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Sixth sense - air traffic control prediction scenario augmented by sensors
Abstract
This paper is focused on the fault tolerance of Human Machine Interfaces in the field of air traffic control (ATC) by accepting the overall user's body language as input. We describe ongoing work in progress in the project called Sixth Sense. Interaction patterns are reasoned from the combination of a recommendation and inference engine, the analysis of several graph database relationships and from multiple sensor raw data aggregations. Altogether, these techniques allow us to judge about different possible meanings of the current user's interaction and cognitive state. The results obtained from applying different machine learning techniques will be used to make recommendations and predictions on the user's actions. They are currently monitored and rated by a human supervisor- Conference Paper
- doc-type:Conference Paper
- inference
- mental map
- sensor fusion
- machine learning
- expert system
- asynchronous transfer mode (ATM)
- human factor
- experiment
- verification
- Business Field: Visual decision support
- Research Line: Human computer interaction (HCI)
- Forschungsgruppe Semantic Models, Immersive Systems (SMIS)