Adaptive learning approach for a drone
One example method of operation may include identifying a likelihood of an object presence at one or more locations within a predefined distance of locations explored by a drone during one or more monitoring actions performed by the drone during a mission including a number of mission requirements, selecting one or more new monitoring actions to perform by the drone based on the likelihood of the object presence to satisfy the mission requirements, and performing the one or more new monitoring actions by the drone.
1. A method comprising
performing one or more monitoring actions by a drone at one or more locations during a mission comprising a plurality of mission requirements, wherein the mission requirements require the drone to fly in a particular pattern over a designated area to identify objects of interest;
identifying, via the drone, one or more vehicles at one or more locations based on image data captured by the drone;
forwarding, via the drone, the image data to a ground station;
performing, via the ground station, with machine-learning models to determine whether the one or more vehicles are above a threat threshold and require additional action by the drone based on an image analysis of the image data including the one or more vehicles being paired with stored image data of known vehicles associated with the threat threshold;
receiving, via the drone, a mission update from the ground station comprising additional mission objectives, wherein the mission update comprises additional flying patterns to identify a candidate object which is predicted to be present within a predefined area between the one or more vehicles based on the machine-learning models determining a likelihood of a presence of the candidate object;
determining a range of additional locations for the drone to perform one or more new monitoring actions comprising additional image captures and communication signal monitoring
performing the one or more new monitoring actions by the drone; and
performing an image analysis of the additional image captures to identify the candidate object.
2. An apparatus comprising a processor configured to
instruct a drone to perform one or more monitoring actions at one or more locations during a mission comprising a plurality of mission requirements, wherein the mission requirements require the drone to fly in a particular pattern over a designated area to identify objects of interest;
identify, via the drone, one or more vehicles at one or more locations based on image data captured by the drone;
forward, via the drone, the image data to a ground station;
perform, via the ground station, with machine-learning models to determine whether the one or more vehicles are above a threat threshold and require additional action by the drone based on an image analysis of the image data including the one or more vehicles being paired with stored image data of known vehicles associated with the threat threshold;
receive, via the drone, a mission update from the ground station comprising additional mission objectives, wherein the mission update comprises additional flying patterns to identify a candidate object which is predicted to be present within a predefined area between the one or more vehicles based on the machine-learning models determining a likelihood of a presence of the candidate object;
determine a range of additional locations for the drone to perform one or more new monitoring actions comprising additional image captures and;
perform the one or more new monitoring actions by the drone; and
perform an image analysis of the additional image captures to identify the candidate object.
3. A non-transitory computer readable storage medium comprising instructions that when executed cause a processor to perform:
performing one or more monitoring actions by a drone at one or more locations during a mission comprising a plurality of mission requirements, wherein the mission requirements require the drone to fly in a particular pattern over a designated area to identify objects of interest;
identifying, via the drone, one or more vehicles at one or more locations based on image data captured by the drone;
forwarding, via the drone, the image data to a ground station;
performing, via the ground station, with machine-learning models to determine whether the one or more vehicles are above a threat threshold and require additional action by the drone based on an image analysis of the image data including the one or more vehicles being paired with stored image data of known vehicles associated with the threat threshold;
receiving, via the drone, a mission update from the ground station comprising additional mission objectives, wherein the mission update comprises additional flying patterns to identify a candidate object which is predicted to be present within a predefined area between the one or more vehicles based on the machine-learning models determining a likelihood of a presence of the candidate object;
determining a range of additional locations for the drone to perform one or more new monitoring actions comprising additional image captures and communication signal monitoring;
performing the one or more new monitoring actions by the drone; and
performing an image analysis of the additional image captures to identify the candidate object.