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ITU-T F.AI-DLFE - Deep Learning Software Framework Evaluation Methodology
ITU-T F.AI-DMPC - Technical framework for Deep Neural Network model partition and collaborative execution
ITU-T F.AI-FASD - Framework for audio structuralizing based on deep neural network
ITU-T F.AI-ILICSS - Technical Requirements and Evaluation Methods of Intelligent Levels of Intelligent Customer Service System
ITU-T F.AI-RMCDP - Requirements of multimedia composite data preprocessing
F.AI-SCS - Use cases and requirements for speech interaction of intelligent customer service
ITU-T F.IMCS - Requirements for smart speaker based Intelligent Multimedia Communication System
F.Supp-OCAIB - Overview of convergence of artificial intelligence and blockchain
ITU-T F.746.11 (ex F.IQAS-INT) - Interfaces for intelligent question answering system
ITU-T F.743.12 (06/2021)Requirements for edge computing in video surveillance
Recommendation ITU-T F.743.12 defines the requirements for edge computing in video surveillance. Edge computing is a distributed computing paradigm aimed at providing various computing services at the edge of the network, and it brings computation and data storage closer to the data source or the location where it is needed, to improve response time and save bandwidth. By using the edge computing technology, the video surveillance system can perform intelligent video analysis and store data near the network premises units. And the edge computing platform provides the management capabilities of the edge resources and functional components to the video surveillance system. It can improve the video processing efficiency and quality of services and reduce the infrastructure cost of the video surveillance system. This Recommendation describes the application scenarios and requirements for edge computing in the video surveillance system.
ITU-T Study Group 20ITU-T - SG20 - Internet of things (IoT) and smart cities and communities (SC&C)
SG20 develops international standards to enable the coordinated development of IoT technologies, including machine-to-machine communications and ubiquitous sensor networks. A central part of this study is the standardization of end-to-end architectures for IoT, and mechanisms for the interoperability of IoT applications and datasets employed by various vertically oriented industry sectors.