Information pushing method and system based on big data

Abstract

The invention is suitable for the field of computers, and provides an information pushing method and system based on big data, and the method comprises the steps: obtaining regional driving information within a first preset time period through big data recognition, and extracting a first vehicle identifier set in the regional driving information; after the management authority is obtained, third-party charging record information in a second preset time period is obtained, a second vehicle identifier set in the third-party charging record information is extracted, and the second vehicle identifier set comprises a vehicle frame number set; and identifying the vehicles of which the vehicles corresponding to the first vehicle identifier set are not included in the vehicles corresponding to the second vehicle identifier set, and marking the vehicles as suspicious vehicles. The method has the beneficial effects that the behavior of private cable charging is automatically positioned and identified by means of big data, so that personnel at a center end can conveniently respond in time, and the charging efficiency is improved. And dangerous events are reduced.

Description

Technical Field

[0001] The present invention belongs to the field of computers, and in particular, relates to an information push method and system based on big data. Background Art

[0002] "Data elements are the core engine of the digital economy." In the era of digital economy, big data has become one of the key elements to promote economic and social development. Big data, or big data, refers to massive, high-growth and diversified information assets that require new processing models to have stronger decision-making, insight and process optimization capabilities.

[0003] Big data serves information collection and realizes information feedback. How to use big data within the scope of legal authority to improve user satisfaction has always been the core goal of information push. In the existing technology, vehicle charging is related to the user's safe driving and the safety of the public, but there are still some users who privately pull wires for charging. This phenomenon is difficult to detect and is repeatedly banned. The efficiency of manual verification is extremely low. Therefore, a method and system for information push based on big data are proposed. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a method and system for pushing information based on big data, aiming to solve the problems raised in the above-mentioned background technology.

[0005] The embodiment of the present invention is implemented as follows: on the one hand, a method for pushing information based on big data, the method comprising the following steps:

[0006] Acquire regional driving information within a first preset time period identified by big data, and extract a first vehicle identification set from the regional driving information;

[0007] After obtaining the management authority, obtaining third-party charging record information within a second preset time period, extracting a second vehicle identification set from the third-party charging record information, wherein the second vehicle identification set includes a frame number set;

[0008] Identify vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and mark such vehicles as suspicious vehicles;

[0009] The corresponding parking area of ​​the suspicious vehicle is traced according to the regional driving information, and an action instruction is sent to the camera terminal in the corresponding parking area. The action instruction is used to instruct the camera terminal to perform a rotation camera action, and the image information obtained by performing the rotation camera action is pushed to the central end.

[0010] As a further solution of the present invention, the step of obtaining regional driving information within a preset time period identified by big data and extracting a first vehicle identification set from the regional driving information includes:

[0011] Obtaining an input of a first preset time period, where the first preset time period is at least the longest average flight time;

[0012] Obtain vehicle driving record information at each import and export point in the target area;

[0013] Identifying vehicle entry information exceeding a first preset number of times in vehicle driving record information;

[0014] Identifying vehicle exit information exceeding a second preset number of times in the vehicle driving record information, wherein the vehicles corresponding to the vehicle entry information and the vehicle exit information are different vehicles;

[0015] The vehicle identifications in the vehicle entry information and the vehicle exit information are respectively identified and counted to generate a first vehicle identification set, wherein the first vehicle identification set includes a license plate number set.

[0016] As a further solution of the present invention, after obtaining the management authority, obtaining the third-party charging record information within a second preset time period, extracting the second vehicle identification set in the third-party charging record information, the second vehicle identification set including the frame number set, including:

[0017] Obtain the authority to manage charging record information of third-party charging;

[0018] Acquire all third-party charging record information in the target area within a second preset time period, wherein the first preset time period is included in the second preset time period, and the second preset time period is between one time the longest average battery life and two times the longest average battery life;

[0019] A second vehicle identification set is extracted from all third-party charging record information, and duplicate second vehicle identifications are removed, where the second vehicle identification includes a frame number.

[0020] As a further aspect of the present invention, the method further comprises:

[0021] Obtain the registration information of license plates and frames in the target area;

[0022] Based on the license plate and frame registration information, identifying the frame number corresponding to the license plate number in the first vehicle identification set, and generating a first frame number;

[0023] The first frame number is compared with the frame number in the second vehicle identification, a frame number in the first frame number that is different from the frame number in the second vehicle identification is obtained, and a second frame number is generated. The vehicle corresponding to the second frame number is a suspicious vehicle.

