Drone device security system

• US 10,183,749 B2
• Filed: 06/25/2018
• Issued: 01/22/2019
• Est. Priority Date: 02/28/2014
• Status: Active Grant

• Current Assignee: Lucas Myslinski
• Original Assignee: Lucas Myslinski
• Inventors: Myslinski, Lucas J.
• Primary Examiner(s): Anwari, Maceeh
• Application Number:
  US16/017,168
• Publication Number:
  US 20180305015A1
• Time in Patent Office: 211 Days
• Field of Search: 701 3
• CPC Class Codes: B64D 47/02 Arrangements or adaptations of signal or lighting devices
• CPC Class Codes: B64D 5/00 Aircraft transported by aircraft, e.g. for release or reberthing during flight flying units formed by separate aircraft B64C37/02
• CPC Class Codes: B64U 20/10 for stealth, e.g. reduction of cross-section detectable by radars
• CPC Class Codes: B64U 20/50 Foldable or collapsible UAVs with frangible components B64U20/30
• 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 2201/10 autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
• CPC Class Codes: B64U 80/25 for recharging batteries; for refuelling
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0094 involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
• 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: G06F 40/205 Parsing
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0282 : Rating or review of business operators or products
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: G06Q 50/26 : Government or public services business processes related to the transportation industry G06Q50/40
• CPC Class Codes: G06T 2207/10016 : Video; Image sequence
• CPC Class Codes: G06T 2207/10032 : Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/30196 : Human being; Person
• CPC Class Codes: G06T 2207/30232 : Surveillance
• CPC Class Codes: G06T 7/20 : Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 20/40 : in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/52 : Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/10 : Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G08B 21/18 : Status alarms G08B21/02 takes precedence
• CPC Class Codes: H04N 5/77 : between a recording apparatus and a television camera
• CPC Class Codes: H04N 5/772 : the recording apparatus and the television camera being placed in the same enclosure
• CPC Class Codes: H04N 7/183 : for receiving images from a single remote source
• CPC Class Codes: H04N 7/188 : Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position signal generation from motion picture films H04N5/253

Abstract

A fact checking system utilizes social networking information and analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The social networking fact checking system automatically monitors information, processes the information, fact checks the information and/or provides a status of the information, including automatically modifying a web page to include the fact check results. The fact checking system is able to be implemented utilizing a drone device.

Claims

1. A system comprising:

a. a controller; and

b. an aerial drone device configured to acquire content and communicate with the controller, wherein the aerial drone device includes a device body configured to transition from a folded configuration to an unfolded configuration and from the unfolded configuration to the folded configuration, wherein the device body includes components capable of folding such that the aerial drone device has a smaller storage footprint when in the folded configuration than when in the unfolded configuration, wherein the aerial drone device is configured to fly in the unfolded configuration, wherein while in the folded configuration the aerial drone device appears to look like another object, wherein the device body is configured to secure at least one power supply, the at least one power supply configured to supply power to;

at least one motor which causes at least one propeller to move,

a plurality of information acquisition components, wherein a first information acquisition component of the plurality of information acquisition components is positioned in an opposite direction of a second information acquisition component of the plurality of information acquisition components, wherein the plurality of information acquisition components are configured to acquire external information, and

at least one camera,

the at least one camera configured to acquire the content including images and/or videos, further wherein the at least one camera is configured to scan an area,

wherein the aerial drone device further includes;

a memory configured for storing an application, the application configured to;

process the content acquired by the at least one camera and the external information acquired by the plurality of information acquisition components;

acquire depth information using the at least one camera, the plurality of information acquisition components, or any combination thereof;

direct the aerial drone device to navigate based on the content from the at least one camera, the external information from the plurality of information acquisition components, or any combination thereof, including avoiding at least one obstacle;

detect a plurality of objects simultaneously;

track at least one object utilizing the depth information;

generate a depth map using the depth information, wherein the depth map is used to track the at least one object;

predict a trajectory of the at least one object;

track the at least one object based on the trajectory when a view of the at least one object is obstructed; and

determine and follow a flight path; and

a processor configured to process the application,

wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and/or police information and detecting keywords within the social networking information and/or the police information, and when a number of keywords detected is above a threshold, the aerial drone device moves based on the keywords.

2. The system of claim 1 wherein the aerial drone device is configured to determine when to patrol an area by analyzing the social networking information and/or the police information and detecting one or more keywords within the social networking information and/or the police information.

3. The system of claim 1 wherein the aerial drone device includes a storage compartment configured to store a tracking device, wherein the tracking device is deployed by the aerial drone device by dropping the tracking device onto an object and tracking the tracking device.

4. The system of claim 1 wherein the aerial drone device includes a shielding component configured to protect the aerial drone device, wherein the shielding component includes one or more extendible wings.

5. The system of claim 1 wherein the aerial drone device is configured to communicate with a security system which includes one or more motion sensors and one or more breach detectors, wherein when the one or more motion sensors or the one or more breach detectors are triggered, the security system sends a signal and identification data to the aerial drone device.

6. The system of claim 1 wherein the aerial drone device is configured to acquire base images of the area and compare the base images of the area with the content which includes a current image of the area to determine if the breach has occurred.

