ISO/IEC

This document describes best practices for use case projects in terms of characterization, template, plan and maintenance. It is intended to developers of use case projects, including in the context of standardisation. The document can be used to complement existing methodology standards such as IEC 62559 or IEC Guide 125.

This document specifies an Internet of Things (IoT) reference architecture (IoT RA). The IoT RA is a generalization of existing practice including the distinguishing characteristics of IoT systems and other 195 fundamental characteristics exhibited by IoT systems. The IoT RA addresses stakeholder concerns related to 196 the business value of IoT systems. The IoT RA also addresses the interactions between the IoT system, the 197 users, and the physical environment. Implementation of IoT systems is also addressed in this IoT RA. Among 198 the characteristics specified in the IoT RA are abstract functions within IoT systems and a variety of structures 199 that are used to construct IoT systems.

This document defines a set of processes and associated terminology for describing the life cycle of AI systems. This document forms the foundation of a detailed AI system life cycle specification. It is based on ISO/IEC/IEEE 15288 and ISO/IEC/IEEE 12207 with substitutes for and additions of AI specific processes, whose foundation is based on ISO/IEC 22989 and ISO/IEC 23053. Selected sets of these processes can be applied throughout the life cycle for managing and performing the stages of an AI system's life cycle. This document provides processes that support the definition, control and improvement of the AI system life cycle processes used within an organization or a project. Organizations and projects can use these processes when developing or acquiring AI systems. When an element of an AI system is traditional software or a traditional system, the software life cycle processes in ISO/IEC/IEEE 12207 and the system life cycle processes in ISO/IEC/IEEE 15288 may be used to implement that element.

This document defines a reference architecture of Knowledge Engineering (KE) in Artificial Intelligence (AI). The reference architecture describes KE roles, activities, constructional layers, components and their relationships among themselves and other systems from systemic user and functional views. This document also provides a common KE vocabulary by defining KE terms.

This document provides guidance for members of the governing body of an organization to enable and govern the use of Artificial Intelligence (AI), in order to ensure its effective, efficient and acceptable use within the organization. This document also provides guidance to a wider community, including: executive managers; external businesses or technical specialists, such as legal or accounting specialists, retail or industrial associations, or professional bodies; public authorities and policymakers; internal and external service providers (including consultants); assessors and auditors. This document is applicable to the governance of current and future uses of AI as well as the implications of such use for the organization itself. This document is applicable to any organization, including public and private companies, government entities and not-for-profit organizations. This document is applicable to an organization of any size irrespective of their dependence on data or information technologies.

This document provides guidance on how organizations that develop, produce, deploy or use products, systems and services that utilize artificial intelligence (AI) can manage risk specifically related to AI. The guidance also aims to assist organizations to integrate risk management into their AI-related activities and functions. It moreover describes processes for the effective implementation and integration of AI risk management. The application of this guidance can be customized to any organization and its context.

The human information data model for VR-based smart cities is defined to represent human-related information in 3D virtual environments. It defines concepts, a data model, and how to integrate 3D virtual worlds and information related to sensors that people carry with them. It defines an exchangeable information data model necessary for transferring and storing human information in 3D virtual smart cities. This document will specify:

- Representation of human information in a 3D virtual smart city.

- Representation of human information with sensors in a 3D virtual smart city.

- Representation of human semantic and physiological information for a 3D virtual smart city.

- Definition of an interchangeable data model for human information for a VR smart city.

This document provides a collection of representative use cases of DT applications in a variety of domains.

This document specifies a general Digital Twin Reference Architecture in terms of defining system characteristics, a Reference Model and architecture views for Digital Twins.

This document provides a generic digital twin maturity model, definition of assessment indicators, and guidance for a maturity assessment.

This document establishes terminology for Digital Twin (DT) and describes concepts in the field of Digital Twin, including the terms and definitions of Digital Twin, concepts of Digital Twin (e.g., Digital Twin ecosystem, lifecycle process for Digital Twin, and classifications of Digital Twin), Functional view of Digital Twin and Digital Twin stakeholders. This document can be used in the development of other standards and in support of communications among diverse, interested parties/stakeholders. This document is applicable to all types of organizations (e.g., commercial enterprises, government agencies, not-for-profit organizations).

Defines:

- common formats,

- values, and

- coding for Internet of things (IoT).