Standard

The present document provides an overview and an introduction to the interface specification for the reference points "AR 16 - World Anchors" and "AR 17 - Reference Objects" of the AR framework architecture, ETSI GS ARF 003 (V1.1.1): Augmented Reality Framework (ARF) AR framework architecture, developed by the ETSI Industry Specification Group (ISG) for an Augmented Reality Framework (ARF). The actual interface specification is provided as OpenAPI™ specification, ARF005 - World Storage API, revision 1.0.0, and forms the baseline for the present document.

The present document reviews the high level Reference Point requirements between the Scene Management and External Application Support functions as they are described in ETSI GS ARF 003 (V1.1.1): Augmented Reality Framework (ARF) AR framework architecture.

ISO 29481-2:2012 specifies a methodology and format for describing coordination between actors in a building construction project during all life cycle stages. It therefore specifies: a methodology that describes an interaction framework, an appropriate way to map responsibilities and interactions that provides a process context for information flow; a format in which the interaction framework should be specified. ISO 29481-2:2012 is intended to facilitate interoperability between software applications used in the construction process, to promote digital collaboration between actors in the building construction process, and to provide a basis for accurate, reliable, repeatable, and high-quality information exchange.

This document presents considerations for using VR content in the learning, education and training (LET) domain for reducing reality and virtual reality crossover confusion among users and assisting users to effectively use these emerging technologies. This document addresses VR content that uses a head-mounted display (HMD) in the LET domain. It does not address VR content using immersive technology and does not address augmented reality, mixed or merged reality content.

This recommended practice produces best practices for meeting the requirements of IEEE P7004: Standard for Child and Student Data Governance, when designing, provisioning, configuring, operating, and maintaining an online virtual classroom experience for synchronous online learning, education, and training. The recommended practice includes language that can be referenced in requests for proposals (RFPs) for online (also known as virtual) classroom solutions, the operational runbook(s) for such solutions, and the assessment and certification guideline(s) for compliance process of such solutions.

The standard defines specific terminology utilized in artificial intelligence and machine learning (AI/ML). The standard provides clear definition for relevant terms in AI/ML. Furthermore, the standard defines requirements for data formats.

This standard establishes a uniform set of definitions and a process model for the procurement of Artificial Intelligence (AI) and Automated Decision Systems (ADS) by which government entities can address socio-technical and responsible innovation considerations to serve the public interest. The process requirements include a framing of procurement from an IEEE Ethically Aligned Design (EAD) foundation and a participatory approach that redefines traditional stages of procurement as: problem definition, planning, solicitation, critical evaluation of technology solutions (e.g. Impact assessments), and contract execution. The scope of the standard not only addresses the procurement of AI in general, but also government in-house development and hybrid public-private development of AI and ADS as an extension of internal government procurement practices.

This standard defines mandatory and optional requirements and constraints that need to be satisfied for an AI method, algorithm, application or system to be recognized as explainable. Both partially explainable and fully or strongly explainable methods, algorithms and systems are defined. XML Schema are also defined.

This standard defines attributes related to industrial Artificial Intelligence (AI) data that facilitates the classification, association, and mapping towards value creation using data. The attributes include but are not limited to data source, type, ownership, sampling frequency, traceability, privacy attributes for modeling, sampling, shareability and its use in AI algorithms.

A set of operator interfaces frequently used in artificial intelligence (AI) applications is defined in this standard, where the AI operators refer to the standard building blocks and primitives for performing basic AI operations. The functionality and the specific input and output operands of an AI operator are discussed, as well as both generality and efficiency. Various types of operators, such as those related to basic mathematics, neural network, and machine learning, are highlighted.

This guide provides a technological framework that facilitates the increase of trustworthiness of AI (Artificial Intelligence) systems, by using explainable artificial intelligence (XAI) technologies and methods including the following aspects:

1) the requirements of providing XAI systems in different application scenarios;

2) the categorization of a series of XAI tools that offer human-understandable explanations; and

3) a set of measurable solutions to evaluate XAI systems in terms of performances concerning the accuracy, privacy, and security.

This standard describes a Hyperspace Transaction Protocol (HSTP) that enables interoperable, semantically compatible connections between connected hardware (e.g. autonomous drones, sensors, smart devices, robots) and software (e.g. services, platforms, applications, artificial intelligence systems) and includes specifications for:

1) a spatial range query format and response language for requesting data about objects within a dimensional range (spatial, temperature, pressure, motion) and their content.

2) a semantic data ontology schema for describing objects, relations, and actions in a standardized way

3) a verifiable credentialing and certification method for permissioning create, retrieve, update, and delete (CRUD) access to devices, locations, users, and data; and

4) a human and machine-readable contracting language that enables the expression and automated execution of legal, financial and physical activities.