Discusses Robotics in the scope of Health and Societal Applications of AI
Area, Active assisted living (AAL) / Terms and definitions relating to devices and systems. IEV ref, 871-04-07. en. assistive robot. robot that assists an ...
IEC 80601-2-77:2019 applies to the BASIC SAFETY and ESSENTIAL PERFORMANCE of ROBOTICALLY ASSISTED SURGICAL EQUIPMENT (RASE) and ROBOTICALLY ASSISTED SURGICAL SYSTEMS (RASS), referred to as ME EQUIPMENT and ME SYSTEMS together with their INTERACTION CONDITIONS and INTERFACE CONDITIONS.
EC 80601-2-78:2019 applies to the general requirements for BASIC SAFETY and ESSENTIAL PERFORMANCE of MEDICAL ROBOTS that physically interact with a PATIENT with an IMPAIRMENT to support or perform REHABILITATION, ASSESSMENT, COMPENSATION or ALLEVIATION related to the PATIENT’S MOVEMENT FUNCTIONS, as intended by the MANUFACTURER.IEC 80601-2-78:2019 does not apply to• external limb prosthetic devices (use ISO 22523),• electric wheelchairs (use ISO 7176 (all parts)),
Self-management of health, with decision-making processes(cognitive and robotics)
This standard addresses quantum technologies specific terminology and establishes definitions necessary to facilitate clarity of understanding to enable compatibility and interoperability.
The Thing Description (TD) ontology is an RDF axiomatization of the TD information model, one of the building blocks of the Web of Things (WoT). Besides providing an alternative to the standard JSON representation format for TD documents, the TD ontology can also be used to process contextual information on Things and for alignments with other WoT-related ontologies.
This document provides the basic concepts for IoT systems semantic interoperability, as described in the facet model of ISO/IEC 21823-1, including: - requirements of the core ontologies for semantic interoperability; - best practices and guidance on how to use ontologies and to develop domain-specific applications, including the need to allow for extensibility and connection to external ontologies; - cross-domain specification and formalization of ontologies to provide harmonized utilization of existing ontologies; - relevant IoT ontologies along with comparative study of the characteristics and approaches in terms of modularity, extensibility, reusability, scalability, interoperability with upper ontologies, and so on, and; - use cases and service scenarios that exhibit necessities and requirements of semantic interoperability.
The Semantic Sensor Network (SSN) ontology is an ontology for describing sensors and their observations, the involved procedures, the studied features of interest, the samples used to do so, and the observed properties, as well as actuators. SSN follows a horizontal and vertical modularization architecture by including a lightweight but self-contained core ontology called SOSA (Sensor, Observation, Sample, and Actuator) for its elementary classes and properties. With their different scope and different degrees of axiomatization, SSN and SOSA are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Web of Things. Both ontologies are described below, and examples of their usage are given.
SAREF4SYST defines Systems, Connections between systems, and Connection Points at which systems may be connected.
SEAS ontology describes energy systems and their interactions.
SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured.