CN113378157A - Car networking data acquisition system based on embedded software secondary development - Google Patents
Car networking data acquisition system based on embedded software secondary development Download PDFInfo
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Abstract
The invention belongs to the technical field of vehicle networking, and particularly relates to a vehicle networking data acquisition system based on embedded software secondary development. The monitoring terminal processes relevant vehicle-mounted big data according to the cloud platform, and the main functional modules comprise a data management module, a data analysis module and a data storage module. The invention can not only collect and record various data in the vehicle running process in real time, but also monitor the running state and the vehicle using state of the target vehicle in real time and position and track the target vehicle in real time; meanwhile, aiming at different user requirements, the system operation command can be designed by self, and the humanized design of the system based on different users is realized. The vehicle-mounted big data analysis and management method is based on the cloud platform, and is convenient for analysis and management of the vehicle-mounted big data.
Description
Technical Field
The invention belongs to the technical field of vehicle networking, and particularly relates to a vehicle networking data acquisition system based on embedded software secondary development.
Background
At present, with the continuous development of the internet of things technology, in the field of intelligent automobile control, a large amount of local data of an automobile needs to be interacted with a remote server, and a traditional vehicle-mounted terminal is developed based on an embedded system, is complex in structure and high in development cost, and is poor in compatibility with existing equipment and limited in application range.
Data transmission terminals often contain sensitive information of users, such as power-on passwords, user privacy, biological characteristic information and the like, and the traditional scheme is to encrypt the sensitive information by using software, calculate the user information by using an encryption algorithm and an encryption key to generate a ciphertext, and store the key and the ciphertext in Flash. Due to the characteristics of publicization and standardization of the modern cryptographic technology, an encryption algorithm is not secret, a secret key is true secret, an operating system is inevitable to have a bug, and an attacker can break through the limitation of the operating system to obtain the secret key, so that the security of the secret key cannot be guaranteed by a pure software method. The terminal has the functions of strong network connection, data uploading, equipment control, remote monitoring and the like, and the identity of the remote terminal is confirmed through information such as an IP address, an MAC address and the like in the traditional method of an authorized operator, and the identity is easy to forge, so that an attack event is caused.
Through the above analysis, the problems and defects of the prior art are as follows: the traditional data transmission terminal has insufficient safety and is very easy to attack; the traditional vehicle-mounted terminal is developed based on an embedded system, and secondary development is difficult to carry out. Meanwhile, the traditional vehicle-mounted terminal is complex in structure, high in development cost, poor in compatibility of equipment and limited in application range.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a vehicle networking data acquisition system based on embedded software secondary development.
The invention is realized in this way, a vehicle networking data acquisition system based on embedded software secondary development, the vehicle networking data acquisition system based on embedded software secondary development includes: the system comprises a vehicle-mounted terminal, a monitoring terminal and a cloud platform;
the vehicle-mounted terminal includes: the device comprises an equipment control module, a programming module, a visualization module, an MCU control module, a communication module, a remote control module and a positioning module;
the equipment control module is used for acquiring data, controlling hardware operation and setting the acquired data;
the programming module is used for customizing commands and monitoring parameter settings for users;
the visualization module is used for displaying the monitoring parameters in an interface mode and processing the acquired images;
in the process of image processing, the specific process of denoising the image is as follows:
a basic processing stage:
grouping, determining a reference block with a size of k multiplied by k in a noise image, searching in a region with a proper size around the reference block, searching for a plurality of blocks with minimum difference, integrating the blocks into a 3-dimensional matrix, integrating the reference block into the 3-dimensional matrix, and searching for a similar block model:
G(P)＝{Q：d(P，Q)≤τstep}；
d (P, Q) is the Euclidean distance between two blocks, the two blocks are sorted from small to large according to the distance, and 1 MAXNs are selected and stacked into a three-dimensional array;
performing collaborative filtering, namely performing two-dimensional transformation on a two-dimensional block in each three-dimensional matrix and then performing one-dimensional transformation on the third dimension of the matrix; after transformation, the value is smaller than the hyper-parameter lambda in a hard threshold mode3DThe component (A) is 0; meanwhile, counting the number of non-zero components as a reference of subsequent weight, and finally obtaining a processed image block through one-dimensional inverse transformation and two-dimensional inverse transformation in the third dimension;
the image blocks are put back to the original position after inverse transformation, the number of nonzero components is utilized to count the superposition weight, the superposed images are divided by the weight of each point to obtain an image of basic estimation, the weight depends on the number of 0 blocks and the noise intensity, and the noise of the image is greatly removed;
