CN110930537A - Vehicle data acquisition method, device and equipment based on big data and storage medium - Google Patents
Vehicle data acquisition method, device and equipment based on big data and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a vehicle data acquisition method, device, equipment and storage medium based on big data, and relates to the technical field of big data processing. The method comprises the following steps: receiving a service starting instruction; collecting original state information of a vehicle; receiving a data query instruction, and extracting target state information from original state information based on an information query requirement in the data query instruction; calling a matched target report template from a preset report template library; and generating a target status report based on the target status information and the target report template, and sending the target status report to the target user. The method can acquire the state information of the vehicle in real time, quickly generate a corresponding report according to the query requirement and send the report to the user for reference, so that the processing efficiency of the vehicle data is improved, the user can effectively avoid the problems that the vehicle data is not acquired timely and the acquired data is inaccurate, and the user can conveniently take corresponding measures according to the reference result to realize various service functions.
Description
Technical Field
The application relates to the technical field of big data processing, in particular to a big data-based vehicle data acquisition method, device, equipment and storage medium.
Background
In the prior art, with the popularization of automobiles, more and more people choose to drive the automobiles to go out, and the urban driving safety problem becomes the focus of social and personal attention. The bad driving habits of drivers have the hidden trouble of causing traffic accidents, and the traffic accidents caused by the bad driving habits are in tens of thousands every year. When a driver is driving a vehicle, some undesirable driving behaviors such as cross-line driving, rapid acceleration, rapid deceleration and the like may often occur. However, the driver usually cannot know the bad driving behavior occurring in the driving process, and cannot correct the bad driving behavior. In the prior art, when a traffic accident occurs to a vehicle, after the vehicle owner stops the vehicle, the vehicle is manually called to give an alarm, and then the vehicle state information is manually acquired, so that the specific data of the vehicle cannot be acquired in real time manually and can only be judged according to some simple one-sided data, the specific data of the vehicle cannot be accurately acquired for utilization, the vehicle state information is not fully applied to accident judgment when the accident is judged, and a judgment error easily exists. Therefore, in the prior art, the problems that the vehicle data is not obtained timely and the obtained data is inaccurate exist.
Disclosure of Invention
The embodiment of the application aims to provide a vehicle data acquisition method, a device, equipment and a storage medium based on big data, and can solve the problem that more accurate vehicle data cannot be acquired in time.
In order to solve the above technical problem, an embodiment of the present application provides a vehicle data acquisition method based on big data, which adopts the following technical solutions:
the vehicle data acquisition method based on big data comprises the following steps:
receiving a service starting instruction;
activating a vehicle detection service in response to the service initiation instruction to collect original state information of a vehicle;
receiving a data query instruction, and extracting target state information from the original state information based on an information query requirement in the data query instruction;
calling a matched target report template from a preset report template library according to the information query requirement;
and generating a target state report based on the target state information and the target report template, and sending the target state report to a target user.
According to the vehicle data acquisition method based on the big data, the state information of the vehicle can be acquired in real time, the corresponding report is rapidly generated according to the query requirement and sent to the user for reference, the processing efficiency of the vehicle data is improved, the user can effectively avoid the problems that the vehicle data are not acquired timely and the acquired data are inaccurate, and the user can conveniently take corresponding measures according to the reference result to realize various service functions.
Further, in the big data-based vehicle data acquisition method, the step of receiving a service start instruction includes: and detecting a vehicle starting state, and activating and receiving a preset service starting instruction sent by a vehicle central control server after detecting that the vehicle is started.
Further, after the step of collecting the original state information of the vehicle, the method for acquiring vehicle data based on big data further comprises the steps of:
reading a preset identification code;
identifying the service terminal matched with the identification code;
and establishing communication connection with the service terminal so as to synchronize the original state information to the service terminal.
Further, after the step of collecting the original state information of the vehicle, the method for acquiring vehicle data based on big data further comprises the steps of:
acquiring normal driving state information from a server database;
monitoring the original state information, and judging whether the original state information has abnormal driving state information or not based on the normal driving state information;
and if the abnormal driving state information exists in the original state information, generating an alarm message based on the abnormal driving state information, and sending the alarm message to a target terminal for reminding.
