This standard specifies the collaboration protocols of enabling machine learning on the edge computing node with support from industrial clouds. This standard provides implementation reference of machine learning upon lower powered, cheaper, embedded devices, a specific hardware-based method of accepting the introduced machine learning models and then online optimization, i.e. comparing the models with incoming live data.
- Sponsor Committee
- IES/IES - Industrial Electronics Society Standards Committee
Learn More About IES/IES - Industrial Electronics Society Standards Committee - Status
- Active PAR
- PAR Approval
- 2019-02-08
Working Group Details
- Society
- IEEE Industrial Electronics Society
- Sponsor Committee
- IES/IES - Industrial Electronics Society Standards Committee
Learn More About IES/IES - Industrial Electronics Society Standards Committee - Working Group
-
ECN - Edge Computing Node
- IEEE Program Manager
- Vanessa Lalitte
Contact Vanessa Lalitte - Working Group Chair
- Wenbin Dai
Other Activities From This Working Group
Current projects that have been authorized by the IEEE SA Standards Board to develop a standard.
P2805.1
Self-Management Protocols for Edge Computing Node
This standard specifies the self-management protocols for edge computing node. These requirements include management protocols of Self-organization, self-configuration, self-recovery and self-discovery between multiple edge computing nodes. The autonomic management features for edge computing node shall cover discovery, node identification, negotiation, transport, messaging and security mechanisms.
P2805.2
Data acquisition, Filtering and buffering Protocols for Edge Computing Node
This standard specifies the protocols used by the edge computing node of buffering, filtering and pre-processing data collected from controllers including programmable logic controllers, computer numerical controllers (CNC) and industrial robots. The data acquisition from field devices with different interfaces must be automatically stored, filtered and calculated according to reconfigurable rules (including buffering data from selected time frame, convert data format and filter invalid data) from industrial clouds and other edge computing nodes.
P2805.5
Recommended Practice for Low-Code Development in Industrial Edge Computing
This recommended practice specifies the low-code and no-code development method during the design and development process of industrial edge computing. These methods include both model-driven engineering and data-driven approaches for developing industrial edge applications. In addition, automatic code generation for operation technologies and information technologies converged industrial edge applications are specified. Use cases from discrete manufacturing, batch control, and process control are provided.
P2805.6
Recommended Practice for Cloud-Edge Collaborative Industrial Automation System Architecture
This recommended practice specifies a reference architecture of the next-generation cloud-edge collaborative industrial automation systems. This practice includes definitions of cloud, edge, and network devices used in the next-generation industrial automation systems. In addition, the practice includes definitions and general requirements of cloud-based and virtualized controllers based on cloud-edge collaboration. Use cases from discrete manufacturing, batch control and process control are provided.
Standards approved by the IEEE SA Standards Board that are within the 10-year lifecycle.
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These standards have been replaced with a revised version of the standard, or by a compilation of the original active standard and all its existing amendments, corrigenda, and errata.
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