Fixed drone visualization in security systems
An unmanned aerial vehicle is described and includes a computer carried by the unmanned aerial vehicle to control flight of the unmanned aerial vehicle and at least one sensor. The unmanned aerial vehicle is caused to fly to a specific location within a facility, where the unmanned aerial vehicle enters a hover mode, where the unmanned aerial vehicle remains in a substantially fixed location hovering over the specific location within the facility and sends raw or processing results of sensor data from the sensor to a remote server system.
1. A method of aerial surveillance, comprising:
receiving, by a computer system from a server of a building, an alarm condition;
programming, by the computer system and responsive to the alarm condition, an electronic component of a drone with a route between a starting point and a location associated with the alarm condition, the route indicated by a data structure representation of a plurality of radio-frequency (RF) devices;
the drone configured to navigate to the location associated with the alarm condition based on determinations of drone position on the route using signals from the plurality of RF devices; and
sending, by the drone, to the computer system, sensor data associated with the location associated with the alarm condition.
2. The method of claim 1 , comprising:
providing a flight plan to cause the drone to hover.
3. The method of claim 1 , comprising:
receiving the alarm condition from a sensor of a facility.
4. The method of claim 1 , comprising:
the alarm condition indicating an open window, broken glass, or an intrusion.
5. The method of claim 1 , comprising:
identifying, by the computer system, an indication of a detected movement at the location associated with the alarm condition.
6. The method of claim 1 , wherein the drone is a first drone, comprising:
programming a second drone with the route between the starting point and the location associated with the alarm condition.
7. The method of claim 1 , comprising:
providing, to the drone, a command to return to the starting point.
8. The method of claim 1 , comprising:
the data structure representation comprising a series of features extracted from images; and
the drone adjusting the route based on applying feature recognition to the series of features, feature recognition comprising:
capturing flight images;
extracting recognized features from the flight images; and
comparing the recognized features to the series of features.
9. The method of claim 1 , comprising:
the data structure representation including a feature extracted from an image; and
adjusting the route based on applying feature recognition to the feature, the feature recognition including:
obtaining a flight image;
extracting a flight image feature from the flight image; and
comparing the flight image feature with the feature extracted from the image.
10. The method of claim 1 , comprising:
determining a deviation from the route based on a location of the drone; and
obtaining, by the computer system, an indication of the deviation.
11. The method of claim 1 , comprising:
at least one of the plurality of radio-frequency (RF) devices including an asset-to-protect (ATP) waypoint, a home-asset-to-protect (HATP), or a perimeter-point-to-protect (PPP) waypoint.
12. An aerial surveillance system, comprising:
a plurality of radio-frequency (RF) devices;
a computer system to:
generate an indication of a route between a starting point and a location of interest, the indication of the route comprising a data structure representation of the plurality of RF devices; and
a drone to:
receive at least a portion of the indication of the route from the computer system;
navigate to the location of interest based on signals from the plurality of RF devices; and
send to the computer system sensor data of the location of interest.
13. The system of claim 12 , comprising:
the data structure representation including a feature extracted from an image; and
the drone to adjust the route based on feature recognition of the feature.
14. The system of claim 12 , comprising:
the drone to determine a deviation from the route, and to report the deviation from the route to the computer system.
15. The system of claim 12 , comprising:
the computer system to update the route based on a deviation.
16. The system of claim 12 , comprising:
the computer system to compare the sensor data to previous sensor data; and
send an indication to a server of a building in response to determination of a feature difference based on the comparison.
17. The system of claim 12 , comprising:
the plurality of radio-frequency (RF) devices including an asset-to-protect (ATP) waypoint, a home-asset-to-protect (HATP) waypoint, or a perimeter-point-to-protect (PPP) waypoint.
18. The system of claim 12 , comprising:
the data structure representation comprising a set of nodes and a set of edges, each of the set of nodes corresponding to one of the plurality of RF devices and the set of edges defining a relationship between the set of nodes.
19. A navigation system for an indoor aerial surveillance system comprising:
a plurality of radio-frequency (RF) devices; and
a computer system to:
generate a data structure representation of a path between a starting point and a location of interest, the data structure representation comprising the plurality of RF devices and one or more routes between each of the plurality of RF devices;
update the data structure representation based on data received from one or more drones;
send a route of the one or more routes to a drone of the one or more drones; and
the drone configured to navigate to a RF device of the plurality of RF devices based on the route and a position based on a signal from at least one of the plurality of RF devices.
20. The system of claim 19 , comprising:
each of the plurality of radio-frequency (RF) devices including an asset-to-protect (ATP) waypoint, a home-asset-to-protect (HATP) waypoint, or a perimeter-point-to-protect (PPP).