CN115225524A - Internet of vehicles data visualization method, device, equipment, medium and program product - Google Patents
Internet of vehicles data visualization method, device, equipment, medium and program product Download PDFInfo
- Publication number
- CN115225524A CN115225524A CN202210724716.0A CN202210724716A CN115225524A CN 115225524 A CN115225524 A CN 115225524A CN 202210724716 A CN202210724716 A CN 202210724716A CN 115225524 A CN115225524 A CN 115225524A
- Authority
- CN
- China
- Prior art keywords
- data
- target
- file
- visualization
- target data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 78
- 238000013079 data visualisation Methods 0.000 title claims abstract description 23
- 238000012800 visualization Methods 0.000 claims abstract description 85
- 238000012545 processing Methods 0.000 claims abstract description 79
- 230000006855 networking Effects 0.000 claims abstract description 52
- 238000004590 computer program Methods 0.000 claims abstract description 38
- 230000006870 function Effects 0.000 claims description 62
- 238000007781 pre-processing Methods 0.000 claims description 43
- 238000004458 analytical method Methods 0.000 claims description 39
- 238000012216 screening Methods 0.000 claims description 29
- 230000009467 reduction Effects 0.000 claims description 26
- 238000005070 sampling Methods 0.000 claims description 23
- 238000001914 filtration Methods 0.000 claims description 17
- 238000010606 normalization Methods 0.000 claims description 12
- 238000009877 rendering Methods 0.000 claims description 11
- 230000000007 visual effect Effects 0.000 abstract description 4
- 230000009286 beneficial effect Effects 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 13
- 238000004364 calculation method Methods 0.000 description 12
- 230000008569 process Effects 0.000 description 10
- 238000009499 grossing Methods 0.000 description 9
- 230000008676 import Effects 0.000 description 6
- 238000007405 data analysis Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 238000013500 data storage Methods 0.000 description 3
- 239000000446 fuel Substances 0.000 description 3
- 230000003321 amplification Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000003199 nucleic acid amplification method Methods 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 238000012952 Resampling Methods 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 229910021389 graphene Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/04—Processing captured monitoring data, e.g. for logfile generation
- H04L43/045—Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/02—Registering or indicating driving, working, idle, or waiting time only
- G07C5/06—Registering or indicating driving, working, idle, or waiting time only in graphical form
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/02—Capturing of monitoring data
- H04L43/022—Capturing of monitoring data by sampling
- H04L43/024—Capturing of monitoring data by sampling by adaptive sampling
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The application relates to the technical field of vehicle networking intelligence, in particular to a vehicle networking data visualization method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: the method comprises the steps of firstly obtaining a vehicle networking data file, identifying the file type of the vehicle networking data file, then analyzing the vehicle networking data file according to the reading logic corresponding to the file type to obtain target data, and finally carrying out visualization processing on the target data. This embodiment analyzes the car networking data that obtains through the logic that reads that different file types correspond, can handle the car networking data of multiple difference, reduces manual operation, reaches the beneficial effect that improves the visual efficiency of car networking data.
Description
Technical Field
The application relates to the technical field of vehicle networking intelligence, in particular to a vehicle networking data visualization method and device, computer equipment, a storage medium and a computer program product.
Background
With the development of the intelligent technology of the internet of vehicles, the realization method of the visualization of the operation condition data of the internet of vehicles is more and more emphasized by various commercial vehicle host factories.
At present, each commercial vehicle host factory mainly adopts data acquisition equipment or an internet of vehicles Tbox to acquire operation condition data of a large number of vehicles in the internet of vehicles and stores the acquired data on a cloud platform, a research and development engineer downloads required data of the internet of vehicles from the cloud platform to a workstation, and then preprocesses the downloaded data of the internet of vehicles and compiles related codes so as to achieve the purpose of visualizing the data.
However, the data acquisition equipment and the internet of vehicles Tbox are various in variety, and different data acquisition equipment and the file formats of the data stored in the internet of vehicles Tbox are various, so that the data visualization tool which can only process fixed format files cannot process all internet of vehicles data, normal data preprocessing and data analysis work cannot be performed on a large number of internet of vehicles data, and the efficiency of visualization of the internet of vehicles data is greatly reduced.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device, a storage medium, and a computer program product for visualizing internet of vehicles data, which can improve the efficiency of visualizing the internet of vehicles data.
A method of vehicle networking data visualization, the method comprising:
acquiring a vehicle networking data file, and identifying the file type of the vehicle networking data file;
analyzing the Internet of vehicles data file to obtain target data according to the reading logic corresponding to the file type;
and performing visualization processing on the target data.
In one embodiment, before the visualizing the target data, the method further includes:
and preprocessing the target data, wherein the preprocessing comprises at least one of data frequency reduction processing, data screening, filtering, data reduction and data channel processing.
In one embodiment, before the visualizing the target data, the method further includes:
receiving data information setting data, wherein the data information setting data comprise data sampling frequency and data channel names;
and adjusting the target data according to the sampling frequency and the data channel name.
In one embodiment, before the visualizing the target data, the method further includes:
receiving set analysis parameters for at least one of the preprocessing of the target data, visualization of the target data, and analysis of the target data.
In one embodiment, the visualizing the target data includes:
acquiring a data channel and a data type;
calling a rendering function according to the data channel and the data type to determine a visualization mode;
and carrying out graphic drawing on the target data according to the visualization mode, and displaying a drawn graphic.
