[802-LMSC] FWD: IEEE Computer Society Standards Newsletter
Dear 802
Please find attached the IEEE Computer Society Standards Activities Newsletter.
WG and TAG Chairs, please forward to your groups.
Thanks.
--
James Gilb
IEEE 802 LMSC Chair
AK6AI, Amateur Extra
Date: Feb 27, 2026, 11:39 AM
From: bkirk@xxxxxxxxxxxx
To: sab@xxxxxxxxxxxx
Subject: IEEE Computer Society Standards Newsletter
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> IEEE Computer Society Standards
> <https://www.computer.org/?source=email>
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> The IEEE Computer Society Standards Activity Newsletter
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> Issue 1 – February 2026
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> Welcome to the first IEEE Computer Society Standards Activity newsletter. I’ve found that during the many years I’ve worked in standards, that I was unaware of (a) the Computer Society, (b) that different Standards Committees existed, and (c) what other standards were out there being worked on. It was very word-of-mouth, and as a result it was difficult to get new people involved outside of a narrow pool of interest.
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> However, many of the standards being worked on would benefit from the expertise which already exists within our Society. So, I want to address this with this newsletter. This newsletter will cover all of the Project Authorization Requests which have just been approved (so will be looking for willing volunteers), and the standards which have just passed final approval. Please can all Standards Committee Chairs/Vice-Chairs cascade this to the membership, so that we can improve the communication and awareness across our different working groups. If there is anything that is of interest, then please either contact the WG leads, the standards committee chairs or myself, so that we can put you in contact as needed.
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> Thank you for all of your efforts in developing new standards – together we can be even more successful.
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> Darren Galpin
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> 2026 SAB VP for Standards Activities
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> New PARS
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> Artificial Intelligence Standards Committee
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> P3933
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> Standard for Capability Requirements of Artificial Intelligence Agents for Materials Research
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> This standard specifies a capability framework for artificial intelligence (AI) agents that are designed for materials research workflows. The framework comprises three domains> ：
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> (1) Fundamental capabilities help to ensure the basic operational competence required for materials-related research activities. These capabilities address data management, task management, and human–agent interaction.
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> (2) Scientific research capabilities address essential computational, analytical, and experimental functions of materials science. These capabilities cover tasks such as materials simulation, property characterization, and experimental–computational integration. AI agents are required to explicitly state their applicability domain and data constraints. This supports transparency and controllability in materials research scenarios.
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> (3) Service capabilities support the deployment and effective use of AI agents and enable collaboration with human experts. These capabilities address deployment, compatibility with relevant software environments, data formats, and deployment infrastructures, as well as monitoring of engineering maturity and operational reliability in practical applications.
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> The standard also specifies agent competencies related to interoperability with external tools, data sources, and computational platforms used in materials research workflows, as well as algorithmic integration, advanced perception, and effective collaboration with human experts. Requirements for underlying model training strategies, data scale, or feature representation methods are beyond the scope of this standard.
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> P7804
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> Recommended Practice for Integrated Agentic Food Waste Management Process In Schools
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> This recommended practice outlines procedures for applying agentic Artificial Intelligence (AI) tools and integrated logistics to help schools and their communities reduce food waste across the supply chain.
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> The purpose of this recommended practice is to extend and formalize the demonstrated effectiveness of school-based initiatives that reduce food waste by
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> 1) helping students avoid ordering food they will not consume
> 2) supporting the redistribution of uneaten meals to children, classmates, or other community members who need them.
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> By specifying the use of an integrated set of artificial intelligence (AI) agents, including Generative Artificial Intelligence (GenAI) systems and other AI technologies, this practice seeks to improve and streamline supply chain and logistics operations, thereby reducing resource use and operational inefficiencies. In settings where greenhouse gas (GHG) emissions are already being reduced through existing programs that do not use these technologies, the integration of AI systems as described in this standard enables significant additional reductions in both GHG emissions and food waste at scale, particularly when the practice is adopted across multiple schools and school districts.
