Vehicle monitoring method, device, equipment and storage medium

Abstract

The application discloses a vehicle monitoring method, device and equipment and a storage medium, and relates to the technical field of vehicle monitoring, and specifically discloses a vehicle monitoring method, which comprises the following steps: receiving a monitoring request of a target vehicle; wherein the monitoring request contains vehicle information of the target vehicle; when monitoring video of the target vehicle is not acquired from an edge computing node of a local administrative region, acquiring the monitoring video of the target vehicle from a cloud computing center node; wherein the cloud computing center node stores monitoring video of vehicles traveling in respective administrative regions which is sent by each edge computing node of the administrative regions. According to the embodiment of the application, the edge computing node and the cloud computing center node work cooperatively, each edge computing node sends monitoring video of the local administrative region to the cloud computing center node, which not only solves the problems of bandwidth, delay, information processing capacity and the like that the cloud computing center node needs to face when collecting video data, but also guarantees the control of the cloud computing center node over the monitoring video, and further realizes cross-region vehicle monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of video monitoring, in particular to a vehicle monitoring method, device, equipment and storage medium. BACKGROUND

[0002] In the prior art, the traffic management department deploys video cameras along the main roads and at the intersections of the secondary roads in the jurisdiction. The real-time road conditions of the roads are transmitted to the monitoring center of the traffic management department in the form of videos, and the corresponding videos are saved in the data center of the traffic management department. The traffic management department can monitor the road conditions of the relevant public roads in real time, realize road condition monitoring, and timely discover traffic accidents.

[0003] However, in the above vehicle monitoring method, the monitoring center of each administrative region operates independently, and when the vehicle drives out of the current administrative region, the traffic management department of the current administrative region cannot implement further monitoring, that is, the above method cannot realize cross-administrative region vehicle monitoring. SUMMARY

[0004] In view of the above problems, the embodiments of the present application are proposed to provide a vehicle monitoring method, device, equipment and storage medium which can overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of the embodiments of the present application, a vehicle monitoring method is provided, comprising:

[0006] receiving a monitoring request of a target vehicle; wherein the monitoring request contains vehicle information of the target vehicle;

[0007] obtaining monitoring video of the target vehicle from an edge computing node of the current administrative region according to the vehicle information; wherein the edge computing node stores monitoring video of vehicles driving in the current administrative region sent by the edge computing node of the current administrative region;

[0008] when the monitoring video of the target vehicle is not obtained from the edge computing node of the current administrative region, obtaining the monitoring video of the target vehicle from a cloud computing center node; wherein the cloud computing center node stores monitoring video of vehicles driving in respective administrative regions sent by edge computing nodes of the respective administrative regions.

[0009] According to another aspect of the embodiments of the present application, a vehicle monitoring device is provided, comprising:

[0010] a request receiving module configured to receive a monitoring request of a target vehicle; wherein the monitoring request contains vehicle information of the target vehicle;

[0011] The local acquisition module is configured to acquire the monitoring video of the target vehicle from an edge computing node of the local administrative region according to the vehicle information, wherein the edge computing node stores the monitoring video of the vehicle traveling in the local administrative region sent by the edge computing node of the local administrative region.

[0012] The remote acquisition module is configured to acquire the monitoring video of the target vehicle from a cloud computing center node when the monitoring video of the target vehicle is not acquired from the edge computing node of the local administrative region, wherein the cloud computing center node stores the monitoring video of the vehicle traveling in the respective administrative region sent by each edge computing node of the administrative region.

[0013] According to another aspect of the embodiments of the present application, a computing device is provided, comprising a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete the communication among each other through the communication bus.

[0014] The memory is configured to store at least one executable instruction, and the executable instruction causes the processor to perform the operations of the vehicle monitoring method.

[0015] According to another aspect of the embodiments of the present application, a computer storage medium is provided, and the storage medium stores at least one executable instruction, and the executable instruction causes the processor to perform the operations of the vehicle monitoring method.

[0016] According to the above-mentioned embodiments of the present application, the edge computing node and the cloud computing center node work cooperatively, each edge computing node sends the monitoring video of the local administrative region to the cloud computing center node, which not only solves the problems of bandwidth, delay, information processing capacity and the like that the cloud computing center node needs to face when collecting video data, but also ensures the control of the cloud computing center node over the monitoring video, and realizes the cross-regional vehicle monitoring.