In one embodiment, after the calling a rendering function according to the data channel and the data type to determine the visualization manner, the method further includes:
when the number of the data channels is smaller than or equal to a preset value, continuously and respectively carrying out graphic drawing on the target data of each data channel according to the visualization mode to obtain an image corresponding to each data channel, and displaying a graphic corresponding to each data channel;
and when the number of the data channels is larger than the preset value, after normalization processing is carried out on the target data, drawing the graph of the target data after the normalization processing according to the visualization mode, and displaying the drawn graph.
In one embodiment, after the visualization processing is performed on the target data, a data display function implemented by at least one of the following methods is further included: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
In one embodiment, the method further comprises:
receiving a data export instruction, wherein the data export instruction carries a file format;
processing the data to be exported according to the file format to obtain target export data;
and outputting the target export data.
A vehicle networking data visualization device, the device comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a vehicle networking data file and identifying the file type of the vehicle networking data file;
the analysis module is used for analyzing the Internet of vehicles data file to obtain target data according to the reading logic corresponding to the file type;
and the visualization module is used for performing visualization processing on the target data.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when executing the computer program.
According to the method, the device, the computer equipment, the storage medium and the computer program product for visualizing the data of the Internet of vehicles, the data file of the Internet of vehicles is firstly obtained, the file type of the data file of the Internet of vehicles is identified, then the data file of the Internet of vehicles is analyzed according to the reading logic corresponding to the file type to obtain the target data, and finally the target data is visualized. This embodiment is analyzed the car networking data that obtains through the logic that reads that different file types correspond, can handle the car networking data of multiple difference, reduces manual operation, reaches the beneficial effect who improves the visual efficiency of car networking data.
Drawings
FIG. 1 is an application landscape of a method for visualizing Internet of vehicles data in one embodiment;
FIG. 2 is a schematic flow diagram of a method for visualizing Internet of vehicles data in one embodiment;
FIG. 3 is a system interface diagram of data import, in one embodiment;
FIG. 4 is a system interface diagram of data downconversion and data screening in one embodiment;
FIG. 5 is a system interface diagram of data information setup, in one embodiment;
FIG. 6 is a system interface schematic of engine parameter settings in one embodiment;
FIG. 7 is a system interface diagram of a graphical rendering in one embodiment;
FIG. 8 is a block diagram of an embodiment of a vehicle networking data visualization device;
FIG. 9 is an internal block diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
The vehicle networking data visualization method provided by the embodiment of the application can be applied to the application environment shown in fig. 1. The terminal 101 is in communication with the server 102 through a network, the data acquisition device 103 and the internet of vehicles Tbox104 acquire internet of vehicles data stored in the data storage system, the internet of vehicles data can be processed by the server 102, and the terminal 101 can acquire the internet of vehicles data stored in the data storage system through the network and the server 102. The data storage system may be integrated on the server 102 or may be placed on the cloud or other network server. The terminal 101 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices. The server 102 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.
Referring to fig. 2, fig. 2 is a schematic flowchart of a method for visualizing data in a vehicle networking system according to an embodiment of the present application, and the method is applied to the terminal in fig. 1 for example. The method comprises the following steps:
s201, obtaining the Internet of vehicles data file, and identifying the file type of the Internet of vehicles data file.
Specifically, the vehicle networking data includes data generated by each target device during the driving or stopping process of the vehicle, which may include a throttle, an engine, an instrument, and the like, and geographic position information data of the vehicle, which may include longitude and latitude data and altitude data, without being limited in particular. In practical applications, the vehicle networking data may include at least one of vehicle latitude, vehicle longitude, vehicle altitude data, GPS vehicle speed, throttle opening percentage, engine output torque percentage, engine speed, meter vehicle speed, brake switch signal, and instantaneous fuel consumption, but it should be noted that this embodiment is merely an example, and those skilled in the art may use any data related to the vehicle as the vehicle networking data.
In practical application, the terminal can display a system main interface, the system main interface comprises a data import option, the terminal obtains the data files of the internet of vehicles by receiving operation of a user on the data import option, specifically, the terminal receives a click command for clicking the data import option on the system main interface, and then receives a selection command for selecting the data files to be processed and file types of the data files, so that the terminal can uniquely determine the data files and import the data files into the system, and the system automatically identifies the file types by using a file identification algorithm, for example, identifying the file types by identifying suffixes of the files. The schematic diagram of the system interface for importing data is shown in fig. 3, where the file types in fig. 3 include a csv file, an xls file, an xlsx file, and a txt file, and in other embodiments, the file types may be other, and are not specifically limited.
A monitoring function is arranged at the historical data position of a main interface of the system, when a terminal receives a click command for clicking a certain historical data record, the monitoring function monitors the click command, and starts a data importing function to rapidly display the selected historical data in the system interface, so that the purpose of rapidly importing the historical data is achieved. The system in this embodiment is a set of system developed based on matlab programming software and capable of realizing vehicle networking data visualization, and the system is installed in a terminal, or is a system in which the terminal accesses a server through a front end, such as a browser.
S202, analyzing the Internet of vehicles data file to obtain target data according to the reading logic corresponding to the file type.
Specifically, the reading logic is used for analyzing the data file of the internet of vehicles, for example, format conversion is performed on each row of data in the data file of the internet of vehicles to obtain target data in a target format, wherein different reading logics can correspond to different types of data files of the internet of vehicles, so that after the type of the data file of the internet of vehicles is obtained, the terminal can select the corresponding reading logic according to the type, and then the data file of the internet of vehicles is analyzed through the reading logic. In some optional embodiments, the read logic may include a file read function and a file read model. In some optional embodiments, the terminal is preset with a corresponding relationship between the reading logic and the type of the data file of the internet of vehicles, so that after the terminal acquires the type of the data file of the internet of vehicles, the terminal queries the corresponding relationship, and thus the reading logic can be acquired. In some optional embodiments, if there is no reading logic corresponding to the type of the car networking data file, an error may be reported to facilitate timely update of the system.