[0024] As a further embodiment of the present invention, the method further comprises:

[0025] Based on the second vehicle identification set corresponding to the suspicious vehicle, the regional driving information further includes regional driving sub-information, wherein the regional driving sub-information is first driving information of at least the first and last sections of each road and second driving information of the road intersection section;

[0026] The regional driving sub-information of the suspicious vehicle in the regional driving information is identified, and the corresponding parking area of ​​the suspicious vehicle is determined according to the regional driving sub-information.

[0027] As a further solution of the present invention, the method of determining the corresponding parking area of ​​the suspicious vehicle according to the regional driving sub-information includes:

[0028] When it is identified according to the first driving information that the suspicious vehicle passes through the first section of a road but does not appear in the last section, the parking area corresponding to the positioning may be a sub-area corresponding to the middle section of the road;

[0029] When the suspicious vehicle is still not identified according to the second driving information, it is determined that the parking area corresponding to the suspicious vehicle is a sub-area corresponding to the middle section of a road;

[0030] When the suspicious vehicle is further identified according to the second driving information, the parking area corresponding to the suspicious vehicle is determined to be a sub-area corresponding to the middle section of another road corresponding to the second driving information;

[0031] When a suspicious vehicle is identified as appearing at the beginning or end of a road according to the first driving information, the corresponding parking area is positioned as a sub-area corresponding to the beginning or end of the road.

[0032] As a further solution of the present invention, an action instruction is sent to a camera terminal in a corresponding parking area, wherein the action instruction is used to instruct the camera terminal to perform a rotation camera action, and push image information obtained by performing the rotation camera action to a central end, including:

[0033] Sending an action instruction to the camera terminal in the corresponding parking area, wherein the action instruction carries the number of the camera terminal in the corresponding sub-area and the preset elevation angle of the sub-area relative to the camera terminal;

[0034] Instruct the camera terminal in the sub-area to adjust according to the preset elevation angle and then deflect back and forth to obtain image information within the preset elevation angle of the sub-area;

[0035] If a cable is detected in the image information, the image information obtained by performing a rotating camera action is pushed to the central end and a prompt is issued, and the prompt information is used to indicate that there may be private charging behavior of pulling wires in the corresponding parking area.

[0036] As a further solution of the present invention, on the other hand, a big data-based information push system comprises:

[0037] A first vehicle identification recognition module is used to obtain regional driving information within a first preset time period after big data recognition, and extract a first vehicle identification set from the regional driving information;

[0038] A second vehicle identification recognition module, configured to obtain, after obtaining management authority, third-party charging record information within a second preset time period, and extract a second vehicle identification set from the third-party charging record information, wherein the second vehicle identification set includes a frame number set;

[0039] A suspicious vehicle identification module, used to identify vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and mark such vehicles as suspicious vehicles;

[0040] An action instruction and push module, the action instruction and push module is used to: trace the corresponding parking area of ​​the suspicious vehicle according to the regional driving information, and issue an action instruction to the camera terminal in the corresponding parking area, the action instruction is used to instruct the camera terminal to perform a rotation camera action, and push the image information obtained by performing the rotation camera action to the central end.

[0041] An information push method and system based on big data provided by an embodiment of the present invention can, with the help of big data, identify vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and obtain suspicious vehicles, that is, there is driving behavior but no charging record. Therefore, with the help of third-party charging record information, it is judged that there is a high possibility of private cable charging. At this time, the corresponding parking area of ​​the suspicious vehicle can be traced according to the regional driving information; further, the corresponding position of the suspicious vehicle can be further locked, and with the help of the camera terminal, the image information obtained by executing the rotating camera action can be pushed to the central end, so as to facilitate the personnel at the central end to respond in time and reduce the occurrence of dangerous incidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a main flow chart of an information push method based on big data.

[0043] Figure 2 The invention discloses a flowchart of extracting a first vehicle identification set from the regional driving information in an information push method based on big data.

[0044] Figure 3 The invention discloses a flow chart for determining a corresponding parking area of ​​a suspicious vehicle according to driving sub-information of the area in an information push method based on big data.

[0045] Figure 4 The invention discloses a flowchart related to sending action instructions to a camera terminal in a corresponding parking area in an information push method based on big data.

[0046] Figure 5 It is a main structure diagram of an information push system based on big data. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0049] The present invention provides a method and system for pushing information based on big data, which solves the technical problems in the background technology.