Further, in the vehicle data acquisition method based on big data, the step of extracting the target state information from the original state information based on the information query requirement in the data query instruction includes:
analyzing the information query requirement in the data query instruction, and confirming the report type corresponding to the information query requirement;
determining a plurality of information reporting factors matched with the information query requirement according to the report type;
and extracting a plurality of target state information from the original state information based on the plurality of information reporting factors.
Further, in the vehicle data obtaining method based on big data, if it is determined that the report type corresponding to the information query requirement is a collision report, the plurality of information reporting factors determined according to the report type include: speed information, collision information, line crossing information, lane changing information and start-stop information; the collision information includes: collision time, collision position, collision force, collision direction and collision position;
the step of extracting a plurality of target status information from the original status information based on the plurality of information reporting factors comprises:
further identifying a collision query time interval corresponding to the information query requirement;
determining collision time in the collision information according to the collision query time interval in the original state information;
and extracting a plurality of pieces of target state information matched with the plurality of information reporting factors from the original state information based on the collision time.
Further, in the vehicle data acquiring method based on big data, a target time period corresponding to target state information expected to be queried is specified in the data query instruction, and after the step of extracting the target state information from the original state information based on the information query requirement in the data query instruction, the method further includes the steps of:
respectively vectorizing the target state information at different moments in the target time period to obtain corresponding quantized values, and respectively superposing and storing the quantized values of the same type of target state information in the target time period;
counting the total amount of the quantized values of different target state information in the target time period, and judging whether the total amount of the quantized values exceeds a preset quantized threshold value;
and if so, generating a reminding message for reminding the current vehicle owner of the high-risk driving user.
In order to solve the above technical problem, an embodiment of the present application further provides a vehicle data processing apparatus based on big data, which adopts the following technical solutions:
the big data-based vehicle data acquisition device comprises:
the instruction receiving module is used for receiving a service starting instruction;
the information acquisition module is used for responding to the service starting instruction to activate the vehicle detection service so as to acquire original state information of the vehicle;
the information extraction module is used for receiving a data query instruction and extracting target state information from the original state information based on an information query requirement in the data query instruction;
the template matching module is used for calling a matched target report template from a preset report template library according to the information query requirement;
and the report generating module is used for generating a target state report based on the target state information and the target report template and sending the target state report to a target user.
The vehicle data acquisition device based on big data can acquire the state information of the vehicle in real time, quickly generate a corresponding report according to the query requirement and send the report to a user for reference, improves the processing efficiency of the vehicle data, enables the user to effectively avoid the problems that the vehicle data is not acquired timely and the acquired data is inaccurate, and facilitates the user to take corresponding measures according to the reference result to realize various service functions.
In order to solve the above technical problem, an embodiment of the present application further provides a computer device, which adopts the following technical solutions:
the computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to realize the steps of the vehicle data acquisition method based on big data provided by the embodiment of the application.
In order to solve the above technical problem, an embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solutions:
the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of a big data based vehicle data acquisition method set forth in an embodiment of the present application.
Compared with the prior art, the embodiment of the application mainly has the following beneficial effects:
the embodiment of the application discloses a vehicle data acquisition method, a device, equipment and a medium based on big data, the vehicle data acquisition method based on big data receives a service starting instruction, responds to the service starting instruction to acquire original state information of a vehicle, then receives a data query instruction, extracts target state information from the original state information based on an information query requirement in the data query instruction, calls a target report template matched with the information query requirement from a preset report template library, finally generates a target state report based on the target state information and the target report template, and sends the target state report to a target user. The method can acquire the state information of the vehicle in real time, quickly generate a corresponding report according to the query requirement and send the report to the user for reference, so that the processing efficiency of the vehicle data is improved, the user can effectively avoid the problems that the vehicle data is not acquired timely and the acquired data is inaccurate, and the user can conveniently take corresponding measures according to the reference result to realize various service functions.
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In order to more clearly illustrate the solution of the present application, the drawings needed for describing the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.