The target data is obtained by analyzing the acquired internet of vehicles data, and is stored in a specific address in a mat file format.
After the target data is obtained, the system displays the row number, the column number and the data channel of the file on the left side of the main interface, and displays the import condition of the history file, the state of the imported vehicle networking data and the like on the lower left side of the main interface.
The data channels are data fields, and each data channel includes data of an attribute, for example, a data channel of vehicle latitude includes vehicle latitude data of all target data, and a data channel of vehicle longitude includes vehicle longitude data of all target data.
And S203, performing visualization processing on the target data.
Specifically, the visualization process includes displaying the target data or the analysis result of the target data in the form of a graph such as a curve, a data table, or a histogram. Wherein the curve may comprise a curve of the target data, a curve of the preprocessed data.
For example, the terminal plots all data in the data channel of the vehicle latitude on the system interface in the form of a curve, and changes the color of the curve as required.
According to the method for visualizing the data of the Internet of vehicles, the data file of the Internet of vehicles is obtained, the file type of the data file of the Internet of vehicles is identified, then the data file of the Internet of vehicles is analyzed according to the reading logic corresponding to the file type to obtain target data, and finally the target data is visualized. This embodiment is analyzed the car networking data that obtains through the logic that reads that different file types correspond, can handle the car networking data of multiple difference, reduces manual operation, reaches the beneficial effect who improves the visual efficiency of car networking data.
In some embodiments, before the visualizing the target data, the method further includes: and preprocessing the target data, wherein the preprocessing comprises at least one of data frequency reduction processing, data screening, filtering, data reduction and data channel processing.
In this embodiment, the terminal enters the data preprocessing function interface by receiving an operation instruction for a user to click a data processing option on the system main interface, and then the terminal receives a selection instruction for the user to select a corresponding data preprocessing function on the data preprocessing function interface, so that the terminal can perform data preprocessing on target data to obtain preprocessed data, and a system interface schematic diagram of data frequency reduction processing and data screening is shown in fig. 4, in some optional embodiments, the channel name in fig. 4 is latitude, GPS vehicle speed, engine speed, accelerator opening percentage, accumulated mileage and accumulated oil consumption, for example, when the channel name in fig. 4 is latitude, the corresponding screening condition may be ">10", when the channel name is accelerator opening percentage, the corresponding screening condition may be "<90", and in other embodiments, the channel name may be other vehicle networking data names, and is not specifically limited.
The data frequency reduction processing can perform sparse and frequency reduction processing on the target data, so that the effect of resampling the target data is achieved. Firstly, reading the length of target data and the sampling frequency of the target data by a terminal, then dividing the sampling frequency of the target data by the sampling frequency of preset preprocessing data by the terminal to obtain an integer N, sampling the target data at equal N intervals, and finally storing the sampled data as the preprocessing data by the terminal, wherein for example, the sampling frequency of the target data is 10, and the sampling frequency of the preset preprocessing data is 2, so that the terminal samples the target data once every 5 data.
The data screening method comprises the steps that a terminal receives operation instructions of data channels to be subjected to data screening and screening conditions clicked on a system interface by a user, in some embodiments, the screening conditions comprise boundary conditions, calculation formulas and threshold values related to the data screening, in other embodiments, the screening conditions can be other conditions without specific limitation, then the data channels to be subjected to the data screening and the screening conditions are input to a data screening function by the terminal, after the data channels and the screening conditions are identified by the data screening function, the terminal can designate an executable data screening program to perform data screening on the data channels based on the screening conditions, and finally the terminal stores screened data as preprocessing data, wherein the data screening function and the data screening program are both arranged in the terminal, the data screening function is used for identifying the data channels and the screening conditions, and the data screening program is used for screening the data channels.
The filtering comprises a signal filtering method, curve smoothing processing and altitude signal processing, wherein the signal filtering method can carry out low-pass, high-pass and moving average filtering and special filter filtering on target data or preprocessing data, the curve smoothing processing can carry out curve smoothing on the target data or preprocessing data in a time domain dimension, and the altitude signal processing can call a special algorithm to carry out altitude denoising and altitude smoothing processing on the target data or preprocessing data. Firstly, a terminal calls a signal filtering method, a curve smoothing processing method or an altitude special preprocessing method in a matlab signal filtering tool box, then the terminal inputs a data channel to be filtered to a corresponding signal filtering function, a curve smoothing processing function or an altitude signal preprocessing function according to the called processing method, the function automatically identifies the filtering type according to the input parameter and filters target data or preprocessing data of the data channel to be filtered, and the filtered data is stored in the preprocessing data in a data channel mode.
Data channel processing includes adding data channels and deleting data channels.
Adding a data channel may add a new data channel through mathematical calculations between data channels. The terminal obtains a new data channel generated by writing matlab codes on an added data channel interface of a user in the system, the new data channel is automatically identified by an added data channel function built in the terminal, then the terminal orders an executable added data channel program to add the new data channel into the system, and preprocessed data corresponding to the newly added data channel is stored in the preprocessed data in a mode of adding a new column.
