Digital Twin Smart City Platform for Enterprise: GeoAI & Predictive Maintenance AI IoT in Asset Tracking
Introduction: The Challenge of Siloed Geospatial Data
Enterprise asset data was siloed across disparate tracking systems, preventing staff from accessing a single source of truth for critical tasks like SLA verification, billing, and utilization reporting. Manual reconciliation led to disputes and inefficiency. This demanded an end-to-end smart infrastructure solution built on geospatial engineering services to unify and automate asset intelligence.
Solution Overview: GeoAI and AI GIS Analytics
EurthTech developed an end-to-end tracking platform that normalizes multi-tech telemetry (BLE, Wi-Fi, UWB, GNSS) into a unified asset-event model. The core function is the GeoAI engine, which runs continuous geofencing, dwell analytics, and chain-of-custody logs. This system leverages AI GIS analytics to create and process derived events (e.g., "delayed handoff"), resolving data disputes and integrating seamlessly with ERP/WMS via secure webhooks for automated workflows.
Technical Implementation: Edge AI and Embedded AI India
The platform uses a high-volume ingestion layer (Kafka), a stream processor (Flink) for real-time event derivation, and a time-series DB (TimescaleDB) for history. This system, architected with the input of our Embedded AI India team, includes a rules UI where operations can author geofence polygons and event rules. Cross-checks allow merging of multiple telemetry sources using confidence-weighted logic, acting as an advanced Edge AI embedded system in the cloud. We delivered ERP connectors and a white-label portal used by operations teams.
Results & Impact: Automation and Digital Twin Smart City
By automating SLA billing and verification, the platform reduced disputes by 84% and significantly improved invoice timeliness. Asset utilization dashboards and anomaly detection drove efficiency. This unified, real-time asset platform acts as a foundational component for a Digital twin smart city or campus, providing the granular, reliable data necessary for total asset visibility and effective Predictive maintenance AI IoT.
Operational Success & Partnership: Key success factors included data lineage and customer-specific partitioning for scaling. The platform's ability to automate billing and replenishment confirmed our value as a strategic GIS consulting company. We provided integration adapters for major systems like SAP/Oracle, confirming a robust smart city solutions provider approach to enterprise integration and workflow automation.