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> P3952
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> Standard for Technical Requirements for Large-Scale Models in International Logistics Supply Chain
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> This standard specifies a technical framework for the application of large-scale models in the international logistics supply chain. It covers related data, models, and application services as well as interaction and collaboration layers. For these models, the standard defines business processes and functional, performance, security, and trustworthiness requirements as well as corresponding testing methods.
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> The standard applies to the design, development, deployment, application, operation, and management of these models. The standard provides guidance to related enterprises, technical service providers, and organizations within the international logistics supply chain.
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> P3942
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> Standard for Smart Power Data Query Model and System
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> This standard specifies the overall architecture, functional requirements, performance indicators, interface specifications, security requirements and testing evaluation for intelligent systems querying power consumption and generation data.
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> Software & Systems Engineering Standards Committee
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> P24773-1
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> Software and Systems Engineering — Certification of Software and Systems Engineering Professionals — Part 1: General Requirements
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> The standard specifies requirements for certification schemes and certification bodies in systems and software engineering.
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> Smart Manufacturing Standards Committee
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> P3927
> Standard for Embodied Intelligence Capability Requirements and Assessment Methodology in Industry
> This standard specifies capability requirements and an assessment methodology for embodied intelligence systems in industrial environments, defining an architecture-aligned capability framework, associated maturity levels, and a mapping to application performance metrics. It also standardizes assessment content and processes, and establishes assessment maturity levels to enable comparable, auditable evaluations.
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> P3929
> Standard for Multimodal Data Monitoring System of Auxiliary Equipment on Offshore Engineering Platforms
> This standard specifies a system architecture and technical requirements for data acquisition, processing, fusion, services, applications, and security protection in a multimodal data monitoring system used by auxiliary engineering equipment on offshore platforms.
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> P3930
> Standard for the Construction of Digital Energy and Carbon Management System in Industrial Enterprises
> This standard specifies construction principles, a system architecture, functional requirements, and general security requirements of digital energy and carbon management systems that are used in industrial enterprises. It standardizes the design, development, and construction of digital energy and carbon management system in the manufacturing sector and other industrial fields.
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> P3927.1
> Standard for Acquisition and Processing of Training Data for Embodied-Intelligence Robots
> This standard specifies a framework, requirements, procedures, and acceptance criteria that govern the acquisition, processing, management, and exchange of training data for embodied intelligence robots across various industrial environments. The standard helps ensure cross-vendor interoperability and provides principles for assessment.
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> P3945
> Standard for a System Architecture of Industrial Intelligent Agents
> This standard specifies an architecture for industrial intelligent agent systems. The standard maps IEC 62264 compliant devices and systems to interoperable intelligent agents. The standard also addresses end–edge–cloud resources, defines generic agent models, role categories, and interaction as well as data-flow patterns for scalable, secure, and reliable multi-agent operation in industrial environments.
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> P3945.1
> Standard for Agent-to-Agent Interoperability in Industrial Intelligent Agent Systems
> This standard specifies a profile that enables interoperability between industrial agents. The standard defines baseline requirements for cross-vendor message exchange, capability advertisement and discovery, coordination patterns, and extensibility mechanisms. The specification of interoperability levels and conformance testing supports Agent-to-Agent (A2A) and multi-agent collaboration across devices deployed within a factory as well as services operated at the network's edge and within a cloud.
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> P3945.2
> Standard for Agent-to-Tool and Data Access Interfaces in Industrial Intelligent Agent Systems
> This standard specifies a reference interface model for agent-to-tool and data access in industrial intelligent agent systems. The standard defines architectural principles, interface categories, and extension mechanisms that enable secure, interoperable, and auditable interaction between individual agents and external resources, tools, and control systems, while remaining implementation-neutral and adaptable to future industrial applications.
