Published November 23, 2024
| Version v1
Conference proceeding
Open
Real-time Machine Learning-based IoT Data Analysis in the Edge Cloud Continuum using AC3
Creators
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Ojeda Coronado, Jhofre Eduardo
(Researcher)1
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Amaxilatis, Dimitrios
(Researcher)2
-
Tsironis, Nikolaos
(Researcher)3
-
Sarantakos, Themistoklis
(Researcher)2
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Fonseca, João Pedro
(Researcher)1
-
Adhane, Gereziher
(Researcher)4
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Famitafreshi, Golshan
(Researcher)1, 5
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Famitafreshi, Golshan
(Researcher)1, 5
-
Roy, Swastika
(Researcher)1
- Chari, Shreya (Researcher)1
-
Ghafouri, Navideh
(Researcher)1
-
Ramantas, Kostas
(Researcher)1
-
Verikoukis, Christos
(Researcher)6
Description
The demo highlights how IoT data from Sensirion
sensors and Raspberry Pis are processed using the Agile and Cognitive
Cloud-edge Continuum Management (AC3) framework.
This approach optimizes data processing locations dynamically,
balancing edge response and cloud computational power, enhancing
real-time building management and smart city applications.
Files
a19-ojeda final.pdf
Files
(1.3 MB)
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md5:f9ff4e5a700955015f8ce5c92071205b
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Additional details
Dates
- Accepted
-
2024-12-23IEEE CAMAD 2024