CN115482670A - Unmanned aerial vehicle-based vehicle illegal parking identification method and system - Google Patents
Unmanned aerial vehicle-based vehicle illegal parking identification method and system Download PDFInfo
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- CN115482670A CN115482670A CN202211068747.1A CN202211068747A CN115482670A CN 115482670 A CN115482670 A CN 115482670A CN 202211068747 A CN202211068747 A CN 202211068747A CN 115482670 A CN115482670 A CN 115482670A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64C—AEROPLANES; HELICOPTERS
- B64C39/00—Aircraft not otherwise provided for
- B64C39/02—Aircraft not otherwise provided for characterised by special use
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
Abstract
The invention discloses a vehicle illegal parking identification method and system based on an unmanned aerial vehicle, belonging to the urban management of the unmanned aerial vehicle, aiming at solving the technical problems of efficiently patrolling any area, identifying the vehicle illegal parking in a specified area and improving the real-time performance and efficiency of the illegal parking identification, and the adopted technical scheme is as follows: the method comprises the steps that an unmanned aerial vehicle flies according to a preset air route, a real-time video stream is transmitted to an urban low-altitude intelligent sensing platform through a 5G network, and the urban low-altitude intelligent sensing platform conducts vehicle identification on the real-time video stream through a vehicle illegal parking identification algorithm; after the vehicle is identified, the urban low-altitude intelligent sensing platform informs the unmanned aerial vehicle to continuously take a plurality of vehicle photos in situ, and whether the vehicle is static or not is analyzed according to the vehicle photos; when the vehicle is static, the unmanned aerial vehicle is controlled by the remote controller to zoom in the lens to shoot the vehicle photo again, vehicle information is obtained according to the vehicle photo, and the vehicle information is pushed to the city operation management platform through the interface.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle urban management, in particular to a vehicle illegal parking identification method and system based on an unmanned aerial vehicle.
Background
In the current urban roadside, parking lot or park, the vehicle illegal parking is mainly based on mobile patrol of traffic police, patrol of managers or fixed-point cameras, and the illegal parking identification methods are only suitable for specific scenes and have the defects of occupying labor or single monitoring method and mode and the like, so that the urban roadside, parking lot or park can not cover the non-monitored area or the places where the personnel can not patrol frequently.
Therefore, how to efficiently patrol any region and recognize vehicle illegal parking in a specified region, and improving the real-time performance and efficiency of illegal parking recognition is a technical problem to be solved urgently at present.
Disclosure of Invention
The invention provides a vehicle illegal parking identification method and system based on an unmanned aerial vehicle, and aims to solve the problems that how to efficiently patrol any region, how to identify the illegal parking of vehicles in a specified region and how to improve the real-time performance and efficiency of illegal parking identification.
The technical task of the invention is realized in the following way, the method is that the unmanned aerial vehicle, the remote controller, the urban low-altitude intelligent sensing platform and the urban operation management platform are connected through a 5G network, the unmanned aerial vehicle flies according to a preset air route and transmits a real-time video stream to the urban low-altitude intelligent sensing platform through the 5G network, and the urban low-altitude intelligent sensing platform identifies the vehicle by the real-time video stream through a vehicle parking identification algorithm; after the vehicles are identified, the urban low-altitude intelligent sensing platform informs the unmanned aerial vehicle to continuously take a plurality of vehicle pictures in situ, and whether the vehicles are static or not is analyzed according to the vehicle pictures; when the vehicle is static, the unmanned aerial vehicle is controlled by the remote controller to zoom in the lens to shoot the vehicle photo again, vehicle information is obtained according to the vehicle photo, and the vehicle information is pushed to the city operation management platform through the interface.
Preferably, the method specifically comprises the following steps:
the unmanned aerial vehicle transmits the video stream to a streaming media server of the urban low-altitude intelligent sensing platform;
identifying the video stream file through a vehicle illegal parking identification algorithm, and judging whether the vehicle is static:
if the vehicle is static, acquiring longitude and latitude information of the vehicle through an H20T laser ranging function of the unmanned aerial vehicle;
the urban low-altitude intelligent sensing platform inquires and acquires whether the position information belongs to a no-parking area according to the longitude and latitude information of the vehicle:
if yes, the urban low-altitude intelligent sensing platform sends a command of zooming in a lens to shoot a vehicle photo to the unmanned aerial vehicle;
the unmanned aerial vehicle transmits the shot vehicle photos to the urban low-altitude intelligent sensing platform, and vehicle information is identified through a vehicle violation identification algorithm;
and pushing the violation vehicle information to the city operation management platform through the API.
