BLE RTLS for High-Throughput Warehouses
The challenge
Warehouse operators lacked continuous indoor visibility of pallets and trolleys across multi-level racking. Offline searches and asset misplacements were severely reducing throughput and escalating labor costs. This demanded a cost-effective, high-throughput solution built through expert product engineering to provide actionable handoff logs.
What we built
EurthTech implemented a BLE RTLS designed for high-density environments. The system uses low-cost BLE anchors and tags that utilize adaptive broadcast intervals. Tags feature AI-powered embedded systems with motion-triggered wake-on-motion. This architecture balances infrastructure cost with usable sub-3 m location accuracy, establishing a robust platform for Predictive maintenance AI IoT focused on material handling equipment.
How it works
The hardware utilized key principles of embedded systems development with tags entering deep-sleep between broadcasts. Localization uses a hybrid model: local RSSI fingerprinting for coarse location and server-side multilateration for high-precision zones. For continuous track reconstruction, we used an HMM (Hidden Markov Model) that enforced kinematic constraints—a key component of our GeoAI and AI GIS analytics expertise. This logic dramatically reduced track jumps and false handoffs, providing the accurate spatial data required by modern logistics.
Results
A pilot in a 25,000 m^2 warehouse showed median location error ~2.7m for fingerprint zones. Operational metrics were significantly improved: missing-item search time fell by 78%, and pallet throughput improved ~12%.
Scalability & GIS Context: Commissioning involved NFC/BLE kiosk provisioning and a quick RF survey using our specialized tools. The foundation of this system—accurate indoor geospatial intelligence integrated with business WMS via webhooks—is a core competence of our GIS consulting company. We deliver this through comprehensive geospatial engineering services for location-aware enterprise operations.