Deleting the data channel can delete the newly added data channel and the original data channel. The terminal obtains a selection instruction of a data channel to be deleted clicked by a user, then a data channel deleting function built in a terminal command judges whether preprocessed data exists in the system or not, if the preprocessed data exists in the system, the terminal can command a data channel deleting program to delete the data channel of the preprocessed data and restore the preprocessed data, if the preprocessed data does not exist in the system, the terminal can copy a piece of target data, then the terminal commands the data channel deleting program to delete the data channel in the copied target data, and the copied target data is saved as the preprocessed data.
Data restoration may recover target data imported into the system. No matter how the target data is preprocessed, the target data is stored in the system, the terminal calls a data reduction function in the system to identify all preprocessed data, then the data reduction program is instructed to delete all preprocessed data identified by the data reduction function, only the target data is reserved, and the name of a data channel is reduced to the channel name of the target data.
According to the method provided by the embodiment, the target data can be sparse and frequency-reduced by data frequency reduction processing according to actual requirements, the target data is screened by data screening, noise data and abnormal data are filtered by filtering, and addition, deletion and data restoration of a data channel can be realized; and the data preprocessing can be realized only by simple operation on the system, the data processing complexity is reduced, and the data processing speed is increased.
In some embodiments, before the visualizing the target data, the method further includes: receiving data information setting data, wherein the data information setting data comprise data sampling frequency and data channel names; and adjusting the target data according to the sampling frequency and the data channel name.
In this step, the terminal may obtain an operation that the user sequentially clicks "set" and "data information set" on the top of the system interface, then the terminal enters the data information setting interface, and the terminal may also sequentially obtain an operation that the user right clicks a name of a data channel located on the left side of the system interface, an operation that the user clicks "data information set" and then enters the data information setting interface, and the user may set a data sampling frequency and a data channel name on the data information setting interface, where the system interface schematic diagram of the data information setting is shown in fig. 5, for example, the sampling frequency may be 10 in fig. 5, and the channel name may be longitude, latitude, altitude, GPS vehicle speed, accelerator opening percentage, engine output torque percentage, engine speed, instrument vehicle speed, brake switch signal, and instantaneous fuel consumption, and in other embodiments, the channel name may be other vehicle networking data names, and is not particularly limited.
The terminal calls a data playback function to read corresponding template data and displays the read data in an interface when acquiring the operation of the created data information template clicked by the user.
The method provided by the step can set the relevant data information of the target data according to the actual requirement, and can correspondingly adjust the target data.
In some embodiments, before performing the visualization processing on the target data, the method further includes:
receiving set analysis parameters, wherein the analysis parameters are used for at least one of preprocessing of the target data, visualization processing of the target data and analysis of the target data.
In this embodiment, the terminal implements an analysis parameter setting window through a matlab GUI function module, and a corresponding callback function is provided for each analysis parameter item terminal, where the callback function can implement functions of adding an analysis parameter, modifying an analysis parameter, deleting an analysis parameter, and saving an analysis parameter template, and each analysis parameter item specifies a fixed position for storage.
The terminal receives the operation that a user sequentially clicks and selects 'setting' and 'analysis parameter setting' on a navigation bar at the top of the system to enter an analysis parameter setting interface, wherein the analysis parameter setting comprises finished automobile parameter setting and data calculation parameter setting, the finished automobile parameter setting comprises engine parameter setting, gearbox parameter setting, drive axle parameter setting, tire model parameter setting and the like, the data calculation parameter setting comprises gear calculation parameter setting, gradient calculation parameter setting, oil consumption calculation parameter setting and the like, and as shown in fig. 6, fig. 6 is a system interface schematic diagram of the engine parameter setting. The engine parameters comprise reference torque, idle speed, engine model, idle maximum rotating speed and the like, the gearbox parameters comprise gearbox model, gearbox maximum input torque, transmission speed ratio of each gear of the gearbox, transmission efficiency of each gear under different rotating speeds and the like, the drive axle parameters comprise drive axle model, drive axle maximum input torque, main reduction ratio and the like, the tire model settings comprise tire model, tire rolling radius and the like, the gear calculation parameters comprise signals of vehicle speed, rotating speed, torque, an accelerator, a clutch and the like, the gradient calculation parameters comprise fields and parameters of vehicle speed, rotating speed, altitude, spacing distance and the like, the oil consumption calculation parameters comprise parameters of rotating speed, vehicle speed, instantaneous fuel consumption and the like, in other embodiments, the whole vehicle parameter settings and the data calculation parameter settings can also be settings of other analysis parameters of the vehicle, and no specific limitation is made herein.
The analysis parameters may also be used for preprocessing of the preprocessed data, visualization of the preprocessed data, and analysis of the preprocessed data.
According to the method provided by the embodiment, analysis parameters which can be used for data preprocessing, data visualization processing and data analysis are set, and parameter setting preparation is made for subsequent data preprocessing, data visualization processing, data analysis and other processes.
In some embodiments, visualizing the target data comprises: acquiring a data channel and a data type; calling a drawing function according to the data channel and the data type to determine a visualization mode; and carrying out graphic drawing on the target data according to a visualization mode, and displaying the drawn graphic.
The terminal receives the operations that a user selects a data channel needing to draw a graph on the left side of a system main interface in sequence and clicks a right key to draw the graph, then the terminal commands a drawing function to identify the name, the number and the type of the selected data channel, and after the drawing function is identified, the terminal commands a drawing program to draw the graph on the system interface according to the name, the number and the type of the data channel identified by the drawing function.