[0017] The above description is only a summary of the technical solutions of the embodiments of the present application, in order to more clearly understand the technical means of the embodiments of the present application, the embodiments of the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, characteristics and advantages of the embodiments of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art, upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments and are not meant to limit the present application. Furthermore, the same reference numerals are used throughout the several drawings to refer to the same or like parts. In the drawings:

[0019] Figure 1A flow chart of a vehicle monitoring method provided by an embodiment of the present application is shown;

[0020] Figure 2 A flow chart of a vehicle monitoring method provided by an embodiment of the present application is shown;

[0021] Figure 3 A schematic diagram of an application scenario in the vehicle monitoring method provided by the second embodiment of the present application is shown;

[0022] Figure 4 A structural schematic diagram of a vehicle monitoring device provided by an embodiment of the present application is shown;

[0023] Figure 5 A structural schematic diagram of a computing device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0024] Exemplary embodiments of the present application will be described in detail with reference to the drawings. Although exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be accurately conveyed to those skilled in the art.

[0025] Embodiment One

[0026] Figure 1 A flow chart of a vehicle monitoring method provided by an embodiment of the present application is shown. As shown in the figure, the method comprises the following steps: Figure 1

[0027] Step S110, receiving a monitoring request of a target vehicle; wherein the monitoring request contains vehicle information of the target vehicle.

[0028] The target vehicle can be one or more, and is set by a monitoring personnel.

[0029] The vehicle information includes a license plate number and a geographic location, and the geographic location can be obtained through Global Positioning System (GPS) positioning or Beidou positioning.

[0030] The execution subject of the present embodiment can be a vehicle monitoring device provided by an embodiment of the present application, which can be integrated in edge computing nodes and / or cloud computing center nodes of each administrative region, so that the edge computing nodes and / or cloud computing center nodes of each administrative region can implement the vehicle monitoring method of the present embodiment. The edge computing nodes of each administrative region can implement vehicle monitoring of the present administrative region, and the cloud computing center nodes can implement vehicle monitoring.

[0031] ​Specifically, a monitoring interface can be provided in the vehicle monitoring device, in which a virtual button, a target vehicle option list and a monitoring video display screen are provided. A user can select a target vehicle to be monitored through the target vehicle option list, and after selection, the monitoring program is started by triggering the virtual button, and then the obtained monitoring video is displayed in the monitoring video display screen.

[0032] In step S120, the monitoring video of the target vehicle is obtained from the edge computing node of the administrative region according to the vehicle information; wherein the edge computing node stores the monitoring video of the vehicle traveling in the administrative region sent by the edge computing node of the administrative region.

[0033] After obtaining the monitoring request, first, the monitoring video of the target vehicle is obtained from the edge computing node of the administrative region according to the location of the target vehicle (wherein the vehicle information contains the geographic location). The edge computing node of the administrative region stores the monitoring video of the vehicle traveling in the administrative region.

[0034] The edge computing node is an edge data center for collecting monitoring videos, processing monitoring videos and storing video monitoring, which is generally deployed in a physical machine room of a prefecture-level city, and the edge computing node is connected to the cloud computing center node through a dedicated network. In this embodiment, in order to save the memory of the edge computing node and improve the data processing speed of the edge computing node, the edge computing node of the administrative region can send the monitoring video of the vehicle traveling in the administrative region to the edge storage node of the administrative region for storage, and then obtain the monitoring video of the target vehicle from the edge storage node of the administrative region according to the location of the target vehicle.

[0035] The edge storage node stores the raw data of the monitoring video in the form of object storage. The deployment location of the edge storage node can be in the same prefecture-level city as the physical location of the edge computing node, or several edge computing nodes can share one edge storage node. The edge storage node can ensure the read-write performance of data storage, 99.99999% data integrity, and 99.97% read-write availability.

[0036] When the monitoring video of the target vehicle is not obtained from the edge computing node of the administrative region, it indicates that the target vehicle has left the administrative region, and step S130 is performed.