Preferably, the video stream file is identified by a vehicle violation identification algorithm as follows:
decoding the video stream through a vehicle illegal parking recognition algorithm and preprocessing the video stream frame by using an opencv library to obtain an image matrix;
inputting the image matrix into a trained yolov5s neural network;
acquiring coordinate data of the vehicle in the image by the yolov5s neural network;
marking coordinate data of the vehicle in the image through an opencv library to obtain a vehicle image with a target frame;
and tracking and judging the monitored vehicle by using a deepsort method, and further determining whether the vehicle is static.
Preferably, the vehicle information is identified by a vehicle violation identification algorithm as follows:
preprocessing the vehicle picture through a vehicle illegal parking recognition algorithm to obtain a preprocessed vehicle picture;
inputting the preprocessed vehicle picture into a trained yolov5s neural network, and outputting the license plate position by the yolov5s neural network;
intercepting a license plate picture from a vehicle picture according to the license plate position;
and recognizing the character information on the license plate picture by using an OCR technology, acquiring vehicle information, and storing the vehicle information to a database.
Preferably, the vehicle information includes a vehicle picture, a license plate picture and vehicle position information.
Preferably, the vehicle photos are preprocessed by the vehicle parking violation recognition algorithm, and the preprocessed vehicle photos comprise letterbox and resize.
An unmanned aerial vehicle-based vehicle parking violation identification system comprises,
the unmanned aerial vehicle is used for flying according to a preset air route and shooting real-time video streams and vehicle photos;
the remote controller is used for controlling the unmanned aerial vehicle through the private communication protocol of the Xinjiang province;
the urban low-altitude intelligent sensing platform is used for tracking the vehicle through video streaming, further judging whether the vehicle is static or not and video-recording vehicle information according to the vehicle photo;
and the city operation management platform is used for receiving the violation vehicle information.
Preferably, the urban low-altitude intelligent perception platform comprises a video stream recognition unit and a vehicle photo recognition unit;
the video stream identification unit is used for identifying vehicles in the video stream;
the vehicle photo recognition unit is used for recognizing a vehicle picture, a license plate number picture and vehicle position information in the vehicle photo.
Wherein the video stream identification unit includes,
the first preprocessing module is used for decoding the video stream through a vehicle illegal parking recognition algorithm and preprocessing the video stream frame by utilizing an opencv library to obtain an image matrix;
the input module I is used for inputting the image matrix into the trained yolov5s neural network;
the coordinate acquisition module is used for acquiring coordinate data of the vehicle in the image through the yolov5s neural network;
the marking module is used for marking the coordinate data of the vehicle in the image through an opencv library to obtain a vehicle image with a target frame;
the tracking module is used for tracking and judging the monitored vehicle by using a deppsort method so as to determine whether the vehicle is static or not;
the vehicle photo recognition unit includes a photo recognition unit,
the second preprocessing module is used for preprocessing the vehicle picture through a vehicle illegal parking recognition algorithm to obtain a preprocessed vehicle picture;
the input module II is used for inputting the preprocessed vehicle pictures into the trained yolov5s neural network;
the license plate position acquisition module is used for outputting the license plate position through a yolov5s neural network;
the intercepting module is used for intercepting the license plate picture from the vehicle picture according to the license plate position;
and the recognition module is used for recognizing the character information on the license plate picture by using an OCR technology, acquiring the vehicle information and storing the vehicle information to the database.
An electronic device, comprising: a memory and at least one processor;
wherein the memory has stored thereon a computer program;
the at least one processor executes the computer program stored by the memory such that the at least one processor executes the drone-based vehicle violation identification method as described above.
A computer-readable storage medium having stored thereon a computer program executable by a processor to implement a drone-based vehicle violation identification method as described above.
The unmanned aerial vehicle-based vehicle illegal parking identification method and system have the following advantages:
compared with manual inspection and road fixed monitoring facilities, the unmanned aerial vehicle intelligent monitoring system has the advantages of flexibility and multiple viewing angles, can quickly identify the license plate number through an artificial intelligence algorithm after the unmanned aerial vehicle is used for carrying out vehicle illegal parking phenomenon inspection, and further pushes the license plate number to a city operation platform, thereby effectively reducing the occurrence of illegal parking phenomenon, improving the city management efficiency and improving the overall image of the city;
and secondly, the unmanned aerial vehicle is adopted, so that the unmanned aerial vehicle has the advantages of aerial visual angle and aerial inspection, can efficiently inspect a certain area, replaces personnel or fixed-point monitoring to identify the vehicle illegal parking condition in the specified area, and improves the instantaneity and efficiency of illegal parking identification.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a vehicle parking violation identification method based on an unmanned aerial vehicle;
FIG. 2 is a block diagram of a process for identifying a video stream file by a vehicle violation identification algorithm;
FIG. 3 is a block diagram of a process for identifying vehicle information via a vehicle violation identification algorithm.
