OMiLAB's IoT infrastructure, including the Dobot Magician, requires extensive programming knowledge to operate. This project aims to bridge this gap by extending the AOAME tool with a model-based approach, allowing non-experts to control cyber-physical systems. Furthermore, it enables domain experts to participate in the creation of the process and/or decision logic. The challenge lies in integrating the necessary libraries, creating a user-friendly interface and storing the data permanently.

Following a design science approach, the project involved analysing AOAME's capabilities and requirements, designing a conceptual framework, and implementing the designed features with rigorous testing. Key phases included research, design, and implementation, with milestones such as developing frontend and backend components, enabling permanent data storage with Apache Jena Fuseki server, and ensuring system integration. A crucial phase of the implementation process was the rigorous testing of the newly created code in the OMiLAB environment, with the objective of ensuring its functionality.

The extended AOAME tool now enables non-expert users to control the Dobot Magician via a model-based interface, thereby facilitating the operation of IoT systems at OMiLAB. The new functionality enables users to perform actions such as calibrating the robot arm, moving it to specific positions, or switching the suction cup on without the need for extensive programming knowledge. Furthermore, the project ensures the permanent storage of data in the Triple Store, thus facilitating the creation of models and their reuse. The provided documentation allows for future development and the creation of new projects. Additionally, this solution enhances the usability of OMiLAB's infrastructure, making it more accessible to a broader audience, thereby increasing the efficiency and effectiveness of its cyber-physical systems.