FIG. 1 is a diagram of an exemplary system architecture to which embodiments of the present application may be applied;
FIG. 2 is a flow chart of one embodiment of a big-data based vehicle data acquisition method as described in embodiments of the present application;
FIG. 3 is a schematic structural diagram of an embodiment of a big data-based vehicle data acquisition device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an embodiment of a computer device in an embodiment of the present application.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "including" and "having," and any variations thereof, in the description and claims of this application and the description of the above figures are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and claims of this application or in the above-described drawings are used for distinguishing between different objects and not for describing a particular order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various communication client applications installed thereon, such as a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture experts Group Audio Layer III, mpeg compression standard Audio Layer 3), MP4 players (Moving Picture experts Group Audio Layer IV, mpeg compression standard Audio Layer 4), laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.
It should be noted that the vehicle data acquiring method of big data provided in the embodiment of the present application is generally executed by a server/terminal device, and accordingly, the vehicle data acquiring apparatus of big data is generally disposed in the server/terminal device.
It should be understood that the number of mobile terminals, servers, and car sticker apparatuses in fig. 1 is merely illustrative. There may be any number of mobile terminals, servers, and car sticker devices, as desired for implementation.
With continued reference to FIG. 2, a flow chart of one embodiment of a big-data based vehicle data acquisition method as described in embodiments of the present application is shown. The big data-based vehicle data acquisition comprises the following steps:
step 201: and receiving a service starting instruction.
The service initiation instruction is used to initiate a vehicle detection service in the vehicle. In this embodiment of the application, the service start instruction may be automatically issued by the vehicle central control server, or may be issued after being triggered by an operation performed in the vehicle central control server by a user operating the vehicle. The receiver of the service starting instruction can be intermediate-end equipment used for collecting vehicle state data on vehicles such as vehicle stickers containing various sensors.
In some embodiments of the present application, the step 201 comprises the steps of: and detecting a vehicle starting state, and activating and receiving a preset service starting instruction sent by a vehicle central control server after detecting that the vehicle is started. Therefore, the detection service can be automatically started when the vehicle is started so as to carry out a complete state monitoring process for vehicle operation and ensure the integrity of the collected driving data.
Sometimes, in order to collect the state information of the vehicle in real time, for example, when the vehicle is parked, the vehicle central control server also sends a service starting instruction so as to avoid that the vehicle cannot collect corresponding collision information when being collided by other vehicles after being parked in a parking lot or other parking places. The vehicle detection service consumes server resources, and in order to prevent resource waste, when the self-starting vehicle detection service is not performed, an operation user of the vehicle can select a starting time according to the requirement of the operation user, the operation user operates on the vehicle central control server to send a service starting instruction to the intermediate terminal device, and the intermediate terminal device starts the corresponding vehicle detection service after receiving the service starting instruction.
Step 202: and activating a vehicle detection service in response to the service starting instruction to collect original state information of the vehicle.
The original state information of the vehicle includes vehicle data when the vehicle stops and various driving data during the driving process of the vehicle, such as speed information, collision information, line crossing information, lane changing information, start and stop information and the like during the driving of the vehicle, and passive collision information and the like during the stopping of the vehicle. The driving data can be collected through various sensors in the middle-end equipment, such as a speed sensor, an acceleration sensor, a pressure sensor, a gyroscope and the like.
In some embodiments of the present application, after step 202, the big-data based vehicle data acquisition method further comprises the steps of:
reading a preset identification code;
identifying the service terminal matched with the identification code;
and establishing communication connection with the service terminal so as to synchronize the original state information to the service terminal.
The identification code can be a one-dimensional code, a two-dimensional code and other identification codes arranged on the intermediate-end equipment, and the two-dimensional code is better. The identification code is bound with application programs on other service terminals in advance, the service terminal bound by the identification code is identified, and communication connection is established between the service terminal and the identification code, so that original state information acquired by the intermediate terminal equipment is synchronized into the application program of the service terminal in real time for a vehicle owner or other users to check in the application program of the service terminal, and the vehicle owner or other users can know driving data of the vehicle in time.
In some embodiments of the present application, after step 202, the big-data based vehicle data acquisition method further comprises the steps of:
acquiring normal driving state information from a server database;
monitoring the original state information, and judging whether the original state information has abnormal driving state information or not based on the normal driving state information;
and if the abnormal driving state information exists in the original state information, generating an alarm message based on the abnormal driving state information, and sending the alarm message to a target terminal for reminding.