The visualization mode comprises curve drawing and track drawing, wherein the curve drawing function is realized by utilizing a drawing toolbox of matlab based on functional areas such as common operation modes and components, drawing windows, mode conversion and the like of a visualization interface of a GUI integrated by a terminal, and the track drawing function is drawn and displayed by calling an API (application programming interface) of a map.
If the visualization mode is curve drawing, after drawing a curve graph on a system interface, the terminal can display all selected data channels by using curves with different colors at the upper right corner of the interface, and if the terminal receives an operation instruction of clicking a check box in front of one data channel by a user at the moment, the terminal can hide or display the data channel graph; if the visualization mode is track drawing, firstly, the terminal receives a track drawing mode of a data channel clicked by a user, wherein the track drawing mode of the data channel comprises a street map, a thermal map or a satellite map, meanwhile, the terminal can identify the data channel containing longitude and latitude to obtain the longitude and latitude of a vehicle, then the terminal displays the drawn map track at the lower right corner of a system interface according to the selected map and the obtained longitude and latitude information of the vehicle, after the map track is drawn, the terminal can also receive operation instructions of functions of amplifying, reducing, searching and the like of the map by the user, a schematic diagram of the system interface drawn by the graph is shown in fig. 7, and the data type can be selected from target data and preprocessed data.
The method provided by the embodiment can select a proper visualization mode to visualize the data according to actual requirements, and has high flexibility; and the data are converted into curves or tracks, so that the analysis of the car networking data is facilitated.
In some embodiments, after the determining the visualization manner by calling the rendering function according to the data channel and the data type, the method further includes: when the number of the data channels is smaller than or equal to a preset value, respectively carrying out graph drawing on the target data of each data channel according to a visualization mode to obtain an image corresponding to each data channel, and displaying a graph corresponding to each data channel; and when the number of the data channels is larger than a preset value, after normalization processing is carried out on the target data, graph drawing is carried out on the normalized target data according to a visualization mode, and the drawn graph is displayed.
For example, if the preset value is 5 and the number of the selected data channels is 4, the data of the 4 data channels are respectively displayed on the system interface by 4 curve graphs; if the preset value is 5 and the number of the selected data channels is 6, the terminal calls a normalization processing program to perform normalization processing on the data of the 6 data channels respectively, and then displays the data of the 6 data channels after normalization processing on a system interface by 6 curve graphs respectively. Wherein the presented data may be target data or pre-processed data.
According to the method provided by the embodiment, when the number of the data channels is larger than the preset value, the data is normalized and then the graph is drawn, so that the situation that the data channels are too dense on the interface is avoided, and the situation that too large or too small data on the data channels with larger data ranges are displayed on the interface unclearly due to different data ranges of each channel is avoided.
In some embodiments, after S103, a data display function implemented in at least one of the following manners is further included: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
The terminal receives an operation instruction of a user for selecting the start and end coordinates of a certain range of a drawn curve graph by using a left mouse button frame, generates a graph only containing the frame selection range on a system interface by the terminal to realize graph amplification, then receives an operation instruction of a global display function on the system interface by right clicking of the user by the terminal, and redisplays the graph before frame selection on the system interface, thereby realizing graph reduction.
The terminal receives an operation instruction of selecting a single-cursor value taking function on a system interface by a user, then generates a vertical line provided with a monitoring function and a callback function in the middle of a drawn curve graph, and displays data of all data channels on the vertical line in a form of a table at the upper right corner of a main interface of the system if the terminal receives the operation instruction of dragging the vertical line by the user, so that the single-cursor value taking display function is realized.
The terminal receives an operation instruction of selecting a double-cursor value taking function on a system interface by a user, then two vertical lines provided with a monitoring function and a callback function are generated in the middle of a drawn curve graph, if the terminal receives the operation instruction of dragging the two vertical lines by the user, the terminal displays an oblique line in the middle of the two vertical lines to determine a selected range, and displays data of all data channels on the two vertical lines in the right middle of a main interface in a form of a table, so that the double-cursor value taking display function is realized.
The method provided by the embodiment can perform operations such as graphic amplification or graphic reduction, single-cursor value display, double-cursor value display and the like on the drawn curve graphics according to needs, and is more favorable for an engineer to analyze data according to actual requirements.
In some embodiments, the terminal can write a specification based on a data analysis function developed by the system, and define the format and data type of the input parameter and the output parameter, thereby realizing customized development and visual display quickly.
In some embodiments, the method further comprises receiving a data export instruction, the data export instruction carrying a file format; processing the data to be exported according to the file format to obtain target export data; and outputting the target derived data.
The data export instruction is realized by the terminal receiving an operation instruction of clicking an export function on a system interface by a user, and the exported data can be target data or preprocessed data. And finally, the terminal commands a data export program to output target export data in the selected format.
The method provided by the embodiment can select the appropriate file type to export the target data or the preprocessed data according to the actual requirement, and is more convenient and flexible.
In some embodiments, a terminal receives an imported vehicle networking data file, analyzes the imported vehicle networking data file by using corresponding reading logic to obtain target data, modifies corresponding attributes of the target data by setting a sampling frequency of the data and a name of a data field, receives vehicle parameters and data calculation parameters set by a user according to actual requirements, calls corresponding functions and programs to perform data preprocessing on the target data after the corresponding parameters are set, obtains preprocessed data, and finally performs curve drawing or track drawing on the target data or a data channel of the preprocessed data according to the set parameters.
It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides a vehicle networking data visualization device for realizing the vehicle networking data visualization method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so that specific limitations in one or more embodiments of the car networking data visualization device provided below can be referred to the limitations on the car networking data visualization method in the above, and details are not repeated herein.
