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Library of Reference AI Scenarios and Use Cases

Library of Reference AI Scenarios and Use Cases

In the context of STAR, a Library of Reference AI Scenarios and Use Cases was created. The AI Scenarios and Use Cases identified are related to manufacturing with an emphasis on scenarios directly related to STAR. To elaborate this library of scenarios the elicitation was performed in two groups. The first one related to the STAR scenarios and use cases and the second, to external and public know scenarios and use cases. The figure below depicts the first steps made for the identification of the scenarios.

Identification of AI Scenarios and Use Cases

 

The research for external scenarios and use cases, was mainly performed with the help of platforms, as the IoT-Catalogue.com and the EFFRA portal. The IoT-Catalogue.com was utilised to elicit a list of use cases that are known to use AI in manufacturing together with EFFRA which is a portal that promotes the development of new and innovative production technologies provides quite good information. At the same time also the AI4EU project was analysed to elicit the relevant use cases and scenarios targeted by it. Additionally, an analysis was performed on a study conducted by the Centre for Strategy and Evaluation Services (CSES). The name of the study is Opportunities of Artificial Intelligence and provides an assessment of the state of AI adoption in the European industry.

 

STAR has collected a total of 58 AI Scenarios and Use Cases, distributed in the following way

  • STAR: 10;
  • IoT-Catalogue.com: 14;
  • EFFRA portal: 18;
  • AI4EU: 8.
  • Opportunities of Artificial Intelligence Study: 8.

 

The second figure below  represents the organogram of how the work progressed after the identification of the scenarios.

Methodology used to understand similarities between external and internal scenarios

 

The work performed to understand the similarities between the STAR project scenarios and the external scenarios, had the following steps:

  • Identify and extract the parameters such as Country, project, and year from the elicited scenarios,
  • Analyse and classify the collected information and obtain the domain and category of the AI scenario,
  • relate the STAR project scenarios with the external scenarios.

This enabled the identification of which external scenarios related to the STAR scenarios , and the possible relevance in how the external scenarios can be of use for the implementation and deployment of STAR technologies within the STAR pilots.

 

By: Tiago Teixeira, UNPARALLEL INNOVATION LDA