Demonstration of in-network audio processing for low-latency anomaly detection in smart factories

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragen

Abstract

This demonstration focuses on in-network computing as an enabler for low-latency Industrial Internet of Things (IIoT) applications, such as audio source separation for anomaly detection. By demonstrating a specific industrial application, we show that our method Progressive ICA (pICA), improves accuracy and reduces overall service latency progressively. The idea is to parallelize data transmission and processing along a multi-hop path consisting of in-network computing nodes. The audience can experience the benefits of the novel concept of in-network computing by interacting with the demonstration remotely via the Internet or in person.

Details

OriginalspracheEnglisch
Titel2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)
Seiten933-934
Seitenumfang2
PublikationsstatusVeröffentlicht - 11 Jan. 2022
Peer-Review-StatusNein

Publikationsreihe

ReiheIEEE Consumer Communications and Networking Conference
ISSN2331-9852

Externe IDs

Scopus 85135730895
dblp conf/ccnc/WuST0F22
ORCID /0000-0001-7008-1537/work/142248628
ORCID /0000-0001-8469-9573/work/161890992

Schlagworte

Schlagwörter

  • Internet of Things, audio processing, in-network computing, network softwarization