CN115907836A - Automobile marketing management system based on data analysis and AR technology - Google Patents
Automobile marketing management system based on data analysis and AR technology Download PDFInfo
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Abstract
The invention relates to the technical field of automobile marketing management, in particular to an automobile marketing management system based on data analysis and AR technology, which comprises a server, a vehicle dynamic data analysis unit, a vehicle operation supervision unit, a vehicle evaluation analysis unit, a storage unit, a vehicle marketing interaction unit, a server and a server screen, wherein the server is connected with the server through a network; the invention collects the driving dynamic data and the loss data of the automobile, comprehensively analyzes the automobile and the automobile parts by symbolic calibration, integrated classification and progressive mode, is beneficial to carrying out optimal classification on the automobile and the automobile parts, evaluates the cost performance of the target automobile tire from two dimensions of the loss amount and the loss cost of the tire per kilometer, enlarges the evaluation dimension of the tire cost performance, has more comprehensive analysis, and is beneficial to the automobile selector to know the automobile more quickly by immersing the automobile selector in a three-dimensional environment and showing the complex principle in an interactive AR form after being stereoscopically embodied.
Description
Technical Field
The invention relates to the technical field of automobile marketing management, in particular to an automobile marketing management system based on data analysis and AR technology.
Background
China families have prepared for automobile possession and automobile life entrance, and as the automobile consumption potential market in the world and the automobile consumption market with the second rank in the world, market opportunities hidden in the automobile market in China are unprecedented, and in addition, the marketing system can centralize automobile information (appearance, interior, central control, function, performance parameters, comments and market data) which is most rich in marketing power to be displayed in the cloud;
however, compared with the existing display mode and purchase mode, the latest detailed information of various automobiles and the cost performance of automobiles in the same level cannot be known in real time, the cost performance of the automobiles can be judged by two factors of data promised by the existing suppliers and purchase cost, the obtained evaluation data is inaccurate, the internal supply condition of the automobiles can be reflected only singly, the problem of small evaluation and maintenance range exists, the sequencing of various automobiles is not facilitated, in addition, the automobiles are selected to be viewed and researched in price in the traditional shop, and the automobiles cannot be known deeply in the understanding mode of online photos, and the integral display of the automobiles is not facilitated;
in view of the above technical drawbacks, a solution is proposed.
Disclosure of Invention
The invention aims to provide an automobile marketing management system based on data analysis and AR technology, which solves the technical defects, integrates driving dynamic data and loss data of an automobile, performs comprehensive analysis in a symbolic calibration, integrated classification and progressive mode, combines and compares hierarchical division of a collection object and a processing flow, is further beneficial to carrying out optimal classification on the automobile, evaluates the cost performance of a target automobile tire from two dimensions of a loss amount and a tire loss cost per kilometer, enlarges the evaluation dimension of the tire cost performance, evaluates the oil consumption and the cost performance of power consumption of the target automobile from two dimensions of an oil cost per kilometer and a power cost per kilometer, can evaluate the oil consumption, the power consumption or mixed movement independently through the mode, enlarges the evaluation dimension of the cost performance of loss of the target automobile, is more comprehensive in analysis, enables a driver to be shown in an interactive AR form after a complex principle is three-dimensionally selected in a three-dimensional environment, and is beneficial to the driver to know the automobile more quickly.