Detailed Description
The method and system for identifying vehicle parking violation based on unmanned aerial vehicle of the present invention are described in detail below with reference to the drawings and specific embodiments of the specification.
Example 1
As shown in the attached drawing 1, the embodiment provides a vehicle illegal parking recognition method based on an unmanned aerial vehicle, the method comprises the steps that the unmanned aerial vehicle, a remote controller, an urban low-altitude intelligent sensing platform and an urban operation management platform are connected through a 5G network, the unmanned aerial vehicle flies according to a preset air route and transmits a real-time video stream to the urban low-altitude intelligent sensing platform through the 5G network, and the urban low-altitude intelligent sensing platform recognizes the vehicle through a vehicle illegal parking recognition algorithm on the real-time video stream; after the vehicle is identified, the urban low-altitude intelligent sensing platform informs the unmanned aerial vehicle to continuously take a plurality of vehicle photos in situ, and whether the vehicle is static or not is analyzed according to the vehicle photos; when the vehicle is static, the unmanned aerial vehicle is controlled by the remote controller to zoom in the lens to take the picture of the vehicle again, vehicle information is obtained according to the picture of the vehicle, and the vehicle information is pushed to the city operation management platform through the interface; the method comprises the following specific steps:
s1, transmitting a video stream to a streaming media server of an urban low-altitude intelligent sensing platform;
s2, identifying the video stream file through a vehicle illegal parking identification algorithm, and judging whether the vehicle is static:
if the vehicle is static, executing the step S3;
s3, acquiring longitude and latitude information of the vehicle through an H20T laser ranging function of the unmanned aerial vehicle;
s4, inquiring and acquiring whether the position information belongs to the no-parking area or not by the urban low-altitude intelligent sensing platform according to the longitude and latitude information of the vehicle:
if yes, executing step S5;
s5, the urban low-altitude intelligent sensing platform sends an instruction of zooming in a lens to shoot a vehicle photo to the unmanned aerial vehicle;
s6, the unmanned aerial vehicle transmits the shot vehicle photos to the urban low-altitude intelligent sensing platform, and vehicle information is identified through a vehicle parking violation identification algorithm;
and S7, pushing the violation vehicle information to the city operation management platform through an API.
As shown in fig. 2, in the embodiment, the identification of the video stream file by the vehicle parking violation identification algorithm in step S2 is specifically as follows:
s201, decoding a video stream through a vehicle illegal parking recognition algorithm and preprocessing the video stream frame by using an opencv library to obtain an image matrix;
s202, inputting the image matrix into a trained yolov5S neural network;
s203, acquiring coordinate data of the vehicle in the image by a yolov5S neural network;
s204, marking coordinate data of the vehicle in the image through an opencv library to obtain a vehicle image with a target frame;
s205, tracking and judging the monitored vehicle by using a deepsort method, and further determining whether the vehicle is static.
As shown in fig. 3, the identification of the vehicle information by the vehicle violation identification algorithm in step S6 of the present embodiment is as follows:
s601, preprocessing the vehicle picture through a vehicle illegal parking recognition algorithm to obtain a preprocessed vehicle picture;
s602, inputting the preprocessed vehicle picture into a trained yolov5S neural network, and outputting the license plate position by the yolov5S neural network;
s603, capturing a license plate picture from the vehicle picture according to the license plate position;
s604, recognizing the character information on the license plate picture by using an OCR technology, acquiring vehicle information, and storing the vehicle information to a database.
The vehicle information in this embodiment includes a vehicle picture, a license plate picture, and vehicle position information.
In this embodiment, the manner of preprocessing the vehicle photo by the vehicle parking violation identification algorithm in step S601 includes letterbox and resize.
Example 2:
the embodiment provides a vehicle illegal parking identification system based on unmanned aerial vehicle, which comprises,
the unmanned aerial vehicle is used for flying according to a preset air route and shooting real-time video streams and vehicle photos;
the remote controller is used for controlling the unmanned aerial vehicle through the private communication protocol of the Xinjiang province;
the urban low-altitude intelligent sensing platform is used for tracking the vehicle through video streaming, further judging whether the vehicle is static or not and video the vehicle information according to the vehicle picture;
and the city operation management platform is used for receiving the violation vehicle information.
