Scheduling Tasks for Human Operators in Monitoring and Surveillance Applications

We consider a scheduling problem that arises in the context of surveillance or reconnaissance missions by multiple unmanned aerial vehicles (UAVs) where human operators would be present to perform tasks that require a high level of expertise and reasoning. Each UAV performing the mission provides a video stream of the targets it monitors to the human operator who is required to take critical decisions based on the video stream. A single human operator often examines the video stream from multiple UAVs constantly; this can cause his/her visual attention to drop below an acceptable level while performing the tasks. We propose an automated system to ease the operator's work load by breaking up the video streams into parts and scheduling a subset of them for the operator's inspection. We present the architecture for the system, identify the various components involved to build such a system, formulate the associated scheduling problem as a mixed-integer linear program (MILP) and solve the same. Preliminary results are also presented to corroborate the effectiveness of the formulation.