and (3) a final stage:
after the basic stage is finished, the Euclidean distance of the corresponding basic estimation image blocks is used for measuring the similarity; sorting according to the distance from small to large, and then taking 1 top MAXNs at most; respectively overlapping the basic estimation image blocks and the original image blocks containing noise into two three-dimensional arrays;
two-dimensional and one-dimensional transformation is carried out on the two three-dimensional matrixes, and DCT transformation is adopted for the two-dimensional transformation; scaling a three-dimensional matrix formed by the noise image by using wiener filtering, wherein the coefficient is obtained by the value of the three-dimensional matrix estimated based on the basis and the noise intensity; this process is represented by the following formula, where wpAre the coefficients of the wiener filter:
the image blocks are put back to the original position after inverse transformation, the number of nonzero components is utilized to count the superposition weight, the superposed images are divided by the weight of each point to obtain an image of basic estimation, the weight depends on the number of 0 blocks and the noise intensity, and the noise of the image is greatly removed;
the MCU control module is respectively connected with the equipment control module, the programming module, the visualization module, the communication module, the remote control module and the positioning module to coordinate the normal operation of each module,
the communication module is connected with the monitoring terminal and used for carrying out interactive transmission of data information;
the remote control module is used for analyzing and transmitting the communication protocol information to the remote control module based on corresponding software control, the remote control module further decodes the communication protocol information, and related control signals are transmitted to the MCU control module;
and the positioning module is used for positioning the vehicle through the positioner.
Further, the monitoring terminal processes relevant vehicle-mounted big data according to the cloud platform, collects and records various data in the vehicle running process in real time, monitors the running state and the vehicle using state of the target vehicle in real time, and positions and tracks the target vehicle in real time.
Further, the monitor terminal includes: the system comprises a data management module, a data analysis module and a data storage module;
the data management module is mainly used for adding, deleting and inquiring information;
the data storage module is mainly used for carrying out storage classification based on the label of a user, corresponding vehicle-mounted data and a timestamp;
the data analysis module mainly depends on vehicle-mounted information to perform relevant dimension reduction analysis, and analysis of cross-space information on a time axis is performed.
Further, the specific process of the data storage module for storage classification is as follows:
according to the label of the user, the corresponding vehicle-mounted data and the timestamp data set, determining the classified class or group, and randomly initializing the respective central point;
determining the distance from the data point to be classified to the central point, and classifying the data closest to the central point into one class according to the calculated value of the distance;
and meanwhile, calculating the center point of each type as a new center point, and repeating the steps until the change of the center of each type is not large after each iteration.
Further, the specific processes of adding, deleting and inquiring information by the data management module are as follows;
assuming that the initial state of a given data set is that all vertices have not been visited, one vertex is selected as the initial point of traversal in a given data set, and a depth-first search recursive call is made:
accessing the searched non-accessed adjacent points, and marking the vertex as an accessed node;
searching the non-accessed adjacent point of the vertex, and if the adjacent point exists, starting the same access and search from the adjacent point.
Further, the data collected by the equipment control module mainly comprises information about whether various equipment such as a vehicle speed, various temperatures, a wheel speed, an engine torque, an accelerator, a brake pedal, a gear lever position, an air conditioner works or not and fault information;
furthermore, the setting mode of the data collected by the equipment control module is that the vehicle-mounted terminal is used for the first time, the request for monitoring data is sent, the monitoring terminal returns the initial monitoring data, the user enters the programmable module, the monitoring items are automatically added and deleted, and the customization of the monitoring indexes is realized through storage and uploading.
Further, the protocol adopted by the communication module is a TCP or UDP data protocol.
Another object of the present invention is to provide a computer program product stored on a computer readable medium, which includes a computer readable program for providing a user input interface to implement the embedded software secondary development-based data acquisition system for car networking when the computer program product is executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute the vehicle networking data acquisition system based on embedded software secondary development.
By combining all the technical schemes, the invention has the advantages and positive effects that: the embedded system of the invention can realize the control of system instructions and the control of vehicle monitoring indexes by user programming. And monitoring the multi-information quantity to realize the acquisition of multi-mode information of the vehicle. The collection of vehicle information is expanded. And the monitoring terminal based on the cloud platform realizes storage management of a large amount of vehicle-mounted information.