In one embodiment, as shown in fig. 8, there is provided a vehicle networking data visualization device 800 comprising: an obtaining module 801, an analyzing module 802, and a visualization module 803, wherein:
an obtaining module 801, configured to obtain the data file of the internet of vehicles, and identify a file type of the data file of the internet of vehicles.
And the analysis module 802 is configured to analyze the data file of the internet of vehicles to obtain target data according to the reading logic corresponding to the file type.
And the visualization module 803 is used for performing visualization processing on the target data.
In one embodiment, the internet of vehicles data visualization apparatus 800 may further include:
the preprocessing module is used for preprocessing the target data, and the preprocessing comprises at least one of data frequency reduction processing, data screening, filtering, data restoration and data channel processing.
In one embodiment, the internet of vehicles data visualization apparatus 800 may further include:
the first receiving module is used for receiving data information setting data before visualization processing is carried out on target data, and the data information setting data comprises data sampling frequency and data channel names.
And the adjusting module is used for adjusting the target data according to the sampling frequency and the data channel name.
In one embodiment, the internet of vehicles data visualization apparatus 800 may further include:
the second receiving module is used for receiving the set analysis parameters before the target data is subjected to visualization processing; the analysis parameters are used for at least one of preprocessing of the target data, visualization of the target data, and analysis of the target data.
In one embodiment, the visualization module 803 is also used to obtain data channels and data types; calling a rendering function according to the data channel and the data type to determine a visualization mode; and carrying out graphic drawing on the target data according to a visualization mode, and displaying the drawn graphic.
In an embodiment, the visualization module 803 is further configured to, after the rendering function is called according to the data channels and the data types to determine the visualization manner, when the number of the data channels is less than or equal to a preset value, continue to perform graph rendering on the target data of each data channel according to the visualization manner to obtain an image corresponding to each data channel, and display a graph corresponding to each data channel; and when the number of the data channels is larger than a preset value, after normalization processing is carried out on the target data, graph drawing is carried out on the normalized target data according to a visualization mode, and the drawn graph is displayed.
In one embodiment, after the target data is visualized, the apparatus 800 is specifically configured to implement a data display function implemented by at least one of the following manners: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
In one embodiment, the internet of vehicles data visualization apparatus 800 may further include:
and the third receiving module is used for receiving a data export instruction, and the data export instruction carries a file format.
And the processing module is used for processing the data to be exported according to the file format to obtain target export data.
And the output module is used for outputting the target derived data.
All or part of each module in the internet-of-vehicles data visualization device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing the car networking data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method for visualizing vehicle networking data.
Those skilled in the art will appreciate that the architecture shown in fig. 9 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory having a computer program stored therein and a processor that when executing the computer program performs the steps of: acquiring a vehicle networking data file, and identifying the file type of the vehicle networking data file; analyzing the Internet of vehicles data file to obtain target data according to the reading logic corresponding to the file type; and carrying out visualization processing on the target data.
In one embodiment, before the visualization process of the target data is implemented when the processor executes the computer program, the method further includes: and preprocessing the target data, wherein the preprocessing comprises at least one of data frequency reduction processing, data screening, signal filtering, curve smoothing processing, altitude signal processing, data restoration and data channel processing.
In one embodiment, before the visualization process of the target data is implemented when the processor executes the computer program, the method further includes: receiving data information setting data, wherein the data information setting data comprise data sampling frequency and data channel names; and adjusting the target data according to the sampling frequency and the data channel name.
In one embodiment, before the visualization process of the target data is implemented when the processor executes the computer program, the method further includes: receiving set analysis parameters; the analysis parameters are used for at least one of preprocessing of the target data, visualization of the target data, and analysis of the target data.
In one embodiment, the visualization of the target data implemented by the processor when executing the computer program comprises: acquiring a data channel and a data type; calling a drawing function according to the data channel and the data type to determine a visualization mode; and carrying out graphic drawing on the target data according to a visualization mode, and displaying the drawn graphic.
In one embodiment, after the determining the visualization manner by calling the rendering function according to the data channel and the data type when the processor executes the computer program, the method further includes: when the number of the data channels is smaller than or equal to a preset value, respectively carrying out graph drawing on the target data of each data channel according to a visualization mode to obtain an image corresponding to each data channel, and displaying a graph corresponding to each data channel; and when the number of the data channels is larger than a preset value, after normalization processing is carried out on the target data, graph drawing is carried out on the normalized target data according to a visualization mode, and the drawn graph is displayed.
In one embodiment, the visualization of the target data implemented by the processor when executing the computer program further includes a data display function implemented by at least one of: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
In one embodiment, the processor, when executing the computer program, further comprises: receiving a data export instruction, wherein the data export instruction carries a file format; processing the data to be exported according to the file format to obtain target export data; and outputting the target export data.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: acquiring a vehicle networking data file, and identifying the file type of the vehicle networking data file; analyzing the data file of the Internet of vehicles according to the reading logic corresponding to the file type to obtain target data; and carrying out visualization processing on the target data.
In one embodiment, before the visualization processing of the target data is performed when the computer program is executed by the processor, the method further includes: and preprocessing the target data, wherein the preprocessing comprises at least one of data frequency reduction processing, data screening, signal filtering, curve smoothing processing, altitude signal processing, data restoration and data channel processing.
In one embodiment, before the visualization processing of the target data is performed when the computer program is executed by the processor, the method further includes: receiving data information setting data, wherein the data information setting data comprise data sampling frequency and data channel names; and adjusting the target data according to the sampling frequency and the data channel name.