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> P3960
> Standard for System Architecture for Embodied Intelligence Operating Systems in Industry
> This standard specifies a system architecture for embodied intelligence operating systems that are deployed in industrial environments. The architecture addresses modules, interfaces, and system security.
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> P3972
> Guide for Intelligent Electric Power Material Warehouses
> This guide describes the main components and characteristics of intelligent warehouses for electric power materials. It introduces core functions, including automated execution, precision control, analytics and decision support, status perception, and security assurance. The guide also covers key development processes, including demand identification and establishment, preparation for identified functions, planning and design, and implementation and deployment.
> The purpose of this guide is to establish general requirements for industrial intelligent warehouses, classify and standardize their core capabilities, and guide the industry in leveraging automation and digital technologies to enhance the safety of warehouse operations, the transparency of material data, and overall management efficiency.
> P3973
> Guide for Functional Requirements of Digital-Twin-Enabled Modular Data Centers
> This guide specifies the functional requirements for digital-twin-enabled modular data centers, including establishing a unified system architecture and core functional specifications for such data centers; covering the entire life cycle of design, deployment, operation, and maintenance; and focusing on key capabilities such as operational safety, energy efficiency, reliability, resource utilization, and maintenance convenience.
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> P3975
> Standard for Federated Machine Learning Systems for Trusted Joint Data Analytics in Industrial Internet of Things—Part 1: Reference Architecture
> This standard specifies a reference architecture for federated machine learning (FML) systems for trusted joint data analytics in Industrial Internet of Things (IIoT), in which multiple industrial entities collaboratively train machine learning models without exchanging raw data. It defines the core functional roles in the reference architecture, including local participant, intermediate service provider, central coordinator, and management service provider, and clarifies the responsibilities of each role.
> The standard bridges the gap between general Federated Machine Learning (FML) frameworks and practical Industrial Internet of Things (IIoT) deployments by improving architectural applicability to industrial trusted joint data analytics through explicit consideration of key IIoT challenges, such as device heterogeneity and the lack of lifecycle management and auditability.
> P3955
> Standard for Capability Maturity Assessment Model of Industrial Data Management for Artificial Intelligence Applications
> This standard specifies a capability maturity assessment model for data management in industrial organizations. This standard applies to evaluating maturity level of data acquisition, preprocessing, governance, and semantic integrity, and to the supporting data infrastructure needed to train, validate, deploy, and operate artificial-intelligence (AI) systems and AI-enabled industrial systems in industrial environments.
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> P3961
> Standard for Swarm Intelligence System Architecture and Communication Requirements
> This standard specifies an architecture for swarm‑intelligence systems. It establishes communication requirements, including typical scenarios, capability requirements, and security.
> The purpose of this standard is to respond to the
> demand for collaborative evolution in smart manufacturing groups, addressing issues such as lack of technical specifications, insufficient system compatibility, inefficient communication, and weak security by constructing a unified technical system.At the technical level, it clarifies the reference architecture of the system, the functions of its components, as well as the requirements for communication interfaces, protocols, security, and performance, thereby solving problems like difficult compatibility and integration of heterogeneous systems, and data transmission risks.At the industrial level, it aims to lower the threshold for enterprises' smart transformation, reduce redundant R&D investment, promote the integration of cutting-edge technologies with manufacturing, and accelerate the large-scale application of swarm intelligence technology.
> P3968
> Standard for Capability Maturity Evaluation of Smart Manufacturing
> This standard specifies evaluation models for smart manufacturing capability maturity and gradient cultivation of smart factories. It defines the relevant evaluation elements and criteria, including foundational capability, and performance requirements applicable to smart manufacturing systems and smart factories.
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> Data Compression Standards Committee
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> P3184.5
> Standard for Data Communication and Logical Interface of Drive-by-Wire Chassis in Autonomous Driving Systems
> This standard defines a generic data communication framework, interface protocols, and interaction logic between vehicle-based autonomous driving systems and drive-by-wire chassis. It specifies data formats and logical information involved in bidirectional interactions between control commands from the autonomous driving systems and feedback signals from the drive-by-wire chassis.