Meanwhile, the invention is based on software modular design, vehicle monitoring and data index acquisition, cloud platform technology and the like. The modular design is that simply, the writing of the program does not start to input computer sentences and instructions one by one, but first describes the main structure and flow of the software by using frames such as a main program, a subprogram, a subprocess and the like, and defines and debugs the input and output link relation among the frames. The result of the progressive refinement is a series of algorithmic descriptions in functional block units. The method of designing a program in units of functional blocks to realize the solution algorithm is called modularization. The modularization aims to reduce the complexity of a program and simplify operations such as program design, debugging and maintenance. And only the corresponding module needs to be correspondingly changed when a certain sub-function is changed. The vehicle monitoring and collecting indexes mainly comprise whether various devices such as the vehicle speed, various temperatures, the wheel speed, the engine torque, an accelerator, a brake pedal, the gear lever position, an air conditioner and the like work or not, fault information and the like. Cloud technology (Cloud technology) is based on a general term of network technology, information technology, integration technology, management platform technology, application technology and the like applied in a Cloud computing business model, can form a resource pool, is used as required, and is flexible and convenient. Cloud computing technology will become an important support. Background services of the technical network system require a large amount of computing and storage resources, such as video websites, picture-like websites and more web portals. With the high development and application of the internet industry, each article may have its own identification mark and needs to be transmitted to a background system for logic processing, data in different levels are processed separately, and various industrial data need strong system background support and can only be realized through cloud computing.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a vehicle-mounted terminal of a vehicle networking data acquisition system based on secondary development of embedded software according to an embodiment of the present invention.
Fig. 2 is a flowchart of a monitoring parameter setting process of the vehicle networking data acquisition system of the secondary development of the embedded software according to the embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a monitoring terminal of a vehicle networking data acquisition system for secondary development of embedded software according to an embodiment of the present invention.
Fig. 4 is a flowchart of a method for classifying storage of a data storage module according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for adding, deleting, and querying information by a data management module according to an embodiment of the present invention.
In the figure: 1. a vehicle-mounted terminal; 2. a device control module; 3. a programming module; 4. a visualization module; 5. an MCU control module; 6. a communication module; 7. a remote control module; 8. a positioning module; 9. a monitoring terminal; 10. an information management module; 11. an information analysis module; 12. and an information storage module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The acquisition system based on the embedded vehicle-mounted terminal has relatively less acquired data, and the acquired data is fixed, the vehicle remote control technology is improved, and the cloud technology is developed rapidly. Aiming at the problems in the prior art, the invention provides a vehicle networking data acquisition system based on embedded software secondary development, and the invention is described in detail with reference to the attached drawings.
As shown in fig. 1, the car networking data acquisition system based on embedded software secondary development provided by the embodiment of the present invention includes: the system comprises a vehicle-mounted terminal 1, a monitoring terminal 9 and a cloud platform;
the in-vehicle terminal 1 includes: the device comprises a device control module 2, a programming module 3, a visualization module 4, an MCU control module 5, a communication module 6, a remote control module 7 and a positioning module 8.
The equipment control module 2 is used for acquiring data, controlling hardware operation and setting the acquired data; the data collected by the equipment control module mainly comprises information about whether various equipment such as vehicle speed, various temperatures, wheel speed, engine torque, an accelerator, a brake pedal, a gear lever position, an air conditioner and the like work or not and fault information; the setting mode of data acquisition of the equipment control module is that the vehicle-mounted terminal is used for the first time, a request monitoring data request is sent, the monitoring terminal returns initial monitoring data, a user enters the programmable module, monitoring items are automatically added and deleted, and customization of monitoring indexes is achieved through storage and uploading.
The programming module 3 is used for setting user-defined commands and user-defined monitoring parameters;
the visualization module 4 is used for displaying the monitoring parameters in an interface mode and processing the acquired images;
the MCU control module 5 is respectively connected with the equipment control module, the programming module, the visualization module, the communication module, the remote control module and the positioning module and coordinates the normal operation of each module;
the communication module 6 is connected with the monitoring terminal and used for carrying out interactive transmission of data information; the protocol adopted by the communication module is TCP and UDP data protocol.
The remote control module 7 is used for analyzing and transmitting the communication protocol information to the remote control module based on corresponding software control, the remote control module further decodes the communication protocol information, and related control signals are transmitted to the MCU control module;
and the positioning module 8 is used for positioning the vehicle through the positioner.
