TY - GEN
T1 - Liquid Artificial Intelligence Through IDSA and GAIA-X Integration
AU - Waseem, Muhammad
AU - Ahmad, Aakash
AU - Mäkitalo, Niko
AU - Kotilainen, Pyry
AU - Hästbacka, David
AU - Mätäsniemi, Krista
AU - Systä, Kari
AU - Mikkonen, Tommi
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Liquid artificial intelligence is a dynamic data processing approach that enables real-time, adaptable management and analysis of data across various platforms. So far, Liquid AI has been considered as a technical concept, and there are no studies that relate it to data governance frameworks such as those proposed by the international data spaces association and GAIA-X, which play a key role when setting standards for data sovereignty, security, and interoperability. To address this gap, we propose a reference architecture and algorithms for integrating the IDSA and GAIA-X frameworks within the context of Liquid AI, with a focus on their application in Intelligent Hospital Management and Intelligent Traffic Control systems. Based on the study, future work will focus on experimentally and empirically evaluating the proposed reference architecture in real-world settings and exploring its interoperability with other frameworks, as well as integrating emerging technologies to improve its effectiveness.
AB - Liquid artificial intelligence is a dynamic data processing approach that enables real-time, adaptable management and analysis of data across various platforms. So far, Liquid AI has been considered as a technical concept, and there are no studies that relate it to data governance frameworks such as those proposed by the international data spaces association and GAIA-X, which play a key role when setting standards for data sovereignty, security, and interoperability. To address this gap, we propose a reference architecture and algorithms for integrating the IDSA and GAIA-X frameworks within the context of Liquid AI, with a focus on their application in Intelligent Hospital Management and Intelligent Traffic Control systems. Based on the study, future work will focus on experimentally and empirically evaluating the proposed reference architecture in real-world settings and exploring its interoperability with other frameworks, as well as integrating emerging technologies to improve its effectiveness.
KW - GAIA-X
KW - Hybrid cloud
KW - IDSA
KW - Liquid AI
U2 - 10.1007/978-3-031-84457-7_2
DO - 10.1007/978-3-031-84457-7_2
M3 - Conference contribution
AN - SCOPUS:105000776994
SN - 9783031844560
VL - 1
T3 - Lecture Notes in Networks and Systems
SP - 17
EP - 37
BT - Advances in Information and Communication
A2 - Arai, Kohei
PB - Springer
T2 - Future of Information and Communication Conference
Y2 - 28 April 2025 through 29 April 2025
ER -