Search: onr:"swepub:oai:DiVA.org:kau-94900" >
AIDA—Aholistic AI-d...
AIDA—Aholistic AI-driven networking and processing framework for industrial IoT applications
-
- Chahed, Hamza (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
- Usman, Muhammad (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
- Chatterjee, Ayan (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
show more...
-
- Bayram, Firas (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
- Chaudhary, Rajat (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
- Brunstrom, Anna, 1967- (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
- Taheri, Javid (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
-
- Ahmed, Bestoun S., 1982- (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013),Czech Technical University in Prague, Czech Republic
-
- Kassler, Andreas, 1968- (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013),Deggendorf Institute of Technology, Germany
-
show less...
-
(creator_code:org_t)
- Elsevier, 2023
- 2023
- English.
-
In: Internet of Things. - : Elsevier. - 2542-6605. ; 22
- Related links:
-
https://doi.org/10.1...
-
show more...
-
https://kau.diva-por... (primary) (Raw object)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
show less...
Abstract
Subject headings
Close
- Industry 4.0 is characterized by digitalized production facilities, where a large volume of sensors collect a vast amount of data that is used to increase the sustainability of the production by e.g. optimizing process parameters, reducing machine downtime and material waste, and the like. However, making intelligent data-driven decisions under timeliness constraints requires the integration of time-sensitive networks with reliable data ingestion and processing infrastructure with plug-in support of Machine Learning (ML) pipelines. However, such integration is difficult due to the lack of frameworks that flexibly integrate and program the networking and computing infrastructures, while allowing ML pipelines to ingest the collected data and make trustworthy decisions in real time. In this paper, we present AIDA - a novel holistic AI-driven network and processing framework for reliable data-driven real-time industrial IoT applications. AIDA manages and configures Time-Sensitive networks (TSN) to enable real-time data ingestion into an observable AI-powered edge/cloud continuum. Pluggable and trustworthy ML components that make timely decisions for various industrial IoT applications and the infrastructure itself are an intrinsic part of AIDA. We introduce the AIDA architecture, demonstrate the building blocks of our framework and illustrate it with two use cases.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Keyword
- Edge/cloud computing
- Internet of Things (IoT)
- Machine Learning
- Time-Sensitive Networks (TSN)
- Computer Science
- Datavetenskap
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
To the university's database
- By the author/editor
-
Chahed, Hamza
-
Usman, Muhammad
-
Chatterjee, Ayan
-
Bayram, Firas
-
Chaudhary, Rajat
-
Brunstrom, Anna, ...
-
show more...
-
Taheri, Javid
-
Ahmed, Bestoun S ...
-
Kassler, Andreas ...
-
show less...
- About the subject
-
- NATURAL SCIENCES
-
NATURAL SCIENCES
-
and Computer and Inf ...
-
and Computer Enginee ...
-
- NATURAL SCIENCES
-
NATURAL SCIENCES
-
and Computer and Inf ...
-
and Computer Science ...
- Articles in the publication
-
Internet of Thin ...
- By the university
-
Karlstad University