Determining mission evolution through UAV telemetry by using decision trees

The control and monitoring of the UAV missions is a challenge in terms of operator workload. Two relevant issues are the situational awareness and the decision support of operators. This paper proposes a system that is able to analyze the telemetry of UAV to deduce the state of mission. This system uses Petri nets for determining the state and decision trees for estimating the evolution. Both the Petri nets and the decision trees are generated automatically from the telemetry of previous missions. The whole system is validated by monitoring a set of UAV missions in a realistic simulator. The results can be applied to diverse areas, including the development of intelligent and adaptive interfaces or decision support systems.