[0037] In step S130, the monitoring video of the target vehicle is obtained from the cloud computing center node; wherein the cloud computing center node stores the monitoring video of the vehicle traveling in the respective administrative region sent by the edge computing node of each administrative region.

[0038] The embodiment cooperates with the cloud computing center node through the edge computing node, each edge computing node sends the monitoring video of the administrative region to the cloud computing center node, not only solves the problems of bandwidth, delay, information processing capacity and the like when the cloud computing center node collects video data, but also guarantees the control of the cloud computing center node on the monitoring video, and can realize cross-regional vehicle monitoring. For example, the monitoring video of the administrative region can realize vehicle tracking or fake vehicle screening in the administrative region, and the monitoring video of the cloud computing center can realize vehicle tracking or fake vehicle screening.

[0039] In an optional embodiment, before the above-mentioned embodiment one is executed, the method further includes a process in which the edge computing node of each administrative region reports the monitoring video to the cloud computing center node, specifically including the following steps:

[0040] Step S140, receiving the monitoring video of the vehicle sent by the camera equipment deployed in the administrative region.

[0041] Specifically, each administrative region is respectively provided with corresponding camera equipment, which is a device for collecting real-time pictures of roads, such as a camera. The camera equipment can be deployed at positions such as the line of public roads, road intersections, around buildings, underground parking lots built in buildings and the like in the respective administrative region. The camera equipment of each administrative region directly sends the collected video to the edge computing node of the respective administrative region. The camera equipment can transmit the monitoring video to the edge computing node through wired network or wireless network. And each camera equipment records the geographical position information such as GPS, road, building direction and the like of the specific installation position.

[0042] Step S150, determining the video sending period according to the received monitoring video.

[0043] Specifically, the edge computing node samples the collected monitoring video, converts it into multiple pictures with vehicle information, then performs image recognition processing on the pictures, recognizes the motor vehicle license plate information appearing in the image, takes the position information of the corresponding camera equipment as the vehicle position of the target vehicle with the license plate number as the dimension, and further determines the video sending period according to the vehicle position of the target vehicle.

[0044] Among them, the edge computing node and the center computing node are connected through a dedicated line network. The edge computing node sends the monitoring video in the video sending period to the cloud computing center node through the dedicated line network.

[0045] Specifically, after the monitoring video in each video sending period ends, in order to save storage space, the monitoring video in the video sending period is deleted, and the deleted monitoring video is also reported to the cloud computing center node. The next video sending period is the first monitoring video in the last monitoring video of the previous video sending period.

[0046] In an optional embodiment, step S150 specifically includes:

[0047] Step S1501, when the total number of received monitoring videos is more than the first total number, the turning point is determined according to the coordinate point corresponding to the vehicle position in the received monitoring video.

[0048] The first total number can be a positive integer greater than or equal to 3, and the target vehicle is recorded once by a camera device as a monitoring video. When the number of received monitoring videos is equal to the first total number, the turning point is calculated. Specifically, when calculating the turning point, first, the vehicle position in the received monitoring video is obtained, each vehicle position is taken as a point, the coordinate point corresponding to the vehicle position in the first received monitoring video and the coordinate point corresponding to the vehicle position in the last monitoring video are connected to form a straight line, the distance from the coordinate point corresponding to the vehicle position in the other monitoring video to the straight line is determined, which is the offset distance, for example, can be the shortest distance, and the coordinate point corresponding to the vehicle position in the monitoring video whose distance exceeds the preset distance is taken as the turning point. The preset distance can be set by the user.

[0049] When the turning point exists, step S1502 is performed. When the turning point does not exist, the monitoring video is continuously received.

[0050] Step S1502, determining the video sending period according to the turning point.

[0051] Specifically, after the turning point is determined, the monitoring video corresponding to the turning point is taken as the last monitoring video received in the video sending period, that is, the first received monitoring video, the monitoring video between the first monitoring video and the last monitoring video, and the last monitoring video form a video sending period. Or, after the turning point is determined, it is further judged whether the monitoring video in the video sending period determined based on the turning point exists a deviation point, and the video sending period is further determined according to the deviation point. See the optional embodiment below for details.

