PARKING SPACE CONTROL METHOD AND SYSTEM WITH UNMANNED PAIRED AERIAL VEHICLE (UAV)

• US 20170161961A1
• Filed: 11/27/2016
• Published: 06/08/2017
• Est. Priority Date: 12/07/2015
• Status: Abandoned Application

• Current Assignee: Paul Salsberg
• Original Assignee: Paul Salsberg
• Inventors: Salsberg, Paul
• Application Number:
  US15/361,469
• Publication Number:
  US 20170161961A1
• Time in Patent Office: Days
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• 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: G06V 20/13 Satellite images
• CPC Class Codes: G06V 20/17 taken from planes or by drones
• CPC Class Codes: G06V 20/176 Urban or other man-made structures
• CPC Class Codes: G06V 20/182 Network patterns, e.g. roads or rivers
• 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: G07B 1/08 portable
• CPC Class Codes: G07B 15/00 Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points handling coins or valuable papers, e.g. banknotes, G07D; apparatus for vending or hiring articles or services activated by coins, credit cards, paper currency or the like G07F7/00, G07F17/00
• CPC Class Codes: G07B 15/02 taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems G07B15/06 takes precedence; taximeters G07B13/00; parking meters per se G07F17/24; car rental systems per se G07B15/00
• CPC Class Codes: H04N 7/183 for receiving images from a single remote source

Abstract

A method for parking space control including the steps of: a) flying a drone at regular intervals along a predefined path that covers an area of a parking lot; b) scanning and registering the parking lot; c) using, by software, features detection techniques as a part of image analysis algorithms; d) scanning and searching data from the parking lot for similarities within a given time period to form an analysis; e) determining, by the analysis, two outcomes for a specific parking lot including either a new vehicle is parked or an old vehicle is still located at the same parking lot; f) registering new vehicles at the time of detection; g) registering and checking longer parked vehicles'"'"' stay time for violation; h) determining if there is a violation; i) flagging and marking the vehicle(s) on a smart phone or tablet for an officer to view, locate, and ticket, if the answer to step h is yes; j) determining if the parking time exceeds the one allowed in the area of the parking lot; k) flagging ticket alerts on the program and emailing to the supervisor for evaluation and printing, if answer to step j is yes; l) determining if a vehicle can be exempt from the rules; m) deciding, by the supervisor, to generate a ticket with a click of a button, if answer to step 1 is no; n) creating, by the supervisor, the ticket; o) walking to the vehicle in order to assign the ticket thereto; and p) repeating cycle after an hour or as approved.

Claims

1. A method for parking space control, comprising the steps of:

a) flying a drone at regular intervals along a predefined path that covers an area of a parking lot;

b) scanning and registering the parking lot;

c) using, by software, features detection techniques as a part of image analysis algorithms;

d) scanning and searching data from the parking lot for similarities within a given time period to form an analysis;

e) determining, by the analysis, two outcomes for a specific parking lot including one of a new vehicle is parked and an old vehicle is still located at a same parking lot;

f) registering new vehicles at the time of detection;

g) registering and checking longer parked vehicles'"'"' stay time for violation;

h) determining if there is a violation;

i) flagging and marking the vehicle on a smart phone or tablet for an officer to view, locate, and ticket, if the answer to step h is yes;

j) determining if the parking time exceeds that allowed in the area of the parking lot;

k) flagging ticket alerts on program and emailing to a supervisor for evaluation and printing, if answer to step j is yes;

l) determining if a vehicle can be exempt from the rules;

m) deciding, by the supervisor, to generate a ticket with a click of a button, if answer to step 1 is no;

n) creating, by the supervisor, the ticket;

o) walking to the vehicle in order to assign the ticket thereto; and

p) repeating cycle after one of an hour and as approved.

2. The method of claim 1, wherein the vehicle that can be exempt from the rules include personnel cars, other types of parked vehicles, and vehicles of vendors.

3. A method for controlling a parking lot, comprising the steps of:

a) inputting data;

b) image detecting analyzing with feature detection, key point detector, and descriptor extractor algorithm;

c) extracting key points;

d) decision analyzing; and

e) defining results and channeling analysis towards an application in parking areas'"'"' surveillance methodologies.

4. The method of claim 3, wherein said inputting step includes inputting three images at a beginning of each step of an analysis at a specific waypoint.

5. The method of claim 3, wherein said inputting step includes inputting two images if a drone is arriving at a waypoint for the first time during a monitoring flight.

6. The method of claim 3, wherein said extracting step includes extracting areas with specific location and magnitude in image data defining features in each image generated during image detecting.

7. The method of claim 3, wherein said analyzing step includes processing and interpreting results for the all three images.

8. The method of claim 3, wherein said analyzing step includes comparing distances between key points for the three images in order to define significant differences between them.

9. The method of claim 3, wherein said analyzing step includes removing noises generated by environment and return key points having only significant features.

10. The method of claim 3, wherein said defining step includes defining results and channeling analysis towards the application in parking areas'"'"' surveillance methodologies.

11. The method of claim 3, wherein the results include one of:

a) no differences detected between the three images, and as such, a vehicle is not parked and the parking lot is empty;

b) difference detected between all of the three images, and as such, the parking lot is either vacated or there is an arrival of a new vehicle; and

c) differences detected between an original image, but not between a current image and a previous image, and as such, there is an old vehicle that had been detected last time and still occupies the parking lot, so thereby do one of issue a ticket and note an update on duration of parking since registration.