The server database can be a database in a vehicle central control server or a server database which is connected with the intermediate terminal equipment through a network and stores normal driving state information. In the process of collecting and monitoring the original state information, if some driving data in the original state information is found to be obviously different from normal driving data, the driving data is used as abnormal driving state information to be integrated and recorded, and a corresponding warning message is generated and sent to a target terminal to remind. The target to be reminded is a user currently driving a vehicle, and the target terminal may be communication equipment of the user currently driving the vehicle or alarm equipment in a vehicle central control server of the current vehicle. The form of the reminder includes but is not limited to short message, voice, text display, etc.
If bad driving behaviors occur when a driver drives a vehicle, such as cross-line driving, rapid acceleration, rapid deceleration and the like, sometimes the driver cannot timely know that the bad driving behaviors exist, the driver cannot timely pay attention to and correct the bad driving behaviors, and great potential safety hazards exist.
Step 203: and receiving a data query instruction, and extracting target state information from the original state information based on an information query requirement in the data query instruction.
In different demand scenes, the vehicle state data which the user wants to inquire are different, and the user can configure the information inquiry requirement in the data inquiry instruction according to different demands, so that the intermediate terminal equipment extracts different target state information from the original state information based on different information inquiry requirements.
In some embodiments of the present application, the step of extracting target state information from the original state information based on the information query requirement in the data query instruction in step 203 includes:
analyzing the information query requirement in the data query instruction, and confirming the report type corresponding to the information query requirement;
determining a plurality of information reporting factors matched with the information query requirement according to the report type;
and extracting a plurality of target state information from the original state information based on the plurality of information reporting factors.
Therefore, before extracting the required target state information from the original state information, the report type corresponding to the information query requirement can be obtained by analyzing the information query requirement in the data query instruction. Based on various vehicle reports classified in advance under big data, a plurality of information reporting factors required in query can be conveniently determined according to report types. Each information reporting factor uniquely determines the state information of one type of vehicle, so that a plurality of target state information which is required by the information inquiry and is compounded can be extracted from the original state information according to a plurality of information reporting factors.
Further, in a specific implementation manner of the embodiment of the present application, if it is determined that the report type corresponding to the information query requirement is a collision report, the several information reporting factors determined according to the report type include: speed information, collision information, line crossing information, lane changing information and start-stop information; the collision information includes: collision time, collision position, collision force, collision direction and collision position;
the step of extracting a plurality of target status information from the original status information based on the plurality of information reporting factors comprises:
further identifying a collision query time interval corresponding to the information query requirement;
determining collision time in the collision information according to the collision query time interval;
and extracting a plurality of pieces of target state information matched with the plurality of information reporting factors from the original state information based on the collision time.
The speed information may be a current speed (magnitude), acceleration (magnitude), rapid deceleration (magnitude), speed (magnitude) of a sharp turn, etc. of the vehicle, for example: the current speed was 160 km/h. The crossline information may be illegal crossline information, such as: white solid lines are crossed in the same-direction driving, yellow solid lines are crossed in the two-way lane, and the like. The lane change information may be switching between multiple lanes in the same direction, for example: changing lanes from the first lane to the second lane.
The start-stop information comprises flameout information and ignition information. The flameout information can be flameout in the driving process, flameout when waiting for a traffic light, flameout when starting and the like; the ignition information may be various index states of the vehicle at the time of starting, for example: the speed is started.
The collision time in the collision information may be accurate to seconds, and may even be minutes or milliseconds, such as: year 2018, month 2, day 6, 17:12: 32. The collision location may be accurate from latitude and longitude to seconds, for example: n22 ° 30' 14.5 ". The collision force may be the magnitude of the collision force, and specifically, the collision force may be set to a level, for example, first, second, third, and so on. The collision direction and the collision location may be determined from respective sensors and gyroscopes, for example: the left side below the front part is deviated from the left 20 degrees direction. Through the data acquired by each sensor in the intermediate-end equipment, the acquisition efficiency of the vehicle state data can be improved, the state of the vehicle can be accurately processed and judged, and misjudgment or trouble caused by manual processing can be avoided as much as possible.
