Intelligence Stratum for IoT. Architecture Requirements and Functions

TL;DR

This paper proposes a layered intelligence architecture for IoT to address heterogeneity and interoperability challenges in deploying AI, aiming to enable effective AI distribution across IoT networks.

Contribution

It introduces a new layered architecture tailored for IoT AI distribution, considering current network requirements and challenges.

Findings

Highlights the need for a layered AI architecture in IoT

Defines key characteristics and implications of the proposed architecture

Enumerates open challenges for future research

Abstract

The use of Artificial Intelligence (AI) is becoming increasingly pervasive and relevant in many different application areas. Researchers are putting a considerable effort to take full advantage of the power of AI, while trying to overcome the technical challenges that are intrinsically linked to almost any domain area of application, such as the Internet of Things (IoT). One of the biggest problems related to the use of AI in IoT is related to the difficulty of coping with the wide variety of protocols and software technologies used, as well as with the heterogeneity of the hardware resources consuming the AI. The scattered IoT landscape accentuates the limitations on interoperability, especially visible in the deployment of AI, affecting the seamless AI life-cycle management as well. In this paper, it is discussed how to enable AI distribution in IoT by introducing a layered intelligence architecture that aims to face the undertaken challenges taking into account the special requirements of nowadays IoT networks. It describes the main characteristics of the new paradigm architecture, highlighting what are the implications of its adoption from use cases perspective and their requirements. Finally, a set of open technical and research challenges are enumerated to reach the full potential of the intelligence distribution's vision.