Drone device for news reporting

• US 10,301,023 B2
• Filed: 06/25/2018
• Issued: 05/28/2019
• 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:
  US16/017,536
• Publication Number:
  US 20180305017A1
• Time in Patent Office: 337 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 computing device; and

an aerial drone device configured to acquire content and communicate with the computing device, wherein the aerial drone device includes a body configured to transition from a first configuration to a second configuration and from the second configuration to the first configuration, wherein the body includes components capable of folding such that the aerial drone device is more compact when in the first configuration than when in the second configuration, wherein while in the first configuration the aerial drone device appears to look like another object, wherein the body is further 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,

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, and

a plurality of information acquisition components coupled to the body, wherein a first information acquisition component of the plurality of information acquisition components is positioned in different direction than 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,

wherein the aerial drone device is further 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;

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 an obstruction; and

track at least one object; and

generate a depth map using the depth information, wherein the depth map is used to avoid the obstruction, track the at least one object, or any combination thereof,

wherein the aerial drone device is configured to automatically re-position itself to avoid the obstruction by generating the depth map and utilizing an obstruction threshold, wherein generating the depth map includes using an object size calculation analysis, wherein when an amount of obstruction is above the obstruction threshold, the aerial drone device moves to reduce the amount of obstruction.

2. The system of claim 1 further comprising at least one additional aerial drone device to comprise a plurality of aerial drone devices, wherein the plurality of aerial drone devices are positioned in different locations around a city to provide faster access to the content, wherein the content comprises news content.

3. The system of claim 1 wherein when a number of sources above a threshold provide same or similar information, the aerial drone device moves.

4. The system of claim 1 wherein when a number of sources in a designated class above a threshold provide same or similar information, the aerial drone device moves.

5. The system of claim 1 further comprising at least one additional aerial drone device to comprise a plurality of aerial drone devices, wherein the plurality of aerial drone devices are utilized to determine a location of a source of a sound based on how long the sound takes to reach a subset of drones of the plurality of drones.

6. The system of claim 1 wherein the aerial drone device generates a story by sending the content via a social network.

7. The system of claim 1 wherein the aerial drone device and/or the computing device automatically summarize the content by generating a plurality of video summaries.

8. The system of claim 1 wherein the aerial drone device and/or the computing device automatically filter the content by deleting dead time, wherein dead time is determined based on a delta between a set of frames, and when the delta is below a delta threshold, the set of frames is deleted.

9. The system of claim 1 wherein the aerial drone device and/or the computing device are configured to determine an accuracy of news content by comparing the news content with the content acquired by the aerial drone device.

10. The system of claim 1 wherein the aerial drone device and/or the computing device are configured to classify objects detected in the content into categories and sub-categories within the categories.

11. The system of claim 1 wherein a highlight of the content is determined by extracting a video clip and/or an image of the content.

12. The system of claim 1 wherein the aerial drone device is configured to acquire the content from a plurality of angles.

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

14. The system of claim 1 wherein the aerial drone device continues to re-position itself to find a lowest amount of obstruction.

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

16. The system of claim 1 wherein the at least one object comprises a tracking device.

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

receiving location information;

moving the aerial drone device based on the location information;

acquiring the content with the aerial drone device;

acquiring external information with the aerial drone device;

processing the content acquired by the aerial drone device, the external information acquired by the aerial drone device, or any combination thereof;

determining depth information based on the content acquired by the aerial drone device, the external information acquired by the aerial drone device, or any combination thereof;

navigating the aerial drone device based on the content acquired by the aerial drone device, the external information acquired by the aerial drone device, or any combination thereof;

generating a depth map using the depth information;

tracking at least one object;

automatically re-positioning the aerial drone device to avoid an obstruction by generating the depth map and utilizing an obstruction threshold, wherein generating the depth map includes using an object size calculation analysis, wherein when an amount of obstruction is above the obstruction threshold, the aerial drone device moves to reduce the amount of obstruction; and

transitioning from a first configuration to a second configuration and from the second configuration to the first configuration, wherein a body of the aerial drone device includes components capable of folding such that the aerial drone device is more compact when in the first configuration than when in the second configuration, wherein while in the first configuration the aerial drone device appears to look like another object,

wherein the 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, 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.

18. The method of claim 17 wherein tracking the at least one object includes tracking a tracking device.

19. The method of claim 17 further comprising determining a current location using GPS.

20. An aerial drone device comprising:

a device body configured to transition from a first configuration to a second configuration and from the second configuration to the first configuration, wherein the device body includes components capable of folding such that the aerial drone device is more compact when in the first configuration than when in the second configuration, wherein while in the first configuration the aerial drone device appears to look like another object;

at least one motor coupled to the device body;

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

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

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 different direction than 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;

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;

a memory configured to store 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;

direct the aerial drone device to move to an area based on the content from the at least one camera, the processed external information from the plurality of information acquisition components, or any combination thereof;

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

generate a depth map using the depth information;

track at least one object; and

automatically re-positioning the aerial drone device to avoid an obstruction by generating the depth map and utilizing an obstruction threshold, wherein generating the depth map includes using an object size calculation analysis, wherein when an amount of obstruction is above the obstruction threshold, the aerial drone device moves to reduce the amount of obstruction; and

a processor configured to process the application.