The target state information is extracted from the original state information to acquire vehicle data at the time of collision for the purpose of generating a collision report, and a user who makes an inquiry generally defines an approximate range of collision time and desires to inquire vehicle collision information within the range.
Therefore, by further identifying the collision inquiry time interval specified by the user when the information inquiry requirement is configured, and determining the collision time from the original state information based on the time interval, a plurality of required target state information can be extracted from the original state information by taking the collision time as a node or an interval more accurately.
If the inquiry is about the vehicle running, namely the collision report in the running process, the collision factor can also comprise the driving track route information, and the information can be acquired after the vehicle runs and is connected with the satellite navigation system through the intermediate terminal equipment.
In the embodiment of the present application, the electronic device (for example, the server/terminal device shown in fig. 1) on which the big data based vehicle data acquisition method operates may receive the service initiation instruction and the data query instruction through a wired connection manner or a wireless connection manner. It should be noted that the Wireless connection manner may include, but is not limited to, a 3G/4G connection, a WiFi (Wireless-Fidelity) connection, a bluetooth connection, a wimax (worldwide Interoperability for microwave access) connection, a Zigbee (low power local area network protocol), a uwb (ultra wideband) connection, and other Wireless connection manners known now or developed in the future.
Step 204: and calling the matched target report template from a preset report template library according to the information query requirement.
Step 205: and generating a target state report based on the target state information and the target report template, and sending the target state report to a target user.
In the embodiment of the application, the type of the report is selected differently according to different requirement scenes of the target user. The generated user status report is used to provide support for various vehicle data to the target user. Configuring and storing a plurality of report templates corresponding to different demand scenarios in a report template library of a server in advance, so that after a target user desires to obtain a corresponding report and configures an information query demand, an intermediate terminal device calls a required target report template from the report template library of the server according to the information query demand, and then fills the extracted target state information into the target report template to generate a target state report.
In this embodiment, the target user may include: a car owner terminal, a traffic police terminal, an insurance company terminal, a hospital terminal, etc. Correspondingly, the target status report may include: driving reports, warning reports, insurance reports, and the like. The owner end generally corresponds to a driving report, the traffic police end can correspond to an alarm report, and the insurance company corresponds to an insurance report.
Specifically, the driving report may provide driving data to a target user, such as a driver, so that the user can know the current driving data of the vehicle and know the driving behavior of the user. The alarm report can be generated according to collision information of accidents and the like when the vehicle has an accident, and the alarm report is sent to law enforcement personnel when the vehicle has the accident, so that the law enforcement personnel can analyze the vehicle accident, judge the reason and the severity of the accident caused by the vehicle accident, and further improve the accuracy and the processing efficiency of the accident analysis. The insurance report can know the specific condition of the accident loss for the insurance company, so that the insurance company can conveniently carry out insurance and compensation analysis and reasonably process the matter of settlement of the claim.
The user status report may further include a vehicle moving report and the like. The vehicle moving report is generated when other users beside the parked vehicle want to contact the owner of the parked vehicle to move the parked vehicle, so that target users (such as the owners) can view and know the relevant information on the application program corresponding to the terminal. Other users can send out a data query instruction for generating a vehicle moving report by scanning the two-dimensional code on the intermediate-end device, and the traditional telephone remaining mode is replaced by a code scanning mode, so that privacy exposure of a personal number and the like of an owner can be effectively avoided.
In a specific implementation manner of the embodiment of the present application, after the step 203, a target time period corresponding to target state information that is expected to be queried is specified in the data query instruction, and the vehicle data acquisition method based on big data further includes the steps of:
respectively vectorizing the target state information at different moments in the target time period to obtain corresponding quantized values, and respectively superposing and storing the quantized values of the same type of target state information in the target time period;
counting the total amount of the quantized values of different target state information in the target time period, and judging whether the total amount of the quantized values exceeds a preset quantized threshold value;
and if so, generating a reminding message for reminding the current vehicle owner of the high-risk driving user.
The quantized value refers to quantizing data corresponding to the target state information of one vehicle into one value, and may be specifically set to different integer values, such as 1, 2, 3, or 5, according to needs. And performing vectorization on each type of obtained target state information at a certain moment, counting and storing, and performing vectorization processing and accumulating and storing with the previously stored quantized value of the target state information when the same target state information is acquired again at the next moment. If a plurality of target state information are collected simultaneously, quantization can be carried out respectively, accumulation is carried out respectively, and storage is carried out respectively.
