ISO/IEC

ISO/IEC 30163:2021 specifies the system requirements of an Internet of Things (IoT)/Sensor Network (SN) technology-based platform for chattel asset monitoring supporting financial services, including: - System infrastructure that describes functional components; - System and functional requirements during the entire chattel asset management process, including chattel assets in transition, in/out of warehouse, storage, mortgage, etc.; - Performance requirements and performance specifications of each functional component; - Interface definition of the integrated platform system. This document is applicable to the design and development of IoT/SN system for chattel asset monitoring supporting financial services.

ISO/IEC 23053:2022 This document establishes an Artificial Intelligence (AI) and Machine Learning (ML) framework for describing a generic AI system using ML technology. The framework describes the system components and their functions in the AI ecosystem. This document is applicable to all types and sizes of organizations, including public and private companies, government entities, and not-for-profit organizations, that are implementing or using AI systems.

ISO 20140-5:2017 specifies the types of environmental performance evaluation (EPE) data, including their attributes, which can be used for evaluating the environmental performance of manufacturing systems based on the general principles described in ISO 20140_1. It also provides recommendations for mapping the EPE data on to information models specified by IEC 62264. ISO 20140-5:2017 applies to discrete, batch and continuous manufacturing. ISO 20140-5:2017 is applicable to entire manufacturing facilities and to parts of a manufacturing facility. ISO 20140-5:2017 specifically excludes from its scope the syntax of the data and information models, the protocols to exchange data models, the functions that can be enabled by data models, and the activities in Level 1 and Level 2. The scope of ISO 20140-5:2017 also includes indicating the differences among various data and information models and the differences among various representations of environmental performance by actual data. ISO 20140-5:2017 refers to the semantics of the structured data and information models used by communication protocols. The semantics explain the meaning of the attributes and of the context information. The following are outside the scope of ISO 20140-5:2017: a) product life cycle assessment; b) EPE data that are specific to a particular industry sector, manufacturer or machinery; c) acquisition of data; d) the activity of data communication.

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 provides a standardized generic Digital Twin maturity model, definition of assessment indicators, guidance for a maturity assessment, and other practical classifications of Digital Twin capabilities, etc.

Software quality: Quality assessment for AI-based systems (see also 4.1.1 and 4.3.1.4)

Assessment of AI systems: Metrics for the performance capability of AI

This document describes the framework of the big data reference architecture and the process for how a user of the document can apply it to their particular problem domain.

SO/IEC TR 20547-2:2018 provides examples of big data use cases with application domains and technical considerations derived from the contributed use cases.

ISO/IEC TR 20547-5:2018 describes big data relevant standards, both in existence and under development, along with priorities for future big data standards development based on gap analysis.