[0050] like Figure 1 As shown, it is a main flow chart of a method for pushing information based on big data provided by an embodiment of the present invention, and the method for pushing information based on big data includes:

[0051] Step S10: Acquire regional driving information within a first preset time period identified by big data, and extract a first vehicle identification set from the regional driving information;

[0052] Step S11: after obtaining the management authority, obtaining the third-party charging record information within a second preset time period, extracting the second vehicle identification set in the third-party charging record information, wherein the second vehicle identification set includes a frame number set;

[0053] Step S12: identifying vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and marking such vehicles as suspicious vehicles;

[0054] Step S13: trace the corresponding parking area of ​​the suspicious vehicle according to the regional driving information, and send an action instruction to the camera terminal in the corresponding parking area, wherein the action instruction is used to instruct the camera terminal to perform a rotation camera action, and push the image information obtained by performing the rotation camera action to the central end.

[0055] When this embodiment is applied, it combines big data to identify regional driving information within a first preset time period to obtain a first vehicle identification set. The first vehicle identification set represents real-time driving behavior records obtained through big data, and the third-party charging record information obtained is the charging behavior record of vehicles in the target area. Since the first vehicle identification and the second vehicle identification are unique to the vehicle, it is possible to identify vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and obtain suspicious vehicles, that is, there is driving behavior, but no charging record is left. Therefore, with the help of the third-party charging record information, it is judged that there is a high possibility of private cable charging behavior. At this time, the corresponding parking area of ​​the suspicious vehicle is traced back according to the regional driving information;

[0056] An action instruction is sent to the camera terminal in the corresponding parking area, and the action instruction is used to instruct the camera terminal to perform a rotating camera action, and the image information obtained by performing the rotating camera action is pushed to the central end, which can further lock the corresponding position of the suspicious vehicle, and with the help of the camera terminal, the image information obtained by performing the rotating camera action is pushed to the central end, so as to facilitate the personnel at the central end to respond in time and reduce the occurrence of dangerous incidents.

[0057] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of obtaining the regional driving information within a preset time period identified by big data and extracting the first vehicle identification set from the regional driving information includes:

[0058] Step S101: obtaining an input of a first preset time period, where the first preset time period is at least the longest average endurance duration;

[0059] Step S102: Acquire vehicle driving record information at each entrance and exit in the target area;

[0060] Step S103: Identify vehicle entry information exceeding a first preset number of times in the vehicle driving record information;

[0061] Step S104: identifying vehicle exit information exceeding a second preset number of times in the vehicle driving record information, wherein the vehicles corresponding to the vehicle entry information and the vehicle exit information are different vehicles; the first preset number of times and the second preset number of times may be the same; or they may be different, depending on the specific actual situation, such as when there is a restriction on entry or exit within a certain period of time;

[0062] Step S105: respectively identifying and counting vehicle identifications in the vehicle entry information and the vehicle exit information to generate a first vehicle identification set, wherein the first vehicle identification set includes a license plate number set.

[0063] It is understandable that the longest average cruising time can be obtained based on the initial preliminary investigation and is determined based on normal riding time (such as every day under normal circumstances). The vehicles corresponding to the vehicle entry information and the vehicle exit information are different vehicles. The reason is that under normal circumstances, the entry or exit exceeds the preset number of times, thus indicating that the corresponding vehicle is most likely a vehicle of a user in the target area, rather than an external vehicle, and the entry and exit appear in pairs, so the vehicle driving records in the vehicle entry information and the vehicle exit information are only counted once, which is convenient for reducing the subsequent data calculation amount.

[0064] As a preferred embodiment of the present invention, after obtaining the management authority, obtaining the third-party charging record information within the second preset time period, extracting the second vehicle identification set in the third-party charging record information, the second vehicle identification set including the frame number set, including:

[0065] Step S111: obtaining the authority to manage the charging record information of the third party;

[0066] Step S112: Acquire all third-party charging record information in the target area within a second preset time period, wherein the first preset time period is included in the second preset time period, and the second preset time period is between one time the longest average endurance time and two times the longest average endurance time;

[0067] Step S113: extracting a set of second vehicle identifications from all third-party charging record information, and removing duplicates of identical second vehicle identifications, wherein the second vehicle identification includes a vehicle frame number.