The prompt message for prompting that the current vehicle owner is a high-risk driving user can be sent to the application program of the mobile terminal for the vehicle owner to know the driving condition of the vehicle owner, and can also be sent to a system of a vehicle equipment management company for the company to analyze the driving condition of the vehicle owner.
The target time period can be set at will, and different quantitative threshold values for judging whether the vehicle owner is a high-risk driving user can be set in advance according to different target time periods. This is further understood by the following particulars: the target time period is set to be half an hour, the correspondingly set quantization threshold value is 20, and the target state information comprises speed change information, cross-line information and start-stop information; if the acquired vehicle is accelerated rapidly for 12 times, the line crossing times are 10 times, the ignition is 15 times, and the flameout is 5 times, it can be understood that the quantized value of the speed change information in the target time period is 12, the quantized value corresponding to the line crossing information is 10, the quantized value corresponding to the start-stop information is 20, the total amount of the quantized values is 42, and exceeding the quantized threshold value indicates that the vehicle owner has a large bad driving behavior, so that the current vehicle owner is judged to be a high-risk driving user.
According to the vehicle data acquisition method based on the big data, the state information of the vehicle can be acquired in real time, the corresponding report is rapidly generated according to the query requirement and sent to the user for reference, the processing efficiency of the vehicle data is improved, the user can effectively avoid the problems that the vehicle data are not acquired timely and the acquired data are inaccurate, and the user can conveniently take corresponding measures according to the reference result to realize various service functions.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the computer program is executed. The storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
With further reference to fig. 3, fig. 3 is a schematic structural diagram of an embodiment of the big-data based vehicle data acquisition apparatus according to the embodiment of the present application. As an implementation of the method shown in fig. 2, the present application provides an embodiment of a big data-based vehicle data acquisition apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which can be applied to various electronic devices.
As shown in fig. 3, the big-data-based vehicle data acquisition apparatus according to the present embodiment includes:
an instruction receiving module 301; for receiving a service initiation instruction.
An information acquisition module 302; for activating a vehicle detection service in response to the service initiation instruction to collect raw state information of the vehicle.
An information extraction module 303; the system is used for receiving a data query instruction and extracting target state information from the original state information based on an information query requirement in the data query instruction.
A template matching module 304; and the target report template is used for calling the matched target report template from a preset report template library according to the information query requirement.
A report generation module 305; and the target report module is used for generating a target status report based on the target status information and the target report template and sending the target status report to a target user.
In some embodiments of the present application, the instruction receiving module 301 comprises: the detection submodule is started. The starting monitoring submodule is used for detecting a vehicle starting state so as to activate and receive a preset service starting instruction sent by a vehicle central control server after detecting that the vehicle is started.
In some embodiments of the present application, the big-data based vehicle data acquisition apparatus further comprises: and an information synchronization module. After the information acquisition module 302 acquires the original state information of the vehicle, the information synchronization module is used for reading a preset identification code; identifying the service terminal matched with the identification code; and establishing communication connection with the service terminal so as to synchronize the original state information to the service terminal.
In some embodiments of the present application, the big-data based vehicle data acquisition apparatus further comprises: and an abnormal state processing module. After the information acquisition module 302 acquires the original state information of the vehicle, the abnormal state processing module is used for acquiring the normal driving state information from the server database; monitoring the original state information, and judging whether the original state information has abnormal driving state information or not based on the normal driving state information; and if the abnormal driving state information exists in the original state information, generating an alarm message based on the abnormal driving state information, and sending the alarm message to a target terminal for reminding.
In some embodiments of the present application, the information extraction module 303 includes: and a target extraction submodule. The target extraction sub-module is used for analyzing the information query requirement in the data query instruction and confirming the report type corresponding to the information query requirement; determining a plurality of information reporting factors matched with the information query requirement according to the report type; and extracting a plurality of target state information from the original state information based on the plurality of information reporting factors.
