Abstract :
[en] Artificial intelligence (AI) and Internet of things (IoT) are progressively entering in all domains of our daily lives. Nowadays, both domains are combined in what is called artificial intelligence of thing (AIoT). With the increase of the amount of data produced by the myriad of connected things and the large wide of data needed to train Artificial Intelligence model,data processing and storage became a real challenge.
Indeed, the amount of data to process, to transfer by network and to treat in the cloud have call into question classical data storage and processing architectures. Also, the large amount of data generated at the edge has increased the speed of data transportation that is becoming the bottleneck for the cloud-based computing paradigms.
The post-cloud approaches using Edge computing allow to improve latency and jitter. These infrastructures manage mechanisms of containerization for rapidly deploy and migrate services such as reasoning mechanisms and ontology on one hand and specifically adapted artificial intelligence algorithms.
In this paper we propose a new architecture used to deploy micro services and adapted artificial intelligence algorithms at edge level.
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