[0068] It is understandable that the first preset time period should be smaller than the second preset time period, that is, the second preset time period must include at least a complete first preset time period in order to be able to collect the vehicle's charging record information. Since the second preset time period is limited based on the longest average cruising range, it is possible to collect the charging record information of the same vehicle twice. Therefore, deduplication is required in advance to reduce the amount of subsequent comparison and identification calculations for the vehicle frame number.

[0069] As a preferred embodiment of the present invention, the method further includes:

[0070] Step S20: Acquire the registration information of the license plate and frame in the target area;

[0071] Step S21: Based on the license plate and frame registration information, identify the frame number corresponding to the license plate number in the first vehicle identification set, and generate a first frame number;

[0072] Step S22: Compare the first frame number with the frame number in the second vehicle identification, obtain the frame number in the first frame number that is different from the frame number in the second vehicle identification, generate a second frame number, and the vehicle corresponding to the second frame number is a suspicious vehicle.

[0073] It should be understood that the license plate and frame registration information can generally be obtained at the property management office or traffic control center, and the license plate and frame are unique, and the correspondence between the two is generally unique (without changing the vehicle). By obtaining the frame number in the first frame number that is different from the frame number in the second vehicle identification, the vehicle that is running but not charged can be locked. Of course, if the charging record information of the non-target area is missing, it cannot be ruled out that the vehicle is neither charged in the target area nor charged with private wires.

[0074] As a preferred embodiment of the present invention, the method further includes:

[0075] Step S30: Based on the second vehicle identification set corresponding to the suspicious vehicle, the regional driving information further includes regional driving sub-information, wherein the regional driving sub-information is first driving information of at least the first and last sections of each road and second driving information of the road intersection section; according to common sense, the road intersection section generally refers to the intersection section of two roads;

[0076] Step S31: identifying the regional driving sub-information of the suspicious vehicle in the regional driving information, and determining the corresponding parking area of ​​the suspicious vehicle according to the regional driving sub-information.

[0077] By acquiring the first driving information and the second driving information, the parking position of the suspicious vehicle can be determined while minimizing the information to be identified.

[0078] like Figure 3 As shown, in one case of this embodiment, the step of determining the corresponding parking area of ​​the suspicious vehicle according to the regional driving sub-information includes:

[0079] Step S1311: when it is identified according to the first driving information that a suspicious vehicle passes through the first section of a road but does not appear at the last section, the corresponding parking area may be located as a sub-area corresponding to the middle section of the road;

[0080] Step S1312: when the suspicious vehicle is still not identified according to the second driving information, determining that the parking area corresponding to the suspicious vehicle is a sub-area corresponding to a middle section of a road;

[0081] Step S1313: when a suspicious vehicle is further identified according to the second driving information, determining that the parking area corresponding to the suspicious vehicle is a sub-area corresponding to the middle section of another road corresponding to the second driving information;

[0082] Step S1314: when it is identified according to the first driving information that the suspicious vehicle appears at the beginning or the end of a road, the corresponding parking area is located as a sub-area corresponding to the beginning or the end of the road.

[0083] It can be understood that, generally, there are many roads from the entrance (exit) of the target area to the location of each sub-area, and these roads include intersecting roads and / or direct roads. Through the joint identification of the first driving information and the second driving information, the parking position of the suspicious vehicle can be narrowed down more accurately, that is, the corresponding parking area can be determined, thereby facilitating the reduction of the identification range of privately pulled cables and improving the judgment efficiency.

[0084] like Figure 4 As shown, as a preferred embodiment of the present invention, an action instruction is sent to a camera terminal in a corresponding parking area, wherein the action instruction is used to instruct the camera terminal to perform a rotation camera action, and push the image information obtained by performing the rotation camera action to the central end, including:

[0085] Step S1321: issuing an action instruction to the camera terminal in the corresponding parking area, wherein the action instruction carries the number of the camera terminal in the corresponding sub-area and the preset elevation angle of the sub-area relative to the camera terminal;

[0086] Step S1322: instructing the camera terminal in the sub-area to adjust and deflect back and forth according to the preset elevation angle to obtain image information within the preset elevation angle of the sub-area;

[0087] Step S1323: If a cable is detected in the image information, the image information obtained by executing the rotating camera action is pushed to the central end and a prompt is issued, and the prompt information is used to indicate that there may be private charging behavior of pulling wires in the corresponding parking area.