The purpose of the invention can be realized by the following technical scheme: a vehicle marketing management system based on data analysis and AR technology is characterized by comprising a server, a vehicle dynamic data analysis unit, a vehicle operation supervision unit, a vehicle evaluation analysis unit, a storage unit, a vehicle marketing interaction unit, a server and a server screen;
the vehicle dynamic data analysis unit is used for acquiring driving dynamic data of the vehicle before marketing, wherein the driving dynamic data comprises the original pattern depth of the automobile tire of a target vehicle, the total first automobile tire maintenance cost and the total number of kilometers of the vehicle in running, analyzing the driving dynamic data to obtain a tire damage coefficient SZi, an exclusion signal and an optimization signal, sending the tire damage coefficient SZi to the vehicle evaluation analysis unit, and sending the exclusion signal and the optimization signal to the storage unit;
the vehicle operation monitoring unit is used for acquiring loss data of a target vehicle running for hundreds of kilometers, wherein the loss data comprises total oil consumption number and total power consumption number of the target vehicle running for hundreds of kilometers, analyzing the loss data to obtain a loss coefficient SH i, an abnormal signal and a normal signal, sending a tire damage coefficient SZi to the vehicle evaluation and analysis unit, and sending the abnormal signal and the normal signal to the storage unit;
after receiving the tire damage coefficient SZi and the loss coefficient SHI, the vehicle evaluation and analysis unit immediately analyzes the tire damage coefficient SZi and the loss coefficient SHI to obtain an evaluation performance coefficient Pi;
the vehicle marketing interaction unit is used for acquiring a real object scene characteristic image of the target automobile during marketing, checking and analyzing the real object scene characteristic image to obtain an image folder SPi, and sending the image folder SPi to the storage unit;
when the server sends a viewing instruction of the target automobile, the image folder SPi of the target automobile corresponding to the viewing instruction is called from the storage unit and is sent to the server.
Preferably, the driving dynamic data analyzing unit specifically analyzes the driving dynamic data in the following steps:
the method comprises the following steps: marking a target automobile in the same-level automobile as i, wherein i is a natural number greater than zero, the target automobile refers to an automobile extracted as analysis, acquiring the original pattern depth of the automobile tire of the target automobile, acquiring the pattern depth of the automobile tire after a hundred kilometers test, acquiring the abrasion loss of the automobile tire for a hundred kilometers according to the difference between the original pattern depth of the automobile tire and the pattern depth of the automobile tire after the hundred kilometers test, acquiring the abrasion depth of the automobile tire for a unit kilometer according to the abrasion loss of the automobile tire for the hundred kilometers, and marking the abrasion depth as a breaking loss Zi;
step two: acquiring the total first automobile tire maintenance cost and the total running kilometer number of a target automobile, dividing the total first automobile tire maintenance cost by the total running kilometer number to obtain unit kilometer tire loss cost, and marking the unit kilometer tire loss cost as unit kilometer tire loss cost Si;
step three: and obtaining the tire damage coefficient SZi through a formula.
Preferably, the vehicle evaluation and analysis unit specifically analyzes the following processes:
the formula is shown as follows:
obtaining an evaluation performance coefficient, and sending the evaluation performance coefficient Pi, the tire damage coefficient SZi and the loss coefficient SHI to a storage unit for storage;
meanwhile, a set { P1, P2, P3,. And Pi } of the evaluation performance coefficients Pi is constructed, and the subsets in the set are sorted from small to large.
Preferably, the vehicle marketing interaction unit viewing analysis process is as follows:
the method comprises the steps of obtaining object scene characteristic images of each target automobile, establishing a rectangular coordinate system by using the middle points of the object scene characteristic images, inputting length and width thresholds of preset object scene characteristic images, cutting the object scene characteristic images in a corresponding coordinate system, obtaining processed object scene characteristic images with uniform size, marking the processed object scene characteristic images as analysis images, carrying out compression transcoding processing on the analysis images, namely carrying out low-resolution and high-resolution compression transcoding processing on the analysis images, storing the low-resolution images and the high-resolution images obtained after transcoding processing into a folder, and marking the low-resolution images and the high-resolution images as image folders SPi.