The urban low-altitude intelligent sensing platform in the embodiment comprises a video stream identification unit and a vehicle photo identification unit;
the video stream identification unit is used for identifying vehicles in the video stream;
the vehicle photo recognition unit is used for recognizing a vehicle picture, a license plate number picture and vehicle position information in the vehicle photo.
Wherein the video stream identification unit includes,
the first preprocessing module is used for decoding the video stream through a vehicle illegal parking recognition algorithm and preprocessing the video stream frame by utilizing an opencv library to obtain an image matrix;
the input module I is used for inputting the image matrix into the trained yolov5s neural network;
the coordinate acquisition module is used for acquiring coordinate data of the vehicle in the image through the yolov5s neural network;
the marking module is used for marking the coordinate data of the vehicle in the image through an opencv library to obtain a vehicle image with a target frame;
the tracking module is used for tracking and judging the monitored vehicle by using a deppsort method so as to determine whether the vehicle is static or not;
the vehicle photo recognition unit includes a photo recognition unit,
the second preprocessing module is used for preprocessing the vehicle picture through a vehicle illegal parking recognition algorithm to obtain a preprocessed vehicle picture;
the input module II is used for inputting the preprocessed vehicle pictures into the trained yolov5s neural network;
the license plate position acquisition module is used for outputting the license plate position through a yolov5s neural network;
the intercepting module is used for intercepting the license plate picture from the vehicle picture according to the license plate position;
and the recognition module is used for recognizing the character information on the license plate picture by using an OCR technology, acquiring the vehicle information and storing the vehicle information to the database.
Example 3
An embodiment of the present invention further provides an electronic device, including: a memory and a processor;
wherein the memory stores computer execution instructions;
the processor executes the computer-executable instructions stored by the memory, causing the processor to perform the drone-based vehicle violation identification method of any embodiment of the present invention.
The processor may be a Central Processing Unit (CPU), but may also be other general purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), array of off-the-shelf programmable gates (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. The processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the electronic device by executing or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the terminal, and the like. The memory may also include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a memory only card (SMC), a Secure Digital (SD) card, a flash memory card, at least one disk storage period, a flash memory device, or other volatile solid state memory device.
Example 4
The embodiment of the invention also provides a computer-readable storage medium, wherein a plurality of instructions are stored, and the instructions are loaded by the processor, so that the processor executes the unmanned aerial vehicle-based vehicle illegal parking identification method in any embodiment of the invention. Specifically, a system or an apparatus equipped with a storage medium on which software program codes that realize the functions of any of the above-described embodiments are stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program codes stored in the storage medium.
In this case, the program code itself read from the storage medium can realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.
Examples of the storage medium for supplying the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RYM, DVD-RW, DVD + RW), a magnetic tape, a nonvolatile memory card, and a ROM. Alternatively, the program code may be downloaded from a server computer via a communications network.
Further, it should be clear that the functions of any one of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform a part or all of the actual operations based on instructions of the program code.
Further, it is to be understood that the program code read out from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then a CPU or the like mounted on the expansion board or the expansion unit is caused to perform part or all of the actual operations based on instructions of the program code, thereby realizing the functions of any of the embodiments described above.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A vehicle illegal parking identification method based on an unmanned aerial vehicle is characterized in that the method comprises the steps that the unmanned aerial vehicle, a remote controller, an urban low-altitude intelligent sensing platform and an urban operation management platform are connected through a 5G network, the unmanned aerial vehicle flies according to a preset route and transmits a real-time video stream to the urban low-altitude intelligent sensing platform through the 5G network, and the urban low-altitude intelligent sensing platform identifies the vehicle through a vehicle illegal parking identification algorithm on the real-time video stream; after the vehicle is identified, the urban low-altitude intelligent sensing platform informs the unmanned aerial vehicle to continuously take a plurality of vehicle photos in situ, and whether the vehicle is static or not is analyzed according to the vehicle photos; when the vehicle is static, the unmanned aerial vehicle is controlled by the remote controller to zoom in the lens to shoot the vehicle photo again, vehicle information is obtained according to the vehicle photo, and the vehicle information is pushed to the city operation management platform through the interface.
2. The unmanned aerial vehicle-based vehicle parking recognition method according to claim 1, wherein the method specifically comprises the following steps:
the unmanned aerial vehicle transmits the video stream to a streaming media server of the urban low-altitude intelligent sensing platform;
identifying the video stream file through a vehicle illegal parking identification algorithm, and judging whether the vehicle is static:
if the vehicle is static, acquiring longitude and latitude information of the vehicle through an H20T laser ranging function of the unmanned aerial vehicle;
the urban low-altitude intelligent sensing platform inquires and acquires whether the position information belongs to a no-parking area according to the longitude and latitude information of the vehicle:
if yes, the urban low-altitude intelligent sensing platform sends an instruction of zooming in a lens to shoot a vehicle photo to the unmanned aerial vehicle;
the unmanned aerial vehicle transmits the shot vehicle photos to the urban low-altitude intelligent sensing platform, and vehicle information is identified through a vehicle violation identification algorithm;
and pushing the violation vehicle information to the city operation management platform through the API.