[0088] When this embodiment is applied, the corresponding parking area, such as the corresponding building number, can be locked through the sub-area in the aforementioned embodiment. Generally, each building is equipped with at least one camera terminal. Since the wires are generally pulled from higher floors to the ground, and the camera terminals used for monitoring are generally used to monitor thefts at lower locations such as the entrances and exits on the first floor, the cables pulled from higher floors to the ground can be identified by setting a preset elevation angle, and the preset elevation angle does not have to be very large. By instructing the camera terminal in the sub-area to adjust and deflect back and forth according to the preset elevation angle, all private wire pulling and charging behaviors in the building can be identified as much as possible, which is convenient for the central management personnel to respond in time and reduce the danger.

[0089] like Figure 5 As shown, as another preferred embodiment of the present invention, on the other hand, a big data-based information push system comprises:

[0090] The first vehicle identification recognition module 100 is used to obtain regional driving information within a first preset time period after big data recognition, and extract a first vehicle identification set from the regional driving information;

[0091] The second vehicle identification recognition module 200 is used to obtain the third-party charging record information within a second preset time period after obtaining the management authority, and extract the second vehicle identification set in the third-party charging record information, wherein the second vehicle identification set includes a frame number set;

[0092] A suspicious vehicle identification module 300, for identifying vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and marking such vehicles as suspicious vehicles;

[0093] The action instruction and push module 400 is used to trace the corresponding parking area of ​​the suspicious vehicle according to the regional driving information, and send an action instruction to the camera terminal in the corresponding parking area, wherein the action instruction is used to instruct the camera terminal to perform a rotation camera action, and push the image information obtained by performing the rotation camera action to the central end.

[0094] In the above-mentioned embodiment of the present invention, a method for pushing information based on big data is provided, and based on the method for pushing information based on big data, a system for pushing information based on big data is provided, which can identify, by means of big data, vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and obtain suspicious vehicles, that is, vehicles that have driving behavior but no charging records, so it is judged with the help of third-party charging record information that there is a high possibility of private cable charging behavior, and at this time, the corresponding parking area of ​​the suspicious vehicle is traced back according to the regional driving information;

[0095] An action instruction is sent to the camera terminal in the corresponding parking area, and the action instruction is used to instruct the camera terminal to perform a rotating camera action, and the image information obtained by performing the rotating camera action is pushed to the central end, which can further lock the corresponding position of the suspicious vehicle, and with the help of the camera terminal, the image information obtained by performing the rotating camera action is pushed to the central end, so as to facilitate the personnel at the central end to respond in time and reduce the occurrence of dangerous incidents.

[0096] In order to load the above-mentioned method and system and enable it to run smoothly, the system, in addition to the various modules mentioned above, may also include more or fewer components than described above, or a combination of certain components, or different components, for example, it may include input and output devices, network access devices, buses, processors and memories, etc.

[0097] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the system, and various interfaces and lines are used to connect various parts.

[0098] The above-mentioned memory can be used to store computer and system programs and / or modules, and the above-mentioned processor realizes the above-mentioned various functions by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as an information collection template display function, a product information release function, etc.). The data storage area can store data created according to the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that needs to be released by different product providers, etc.). In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMed i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0099] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0100] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0101] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for pushing information based on big data, characterized in that: The method comprises: Acquire regional driving information within a first preset time period identified by big data, and extract a first vehicle identification set from the regional driving information; After obtaining the management authority, obtaining third-party charging record information within a second preset time period, extracting a second vehicle identification set from the third-party charging record information, wherein the second vehicle identification set includes a frame number set; Identify vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and mark such vehicles as suspicious vehicles; The corresponding parking area of ​​the suspicious vehicle is traced according to the regional driving information, and an action instruction is sent to the camera terminal in the corresponding parking area. The action instruction is used to instruct the camera terminal to perform a rotation camera action, and the image information obtained by performing the rotation camera action is pushed to the central end.

2. The information push method based on big data according to claim 1, characterized in that: The step of obtaining regional driving information within a preset time period identified by big data and extracting a first vehicle identification set from the regional driving information includes: Obtaining an input of a first preset time period, where the first preset time period is at least the longest average flight time; Obtain vehicle driving record information at each import and export point in the target area; Identifying vehicle entry information exceeding a first preset number of times in vehicle driving record information; Identifying vehicle exit information exceeding a second preset number of times in the vehicle driving record information, wherein the vehicles corresponding to the vehicle entry information and the vehicle exit information are different vehicles; The vehicle identifications in the vehicle entry information and the vehicle exit information are respectively identified and counted to generate a first vehicle identification set, wherein the first vehicle identification set includes a license plate number set.

