WILD-LIFE SURVEILLANCE AND PROTECTION

• US 20190246626A1
• Filed: 02/12/2018
• Published: 08/15/2019
• Est. Priority Date: 02/12/2018
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Baughman, Aaron K., Diamanti, Gary F., Marzorati, Mauro, Nyiri, Juraj
• Granted Patent: US 10,674,719 B2
• Time in Patent Office: Days
• CPC Class Codes: A01K 29/005 Monitoring or measuring activity, e.g. detecting heat or mating
• CPC Class Codes: A01M 31/002 Detecting animals in a given area
• CPC Class Codes: A01M 31/06 Decoys
• CPC Class Codes: B64U 2101/00 UAVs specially adapted for particular uses or applications
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2101/31 for surveillance
• CPC Class Codes: B64U 2201/104 using satellite radio beacon positioning systems, e.g. GPS
• CPC Class Codes: B64U 50/37 Charging when not in flight
• CPC Class Codes: B64U 80/25 for recharging batteries; for refuelling
• CPC Class Codes: B64U 80/40 for two or more UAVs
• CPC Class Codes: G05D 1/0202 specially adapted to aircraft
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: G06N 3/008 based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
• CPC Class Codes: G06N 3/044 Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: Y10S 901/01 Mobile robot

Abstract

Aspects of the present disclosure relate to counteracting environmental threat conditions. At least two unmanned air vehicle (UAV) drones are deployed to a target location, the target location being associated with a species. At least one robot is deployed to the target location, wherein the at least one robot mimics an appearance of the species. Sensor data is collected from the at least two UAV drones. The sensor data is analyzed to determine whether a threat condition exists. In response to a determination of the threat condition, the at least one robot is repositioned to counteract the threat condition.

Claims

1. A system comprising:

at least two unmanned air vehicle (UAV) drones;

at least one robot; and

a computer system including at least one memory component and a processor, wherein the processor is configured to perform a method comprising;

deploying the at least two UAV drones to a target location, the target location being associated with a species;

deploying the at least one robot to the target location, wherein the at least one robot mimics an appearance of the species;

collecting sensor data from the at least two UAV drones;

analyzing the sensor data to determine whether a threat condition exists; and

repositioning, in response to a determination that the threat condition exists, the at least one robot to counteract the threat condition.

2. The system of claim 1, further comprising:

identifying a location associated with the threat condition; and

collecting, in response to identifying the location associated with the threat condition, video data from a UAV drone of the at least two UAV drones at the location associated with the threat condition.

3. The system of claim 1, wherein repositioning the at least one robot to counteract the threat condition further comprises:

identifying a location associated with the threat condition; and

repositioning the at least one robot in a direction toward the location of the threat condition.

4. The system of claim 1, wherein repositioning the at least one robot to counteract the threat condition further comprises:

identifying a location associated with the threat condition; and

herding the species in a direction away from the location associated with the threat condition.

5. The system of claim 1, wherein the at least two UAV drones and at least one robot are deployed to the target location based on a Global Positioning System (GPS) tag included in each of the species.

6. The system of claim 1, wherein the sensor data is collected from a video camera, where analyzing the sensor data further comprises:

determining, using a statistically generated model, a classification of a feature of at least one frame of the sensor data collected from the video camera;

calculating a match certainty for the classification;

comparing the match certainty to a match certainty threshold; and

determining, in response to the match certainty exceeding the match certainty threshold, that the threat condition exists.

7. The system of claim 1, wherein the sensor data is collected from an infrared camera, where analyzing the sensor data further comprises:

determining a temperature of an object included in a thermogram of the sensor data;

comparing the temperature of the object to a temperature threshold;

determining, in response to the temperature of the object exceeding the temperature threshold, that the object is a lifeform;

determining, in response to a determination that the object is a lifeform, a shape of the object in the thermogram;

determining, using a statistically generated model, a match certainty of the shape to a human shape;

comparing the match certainty to a match certainty threshold; and

determining, in response to the match certainty exceeding the match certainty threshold, that a threat condition exists.

