Abstract: A method for sharing a point-of-interest across a plurality of video feeds from a plurality of optical imaging devices includes receiving an indication of the point-of-interest associated with a first video feed of the plurality of video feeds, the first video feed provided by a first optical imaging device of the plurality of optical imaging devices; determining a geo-location of an object associated with the point-of-interest; determining a position of a second optical imaging device relative to the determined geo-location of the point-of-interest; and overlaying the point-of-interest on a second video feed, the second video feed provided by the second optical imaging device.

Abstract: A method for configuring a multiple autonomous drone mission includes displaying, a plurality of queries on a display of the computing device. The method further includes receiving, via a user interface, a plurality of inputs responsive to the plurality of queries. At least a first input of the plurality of inputs specifies a type of mission to be performed and at least a second input of the plurality of inputs specifies a geographical area in which a mission to be performed will be carried out. The method further includes automatically determining, based on the plurality of inputs, an initial location to move to for each of a plurality of drones available for implementing the mission. The method further includes automatically determining, based on the plurality of inputs, a series of tasks for each of the plurality of drones.

Abstract: A method for performing automatic trace retrieval includes receiving a first and second model for a system or service (S10). The first model includes a first plurality of model artifacts at least partially represented by a first semantic style and the second model includes a second plurality of artifacts at least partially represented by a second semantic style. Training data including one or more correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts is collected. A semantic transformation table is generated for converting between the first and second semantic styles using the collected training data (S11). The generated semantic transformation table is used in tracing associations between artifacts of the first plurality of artifacts and artifacts of the second plurality of artifacts (S12).