Preferably, when the server receives the image folder SPi, the server simultaneously obtains a view loading mode of the server:
when the server checks and loads by adopting a mobile network, a selection instruction is sent to a server screen, when the server screen receives the selection instruction, two selection keys of a low-resolution image and a high-resolution image are displayed and loaded, when the low-resolution image is selected, the low-resolution image in the image folder SPi is identified by adopting an image identification algorithm, and when the high-resolution image is selected, the high-resolution image in the image folder SPi is identified by adopting the image identification algorithm;
when the server side adopts the Wife to check and load, the image content is directly identified by adopting the image identification algorithm for the high-resolution image in the image folder SPi, and the three-dimensional image corresponding to the image is displayed on the screen of the server side for the image identified by the image identification algorithm.
The invention has the following beneficial effects:
(1) The driving dynamic data and the loss data of the automobile are collected, comprehensive analysis is carried out in a symbolic calibration, integrated classification regular and progressive mode, namely, the collected objects and the hierarchy division of the processing flow are combined and compared, so that the automobile is favorably classified in a preferred mode, the cost performance of a target automobile tire is evaluated from two dimensions of the loss amount and the unit kilometer tire loss cost, the evaluation dimension of the tire cost performance is enlarged, the oil consumption and the cost performance of the power consumption of the target automobile are evaluated from two dimensions of the unit kilometer oil cost and the unit kilometer power cost, and the oil consumption, the power consumption or the hybrid can be evaluated independently through the mode, the evaluation dimension of the cost performance of the loss of the target automobile is enlarged, and the analysis is more comprehensive;
(2) The evaluation performance coefficient is obtained through the weighting factors based on the tire damage coefficient and the loss coefficient, so that the evaluation dimensionality is enlarged, the evaluation accuracy is improved, the subsets in the set are sorted from small to large, the target automobiles are sorted, and the high-class automobiles are preferentially shown;
(3) The loading mode is checked through the in-depth analysis server, analysis images of a target automobile after being processed by the AR technology can be checked reasonably, a user rotates, moves, enlarges, reduces and the like the three-dimensional model on a screen of the server, the principle of each part in the automobile can be observed in detail through interaction of dynamic contents, the analysis images of the target automobile can be processed through the AR technology, the structure composition and the operation principle of automobile parts can be watched in a virtual three-dimensional environment, a vehicle selection person is immersed in the three-dimensional environment, the complex principle can be displayed in an interactive AR form after being subjected to three-dimensional transformation, and the vehicle selection person can know the automobile more quickly.
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The invention will be further described with reference to the accompanying drawings;
FIG. 1 is a block flow diagram of the system of the present invention;
FIG. 2 is a schematic diagram of the object scene feature image analysis of the present invention;
FIG. 3 is a flow diagram of a server in accordance with the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Example 1:
referring to fig. 1-3, the present invention is an automobile marketing management system based on data analysis and AR technology, including a server, a vehicle dynamic data analysis unit, a vehicle operation supervision unit, a vehicle evaluation analysis unit, a storage unit, a vehicle marketing interaction unit, a server and a server screen, wherein the server is in bidirectional communication with the vehicle evaluation analysis unit, the server is in bidirectional communication with the storage unit, the server is in bidirectional communication with the vehicle marketing interaction unit, the vehicle evaluation analysis unit is in bidirectional communication with both the vehicle operation supervision unit and the vehicle dynamic data analysis unit, the server is in bidirectional communication with the server, and the server screen is disposed inside the server;
the vehicle dynamic data analysis unit is used for collecting driving dynamic data of the vehicle before marketing, the driving dynamic data comprises the original automobile tire pattern depth of the target vehicle, the total first automobile tire maintenance cost and the total number of kilometers of the driving, and the driving dynamic data is analyzed, and the specific analysis process is as follows:
marking a target automobile in the same-level automobiles as i, wherein i is a natural number larger than zero, the same-level automobile refers to one of A00 level, A0 level, A level, B level, C level and D level in the prior art, the target automobile refers to an automobile extracted as analysis, acquiring the original pattern depth of an automobile tire of the target automobile, acquiring the pattern depth of the automobile tire after a hundred kilometers of test, acquiring the abrasion loss of the automobile tire for hundred kilometers according to the difference between the original pattern depth of the automobile tire and the pattern depth of the automobile tire after the hundred kilometers of test, acquiring the abrasion depth of the automobile tire for hundred kilometers according to the abrasion loss of the automobile tire for hundred kilometers, marking the abrasion loss as Zi, wherein the service lives of the tires of different brands are different, and accidental tire burst and the like possibly affect the service life of the tire, therefore, carrying out more objective and feasible evaluation on the change of the pattern depth corresponding to the kilometers by unit statistics, constructing a set { Z1, Z2, Z3, Z.