7. The system of claim 1 wherein the aerial drone device is configured to anticipate actions of a suspect by analyzing surroundings based on scanning the area and accessing mapping data.

8. The system of claim 1 wherein the aerial drone device is configured to summarize the content by selecting one or more first items of the content and discarding one or more second items of the content.

9. The system of claim 1 wherein aerial drone device is configured to summarize the content by storing images and/or videos of the content in an order, wherein the order is based on importance as established by one or more keywords.

10. The system of claim 1 wherein the aerial drone device is configured to automatically re-position itself to minimize visual artifacts.

11. The system of claim 1 wherein the aerial drone device is configured to automatically re-position itself to avoid an obstruction by generating the depth map and utilizing an obstruction threshold, wherein when an amount of obstruction is above the obstruction threshold, the aerial drone device moves to reduce the amount of obstruction.

12. The system of claim 11 wherein the aerial drone device continues to re-position itself to find a lowest amount of obstruction.

13. The system of claim 1 wherein the aerial drone device implements privacy protections by blurring or blocking one or more aspects of the content.

14. The system of claim 1 wherein the aerial drone device tags the content as location-specific information.

15. The system of claim 1 wherein the aerial drone device compares the content with pre-recorded content and presents differences within the content by highlighting the differences.

16. The system of claim 1 wherein the aerial drone device automatically sends the content via a social network and includes a hashtag with the content.

17. The system of claim 1 wherein the aerial drone device is configured to communicate the content with a neighboring security system.

18. A method of utilizing an aerial drone device to acquire content and communicate with a device, the method comprising:

a. receiving a signal from the device; and

b. moving to a location based on the signal;

c. automatically re-positioning the aerial drone device to avoid an obstruction,

wherein the aerial drone device includes a body configured to secure at least one power supply, the at least one power supply configured to supply power to;

at least one motor which causes at least one propeller to move,

a plurality of information acquisition components, wherein a first information acquisition component of the plurality of information acquisition components is positioned in an opposite direction of a second information acquisition component of the plurality of information acquisition components, wherein the plurality of information acquisition components are configured to acquire external information, and

at least one camera,

the at least one camera configured to acquire the content including images and/or videos, further wherein the at least one camera is configured to scan an area,

d. processing the content acquired by the at least one camera and the external information acquired by the plurality of information acquisition components;

e. acquiring depth information using the at least one camera, the plurality of information acquisition components, or any combination thereof;

f. directing the aerial drone device to navigate based on the content from the at least one camera, the external information from the plurality of information acquisition components, or any combination thereof;

g. detecting a plurality of objects simultaneously;

h. tracking at least one object utilizing the depth information;

i. generating a depth map using the depth information, wherein the depth map is used to track the at least one object;

j. predicting a trajectory of the at least one object;

k. tracking the at least one object based on the trajectory when a view of the at least one object is obstructed;

l. determining and follow a flight path;

m. transitioning from a folded configuration to an unfolded configuration and from the unfolded configuration to the folded configuration, wherein the aerial drone device includes components capable of folding such that the aerial drone device has a smaller storage footprint when in the folded configuration than when in the unfolded configuration, wherein the aerial drone device is configured to fly in the unfolded configuration, wherein while in the folded configuration the aerial drone device appears to look like another object; and

n. determining when to patrol an area by analyzing social networking information and/or police information and detecting keywords within the social networking information and/or the police information, and when a number of keywords detected is above a threshold, the aerial drone device moves based on the keywords.

19. An aerial drone device comprising:

d. a device body configured to transition from a folded configuration to an unfolded configuration and from the unfolded configuration to the folded configuration, wherein the device body includes components capable of folding such that the aerial drone device has a smaller storage footprint when in the folded configuration than when in the unfolded configuration, wherein the aerial drone device is configured to fly in the unfolded configuration, wherein while in the folded configuration the aerial drone device appears to look like another object;

e. at least one motor coupled to the device body;

f. at least one propeller coupled to the at least one motor;

g. at least one camera coupled to the device body, wherein the at least one camera is configured to acquire content;

h. a plurality of information acquisition components coupled to the device body, wherein a first information acquisition component of the plurality of information acquisition components is positioned in an opposite direction of a second information acquisition component of the plurality of information acquisition components, wherein the plurality of information acquisition components are configured to acquire external information;

i. at least one power supply configured to provide power to the at least one motor, the at least one camera, and the plurality of information acquisition components;

g. a memory configured to store and application, the application configured to;

i. process the content acquired by the at least one camera and the external information acquired by the plurality of information acquisition components;

ii. direct the aerial drone device to navigate an area based on the content from the at least one camera, the external information from the plurality of information acquisition components, or any combination thereof, including avoiding at least one obstacle;

iii. acquire depth information using the at least one camera, the plurality of information acquisition components, or any combination thereof;

iv. detect a plurality of objects simultaneously;

v. track at least one object utilizing the depth information;

vi. generate a depth map using the depth information, wherein the depth map is used to track the at least one object;

vii. predict a trajectory of the at least one object; and

viii. track the at least one object based on the trajectory when a view of the at least one object is obstructed; and

h. a processor configured to process the application,

wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and/or police information and detecting keywords within the social networking information and/or the police information, and when a number of keywords detected is above a threshold, the aerial drone device moves based on the keywords.