IEEE

This standard defines the types of occupations, competency requirements, and evaluation methods of blockchain and distributed ledger technology for service practitioners, including but not limited to competency elements, evaluated process, and employment grade. This standard applies to the ability evaluation and training of blockchain and distributed ledger technology service practitioners.

The standard establishes access control requirements for blockchain systems. The standard addresses the following access control attributes of the system, including but not limited to:a) Node permissions - the permissions of block generation, block synchronization, block verification and broadcasting, and sending transactions.b) Smart contract access permissions - interface access control, user access control, and hybrid access control.c) User permissions - registered user permissions and unregistered permissions. The concept of role is applied to differentiate the permissions of registered users, which means permissions vary according to the role of a user.d) Global permissions - user access to deploy smart contracts, and to read smart contracts.

This standard provides a framework for the implementation, and interaction utilizing Web 3.0 (Web3) in healthcare and life sciences involving privacy challenges. Web 3.0 represents the next iteration of the evolution of the web and is built upon the core concepts of decentralization, openness, and greater user utility. Digital Ledger Technology (DLT) tokens, smart contracts, transactions, assets, networks, off-chain data storage and access architectural patterns, and Web3 permissioned and permission-less DLT are included in the framework.

Augmented Reality (AR) promises to provide significant boosts in operational efficiency by making information available to employees needing task support in context in real time. To support according implementations of AR training systems,this document proposes an overarching integrated conceptual model that describes interactions between the physical world, the user, and digital information, the context for AR-assisted learning and other parameters of the environment. It defines two data models and their binding to XML and JSON for representing learning activities (also known as employee tasks and procedures) and the learning environment in which these tasks are performed (also known as the workplace). The interoperability specification and standard is presented in support of an open market where interchangeable component products provide alternatives to monolithic Augmented Reality-assisted learning systems. Moreover, it facilitates the creation of experience repositories and online marketplaces for Augmented Reality-enabled learning content. Specific attention was given to reuse and repurposing of existing learning content and catering to ‘mixed' experiences combining real world learner guidance with the consumption (or production) of traditional contents such as instructional video material or learning apps and widgets.

This guide will provide a framework that outlines technologies and the processes for planning the evolution of a smart city. Smart Cities and related solutions require technology standards and a cohesive process planning framework for the use of the internet of things to ensure interoperable, agile, and scalable solutions that are able to be implemented and maintained in a sustainable manner. This framework provides a methodology for municipalities and technology integrators to use as a tool to plan for innovative and technology solutions for smart cities.

This Standard describes a data model to support the interchange of agreed upon data elements and their values between a learning-related content object and a runtime service (RTS) used to support learning management. This Standard does not specify the means of communication between a content object and an RTS nor how any component of a learning environment shall behave in response to receiving data in the form specified. This Standard is based on a related data model defined in the "Computer Managed Instruction (CMI) Guidelines For Interoperability," version 3.4, defined by the Aviation Industry CBT Committee (AICC). To balance the need to support existing implementations with the need to make technical corrections and support emerging practice, this Standard selectively includes those data elements from the CMI specification that are commonly implemented; renames some data elements taken from the CMI specification to clarify their intended meaning; modifies the data types of data elements taken from the CMI specification to reflect ISO standard data types and internationalization requirements; removes some organizational structures used in the CMI specification to group data elements that are specific to the AICC community of practice and not generally applicable; and introduces some data elements not present in the CMI specification to correct known technical defects in data elements taken from that specification.

This standard extends IEEE Std 1872-2015, IEEE Standard for Ontologies for Robotics and Automation, to represent additional domain-specific concepts, definitions, and axioms commonly used in Autonomous Robotics (AuR). This standard is general and can be used in many ways--for example, to specify the domain knowledge needed to unambiguously describe the design patterns of AuR systems; to represent AuR system architectures in a unified way; or as a guideline to build autonomous systems consisting of robots operating in various environments.

Discusses Standards Roadmaps for Future Networks, including 5G/6G, as well as in the area of Autonomic/Autonomous Networking (ANs) Standards. The Emerging Industry Requirement for Standardization of a Blueprint for Common Operational Principles for Autonomic/Autonomous Networks (COPAAN) is presented in relation to the Autonomic/Autonomous Networking (ANs) paradigm. The connection of COPAAN and Robotics is illustrated.

The document describes Gaps in Standards for Autonomic/Autonomous Networking (ANs), including Self-Organizing Systems and Networks. The Emerging Industry Requirement for Standardization of a Blueprint for Common Operational Principles for Autonomic/Autonomous Networks (COPAAN) is presented in more detail in relation to the Autonomic/Autonomous Networking (ANs) paradigm. The Model of Interfaces of an AN that call for COPAAN Standard Development is presented. The connection of COPAAN and Robotics is illustrated. Systems Optimization, Traffic Variance, Control Variance, Service Variance, Confluence, Dependency, Complex Systems, Self-Organizing Networks, Self-X, Autonomics, Autonomic Management & Control (AMC), Emergence

This standard extends the IEEE 1873-2015™ Standard for Robot Map Data Representation from two-dimensional (2D) maps to three-dimensional (3D) maps.

This Guide for Verification of Autonomous Systems enables the user to define a customized process for verification of their autonomous system based on their available resources. It documents best practices across all levels of abstraction within a given system.

"Nudges" as exhibited by robotic, intelligent or autonomous systems are defined as overt or hidden suggestions or manipulations designed to influence the behavior or emotions of a user. This standard establishes a delineation of typical nudges (currently in use or that could be created). It contains concepts, functions and benefits necessary to establish and ensure ethically driven methodologies for the design of the robotic, intelligent and autonomous systems that incorporate them.