This PAS gives recommendations for managing security risks that might lead to a compromise of safety in a connected automotive ecosystem. The PAS covers…
Interoperability
ETSI TR 103748 V 1.1.1
Core Network and Interoperability Testing (INT) – Artificial Intelligence (AI) in Test Systems and Testing of AI Models – Use and Benefits of AI Technologies in Testing
The present document provides guidance on the use of AI technologies applied to testing. © Copyright 2023, ETSI
ISO/IEC 19944-1:2020
BS ISO/IEC 19944-1:2020
Cloud computing and distributed platforms. Data flow, data categories and data use. Fundamentals
What is ISO/IEC 19944‑1 about? ISO/IEC 19944‑1 is the first part of the multi-series standard that extends the existing cloud…
ITU-T L Supplement 52
Computer processing, data management and energy perspective
This standard specifies the collaboration protocols of enabling machine learning on the edge computing node with support from industrial clouds.…
This Recommendation provides system context, functional requirements and use cases for machine learning as a service (MLaaS). In particular, the…
ISO 23257:2022
BS ISO 23257:2022
Blockchain and distributed ledger technologies. Reference architecture
What is ISO 23257 – Architecture for Distributed Ledger Technology about? ISO 23257 discusses blockchain and distributed ledger technologies. Ledger…
Recommendation ITU-T Y.3654 specifies the mechanisms of machine learning in big data driven networking (bDDN). A set of related aspects…
This document specifies a framework for verifying and validating the interoperability of manufacturing capability units (MCUs) having a set of…
IEC 62243:2012 * IEEE Std 1232-2010
Artificial intelligence exchange and service tie to all test environments (AI-ESTATE)
Data interchange and standard software services for test and diagnostic environments are defined by Artificial Intelligence Exchange and Service Tie…
ITU-T Y.3179
Architectural framework for machine learning model serving in future networks including IMT-2020
This Recommendation provides an architectural framework for machine learning (ML) models serving in future networks including IMT-2020, i.e., preparing and…
This Recommendation describes the architecture, functional entities, and interfaces for a spontaneous dialogue processing system for language learning. © ITU…
