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

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributed

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

Original languageEnglish
Title of host publicationProceedings of the Consumer Communications Networking Conference (CCNC)
Pages933-934
Number of pages2
Publication statusPublished - 11 Jan 2022
Peer-reviewedNo

External IDs

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

Keywords

Keywords

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