Acquiring the total cost of first automobile tire maintenance of a target automobile and the total kilometer number of the current running of the target automobile, dividing the total cost of first automobile tire maintenance by the total kilometer number of the current running of the target automobile to obtain the tire loss cost per kilometer, marking the tire loss cost per kilometer as Si, constructing a set { S1, S2, S3,. Multidot.Si } of the tire loss cost per kilometer, and corresponding the subsets in the set of the tire loss cost per kilometer to the subsets in the set of the loss amount Zi one by one through a formula:
obtaining a tire damage factor of the target vehicle, wherein alpha and beta are respectively the breaking loss and the tire loss cost per kilometerThe correction factor, α > β > 0, α + β =1.486, SZi is a tire damage coefficient of the target vehicle, it should be noted that the tire damage coefficient is used for reflecting a cost performance condition of the target vehicle, and the cost performance of the target vehicle is evaluated by the tire loss cost per kilometer and the depreciation amount, and compared with a method of judging the cost performance of the vehicle tire by two factors, namely, the travel mileage and the purchase cost promised by the existing supplier, the cost performance of the target vehicle tire is evaluated from two dimensions, namely, the depreciation amount and the tire loss cost per kilometer, and the evaluation dimension of the tire cost performance is enlarged, so that the evaluation accuracy is improved, and the tire cost performance is more comprehensive, in addition, the larger the value of the tire damage coefficient SZi of the target vehicle is, the worse the tire cost performance of the target vehicle is, otherwise, the smaller the value of the tire damage coefficient SZi of the target vehicle is, the better the tire of the target vehicle is corresponding to the target vehicle, and the tire damage coefficient SZi is sent to the vehicle evaluation and analysis unit, and simultaneously, the tire damage coefficient SZ of each target vehicle is compared with a preset tire damage coefficient stored in the vehicle:
if the tire damage coefficient SZi is larger than or equal to the preset tire damage coefficient, generating an exclusion signal, and sending the exclusion signal and the automobile number corresponding to the exclusion signal to a storage unit;
if the tire damage coefficient SZi is smaller than the preset tire damage coefficient, generating an optimal selection signal, sending the optimal selection signal and the automobile number corresponding to the optimal selection signal to a storage unit, constructing a set of tire damage coefficients SZi smaller than the preset tire damage coefficient, and sequencing the tire damage coefficients SZi from small to large in the set so as to select the automobile picture corresponding to the minimum tire damage coefficient in a priority mode and display the automobile picture in a screen of a server;
the vehicle operation supervision unit is used for acquiring loss data of a target vehicle running for hundreds of kilometers, the loss data comprises total oil consumption number and total power consumption number of the target vehicle running for hundreds of kilometers, and the loss data is analyzed, wherein the specific analysis process is as follows:
