Simplifying Edge AI: A Block-Based Development Platform for IoT Applications

This paper aims to develop a visual programming environment that allows users with limited programming knowledge to interact with AI models. This environment is implemented on an Edge-AI platform. The platform, referred to as the OZY board, is designed to simplify and enhance the accessibility of AI applications in practice. The developed visual programming environment focuses on creating an intuitive user interface, making it easier for nonprogrammers to work with AI models through block-based programming, reducing the complexity of machine learning development. The study includes a thorough literature review, evaluation of suitable libraries, and the creation of use cases. UI prototypes are developed, followed by technical implementation and user testing. The results of these tests are used to further refine the application. This research contributes to the field by addressing the challenges of accessibility and usability in AI technologies and provides practical solutions for extending AI access to a wider user base, especially in education to demonstrate simple machine learning algorithms.

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Publication Details

Published
2025-06-02
DOI
https://doi.org/10.1109/mipro65660.2025.11131719
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
1.49
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article

Simplifying Edge AI: A Block-Based Development Platform for IoT Applications

Klaus-Uwe Gollmer, Lejla Begic Fazlic, Guido Dartmann, Alexander Koß
1 citations
IoT and Edge/Fog Computing
1.49
article

Simplifying Edge AI: A Block-Based Development Platform for IoT Applications

Klaus-Uwe Gollmer, Lejla Begic Fazlic, Guido Dartmann, Alexander Koß
article en
1 citations

Abstract

This paper aims to develop a visual programming environment that allows users with limited programming knowledge to interact with AI models. This environment is implemented on an Edge-AI platform. The platform, referred to as the OZY board, is designed to simplify and enhance the accessibility of AI applications in practice. The developed visual programming environment focuses on creating an intuitive user interface, making it easier for nonprogrammers to work with AI models through block-based programming, reducing the complexity of machine learning development. The study includes a thorough literature review, evaluation of suitable libraries, and the creation of use cases. UI prototypes are developed, followed by technical implementation and user testing. The results of these tests are used to further refine the application. This research contributes to the field by addressing the challenges of accessibility and usability in AI technologies and provides practical solutions for extending AI access to a wider user base, especially in education to demonstrate simple machine learning algorithms.

Trier University of Applied Sciences (DE)
Openalex Percentile: Top 13%
IoT and Edge/Fog Computing
1.49
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Simplifying Edge AI: A Block-Based Development Platform for IoT Applications — Klaus-Uwe Gollmer, Lejla Begic Fazlic, et al. · (2025) | TGRS Research Map | TGRS