybrid Localization
EurthTech engineered a hybrid RTLS combining UWB for critical sub-meter positioning and BLE for coarse, long-battery tracking. Tags use a dual-mode AI-powered embedded system where UWB is activated only in high-importance areas, based on BLE region detection. This Edge AI embedded system approach keeps costs down while enabling high-precision tracking where needed, providing a robust backbone for smart lighting systems and general facility management.
Technical Implementation: GeoAI Fusion and Embedded Systems Development
The embedded systems development included tag firmware with adaptive UWB duty cycles based on motion, battery level, and policy. Server-side, our solution features a sophisticated Localization Fusion Engine. This engine is a core GeoAI component, ingesting UWB TDoA fixes, BLE fingerprint cells, and IMU dead-reckoning. We used a factor-graph optimizer to fuse asynchronous fix types and provide a best-estimate trajectory, ensuring AI GIS analytics are highly accurate. UWB anchors were installed with careful geometry and wired sync for the highest precision.
Results & Impact: AI Engineering and Smart City Solutions
In a 3-floor hospital pilot, the hybrid solution achieved a site-wide median error of around 0.9 m while preserving tag battery life of 6-12 months. Critical zone workflows saw equipment retrieval times drop by 68% and asset utilization increase by 15%, showcasing the tangible benefits of our AI engineering solutions. This successful deployment confirms EurthTech's expertise as a smart city solutions provider capable of delivering high-ROI geospatial engineering services that directly impact operational efficiency.
Deployment, Security & Future Scalability: The hybrid approach reduces the need for costly, ubiquitous UWB coverage. Deployment required a careful anchor plan and a policy engine to manage UWB duty. This architecture provides a key layer for a Digital twin smart city strategy, offering the granular data necessary for advanced simulation and Predictive maintenance AI IoT across vast municipal or campus assets.