acquiring the total oil consumption number of the target automobile running for hundreds of kilometers, acquiring the oil consumption number of the target automobile per unit kilometer according to the total oil consumption number of the target automobile running for hundreds of kilometers, and marking the oil consumption numberRecording as a fuel consumption value, obtaining the unit price of gasoline filling of the current target automobile in real time, obtaining the oil cost per kilometer according to the product of the fuel consumption value and the unit price of gasoline filling, wherein the number is Gi, it needs to be explained that the fuel consumption cost of the target automobile in the same-grade automobile is larger and the economic consumption is larger if the number of the oil cost Gi per kilometer is larger, and conversely, the fuel consumption cost of the target automobile in the same-grade automobile is smaller if the number of the oil cost Gi per kilometer is smaller and the economic consumption is smaller; acquiring the total power consumption of a target automobile running for hundred kilometers, acquiring the power consumption of the target automobile per kilometer according to the total power consumption of the target automobile running for hundred kilometers, marking the power consumption as a power consumption value, acquiring the charging unit price of the current target automobile in real time, acquiring the power cost per kilometer according to the product of the power consumption value and the charging unit price, wherein the mark is Fi, and the power cost per kilometer passes through a formula: SHi = [ (a × Gi) + (b × Fi)] 2 Obtaining loss coefficients, wherein a and b are weight factors of unit kilometer oil cost and unit kilometer electricity cost respectively, a is more than b and is more than 0, SHi is a loss coefficient, the oil consumption, the electricity consumption and the hybrid cost performance of a target automobile are evaluated from two dimensions of the unit kilometer oil cost and the unit kilometer electricity cost, the oil consumption, the electricity consumption or the hybrid can be evaluated independently through the method, the evaluation dimension of the cost performance of the target automobile loss is enlarged, the evaluation accuracy is improved, the loss coefficients SHi are sent to a vehicle evaluation and analysis unit, and meanwhile, the loss coefficients SHi of each target automobile and pre-loss coefficients recorded and stored in the vehicle evaluation and analysis unit are compared and analyzed:
if the loss coefficient SHI is larger than or equal to the preset loss coefficient, generating an abnormal signal, and sending the abnormal signal and the automobile number corresponding to the abnormal signal to a storage unit;
if the loss coefficient SHI is smaller than the preset tire loss coefficient, generating a normal signal, sending the normal signal and the automobile number corresponding to the normal signal to a storage unit, constructing a set of the loss coefficients SHI smaller than the preset loss coefficient, and sequencing the automobile numbers in the set from small to large so as to preferentially select the automobile picture corresponding to the minimum loss coefficient and display the automobile picture in a screen of a server;
the vehicle evaluation and analysis unit immediately analyzes the tire damage coefficient SZi and the loss coefficient SHI after receiving the tire damage coefficient SZi and the loss coefficient SHI, and the specific analysis process is as follows:
by the formula:
obtaining an evaluation performance coefficient, wherein epsilon and gamma are weight factors of a tire damage coefficient and a loss coefficient respectively, epsilon > gamma > 0, epsilon + gamma =1.386, pi is an evaluation performance coefficient of each target automobile, and it should be noted that the larger the value of the evaluation performance coefficient Pi is, the worse the overall performance of the automobile is, and conversely, the smaller the value of the evaluation performance coefficient Pi is, the better the overall performance of the automobile is, sending the evaluation performance coefficient Pi, the tire damage coefficient SZi and the loss coefficient SHI to a storage unit for storage, constructing a set { P1, P2, P3,.
