Demo Abstract: Toward the Convergence of the Next-Generation Wireless and AI

被引：0

作者：

Ning, Rui ^{[1
]}

Wang, Chonggang ^{[2
]}

Gazda, Robert ^{[2
]}

Wu, Hongyi ^{[3
]}

机构：

[1] Old Dominion Univ, Dept CS, Norfolk, VA 23529 USA

[2] Univ Arizona, Dept ECE, Tucson, AZ 85721 USA

[3] InterDigital Inc, Conshohocken, PA 19428 USA

来源：

IEEE INFOCOM 2024-IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS, INFOCOM WKSHPS 2024 | 2024年

基金：

美国国家科学基金会;

关键词：

Deep Learning; Federated Learning; Neural Backdoor; Security;

D O I：

10.1109/INFOCOMWKSHPS61880.2024.10620668

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This research paper presents a groundbreaking demonstration of the Pathway-of-Experts (PoE) system, showcasing its superior capabilities in IoT-based human activity recognition compared to traditional single-model systems. The study highlights the PoE system's enhanced accuracy, efficiency, and adaptability in complex environments, setting a new benchmark in smart home technology. By integrating AI with next-generation wireless networks, this demonstration underlines the potential for significant advancements in intelligent IoT environments, paving the way for broader applications and further enhancements of the PoE system.

引用

页数：2

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