Researching technologies to aid in visual computing at the network edge for disaster incident response. This includes (1) experimenting with various advanced visual processing applications, e.g., such as for object tracking or 3D scene reconstructions, utilizing thin-clients capabilities to enhance their Quality of Experience, (2) designing and evaluating novel SDN/KDN algorithms and virtualization technologies (e.g., Docker) that allow rapid, feasible and optimal (or near optimal) assignment of computation instance processes of the computer vision applications to fog/cloud testbed resources (e.g., allocated within GENI or CloudLab infrastructures), and (3) developing and testing APIs to implement SDN-based fog computing processes that can extend cloud computing APIs closer to the network-edge locations of users and data sources.