[0052] The embodiment calculates the turning point. Since the turning point is calculated according to the vehicle position in the monitoring video, the position correlation between the monitoring videos in the video sending period can be ensured by determining the video sending period according to the turning point.

[0053] In an optional embodiment, step S1502 specifically includes:

[0054] Step S15021, taking the monitoring video corresponding to the turning point as the last monitoring video;

[0055] Step S15022, determining the deviating point according to the coordinate point corresponding to the vehicle position in the received first monitoring video and the coordinate point corresponding to the vehicle position in the last monitoring video.

[0056] Specifically, the coordinate point corresponding to the vehicle position in the received first monitoring video and the coordinate point corresponding to the vehicle position in the last monitoring video can be connected to form a straight line, the distance, for example, the shortest distance, of the coordinate point corresponding to the vehicle position in the other monitoring video to the straight line is determined, and the coordinate point corresponding to the vehicle position in the monitoring video whose distance exceeds a preset distance is taken as the deviating point. The preset distance can be set by the user, and the preset distance for judging the deviating point is greater than the preset distance for judging the turning point set in the foregoing. For example, the preset distance for judging the turning point is N meters, and the preset distance for judging the deviating point is 3N meters.

[0057] Step S15023, determining the video sending period according to the deviating point.

[0058] Specifically, when the deviating point is one, the monitoring video corresponding to the deviating point is taken as the last monitoring video received in the video sending period, that is, the first monitoring video received, the monitoring video between the first monitoring video and the last monitoring video, and the last monitoring video form a video sending period.

[0059] When the deviating point is multiple, the monitoring videos corresponding to the multiple deviating points are taken as the demarcation points, the received monitoring videos are divided into multiple groups of monitoring videos, and the video sending period of each group of monitoring videos is determined. For example, a certain video sending period is 10 monitoring videos, the offset distance between the 3rd monitoring video and the 8th monitoring video exceeds 3N meters, the original video sending period is reorganized into 3 video sending periods, the 1st-3rd monitoring videos of the original video sending period form a group, the 3rd-8th monitoring videos of the original video sending period form a group, and the 8th-10th monitoring videos of the original video sending period form a group, the deviating point is calculated again, and the video sending period of each group of monitoring videos is determined again.

[0060] The embodiment determines the video sending period by calculating the deviating point. Since the deviating point is calculated according to the vehicle position in the monitoring video, the position correlation between the monitoring videos in the video sending period can be ensured by determining the video sending period according to the deviating point.

[0061] Embodiment Two

[0062] Figure 2A flow chart of the vehicle monitoring method provided by the second embodiment of the present application is shown. The embodiment is for a specific application scenario, which includes monitoring cameras, edge computing nodes, edge storage nodes, cloud computing center nodes, and the vehicle monitoring method of the present embodiment is used to realize screening of fake vehicles based on the scenario. Figure 3 Figure 3 The vehicle monitoring method of the present embodiment is used to realize screening of fake vehicles, as shown in Figure 2 The method includes the following steps:

[0063] Step S210, the monitoring cameras of each administrative region collect real-time road pictures to obtain monitoring videos containing vehicles, and send the monitoring videos to the edge storage nodes of the respective administrative regions.

[0064] Step S220, the edge storage nodes of each respective administrative region receive the monitoring videos of vehicles sent by the monitoring cameras of the respective administrative regions, and process them into multiple pictures with vehicle information.

[0065] Step S230, the edge storage nodes of each respective administrative region perform image recognition processing on the pictures, identify the motor vehicle license plate information appearing in the images, and write the license plate number as the primary key into the index database.

[0066] Step S240, the edge storage nodes of each respective administrative region determine whether a trajectory conflict occurs according to the vehicle positions of the vehicles in the monitoring videos.

[0067] If a trajectory conflict occurs, step S250 is performed, otherwise step S260 is performed.

[0068] Step S250, the edge storage nodes of each respective administrative region mark the vehicle with a trajectory conflict as a fake vehicle, save the historical vehicle positions of the fake vehicle, and perform step S270.

[0069] Step S260, the edge storage nodes of each respective administrative region save the historical vehicle positions in the index database under the corresponding license plate number, and perform step S270.

[0070] Step S270, the edge storage nodes of each respective administrative region determine the video sending period according to the vehicle positions of the vehicles in the received monitoring videos.