Example 2:
the vehicle marketing interaction unit is used for acquiring a real object scene characteristic image of the target automobile during marketing and checking and analyzing the real object scene characteristic image, and the specific analysis process is as follows:
acquiring a real object scene characteristic image of each target automobile, establishing a rectangular coordinate system by using a midpoint of the real object scene characteristic image, inputting a length and width threshold of a preset real object scene characteristic image, cutting the real object scene characteristic image in a corresponding coordinate system, acquiring a processed uniform-size real object scene characteristic image, marking the processed uniform-size real object scene characteristic image as an analysis image, performing compression transcoding processing on the analysis image, namely performing low-resolution and high-resolution compression transcoding processing on the analysis image, storing the low-resolution image and the high-resolution image obtained after the transcoding processing into a folder, marking the low-resolution image and the high-resolution image as an image folder SPi, and sending the image folder SPi to a storage unit;
when a server sends a viewing instruction of a target automobile, an image folder SPi of the target automobile corresponding to the viewing instruction is called from a storage unit and is sent to a server, the server simultaneously obtains a viewing loading mode of the server when receiving the image folder SPi, when the server uses a mobile network to view and load, a selection instruction is sent to a server screen, when the server screen receives the selection instruction, two selection keys of a low-resolution image and a high-resolution image are displayed and loaded, when the low-resolution image is selected, the low-resolution image in the image folder SPi is identified by using an image identification algorithm, and when the high-resolution image is selected, the high-resolution image in the image folder SPi is identified by using the image identification algorithm, wherein the image identification algorithm identifies the image content and refers to the existing AR technology processing; the AR technology processing is a technology for calculating the position and the angle of a camera image in real time and adding a corresponding image, is a new technology for seamlessly integrating real world information and virtual world information, and aims to sleeve a virtual world on a screen in the real world and perform interaction;
when the server side adopts Wife to check and load, the picture content is directly identified by adopting an image identification algorithm for a high-resolution image in the image folder SPi, the image identified by the image identification algorithm is displayed on a screen of the server side, a user rotates, moves, enlarges, reduces and the like a three-dimensional model on the screen of the server side, the principle of each part in the automobile is observed in detail through the interaction of dynamic content, the analysis image of a target automobile is processed through AR technology, the structure composition and the operation principle of automobile parts are favorably observed in a virtual three-dimensional environment, a vehicle selector is immersed in the three-dimensional environment, the complex principle is displayed in an interactive AR form after being stereoscopically realized, the image processed by the AR technology can observe the flowing process of the internal energy or current of the automobile parts in the three-dimensional space, and the vehicle selector can help to learn the vivid and stereoscopic character or plane picture knowledge before the eyes of the vehicle selector;
in summary, the driving dynamic data and the loss data of the automobile are collected, comprehensive analysis is performed in a symbolic calibration, classification of the set is regular and progressive mode, namely, the collected objects and the hierarchy division of the processing flow are combined and compared, so that the automobile is favorably classified, the cost performance of the target automobile is evaluated through the loss cost and the breaking loss of the tires of a unit kilometer, compared with the mode that the cost performance of the tires of the automobile is judged through two factors of the travel number and the purchase cost promised by the existing supplier, the cost performance of the target automobile tires is evaluated through two dimensions of the breaking loss and the loss cost of the tires of the unit kilometer, the evaluation dimension of the cost performance of the tires is enlarged, the oil consumption, the power consumption or the hybrid of the target automobile is evaluated through the mode, the evaluation dimension of the loss of the target automobile is enlarged, the analysis is more comprehensive, the evaluation dimension of the performance coefficient and the loss coefficient are obtained based on the weight factors of the tire damage coefficient and the loss coefficient, the evaluation of the performance coefficient and the low cost are further, the evaluation of the subset of the small automobile is favorably evaluated and the priority ranking of the set is improved, and the priority ranking of the small automobiles is facilitated; in addition, the loading mode is checked through the in-depth analysis server, analysis images of a target automobile after being processed by the AR technology can be checked reasonably, a user can rotate, move, enlarge, shrink and the like the three-dimensional model on a screen of the server, the principle of each part in the automobile can be observed in detail through interaction of dynamic contents, the analysis images of the target automobile can be processed through the AR technology, the structure composition and the operation principle of automobile parts can be watched in a virtual three-dimensional environment, a vehicle selection person can be immersed in the three-dimensional environment, the complex principle can be displayed in an interactive AR form after being subjected to three-dimensional transformation, and the vehicle selection person can know the automobile more quickly.
The above formulas are obtained by collecting a large amount of data and performing software simulation, and the coefficients in the formulas are set by those skilled in the art according to actual conditions, and the above descriptions are only preferred embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can be within the technical scope of the present invention, and equivalent substitutions or changes according to the technical scheme and the inventive concept thereof should be covered within the scope of the present invention.