8. The system of claim 1, further comprising a plurality of charging stations disposed in a vicinity around the species, wherein the method further comprises:

receiving, from a UAV drone of the at least two drones, an indication of a low battery level;

determining, in response to the indication of the low battery level, a position of the UAV drone and each charging station;

identifying, based on the position of the UAV drone and each charging station, a charging station of the plurality of charging stations nearest to the UAV drone; and

deploying the UAV drone to the charging station nearest to the UAV drone.

9. A method comprising:

deploying at least two unmanned air vehicle (UAV) drones to a target location, the target location being associated with a species;

deploying at least one robot to the target location, wherein the at least one robot mimics an appearance of the species;

collecting sensor data from the at least two UAV drones;

analyzing the sensor data to determine whether a threat condition exists; and

repositioning, in response to a determination that the threat condition exists, the at least one robot to counteract the threat condition.

10. The method of claim 9, further comprising:

identifying a location associated with the threat condition; and

collecting, in response to identifying the location associated with the threat condition, video data from a UAV drone of the at least two UAV drones at the location associated with the threat condition.

11. The method of claim 9, wherein repositioning the at least one robot to counteract the threat condition further comprises:

identifying a location associated with the threat condition; and

repositioning the at least one robot in a direction toward the location of the threat condition.

12. The method of claim 9, wherein repositioning the at least one robot to counteract the threat condition further comprises:

identifying a location associated with the threat condition; and

herding the species in a direction away from the location associated with the threat condition.

13. The method of claim 9, wherein the at least two UAV drones and at least one robot are deployed to the target location based on a Global Positioning System (GPS) tag included in each of the species.

14. The method of claim 9, wherein the sensor data is collected from a video camera, where analyzing the sensor data further comprises:

determining, using a statistically generated model, a classification of a feature of at least one frame of the sensor data collected from the video camera;

calculating a match certainty for the classification;

comparing the match certainty to a match certainty threshold; and

determining, in response to the match certainty exceeding the match certainty threshold, that the threat condition exists.

15. The method of claim 9, further comprising:

receiving, from a UAV drone of the at least two UAV drones, an indication of a low battery level;

determining, in response to the indication of the low battery level, a position of the UAV drone and a position of each of a plurality of charging stations disposed throughout an area;

identifying, based on the position of the UAV drone and each charging station, a charging station of the plurality of charging stations nearest to the UAV drone; and

deploying the UAV drone to the charging station nearest to the UAV drone.

16. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:

deploying at least two UAV drones to a target location, the target location being associated with a species;

deploying at least one robot to the target location, wherein the at least one robot mimics an appearance of the species;

collecting sensor data from the at least two UAV drones;

analyzing the sensor data to determine whether a threat condition exists; and

repositioning, in response to a determination that the threat condition exists, the at least one robot to counteract the threat condition.

17. The computer program product of claim 16, wherein the method further comprises:

identifying a location associated with the threat condition; and

collecting, in response to identifying the location associated with the threat condition, video data from a UAV drone of the at least two UAV drones at the location associated with the threat condition.

18. The computer program product of claim 16, wherein repositioning the at least one robot to counteract the threat condition further comprises:

identifying a location associated with the threat condition; and

repositioning the at least one robot in a direction toward the location of the threat condition.

19. The computer program product of claim 16, wherein the at least two UAV drones and at least one robot are deployed to the target location based on a Global Positioning System (GPS) tag included in each of the species.

20. The computer program product of claim 16, wherein the sensor data is collected from a video camera, where analyzing the sensor data further comprises:

determining, using a statistically generated model, a classification of a feature of at least one frame of the sensor data collected from the video camera;

calculating a match certainty for the classification;

comparing the match certainty to a match certainty threshold; and

determining, in response to the match certainty exceeding the match certainty threshold, that the threat condition exists.