OT to IT Integration with Industrial Edge and AWS

This solution combines Industrial Edge with AWS IoT SiteWise Edge and a set of AWS cloud services to deliver a scalable, secure, and vendor-independent path from field devices to enterprise decision making. On-premise edge components collect, normalize and pre-process OT data; SiteWise Edge builds asset models and local operations views; the cloud hosts digital twins, visualization, analytics, and ML to drive continuous improvement and predictive capabilities.

This architecture is built around an edge-first pattern that brings together Siemens Industrial Edge and AWS IoT SiteWise Edge to collect, harmonize and pre-process shop‑floor data before sending a consistent, analytics-ready stream to AWS for enterprise-scale processing. On the shop floor, Industrial Edge hosts vendor-agnostic connectors and local HMIs, enabling low-latency access to device signals and immediate operational views while preserving existing automation investments.

At the edge, AWS IoT SiteWise Edge performs time‑series ingestion and asset modelling close to the source. SiteWise Edge builds the same asset hierarchies and KPIs you’ll see in the cloud, executes local calculations and aggregations, and buffers data during connectivity interruptions so that key metrics remain available and only harmonized, compressed data is forwarded to the cloud.

Industrial Edge Management and the Industrial Edge Hub provide app orchestration, lifecycle management and observability for all edge components: connectors, SiteWise Edge, AI inference servers and local operator apps (e.g., WinCC Unified, LiveTwin). This layer simplifies deployments, model updates and monitoring of inference models, ensuring edge applications are consistent across devices and easy to maintain.

In the cloud, AWS IoT SiteWise (together with IoT TwinMaker, SiteWise Monitor, Managed Grafana, S3, Athena, QuickSight and SageMaker) hosts the enterprise digital twin, historical storage, visualization and analytics/ML pipelines. Harmonized asset and time‑series data from the edge enable cross-site KPIs, fleet comparisons and scalable model training, while the cloud tooling supports dashboards, ad‑hoc queries and long‑term retention.

Security and operations are enforced end‑to‑end: local certificates and secure channels protect edge-to-cloud transport, and AWS IAM/KMS plus centralized logging and monitoring govern access and observability in the cloud. Because key modelling and buffering occur on‑premises, the solution remains resilient to internet outages—operators keep local visibility and alarms while the cloud receives consistent, gap‑free data once connectivity is restored.