3. The method for pushing information based on big data according to claim 1 or 2, characterized in that: After obtaining the management authority, obtaining the third-party charging record information within the second preset time period, extracting the second vehicle identification set in the third-party charging record information, wherein the second vehicle identification set includes a frame number set, including: Obtain the authority to manage charging record information of third-party charging; Acquire all third-party charging record information in the target area within a second preset time period, wherein the first preset time period is included in the second preset time period, and the second preset time period is between one time the longest average battery life and two times the longest average battery life; A second vehicle identification set is extracted from all third-party charging record information, and duplicate second vehicle identifications are removed, where the second vehicle identification includes a frame number.

4. The information push method based on big data according to claim 3 is characterized in that: The method further comprises: Obtain the registration information of license plates and frames in the target area; Based on the license plate and frame registration information, identifying the frame number corresponding to the license plate number in the first vehicle identification set, and generating a first frame number; The first frame number is compared with the frame number in the second vehicle identification, a frame number in the first frame number that is different from the frame number in the second vehicle identification is obtained, and a second frame number is generated. The vehicle corresponding to the second frame number is a suspicious vehicle.

5. The information push method based on big data according to claim 2 is characterized in that: The method further comprises: Based on the second vehicle identification set corresponding to the suspicious vehicle, the regional driving information further includes regional driving sub-information, wherein the regional driving sub-information is first driving information of at least the first and last sections of each road and second driving information of the road intersection section; The regional driving sub-information of the suspicious vehicle in the regional driving information is identified, and the corresponding parking area of ​​the suspicious vehicle is determined according to the regional driving sub-information.

6. The information push method based on big data according to claim 5 is characterized in that: The method of determining the corresponding parking area of ​​the suspicious vehicle according to the regional driving sub-information includes: When it is identified according to the first driving information that the suspicious vehicle passes through the first section of a road but does not appear in the last section, the parking area corresponding to the positioning may be a sub-area corresponding to the middle section of the road; When the suspicious vehicle is still not identified according to the second driving information, it is determined that the parking area corresponding to the suspicious vehicle is a sub-area corresponding to the middle section of a road; When the suspicious vehicle is further identified according to the second driving information, the parking area corresponding to the suspicious vehicle is determined to be a sub-area corresponding to the middle section of another road corresponding to the second driving information; When a suspicious vehicle is identified as appearing at the beginning or end of a road according to the first driving information, the corresponding parking area is positioned as a sub-area corresponding to the beginning or end of the road.

7. The information push method based on big data according to claim 1 or 5, characterized in that: Sending an action instruction to a camera terminal in a corresponding parking area, wherein the action instruction is used to instruct the camera terminal to perform a rotation camera action, and pushing image information obtained by performing the rotation camera action to a central end, including: Sending an action instruction to the camera terminal in the corresponding parking area, wherein the action instruction carries the number of the camera terminal in the corresponding sub-area and the preset elevation angle of the sub-area relative to the camera terminal; Instruct the camera terminal in the sub-area to adjust according to the preset elevation angle and then deflect back and forth to obtain image information within the preset elevation angle of the sub-area; If a cable is detected in the image information, the image information obtained by performing a rotating camera action is pushed to the central end and a prompt is issued, and the prompt information is used to indicate that there may be private charging behavior of pulling wires in the corresponding parking area.

8. An information push system based on big data, characterized in that: The system comprises: A first vehicle identification recognition module is used to obtain regional driving information within a first preset time period after big data recognition, and extract a first vehicle identification set from the regional driving information; A second vehicle identification recognition module, configured to obtain, after obtaining management authority, third-party charging record information within a second preset time period, and extract a second vehicle identification set from the third-party charging record information, wherein the second vehicle identification set includes a frame number set; A suspicious vehicle identification module, used to identify vehicles corresponding to the first vehicle identification set that are not included in the vehicles corresponding to the second vehicle identification set, and mark such vehicles as suspicious vehicles; An action instruction and push module, the action instruction and push module is used to: trace the corresponding parking area of ​​the suspicious vehicle according to the regional driving information, and issue an action instruction to the camera terminal in the corresponding parking area, the action instruction is used to instruct the camera terminal to perform a rotation camera action, and push the image information obtained by performing the rotation camera action to the central end.

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