In the process of image processing in the visualization module provided by the embodiment of the invention, the specific process of denoising the image is as follows:
a basic processing stage:
grouping, determining a reference block with a size of k multiplied by k in a noise image, searching in a region with a proper size around the reference block, searching for a plurality of blocks with minimum difference, integrating the blocks into a 3-dimensional matrix, integrating the reference block into the 3-dimensional matrix, and searching for a similar block model:
G(P)＝{Q：d(P，Q)≤τstep}；
d (P, Q) is the Euclidean distance between two blocks, the two blocks are sorted from small to large according to the distance, and 1 MAXNs are selected and stacked into a three-dimensional array;
performing collaborative filtering, namely performing two-dimensional transformation on a two-dimensional block in each three-dimensional matrix and then performing one-dimensional transformation on the third dimension of the matrix; after transformation, the value is smaller than the hyper-parameter lambda in a hard threshold mode3DThe component (A) is 0; meanwhile, counting the number of non-zero components as a reference of subsequent weight, and finally obtaining a processed image block through one-dimensional inverse transformation and two-dimensional inverse transformation in the third dimension;
the image blocks are put back to the original position after inverse transformation, the number of nonzero components is utilized to count the superposition weight, the superposed images are divided by the weight of each point to obtain an image of basic estimation, the weight depends on the number of 0 blocks and the noise intensity, and the noise of the image is greatly removed;
and (3) a final stage:
after the basic stage is finished, the Euclidean distance of the corresponding basic estimation image blocks is used for measuring the similarity; sorting according to the distance from small to large, and then taking 1 top MAXNs at most; respectively overlapping the basic estimation image blocks and the original image blocks containing noise into two three-dimensional arrays;
two-dimensional and one-dimensional transformation is carried out on the two three-dimensional matrixes, and DCT transformation is adopted for the two-dimensional transformation; scaling a three-dimensional matrix formed by the noise image by using wiener filtering, wherein the coefficient is obtained by the value of the three-dimensional matrix estimated based on the basis and the noise intensity; this process is represented by the following formula, where wpAre the coefficients of the wiener filter:
and (3) inversely transforming the image blocks, putting the image blocks back to the original positions, counting the superposition weight by using the quantity of non-zero components, and dividing the superposed images by the weight of each point to obtain a base estimated image, wherein the weight depends on the number of 0 blocks and the noise intensity, and the noise of the image is greatly removed.
As shown in fig. 2, in the monitoring parameter setting method for the vehicle networking data collection system based on secondary development of embedded software according to the embodiment of the present invention, the device control module collects data, the vehicle-mounted terminal is used for the first time, a request for monitoring data is sent, the monitoring terminal returns initial monitoring data, a user enters the programmable module, adds or deletes monitoring items by himself, and customization of monitoring indexes is achieved by storing and uploading.
As shown in fig. 3, the monitoring terminal 9 of the car networking data acquisition system for secondary development of embedded software according to the embodiment of the present invention includes: the system comprises a data management module 10, a data analysis module 11 and a data storage module 12.
The monitoring terminal 9 processes relevant vehicle-mounted big data according to the cloud platform, and the vehicle data acquisition monitoring system can acquire and record various data in the vehicle running process in real time, and can monitor the running state and the vehicle using state of a target vehicle in real time and perform real-time positioning and tracking on the target vehicle. Meanwhile, based on programmable embedded type, the system operation command can be designed by self aiming at different user requirements, and the humanized design of the system based on different users is realized. Based on the cloud platform, the analysis and the management of the vehicle-mounted big data are facilitated. The main functions of the monitoring terminal are information management, information storage and information analysis.
The data management module 10 mainly adds, deletes, and queries information. The data storage module 12 performs storage classification based on the user's tag, corresponding vehicle-mounted data, and timestamp. The data analysis module 11 mainly relies on the vehicle-mounted information to perform relevant dimension reduction analysis, and analyzes information across space on a time axis.
As shown in fig. 4, a specific process of the data storage module for performing storage classification provided in the embodiment of the present invention is as follows:
s101: according to the label of the user, the corresponding vehicle-mounted data and the timestamp data set, determining the classified class or group, and randomly initializing the respective central point;
s102: determining the distance from the data point to be classified to the central point, and classifying the data closest to the central point into one class according to the calculated value of the distance;
s103: and calculating the center point of each type as a new center point, and repeating the steps until the center of each type does not change much after each iteration.