3. The unmanned aerial vehicle-based vehicle parking recognition method according to claim 2, wherein the video stream file is recognized by a vehicle parking recognition algorithm as follows:
decoding the video stream through a vehicle illegal parking recognition algorithm and preprocessing the video stream frame by using an opencv library to obtain an image matrix;
inputting the image matrix into a trained yolov5s neural network;
acquiring coordinate data of the vehicle in the image by the yolov5s neural network;
marking coordinate data of the vehicle in the image through an opencv library to obtain a vehicle image with a target frame;
and tracking and judging the monitored vehicle by using a deepsort method, and further determining whether the vehicle is static.
4. The unmanned aerial vehicle-based vehicle parking recognition method according to claim 2, wherein the vehicle information is recognized through a vehicle parking recognition algorithm as follows:
preprocessing the vehicle picture through a vehicle illegal parking recognition algorithm to obtain a preprocessed vehicle picture;
inputting the preprocessed vehicle pictures into a trained yolov5s neural network, and outputting the license plate position by the yolov5s neural network;
intercepting a license plate picture from a vehicle picture according to the license plate position;
and recognizing the character information on the license plate picture by using an OCR technology, acquiring vehicle information, and storing the vehicle information to a database.
5. The unmanned-aerial-vehicle-based vehicle illegal parking identification method according to claim 4, wherein the vehicle information comprises a vehicle picture, a license plate picture and vehicle position information.
6. The unmanned aerial vehicle-based vehicle parking recognition method of claim 4, wherein the vehicle photos are preprocessed by a vehicle parking recognition algorithm, and the preprocessed vehicle photos comprise letterbox and resize.
7. An unmanned aerial vehicle-based vehicle illegal parking identification system is characterized by comprising,
the unmanned aerial vehicle is used for flying according to a preset air route and shooting real-time video streams and vehicle photos;
the remote controller is used for controlling the unmanned aerial vehicle through the private communication protocol of the Xinjiang province;
the urban low-altitude intelligent sensing platform is used for tracking the vehicle through video streaming, further judging whether the vehicle is static or not and video the vehicle information according to the vehicle picture;
and the city operation management platform is used for receiving the violation vehicle information.
8. The unmanned-aerial-vehicle-based vehicle parking recognition system of claim 7, wherein the urban low-altitude intelligent perception platform comprises a video stream recognition unit and a vehicle photo recognition unit;
the video stream identification unit is used for identifying vehicles in the video stream;
the vehicle photo recognition unit is used for recognizing a vehicle picture, a license plate number picture and vehicle position information in the vehicle photo.
Wherein the video stream identification unit includes,
the first preprocessing module is used for decoding the video stream through a vehicle illegal parking recognition algorithm and preprocessing the video stream frame by using an opencv library to obtain an image matrix;
the input module I is used for inputting the image matrix into the trained yolov5s neural network;
the coordinate acquisition module is used for acquiring coordinate data of the vehicle in the image through the yolov5s neural network;
the marking module is used for marking the coordinate data of the vehicle in the image through an opencv library to obtain a vehicle image with a target frame;
the tracking module is used for tracking and judging the monitored vehicle by using a deepsort method so as to determine whether the vehicle is static;
the photo recognition unit for a vehicle includes,
the second preprocessing module is used for preprocessing the vehicle picture through a vehicle illegal parking recognition algorithm to obtain a preprocessed vehicle picture;
the input module II is used for inputting the preprocessed vehicle pictures into the trained yolov5s neural network;
the license plate position acquisition module is used for outputting the license plate position through a yolov5s neural network;
the intercepting module is used for intercepting a license plate picture from a vehicle picture according to the license plate position;
and the recognition module is used for recognizing the character information on the license plate picture by using an OCR technology, acquiring the vehicle information and storing the vehicle information to the database.
9. An electronic device, comprising: a memory and at least one processor;
wherein the memory has stored thereon a computer program;
the at least one processor executes the memory-stored computer program to cause the at least one processor to perform the drone-based vehicle violation identification method of any of claims 1-6.
10. A computer-readable storage medium, having stored thereon a computer program, the computer program being executable by a processor to implement the method for identifying a vehicle violation based on a drone of any one of claims 1 to 6.
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