This Recommendation specifies a functional framework for network service provisioning based on artificial intelligence (AI) in future networks, including international…
Interoperability
ITU-T Y.3174
Framework for data handling to enable machine learning in future networks including IMT-2020
This Recommendation provides a framework for data handling to enable machine learning (ML) in future networks including International Mobile Telecommunications…
ITU-T F.746.5
Framework for a language learning system based on speech and natural language processing (NLP) technology
This Recommendation presents an overview of the framework for a language learning system based on speech and natural language processing…
ITU-T F.749.13
Framework and requirements for civilian unmanned aerial vehicle flight control using artificial intelligence
This Recommendation provides a framework of civilian unmanned aerial vehicle flight control using artificial intelligence (AI), including the flight navigation…
ETSI GR ENI 012 V 1.1.1
Experiential Networked Intelligence (ENI) – Reactive In-situ Flow Information Telemetry
The present document will describe the motivation, requirements, and challenges of using flow-oriented on-path telemetry techniques which provides relevant measurement…
ETSI GS ENI 005 V 1.1.1
Experiential Networked Intelligence (ENI) – System Architecture
The purpose of this work item is to draft a GS to define the software functional architecture of ENI. This…
ETSI GR ENI 001 V 1.1.1
Experiential Networked Intelligence (ENI) – ENI use cases
The WI will identify and describe use cases and scenarios that are enabled with enhanced experience, through the use of…
ETSI GR ENI 007 V 1.1.1
Experiential Networked Intelligence (ENI) – ENI Definition of Categories for AI Application to Networks
This Work Item will address the aspects of gradual implementation of networked intelligence and specify a categorization framework for systems…
ETSI GR ENI 008 V 2.1.1
Experiential Networked Intelligence (ENI) – InTent Aware Network Autonomicity (ITANA)
This document will discuss various design options, in terms of a set of new stand-alone and/or nested Functional Blocks, for…
ISO/TS 8000-82:2022
PD ISO/TS 8000-82:2022
Data quality – Data quality assessment: Creating data rules
This document describes how data rules apply to various types of data. Such rules exist to sustain the integrity and…
ITU-T L.1305
Data centre infrastructure management system based on big data and artificial intelligence technology
This Recommendation describes specifications of a data centre infrastructure management (DCIM) system based on big data and artificial intelligence (AI)…
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