As shown in fig. 5, the specific processes of adding, deleting, and querying information by the data management module provided in the embodiment of the present invention are as follows;
s201: assuming that the initial state of a given data set is that all vertices have not been visited, one vertex is selected as the initial point of traversal in a given data set, and a depth-first search recursive call is made:
s202: accessing the searched non-accessed adjacent points, and marking the vertex as an accessed node;
s203: searching the non-accessed adjacent point of the vertex, and if the adjacent point exists, starting the same access and search from the adjacent point.
The invention is based on software modular design, vehicle monitoring and data index collection, cloud platform technology and the like. The modular design is that simply, the writing of the program does not start to input computer sentences and instructions one by one, but first describes the main structure and flow of the software by using frames such as a main program, a subprogram, a subprocess and the like, and defines and debugs the input and output link relation among the frames. The result of the progressive refinement is a series of algorithmic descriptions in functional block units. The method of designing a program in units of functional blocks to realize the solution algorithm is called modularization. The modularization aims to reduce the complexity of a program and simplify operations such as program design, debugging and maintenance. And only the corresponding module needs to be correspondingly changed when a certain sub-function is changed. The vehicle monitoring and collecting indexes mainly comprise whether various devices such as the vehicle speed, various temperatures, the wheel speed, the engine torque, an accelerator, a brake pedal, the gear lever position, an air conditioner and the like work or not, fault information and the like. Cloud technology (Cloud technology) is based on a general term of network technology, information technology, integration technology, management platform technology, application technology and the like applied in a Cloud computing business model, can form a resource pool, is used as required, and is flexible and convenient. Cloud computing technology will become an important support. Background services of the technical network system require a large amount of computing and storage resources, such as video websites, picture-like websites and more web portals. With the high development and application of the internet industry, each article may have its own identification mark and needs to be transmitted to a background system for logic processing, data in different levels are processed separately, and various industrial data need strong system background support and can only be realized through cloud computing.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.
Claims (10)
1. The vehicle networking data acquisition system based on embedded software secondary development is characterized by comprising the following components: the system comprises a vehicle-mounted terminal, a monitoring terminal and a cloud platform;
the vehicle-mounted terminal includes: the device comprises an equipment control module, a programming module, a visualization module, an MCU control module, a communication module, a remote control module and a positioning module;
the equipment control module is used for acquiring data, controlling hardware operation and setting the acquired data;
the programming module is used for customizing commands and monitoring parameter settings for users;
the visualization module is used for displaying the monitoring parameters in an interface mode and processing the acquired images;
in the process of image processing, the specific process of denoising the image is as follows:
a basic processing stage:
grouping, determining a reference block with a size of k multiplied by k in a noise image, searching in a region with a proper size around the reference block, searching for a plurality of blocks with minimum difference, integrating the blocks into a 3-dimensional matrix, integrating the reference block into the 3-dimensional matrix, and searching for a similar block model:
G(P)＝{Q：d(P，Q)≤τstep}；
d (P, Q) is the Euclidean distance between two blocks, the two blocks are sorted from small to large according to the distance, and 1 MAXNs are selected and stacked into a three-dimensional array;
performing collaborative filtering, namely performing two-dimensional transformation on a two-dimensional block in each three-dimensional matrix and then performing one-dimensional transformation on the third dimension of the matrix; after transformation, the value is smaller than the hyper-parameter lambda in a hard threshold mode3DThe component (A) is 0; meanwhile, counting the number of non-zero components as a reference of subsequent weight, and finally obtaining a processed image block through one-dimensional inverse transformation and two-dimensional inverse transformation in the third dimension;
the image blocks are put back to the original position after inverse transformation, the number of nonzero components is utilized to count the superposition weight, the superposed images are divided by the weight of each point to obtain an image of basic estimation, the weight depends on the number of 0 blocks and the noise intensity, and the noise of the image is greatly removed;
and (3) a final stage:
after the basic stage is finished, the Euclidean distance of the corresponding basic estimation image blocks is used for measuring the similarity; sorting according to the distance from small to large, and then taking 1 top MAXNs at most; respectively overlapping the basic estimation image blocks and the original image blocks containing noise into two three-dimensional arrays;
two-dimensional and one-dimensional transformation is carried out on the two three-dimensional matrixes, and DCT transformation is adopted for the two-dimensional transformation; scaling a three-dimensional matrix formed by the noise image by using wiener filtering, wherein the coefficient is obtained by the value of the three-dimensional matrix estimated based on the basis and the noise intensity; this process is represented by the following formula, where wpAre the coefficients of the wiener filter:
the image blocks are put back to the original position after inverse transformation, the number of nonzero components is utilized to count the superposition weight, the superposed images are divided by the weight of each point to obtain an image of basic estimation, the weight depends on the number of 0 blocks and the noise intensity, and the noise of the image is greatly removed;
the MCU control module is respectively connected with the equipment control module, the programming module, the visualization module, the communication module, the remote control module and the positioning module and coordinates the normal operation of each module;
the communication module is connected with the monitoring terminal and used for carrying out interactive transmission of data information;
the remote control module is used for analyzing and transmitting the communication protocol information to the remote control module based on corresponding software control, the remote control module further decodes the communication protocol information, and related control signals are transmitted to the MCU control module;
and the positioning module is used for positioning the vehicle through the positioner.