[0071] Step S280, the edge storage nodes of each respective administrative region send the monitoring videos in the video sending period to the cloud computing center nodes.

[0072] Step S290, the edge computing nodes of an administrative region receive a monitoring request of a target vehicle; wherein the monitoring request contains vehicle information of the target vehicle.

[0073] Step S2110, the edge computing nodes obtain the monitoring videos of the target vehicle from the local according to the vehicle information, and perform fake screening on the target vehicle in the administrative region.​

[0074] Step S2111, when the monitoring video of the target vehicle is not acquired from the edge computing node of the administrative region, the monitoring video of the target vehicle is acquired from the cloud computing center node, and the target vehicle is screened for carding.

[0075] The carding screening method is: for the historical vehicle position A of the target vehicle, the historical vehicle position B closest to the target vehicle from the historical vehicle position A is found, the straight-line distance between the historical vehicle position A and the historical vehicle position B is calculated, and the minimum time required for the target vehicle to arrive at the historical vehicle position B from the historical vehicle position A is determined, the vehicle driving speed is determined based on the straight-line distance and the minimum time, and if the vehicle driving speed is greater than the preset speed, the target vehicle is determined as a carding vehicle.

[0076] The embodiment can realize vehicle carding screening based on cloud-edge collaboration.

[0077] Embodiment three

[0078] Figure 4 A structure schematic diagram of a vehicle monitoring device provided by the embodiment three of the application is shown. As shown in the figure, the device comprises a request receiving module 11, a local acquisition module 12, and a remote acquisition module 13; wherein, Figure 4 The request receiving module 11 is configured to receive a monitoring request of a target vehicle; wherein the monitoring request comprises vehicle information of the target vehicle.

[0079] The local acquisition module 12 is configured to acquire a monitoring video of the target vehicle from an edge computing node of an administrative region according to the vehicle information; wherein the edge computing node stores monitoring videos of vehicles driving in the administrative region.

[0080] The remote acquisition module 13 is configured to acquire the monitoring video of the target vehicle from a cloud computing center node when the monitoring video of the target vehicle is not acquired from the edge computing node of the administrative region; wherein the cloud computing center node stores monitoring videos of vehicles driving in respective administrative regions sent by edge computing nodes of the respective administrative regions.

[0081] Further, the device further comprises a video receiving module 14, a period determining module 15, and a video sending module 16; wherein,

[0082] The video receiving module 14 is configured to receive monitoring videos of vehicles sent by camera equipment in the administrative region.

[0083] The period determining module 15 is configured to determine a video sending period according to the received monitoring video.

[0084]

[0085] ​The video sending module 16 is configured to send the monitoring video in the video sending period to the cloud computing center node.

[0086] Further, the period determining module 15 is specifically configured to: when the total number of the received monitoring videos is more than the first total number, determine a turning point according to the vehicle position in the received monitoring videos; and determine the video sending period according to the turning point.

[0087] Further, the period determining module 15 is specifically configured to: take the monitoring video corresponding to the turning point as the last monitoring video; determine a deviating point according to the coordinate point corresponding to the vehicle position in the first received monitoring video and the coordinate point corresponding to the vehicle position in the last monitoring video; and determine the video sending period according to the deviating point.

[0088] Further, the period determining module 15 is specifically configured to: when the total number of the received monitoring videos is equal to the second total number, determine a deviating point according to the coordinate point corresponding to the vehicle position in the first received monitoring video and the coordinate point corresponding to the vehicle position in the last monitoring video; and determine the video sending period according to the deviating point.

[0089] Further, the period determining module 15 is specifically configured to: connect the coordinate point corresponding to the vehicle position in the first received monitoring video and the coordinate point corresponding to the vehicle position in the last monitoring video into a straight line; determine the distance from the coordinate point corresponding to the vehicle position in other monitoring videos to the straight line, and take the coordinate point corresponding to the vehicle position in the monitoring video whose distance exceeds a preset distance as the deviating point.

[0090] Further, the period determining module 15 is specifically configured to: when the deviating point is multiple, take the monitoring video corresponding to the multiple deviating points as the demarcation point, divide the received monitoring videos into multiple groups of monitoring videos; and determine the video sending period of each group of monitoring videos respectively.