12. The method of claim 11, wherein the original image is taken during a set-up flight when the parking lot is empty, and as such, is used as the base state, and as such, is considered a normal state of the area with no object of interest.

13. The method of claim 11, wherein the previous image is taken during a previous flight of the drone for the waypoint of interest.

14. The method of claim 11, wherein the current image is taken during a current flight of the drone for the waypoint of interest.

15. A system for controlling a parking lot, comprising:

a) a managing device;

b) an image capture device;

c) a storage device; and

d) a user device;

wherein said user device is linkable together by network communication links.

16. The system of claim 15, wherein said managing device includes a controller;

and

wherein said controller is part of, or associated with, said managing device.

17. The system of claim 16, wherein said controller is adapted for controlling an analysis of video data received by an UAV camera.

18. The system of claim 17, wherein said controller includes a processor;

and

wherein said processor controls overall operation of said managing device by execution of processing instructions that are stored in a memory connected to said processor.

19. The system of claim 18, wherein said memory represents any type of tangible computer readable medium including at least one of random access memory (RAM), read only memory (ROM), magnetic disk or tape, optical disk, flash memory, and holographic memory.

20. The system of claim 18, wherein said memory includes a combination of random access memory and read only memory.

21. The system of claim 18, wherein said processor includes at least one of a single-core processor, a dual-core processor, a multiple-core processor, a digital processor and cooperating math coprocessor, and a digital controller.

22. The system of claim 15, wherein said managing device is a networked device.

23. The system of claim 22, wherein said networked device of said managing device is at least one of a vehicle capture module and a user device.

24. The system of claim 22, wherein said networked device of said managing device is at least one of a central server, a networked computer, and distributed throughout said network.

25. The system of claim 18, wherein said processor, according to instructions contained in said memory, performs vehicle detection, matching phases, and changes in color, position, size, and angle of position.

26. The system of claim 18, wherein said memory stores a video buffering module;

and

wherein said video buffering module of said memory receives a video of a select parking area that is captured by a video capture device.

27. The system of claim 26, wherein said memory stores an image buffering module;

and

wherein said image buffering module of said memory receives images provided by said video capture device.

28. The system of claim 18, wherein said memory stores a vehicle matching module;

and

wherein said vehicle matching module of said memory matches a vehicle with a vehicle in image data.

29. The system of claim 18, wherein said memory stores a stationary vehicle detection module that;

and

wherein said stationary vehicle detection of said memory detects objects and/or vehicles within a field of view of said UAV camera.

30. The system of claim 18, wherein said memory stores a timing module;

and

wherein said timing module of said memory initiates a timer for measuring a duration that a detected vehicle remains parked in a space.

31. The system of claim 18, wherein said memory stores a violation detection module;

and

wherein said violation detection module of said memory checks if parking time exceeds that allowed in an area, and if so, a ticket alert is sent to a supervisor for evaluation and print.

32. The system of claim 31, wherein said ticket alert is stored in at least one of a single module and as multiple modules embodied in different devices.

33. The system of claim 18, wherein a UAV programming module encompasses any collection of, or set of, software instructions executable by said managing device or another digital system so as to configure said processor or said another digital system to perform a task that is an intent of said software instructions.

34. The system of claim 33, wherein said software instructions are stored in a storage medium including at least one of a RAM, a hard disk, and an optical disk.

35. The system of claim 33, wherein said software instructions encompass firmware that is software stored on a ROM.

36. The system of claim 33, wherein said software instructions are organized in various ways, including software components organized as libraries, Internet-based programs stored on a remote server, source code, interpretive code, object code, and directly executable code.

37. The system of claim 33, wherein said software instructions invoke a system-level code or calls to other software residing on a server or other location to perform certain functions.

38. The system of claim 15, wherein various components of said managing device are connected by a bus.

39. The system of claim 15, wherein said managing device includes at least one communication interface.

40. The system of claim 39, wherein said at least one communication interface includes network interfaces for communicating with external devices.

41. The system of claim 39, wherein said at least one communication interface includes at least one of a modem, a router, a cable, and an Ethernet port.

42. The system of claim 39, wherein said at least one communication interface is adapted to receive video and/or image data as input.

43. The system of claim 15, wherein said managing device includes at least one special purpose or general purpose computing device.

44. The system of claim 43, wherein said at least one special purpose or general purpose computing device is a server computer or digital front end (DFE), or any other computing device capable of executing instructions.

45. The system of claim 15, wherein said managing device is connected to an image source for inputting and/or receiving video data and/or image data in electronic format.

46. The system of claim 45, wherein said image source includes an image capture device.

47. The system of claim 46, wherein said image capture device of said image source includes at least one camera installed on a UAV that captures image and video data from the parking area and/or from a parking area of interest.

48. The system of claim 47, wherein said UAV flies at regular intervals along a predefined path that covers the area.

49. The system of claim 17, wherein said UAV camera includes near infrared (NIR) capabilities at a low-end portion of a near-infrared spectrum (700 nm-1000 nm) for performing at night in parking areas without external sources of illumination.