'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
The ongoing 4th industrial revolution is characterized by the digitization of industrial environments,
mainly based on the use of Internet of Things, Cloud Computing and Artificial Intelligence (AI).
Regarding AI, although data analysis has shown to be a key enabler of industrial Cyber-Physical Systems
(CPS) in the development of smart machines and products, the traditional Cloud-centric solutions are not
suitable to attend the data and time-sensitive requirements. Complementary to Cloud, Edge Computing has
been adopted to enable the data processing capabilities at or close to the physical components. However,
defining which data analysis tasks should be deployed on Cloud and Edge computational layers is not
straightforward. This work proposes a framework to guide engineers during the design phase to determine
the best way to distribute the data analysis capabilities among computational layers, contributing for a lesser
ad-hoc design of distributed data analysis in industrial CPS. Besides defining the guidelines to identify
the data analysis requirements, the core contribution relies on a Fuzzy Logic recommendation system for
suggesting the most suitable layer to deploy a given data analysis task. The proposed approach is validated
in a smart machine testbed that requires the implementation of different data analysis tasks for its operation.This work was supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.info:eu-repo/semantics/publishedVersio