[0091] The vehicle monitoring device provided in the embodiment of the application is used to execute the vehicle monitoring method provided in the above embodiment, and has similar working principles and technical effects, which will not be described herein.

[0092] Embodiment four

[0093] The embodiment of the application provides a nonvolatile computer storage medium, which stores at least one executable instruction, and the computer executable instruction can execute the vehicle monitoring method in any method embodiment.

[0094] Embodiment five

[0095] Figure 5The structural schematic diagram of the computing device provided by the embodiments of the present application is shown, and the embodiments of the present application do not limit the specific implementation of the computing device.

[0096] As shown in the figure, the computing device can include a processor, a communications interface, a memory, and a communications bus. Figure 5

[0097] The processor, the communications interface, and the memory can communicate with each other through the communications bus. The communications interface is configured to communicate with network elements such as clients or other servers. The processor is configured to execute programs, and can execute the related steps in the above-mentioned embodiments of the vehicle monitoring method and the cell azimuth prediction method for the computing device.

[0098] Specifically, the program can include program codes, and the program codes include computer operation instructions.

[0099] The processor can be a central processing unit (CPU) or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the computing device can be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0100] The memory is configured to store programs. The memory can include a high-speed RAM memory, and can also include a non-volatile memory, such as at least one disk memory.

[0101] The program can be specifically used to enable the processor to execute the vehicle monitoring method in any of the above-mentioned method embodiments. The specific implementation of each step in the program can refer to the description of the corresponding steps and units in the above-mentioned vehicle monitoring method embodiments, and will not be described here. Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned device and module can refer to the corresponding process description in the above-mentioned method embodiments, and will not be described here.

[0102] ​The algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems can be used with programs in accordance with the teachings herein, or it can prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will be apparent from the description above. In addition, the present embodiments are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages can be used to implement the teachings of the embodiments as described herein, and any references below to specific languages are provided for disclosure of enablement only.

[0103] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been described in detail in order to avoid obscuring the understanding of this description.

[0104] Similarly, it is to be understood that the mechanical details of the embodiments of the application can sometimes depend on the specifics of the technical field in which the embodiments of the application are used, and that the scope of the present application is measured by the claims that follow. Similarly, it is to be understood that, for brevity and clarity, certain aspects of the application have been presented while omitting others; that a practitioner of ordinary skill in the art will

[0105] Those skilled in the art will appreciate that the modules in the apparatuses in the embodiments can be adapted and placed in one or more apparatuses other than the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and further can be divided into more sub-modules or sub-units or sub-components. Any combination of all the features disclosed in the specification (including the accompanying claims, abstract and drawings), and any method or of the apparatuses so disclosed, can be made, excepting that at least some of such features and / or processes or units are mutually exclusive, unless explicitly stated otherwise. Each feature disclosed in the description (including the accompanying claims, abstract and drawings) can be replaced by alternative features serving the same, equivalent or similar purpose, unless explicitly stated otherwise.

[0106] Furthermore, those skilled in the art will recognize that, while certain embodiments described herein include certain features that are not included in other embodiments, combinations of features of the different embodiments are meant to be within the scope of the application and form different embodiments. For example, in the claims below, any of the claimed embodiments can be used in any combination.

[0107] Various component embodiments of the application can be implemented in hardware, or as software modules running in one or more processors, or in combinations thereof. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functionality of some or all of the components according to embodiments of the application. Embodiments of the application can also be implemented as a program for executing one or more parts of the methods described herein on a computer or a processor (for example, a computer program and a computer program product). Such a program can be stored on a computer readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier medium, or in any other form.

[0108] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. An embodiment of the application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a unit claim, several devices can be listed with a comma. Such listing does not imply that the devices must be co-located. The use of the word 'at least' followed by a list of one or more members does not exclude additional members of the same class or steps. The word 'first','second', 'third', etc. do not imply any order. The terms 'first','second', 'third', etc. are to be interpreted as names. The steps of any of the methods disclosed herein do not have to be performed in the exact order disclosed.