In one embodiment, before the visualization processing of the target data is performed when the computer program is executed by the processor, the method further includes: receiving set analysis parameters; the analysis parameters are used for at least one of preprocessing of the target data, visualization of the target data and analysis of the target data.
In one embodiment, visualizing the target data, as performed by the computer program when executed by the processor, comprises: acquiring a data channel and a data type; calling a drawing function according to the data channel and the data type to determine a visualization mode; and carrying out graphic drawing on the target data according to a visualization mode, and displaying the drawn graphic.
In one embodiment, the implementation of the computer program when executed by a processor, after determining the visualization mode by calling a rendering function according to the data channel and the data type, further comprises: when the number of the data channels is less than or equal to a preset value, continuously and respectively carrying out graphic drawing on the target data of each data channel according to a visualization mode to obtain an image corresponding to each data channel, and displaying the graphic corresponding to each data channel; and when the number of the data channels is larger than a preset value, after normalization processing is carried out on the target data, graph drawing is carried out on the normalized target data according to a visualization mode, and the drawn graph is displayed.
In one embodiment, the computer program, when executed by the processor, further comprises a data display function implemented by at least one of: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
In one embodiment, the computer program, when executed by the processor, further comprises: receiving a data export instruction, wherein the data export instruction carries a file format; processing the data to be exported according to the file format to obtain target export data; and outputting the target export data.
In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of: acquiring a vehicle networking data file, and identifying the file type of the vehicle networking data file; analyzing the data file of the Internet of vehicles according to the reading logic corresponding to the file type to obtain target data; and carrying out visualization processing on the target data.
In one embodiment, before the visualization processing of the target data is performed when the computer program is executed by the processor, the method further includes: and preprocessing the target data, wherein the preprocessing comprises at least one of data frequency reduction processing, data screening, signal filtering, curve smoothing processing, altitude signal processing, data restoration and data channel processing.
In one embodiment, before the visualization of the target data is performed when the computer program is executed by the processor, the method further includes: receiving data information setting data, wherein the data information setting data comprise data sampling frequency and data channel names; and adjusting the target data according to the sampling frequency and the data channel name.
In one embodiment, before the visualization processing of the target data is performed when the computer program is executed by the processor, the method further includes: receiving set analysis parameters; the analysis parameters are used for at least one of preprocessing of the target data, visualization of the target data, and analysis of the target data.
In one embodiment, the visualization of the target data performed by the computer program when executed by the processor comprises: acquiring a data channel and a data type; calling a rendering function according to the data channel and the data type to determine a visualization mode; and carrying out graphic drawing on the target data according to a visualization mode, and displaying the drawn graphic.
In one embodiment, the computer program, when executed by the processor, further comprises, after determining the visualization mode by invoking a draw function according to the data channel and the data type: when the number of the data channels is smaller than or equal to a preset value, respectively carrying out graph drawing on the target data of each data channel according to a visualization mode to obtain an image corresponding to each data channel, and displaying a graph corresponding to each data channel; and when the number of the data channels is larger than a preset value, after normalization processing is carried out on the target data, graph drawing is carried out on the normalized target data according to a visualization mode, and the drawn graph is displayed.
In one embodiment, the visualization of the target data implemented when the computer program is executed by the processor further includes a data display function implemented by at least one of: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
In one embodiment, the computer program, when executed by the processor, further comprises: receiving a data export instruction, wherein the data export instruction carries a file format; processing the data to be exported according to the file format to obtain target export data; and outputting the target derived data.
It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
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 may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in the embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. A method for visualizing Internet of vehicles data, the method comprising:
acquiring a vehicle networking data file, and identifying the file type of the vehicle networking data file;
analyzing the Internet of vehicles data file to obtain target data according to the reading logic corresponding to the file type;
and performing visualization processing on the target data.
2. The method of claim 1, wherein prior to the visualizing the target data, further comprising:
and preprocessing the target data, wherein the preprocessing comprises at least one of data frequency reduction processing, data screening, filtering, data restoration and data channel processing.
3. The method of claim 1, wherein prior to the visualizing the target data, further comprising:
receiving data information setting data, wherein the data information setting data comprise data sampling frequency and data channel names;
and adjusting the target data according to the sampling frequency and the data channel name.
4. The method of claim 1, wherein prior to the visualizing the target data, further comprising:
receiving set analysis parameters for at least one of the preprocessing of the target data, visualization of the target data, and analysis of the target data.
5. The method of claim 1, wherein the visualizing the target data comprises:
acquiring a data channel and a data type;
calling a rendering function according to the data channel and the data type to determine a visualization mode;
and carrying out graphic drawing on the target data according to the visualization mode, and displaying the drawn graphic.
6. The method of claim 5, wherein after the determining the visualization mode by invoking the draw function according to the data channel and the data type, further comprising:
when the number of the data channels is smaller than or equal to a preset value, respectively carrying out graphic drawing on the target data of each data channel according to the visualization mode to obtain an image corresponding to each data channel, and displaying a graphic corresponding to each data channel;
and when the number of the data channels is larger than the preset value, after normalization processing is carried out on the target data, graph drawing is carried out on the target data after normalization processing according to the visualization mode, and a graph obtained through drawing is displayed.
7. The method according to any one of claims 1 to 6, wherein after the visualization processing of the target data, a data display function is further included, which is implemented by at least one of: graphic magnification or graphic reduction, single-cursor value display, and dual-cursor value display.