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> P3161.13
> Standard for Embedding Representation in Digital Retina Systems (DRS)
> This standard provides unified technical guidance for the design, development, integration, and evaluation of embedding representations in Digital Retina Systems (DRS). The standard addresses token-based, tensor-based, and vector-based embeddings, specifies a framework, functional requirements, interfaces, and evaluation methods for embedding representations in DRS, and provides reference technical implementations.
> By defining a general framework, technical requirements and reference implementations, this standard aims to improve interoperability, consistency, and effectiveness of embedding representations in supporting visual information processing and downstream tasks.
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> Blockchain and Distributed Ledger Standards Committee
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> P3241.08
> Standard for Blockchain-Based Prediction of Electric Power Carbon Emission Factors
> This standard provides a blockchain-based, unified, transparent, and verifiable methodology for the prediction of power carbon emission factors. It specifies prediction categories and the format of input data as well as prediction models and procedures. Through an on-chain evidence deposit and sharing mechanism, the standard helps to ensure the verifiability and traceability of both the prediction input data and the prediction output results.
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> This standard applies to regional power grids and inter-regional power systems, supporting power carbon emission factors prediction scenarios across multiple timescales.
> This standard addresses technical gaps in power carbon emission factors prediction, data fragmentation, and the non-verifiability of prediction output results that limit the scientific basis of regional and enterprise-level carbon management. The standard helps accelerating the global carbon neutrality process.
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> Completed Standards
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> Standard Number
> Committee
> Project Title
> 802.3da
> LAN/MAN IEEE 802 Standards Committee
> IEEE Draft Standard for Ethernet Amendment 10: Physical Layer Specifications and Management Parameters for Enhancement of 10 Mb/s Operation over Single Balanced Pair Multidrop Segments
> 730
> Software & Systems Engineering Standards Committee
> IEEE Draft Standard for Software Quality Assurance Processes
> 3179
> Smart Manufacturing Standards Committee
> IEEE Draft Recommended Practice for Digital Mine Construction
> 12207
> Software & Systems Engineering Standards Committee
> ISO/IEC/IEEE Draft International standard - Systems and software engineering -- Software life cycle processes
> 23612
> Software & Systems Engineering Standards Committee
> ISO/IEC/IEEE Draft Software and systems engineering -- Incident management
> 802.1CB-2017/Cor 1
> LAN/MAN IEEE 802 Standards Committee
> IEEE Draft Standard for Local and metropolitan area networks--Frame Replication and Elimination for Reliability - Corrigendum 1: Technical and Editorial Corrections
> 3460
> Knowledge Engineering Standards Committee
> IEEE Draft Guide for a Framework for Auxiliary Decision-Making Systems in Power Grid Operations
> 802.1ASed
> LAN/MAN IEEE 802 Standards Committee
> IEEE Draft Standard for Local and Metropolitan Area Networks -Timing and Synchronization for Time-Sensitive Applications - Amendment: Fault-Tolerant Timing with Time Integrity
> 802.15.9a
> LAN/MAN IEEE 802 Standards Committee
> IEEE Draft Standard for Transport of Key Management Protocol Datagrams Amendment: Additional Key Management Protocol
> 3559
> Artificial Intelligence Standards Committee
> IEEE Draft Standard for Technical Requirements for Multimodal Large Language Models in Smart Home Applications
> 3458
> Artificial Intelligence Standards Committee
> IEEE Draft Standard for Domain-Specific Large Language Model Management Platforms
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> Best,
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> Brian Kirk
> Senior Technology Initiatives & Strategic Programs Manager
> CS Strategy and Governance
> IEEE Computer Society
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> bkirk@xxxxxxxxxxxx
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