Claims

1. A vehicle monitoring method, characterized in that, include: Receive a monitoring request for the target vehicle; wherein the monitoring request contains vehicle information of the target vehicle; Based on the vehicle information, the surveillance video of the target vehicle is obtained from the edge computing node of this administrative region; wherein, the edge computing node stores the surveillance video of vehicles traveling in this administrative region; When the surveillance video of the target vehicle is not obtained from the edge computing node of this administrative region, the surveillance video of the target vehicle is obtained from the cloud computing center node; wherein, the cloud computing center node stores the surveillance videos of vehicles traveling in their respective administrative regions sent by the edge computing nodes of each administrative region. The method further includes: receiving vehicle surveillance video transmitted by camera equipment deployed in the administrative region; The video transmission cycle is determined based on the received surveillance videos. When the total number of received surveillance videos exceeds the first total number, the turning point is determined based on the vehicle position in the received surveillance videos. The video transmission cycle is determined based on the turning point, wherein the surveillance video corresponding to the turning point is taken as the last surveillance video received in the video transmission cycle. The first surveillance video received, the surveillance video located between the first and last surveillance videos, and the last surveillance video constitute a video transmission cycle. The monitoring videos within the video sending period are sent to the cloud computing center node.

2. The method according to claim 1, characterized in that, Determining the video transmission period based on the turning point includes: The monitoring video corresponding to the turning point is used as the last monitoring video; The deviation point is determined based on the coordinates of the vehicle's position in the first received surveillance video and the coordinates of the vehicle's position in the last received surveillance video. The video transmission cycle is determined based on the deviation point.

3. The method according to claim 1, characterized in that, The step of determining the video transmission period based on the received surveillance video includes: When the total number of received surveillance videos equals the second total number, the deviation point is determined based on the coordinates of the vehicle position in the first received surveillance video and the coordinates of the vehicle position in the last surveillance video. The video transmission cycle is determined based on the deviation point.

4. The method according to claim 3, characterized in that, The step of determining the deviation point based on the coordinates of the vehicle's position in the first received surveillance video and the coordinates of the vehicle's position in the last received surveillance video includes: Connect the coordinates of the vehicle's location in the first received surveillance video with the coordinates of the vehicle's location in the last surveillance video by forming a straight line. Determine the distance from the coordinates of the vehicle's location in other surveillance videos to the straight line, and use the coordinates of the vehicle's location in surveillance videos that are more than a preset distance away as deviation points.

5. The method according to claim 3 or 4, characterized in that, The step of determining the video transmission period based on the deviation point includes: When there are multiple deviation points, the received monitoring video is divided into multiple groups of monitoring video by using the monitoring video corresponding to the multiple deviation points as the dividing point; Determine the video transmission cycle for each group of monitoring videos.

6. A vehicle monitoring device, characterized in that, include: A request receiving module is used to receive monitoring requests from a target vehicle; wherein the monitoring request contains vehicle information of the target vehicle; The local acquisition module is used to acquire the surveillance video of the target vehicle from the edge computing node in this administrative region based on the vehicle information; wherein, the edge computing node stores the surveillance video of vehicles traveling in this administrative region. The remote acquisition module is used to acquire the monitoring video of the target vehicle from the cloud computing center node when the monitoring video of the target vehicle cannot be acquired from the edge computing node of the administrative region; wherein, the cloud computing center node stores the monitoring videos of vehicles traveling in their respective administrative regions sent by the edge computing nodes of each administrative region. The video receiving module is used to receive surveillance videos of vehicles sent by camera equipment deployed in this administrative region; The period determination module is used to determine the video transmission period based on the received surveillance videos. When the total number of received surveillance videos is greater than a first total number, the turning point is determined based on the vehicle position in the received surveillance videos. The video transmission period is determined based on the turning point, wherein the surveillance video corresponding to the turning point is taken as the last surveillance video received in the video transmission period. The first surveillance video received, the surveillance video located between the first and last surveillance videos, and the last surveillance video constitute a video transmission period. The video sending module is used to send the monitoring video during the video sending period to the cloud computing center node.

7. A computing device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the vehicle monitoring method as described in any one of claims 1-5.

8. A computer storage medium storing at least one executable instruction that causes a processor to perform the operation of the vehicle monitoring method as described in any one of claims 1-5.

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