Further, in a specific implementation manner of the embodiment of the present application, if it is determined that the report type corresponding to the information query requirement is a collision report, the several information reporting factors determined according to the report type include: speed information, collision information, line crossing information, lane changing information and start-stop information; the collision information includes: collision time, collision position, collision force, collision direction and collision position; the target extraction submodule is also used for further identifying a collision query time interval corresponding to the information query requirement; determining collision time in the collision information according to the collision query time interval; and extracting a plurality of pieces of target state information matched with the plurality of information reporting factors from the original state information based on the collision time.
In a specific implementation manner of the embodiment of the application, the data query instruction specifies a target time period corresponding to target state information that is expected to be queried, and the vehicle data acquisition apparatus based on big data further includes: and a quantization processing module. After the information extraction module 303 extracts the target state information from the original state information, the quantization processing module is configured to perform vectorization on the target state information at different times in the target time period to obtain corresponding quantization values, and perform superposition storage on the quantization values of the same type of target state information in the target time period; counting the total amount of the quantized values of different target state information in the target time period, and judging whether the total amount of the quantized values exceeds a preset quantized threshold value; and if so, generating a reminding message for reminding the current vehicle owner of the high-risk driving user.
The vehicle data acquisition device based on big data can acquire the state information of the vehicle in real time, quickly generate a corresponding report according to the query requirement and send the report to a user for reference, improves the processing efficiency of the vehicle data, enables the user to effectively avoid the problems that the vehicle data is not acquired timely and the acquired data is inaccurate, and facilitates the user to take corresponding measures according to the reference result to realize various service functions.
In order to solve the technical problem, an embodiment of the present application further provides a computer device. Referring to fig. 4, fig. 4 is a block diagram of a basic structure of a computer device according to the present embodiment.
The computer device 6 comprises a memory 61, a processor 62, a network interface 63 communicatively connected to each other via a system bus. It is noted that only a computer device 6 having components 61-63 is shown, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable gate array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.
The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.
The memory 61 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 61 may be an internal storage unit of the computer device 6, such as a hard disk or a memory of the computer device 6. In other embodiments, the memory 61 may also be an external storage device of the computer device 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a flash Card (FlashCard), and the like, which are provided on the computer device 6. Of course, the memory 61 may also comprise both an internal storage unit of the computer device 6 and an external storage device thereof. In this embodiment, the memory 61 is generally used for storing an operating system installed in the computer device 6 and various types of application software, such as program codes of a vehicle data acquisition method based on big data. Further, the memory 61 may also be used to temporarily store various types of data that have been output or are to be output.
The processor 62 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 62 is typically used to control the overall operation of the computer device 6. In this embodiment, the processor 62 is configured to run the program code stored in the memory 61 or process data, for example, the program code of the big data based vehicle data acquisition method.
The network interface 63 may comprise a wireless network interface or a wired network interface, and the network interface 63 is typically used for establishing a communication connection between the computer device 6 and other electronic devices.
The present application provides yet another embodiment that provides a computer-readable storage medium having stored thereon a big-data based vehicle data acquisition program executable by at least one processor to cause the at least one processor to perform the steps of the big-data based vehicle data acquisition method as described above.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
In the above embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and other divisions may be realized in practice, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed.
The modules or components may or may not be physically separate, and the components shown as modules or components may or may not be physical modules, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules or components can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The present application is not limited to the above-mentioned embodiments, the above-mentioned embodiments are preferred embodiments of the present application, and the present application is only used for illustrating the present application and not for limiting the scope of the present application, it should be noted that, for a person skilled in the art, it is still possible to make several improvements and modifications to the technical solutions described in the foregoing embodiments or to make equivalent substitutions for some technical features without departing from the principle of the present application. All equivalent structures made by using the contents of the specification and the drawings of the present application can be directly or indirectly applied to other related technical fields, and the same should be considered to be included in the protection scope of the present application.
It is to be understood that the above-described embodiments are merely illustrative of some, but not restrictive, of the broad invention, and that the appended drawings illustrate preferred embodiments of the invention and do not limit the scope of the invention. This application is capable of embodiments in many different forms and is provided for the purpose of enabling a thorough understanding of the disclosure of the application. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to one skilled in the art that the present application may be practiced without modification or with equivalents of some of the features described in the foregoing embodiments. All other embodiments that can be obtained by a person skilled in the art based on the embodiments in this application without any creative effort and all equivalent structures made by using the contents of the specification and the drawings of this application can be directly or indirectly applied to other related technical fields and are within the scope of protection of the present application.