8. The method according to any one of claims 1-7, further comprising:
receiving a data export instruction, wherein the data export instruction carries a file format;
processing the data to be exported according to the file format to obtain target export data;
and outputting the target export data.
9. A vehicle networking data visualization device, the device comprising:
the acquisition module is used for acquiring the Internet of vehicles data file and identifying the file type of the Internet of vehicles data file;
the analysis module is used for analyzing the Internet of vehicles data file to obtain target data according to the reading logic corresponding to the file type;
and the visualization module is used for performing visualization processing on the target data.
10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210724716.0A CN115225524A (en) | 2022-06-24 | 2022-06-24 | Internet of vehicles data visualization method, device, equipment, medium and program product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210724716.0A CN115225524A (en) | 2022-06-24 | 2022-06-24 | Internet of vehicles data visualization method, device, equipment, medium and program product |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115225524A true CN115225524A (en) | 2022-10-21 |
Family
ID=83609558
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210724716.0A Pending CN115225524A (en) | 2022-06-24 | 2022-06-24 | Internet of vehicles data visualization method, device, equipment, medium and program product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115225524A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111680060A (en) * | 2020-06-03 | 2020-09-18 | 长春博立电子科技有限公司 | Intelligent networked automobile big data real-time visual analysis method and system |
| WO2021008184A1 (en) * | 2019-07-18 | 2021-01-21 | 南京依维柯汽车有限公司 | Remote upgrading system and upgrading method for fota firmware on new energy automobile |
| CN113849464A (en) * | 2021-09-29 | 2021-12-28 | 联想(北京)有限公司 | Information processing method and apparatus |
| CN113905067A (en) * | 2021-09-28 | 2022-01-07 | 湖南大学 | Intelligent network vehicle state monitoring and analyzing system and method |
| CN113946395A (en) * | 2021-10-15 | 2022-01-18 | 阿波罗智联(北京)科技有限公司 | Vehicle-mounted machine data rendering method and device, electronic equipment and storage medium |
| CN114064789A (en) * | 2021-11-12 | 2022-02-18 | 上汽通用五菱汽车股份有限公司 | Visualization method and device for vehicle-mounted terminal data and storage medium |
-
2022
- 2022-06-24 CN CN202210724716.0A patent/CN115225524A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021008184A1 (en) * | 2019-07-18 | 2021-01-21 | 南京依维柯汽车有限公司 | Remote upgrading system and upgrading method for fota firmware on new energy automobile |
| CN111680060A (en) * | 2020-06-03 | 2020-09-18 | 长春博立电子科技有限公司 | Intelligent networked automobile big data real-time visual analysis method and system |
| CN113905067A (en) * | 2021-09-28 | 2022-01-07 | 湖南大学 | Intelligent network vehicle state monitoring and analyzing system and method |
| CN113849464A (en) * | 2021-09-29 | 2021-12-28 | 联想(北京)有限公司 | Information processing method and apparatus |
| CN113946395A (en) * | 2021-10-15 | 2022-01-18 | 阿波罗智联(北京)科技有限公司 | Vehicle-mounted machine data rendering method and device, electronic equipment and storage medium |
| CN114064789A (en) * | 2021-11-12 | 2022-02-18 | 上汽通用五菱汽车股份有限公司 | Visualization method and device for vehicle-mounted terminal data and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101644418B1 (en) | Visualizing relationships between data elements and graphical representations of data element attributes | |
| JP4879566B2 (en) | System and method for interactively linking data with shapes in a diagram | |
| CN112749194A (en) | Visualized data processing method and device, electronic equipment and readable storage medium | |
| Horsburgh et al. | Open source software for visualization and quality control of continuous hydrologic and water quality sensor data | |
| US9852153B2 (en) | Graphically representing programming attributes | |
| US7865835B2 (en) | System and method for hydrological analysis | |
| CN107301214B (en) | Data migration method and device in HIVE and terminal equipment | |
| EP2290578A1 (en) | Method and system to configure security rights based on contextual information | |
| US9558525B2 (en) | Process communication method and system | |
| US10400583B1 (en) | Methods and systems for spatial change indicator analysis | |
| DE112018004407T5 (en) | WEB SERVICE PLATFORM WITH SMART ENTITIES, TIME SERIES AND NESTLED STREAM GENERATION | |
| CN113420009B (en) | Electromagnetic data analysis device, system and method based on big data | |
| CN104991918A (en) | WEBGIS based online big data display method | |
| CN114610923A (en) | Big data processing method, device, equipment and medium | |
| CN115225524A (en) | Internet of vehicles data visualization method, device, equipment, medium and program product | |
| Thorve et al. | EpiViewer: an epidemiological application for exploring time series data | |
| CN114782926B (en) | Driving scene recognition method, device, equipment, storage medium and program product | |
| CN116821659A (en) | Vehicle fuel consumption analysis method and device, computer equipment and readable storage medium | |
| Migliorini et al. | CoPart: a context-based partitioning technique for big data | |
| CN116167441A (en) | Knowledge graph of network security risk assessment and construction method | |
| Orta Alemán et al. | Improved Robustness In Long-term Pressure Data Analysis Using Wavelets and Deep Learning | |
| CN110674196B (en) | GRAPES (generalized Grace temporal evolution) area set forecast inspection display system and display method | |
| CN112966041A (en) | Data processing method, device, equipment and storage medium | |
| CN110580385A (en) | data processing method, device and equipment for underground pipeline and computer storage medium | |
| US11893001B2 (en) | Systems and methods for storing blend objects |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |