Robotics & Machine Learning Daily News2024,Issue(Mar.11) :41-42.

Investigators at Beijing University of Posts and Telecommunications Describe Fin dings in Artificial Intelligence (Task-oriented and Semantic-aware Heterogeneous Networks for Artificial Intelligence of Things: Performance Analysis and ...)

Robotics & Machine Learning Daily News2024,Issue(Mar.11) :41-42.

Investigators at Beijing University of Posts and Telecommunications Describe Fin dings in Artificial Intelligence (Task-oriented and Semantic-aware Heterogeneous Networks for Artificial Intelligence of Things: Performance Analysis and ...)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ar tificial Intelligence. According to news originating from Beijing, People's Repu blic of China, by NewsRx correspondents, research stated, "We propose a novel ta sk-oriented and semantic-aware heterogeneous networks (TOSA-HetNets) framework f or multitype Artificial Intelligence of Things (AIoT) devices with various requi rements, where the dense edge servers with different transmission capabilities, computing resources, and power consumption are divided into different layers to provide on-demand collaboration for AIoT devices located in accessible areas. Mo reover, we propose a device-edge collaboration intelligent tasks inference schem e between edge servers and AIoT devices in TOSA-HetNets, it includes AIoT device s performing semantic features extraction and uploading the corresponding semant ic features to the associated edge servers, multiple layers of edge servers coll aborating with AIoT devices to execute the intelligent tasks and transmit the in telligent task results back to AIoT devices." Financial support for this research came from National Key R&D Prog ram of China.

Key words

Beijing/People's Republic of China/Asi a/Artificial Intelligence/Emerging Technologies/Machine Learning/Beijing Uni versity of Posts and Telecommunications

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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