Claims (10)
1. A big data-based vehicle data acquisition method is characterized by comprising the following steps:
receiving a service starting instruction;
activating a vehicle detection service in response to the service initiation instruction to collect original state information of a vehicle;
receiving a data query instruction, and extracting target state information from the original state information based on an information query requirement in the data query instruction;
calling a matched target report template from a preset report template library according to the information query requirement;
and generating a target state report based on the target state information and the target report template, and sending the target state report to a target user.
2. The big-data based vehicle data acquisition method according to claim 1, wherein the step of receiving a service initiation instruction comprises: and detecting a vehicle starting state, and activating and receiving a preset service starting instruction sent by a vehicle central control server after detecting that the vehicle is started.
3. The big data based vehicle data acquisition method according to claim 1, wherein after the step of collecting raw state information of the vehicle, the method further comprises the steps of:
reading a preset identification code;
identifying the service terminal matched with the identification code;
and establishing communication connection with the service terminal so as to synchronize the original state information to the service terminal.
4. The big data based vehicle data acquisition method according to claim 1, wherein after the step of collecting raw state information of the vehicle, the method further comprises the steps of:
acquiring normal driving state information from a server database;
monitoring the original state information, and judging whether the original state information has abnormal driving state information or not based on the normal driving state information;
and if the abnormal driving state information exists in the original state information, generating an alarm message based on the abnormal driving state information, and sending the alarm message to a target terminal for reminding.
5. The big-data-based vehicle data acquisition method according to claim 1, wherein the step of extracting target state information from the original state information based on an information query requirement in the data query instruction comprises:
analyzing the information query requirement in the data query instruction, and confirming the report type corresponding to the information query requirement;
determining a plurality of information reporting factors matched with the information query requirement according to the report type;
and extracting a plurality of target state information from the original state information based on the plurality of information reporting factors.
6. The big data-based vehicle data acquisition method according to claim 5, wherein if it is determined that the report type corresponding to the information query requirement is a collision report, the plurality of information reporting factors determined according to the report type include: speed information, collision information, line crossing information, lane changing information and start-stop information; the collision information includes: collision time, collision position, collision force, collision direction and collision position;
the step of extracting a plurality of target status information from the original status information based on the plurality of information reporting factors comprises:
further identifying a collision query time interval corresponding to the information query requirement;
determining collision time in the collision information according to the collision query time interval in the original state information;
and extracting a plurality of pieces of target state information matched with the plurality of information reporting factors from the original state information based on the collision time.
7. The big-data-based vehicle data acquisition method according to claim 1, wherein a target time period corresponding to target state information expected to be queried is specified in the data query instruction, and after the step of extracting the target state information from the original state information based on the information query in the data query instruction, the method further comprises the steps of:
respectively vectorizing the target state information at different moments in the target time period to obtain corresponding quantized values, and respectively superposing and storing the quantized values of the same type of target state information in the target time period;
counting the total amount of the quantized values of different target state information in the target time period, and judging whether the total amount of the quantized values exceeds a preset quantized threshold value;
and if so, generating a reminding message for reminding the current vehicle owner of the high-risk driving user.
8. A big-data-based vehicle data acquisition apparatus, characterized by comprising:
the instruction receiving module is used for receiving a service starting instruction;
the information acquisition module is used for responding to the service starting instruction to activate the vehicle detection service so as to acquire original state information of the vehicle;
the information extraction module is used for receiving a data query instruction and extracting target state information from the original state information based on an information query requirement in the data query instruction;
the template matching module is used for calling a matched target report template from a preset report template library according to the information query requirement;
and the report generating module is used for generating a target state report based on the target state information and the target report template and sending the target state report to a target user.
9. A computer device comprising a memory having stored therein a computer program and a processor that when executed implements the steps of a big-data based vehicle data acquisition method as claimed in claim 1.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of a big-data based vehicle data acquisition method as claimed in claim 1.
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