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CiRA CORE: A Low Code Platform that Makes AI Work for Industry 4.0

Author(s)
Loo, Chu Kiong
Boonsang, Siridech
Sasisaowapak, Thanyathep
Chuwongin, Santhad
Tongloy, Teerawat
Nahavandi, Saeid
Wong, Kok Wai
Date Issued
January 1, 2024
Type
Conference Paper
DOI
10.1109/SMC54092.2024.10831625
Abstract
CiRA CORE is a central hub designed to connect AI technology creation with practical application, making it easier to work with ROS (Robot Operating System) and link different systems through a user-friendly drag-and-drop interface. This approach removes the need for extensive coding, making the platform accessible to those with minimal programming experience. CiRA CORE offers a comprehensive suite of features for AI development and robot control, including algorithm creation, AI model training, and device integration commonly used in industrial settings. It supports tasks like image recognition and facilitates data storage, labeling, and integration with other systems for data-driven AI development. Overall, CiRA CORE aims to democratize AI development and robot control, simplifying AI development for Industry 4.0 applications, and leading to increased efficiency, reduced costs, and improved safety in industrial processes. This paper reports the progress of the CiRA CORE training modules funded by the SMCS TEAM Program Award. The project has completed the design of a 6-axis robot 3D training kit and simulation models for CiRA CORE training modules. The next steps involve developing 3D-printed robots and training materials. The main goal is to democratize advanced robotics and AI by simplifying integration through a visual, node-based programming interface. This approach reduces the need for complex coding, making these technologies accessible to users with limited programming experience. This initiative aims to foster widespread adoption in business and industrial settings, aligning with IEEE SMC's mission to promote professional growth and innovation in robotics and AI.
Citation
Conference Proceedings IEEE International Conference on Systems Man and Cybernetics, 1187-1188, 2024
Subjects

Human-Machine Interac...

Human-Machine Interfa...

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