The TEAMING.AI engine software platform is an AI-driven decision support system to guide human-AI interactions based on a digital shadow of a dynamic industrial environment including human- and production-based processes.
It consists of tools
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for the orchestration and analysis of modelled teaming processes
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for continuously monitoring the knowledge graph and its dynamic updates, and
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for the adaptation of teaming workflows.
Application area: Recommender systems for guiding humans (or teams of humans) to interplay with machines or industrial processes, in particular to mitigate the cognitive workload (e.g., in a fault analysis setting for complex machines or process such as injection molding) or to mitigate ergonomic risks in physically demanding work processes. In each application scenario the AI system provides recommendations (e.g., how to reduce ergonomic risks based on a vision system) and it takes feedback from humans to improve overall performance.
| Web resources: | https://www.teamingai-project.eu/exploitable-results |
The current state of the art is limited in terms of team modelling and dynamic adaptability. The project’ approach addresses both by integrating methods for process modelling and knowledge-update mechanisms to come up with an enriched digital shadow that goes beyond static models.
This software tool is designed for real-time process management and ensures the effective execution of these teaming processes. It performs continuous observation and analysis, allowing for the immediate detection of any deviations or disruptions in the team workflows. This recognition supports a prompt response, facilitating adjustments to maintain the operation of the platform.