2. The vehicle networking data acquisition system based on embedded software secondary development as claimed in claim 1, wherein the monitoring terminal processes relevant vehicle-mounted big data according to the cloud platform, acquires and records various data in the vehicle driving process in real time, and performs real-time monitoring and real-time positioning and tracking on the driving state and the vehicle using state of the target vehicle.
3. The vehicle networking data acquisition system based on embedded software secondary development as claimed in claim 1, wherein the monitor terminal comprises: the system comprises a data management module, a data analysis module and a data storage module;
the data management module is mainly used for adding, deleting and inquiring information;
the data storage module is mainly used for carrying out storage classification based on the label of a user, corresponding vehicle-mounted data and a timestamp;
the data analysis module mainly depends on vehicle-mounted information to perform relevant dimension reduction analysis, and analysis of cross-space information on a time axis is performed.
4. The vehicle networking data acquisition system based on embedded software secondary development as claimed in claim 3, wherein the specific process of the data storage module for storage classification is as follows:
according to the label of the user, the corresponding vehicle-mounted data and the timestamp data set, determining the classified class or group, and randomly initializing the respective central point;
determining the distance from the data point to be classified to the central point, and classifying the data closest to the central point into one class according to the calculated value of the distance;
and meanwhile, calculating the center point of each type as a new center point, and repeating the steps until the change of the center of each type is not large after each iteration.
5. The vehicle networking data acquisition system based on embedded software secondary development as claimed in claim 3, wherein the specific processes of adding, deleting and inquiring information by the data management module are as follows;
assuming that the initial state of a given data set is that all vertices have not been visited, one vertex is selected as the initial point of traversal in a given data set, and a depth-first search recursive call is made:
accessing the searched non-accessed adjacent points, and marking the vertex as an accessed node;
searching the non-accessed adjacent point of the vertex, and if the adjacent point exists, starting the same access and search from the adjacent point.
6. The vehicle networking data acquisition system based on embedded software secondary development as claimed in claim 1, wherein the data acquired by the device control module mainly comprises information on whether various devices such as vehicle speed, various temperatures, wheel speed, engine torque, accelerator, brake pedal, gear lever position, air conditioner are working or not and fault information.
7. The vehicle networking data collection system based on embedded software secondary development as claimed in claim 1, wherein the device control module collects data in a setting mode, the vehicle-mounted terminal is used for the first time, sends a request for monitoring data, the monitoring terminal returns initial monitoring data, a user enters the programmable module, adds and deletes monitoring items by himself, and customization of monitoring indexes is achieved by storing and uploading.
8. The vehicle networking data collection system based on embedded software secondary development of claim 1, wherein the protocol adopted by the communication module is TCP or UDP data protocol.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the embedded software secondary development based vehicle networking data collection system of any of claims 1-8 when executed on an electronic device.
10. A computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to execute the vehicle networking data acquisition system based on embedded software secondary development according to any one of claims 1 to 8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117041301A (en) * | 2023-10-08 | 2023-11-10 | 南京翼辉信息技术有限公司 | Vehicle-mounted edge computing system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117041301A (en) * | 2023-10-08 | 2023-11-10 | 南京翼辉信息技术有限公司 | Vehicle-mounted edge computing system |
| CN117041301B (en) * | 2023-10-08 | 2023-12-22 | 南京翼辉信息技术有限公司 | Vehicle-mounted edge computing system |
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