An OT data lake, provides IIoT, OT, MES, and ERP data in dynamic context to intelligence applications in eXponenceTM. For expert users and data scientists, illuminator provides a fully integrated contextual data pipe to build AI applications with tools and libraries of their choice.
Qnnect is a complete, distributed edge and fog, hardware agnostic, software system for IIoT.
Edge Gateways (Qlite) connect to sensor networks, PLC’s, and other edge devices using legacy and modern protocols. Fog nodes (QPro) connect to multiple QLites to create a scalable, layered architecture aligned at each ISA95 level. QRelays may be used between levels to comply with ISA99/IEC62443 zones. Endpoint security and data encryption provide an additional layer of security. Distributed storage and compute allow execution of machine learning on Fog and Edge nodes.
Qlite can be deployed on Edge appliances from Advantech, Dell, HPE and stratus. QPro can be deployed on appliances from Dell, HPE, Stratus or your Virtual Machines. Complete pre-configured appliances are also available from Quartic.ai
IlluminatorTM ingests data streams from multiple sources and protocols for a common reference.
This low-latency, high availability publish-subscribe data pipe provides access to real-time abstracted to build AI applications with eXponenceTM and serves as an OT data Lake.
Advanced users and data scientists can connect with illuminatorTM, for contextual abstract data types to use machine learning tools and libraries of their choice and eliminate data integration needs to speed up deployment. Connectivity with IlluminatorTM is possible using Kafka Pub-Sub, Illuminator API or SDK.
For a single process unit, site or the enterprise, AssetHarborTM provides continuous extraction of context from multiple data streams.
Process operation, both batch and continuous are abstracted in the context of an asset. The IlluminatorTM data pipe then allows publish-subscribe access to the attributes of asset objects for building smart applications. Intelligence and insights created using MetaTrainerTM, Reckon or external applications is added to the asset objects using extensible attributes. The reference data models can be custom, asset-oriented standards such as ISO14224 or manufacturing oriented such as ISA95.