Combining Context-Awareness and Data Analytics in Support of Drone Technology
Boris Shishkov (TU Delft - Information and Communication Technology, Bulgarian Academy of Sciences, Institute IICREST)
Krassimira Ivanova (Bulgarian Academy of Sciences)
A Verbraeck (TU Delft - Policy Analysis)
Marten van Sinderen (University of Twente)
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Abstract
Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. This only partially benefits drone technology because many types of drone missions can be characterized by situations that are hard to predict at design time. We suggest combining context-awareness and data analytics for a better situation coverage. This could be achieved by using performance data (generated at real-time) as training data for supervised machine learning – it would allow relating situations to appropriate behaviors that a drone could follow. The conceptual ideas are presented in this position paper while validation is left for future work.