Claims (6)
1. A vehicle marketing management system based on data analysis and AR technology is characterized by comprising a server, a vehicle dynamic data analysis unit, a vehicle operation supervision unit, a vehicle evaluation analysis unit, a storage unit, a vehicle marketing interaction unit, a server and a server screen;
the vehicle dynamic data analysis unit is used for acquiring driving dynamic data of the vehicle before marketing, wherein the driving dynamic data comprises the original pattern depth of the automobile tire of a target vehicle, the total first automobile tire maintenance cost and the total number of kilometers of the vehicle in running, analyzing the driving dynamic data to obtain a tire damage coefficient SZi, an exclusion signal and an optimization signal, sending the tire damage coefficient SZi to the vehicle evaluation analysis unit, and sending the exclusion signal and the optimization signal to the storage unit;
the vehicle operation supervision unit is used for acquiring loss data of a target vehicle running for hundreds of kilometers, analyzing the loss data, obtaining a loss coefficient SHI, an abnormal signal and a normal signal, sending a tire damage coefficient SZi to the vehicle evaluation and analysis unit, and sending the abnormal signal and the normal signal to the storage unit, wherein the loss data comprises a total oil consumption number and a total power consumption number of the target vehicle running for hundreds of kilometers;
after receiving the tire damage coefficient SZi and the loss coefficient SHI, the vehicle evaluation and analysis unit immediately analyzes the tire damage coefficient SZi and the loss coefficient SHI to obtain an evaluation performance coefficient Pi;
the vehicle marketing interaction unit is used for acquiring a real object scene characteristic image of a target vehicle during marketing, checking and analyzing the real object scene characteristic image to obtain an image folder SPi, and sending the image folder SPi to the storage unit;
when the server sends a viewing instruction of the target automobile, the image folder SPi of the target automobile corresponding to the viewing instruction is called from the storage unit and is sent to the server.
2. The system for vehicle marketing management based on data analysis and AR technology according to claim 1, wherein the driving dynamic data of the vehicle dynamic data analysis unit is specifically analyzed as follows:
the method comprises the following steps: marking a target automobile in the same-level automobile as i, wherein i is a natural number greater than zero, the target automobile refers to an automobile extracted as analysis, acquiring the original pattern depth of the automobile tire of the target automobile, acquiring the pattern depth of the automobile tire after a hundred kilometers test, acquiring the abrasion loss of the automobile tire for a hundred kilometers according to the difference between the original pattern depth of the automobile tire and the pattern depth of the automobile tire after the hundred kilometers test, acquiring the abrasion depth of the automobile tire for a unit kilometer according to the abrasion loss of the automobile tire for the hundred kilometers, and marking the abrasion depth as a breaking loss Zi;
step two: acquiring the total first automobile tire maintenance cost and the total running kilometer number of a target automobile, dividing the total first automobile tire maintenance cost by the total running kilometer number to obtain unit kilometer tire loss cost, and marking the unit kilometer tire loss cost as unit kilometer tire loss cost Si;
step three: obtaining a tire damage coefficient SZi through a formula, and comparing and analyzing the tire damage coefficient SZi of each target automobile with a preset tire damage coefficient recorded and stored in the target automobile:
if the tire damage coefficient SZi is larger than or equal to the preset tire damage coefficient, generating an exclusion signal;
if the tire damage coefficient SZi is smaller than the preset tire damage coefficient, generating an optimal signal, constructing a set of tire damage coefficients SZi smaller than the preset tire damage coefficient, and sequencing the tire damage coefficients SZi from small to large in the set.
3. The system of claim 1, wherein the vehicle operation supervision unit loss data analysis process comprises the following specific steps:
the first step is as follows: acquiring the total oil consumption number of a target automobile running for hundred kilometers, acquiring the oil consumption number of the target automobile per kilometer according to the total oil consumption number of the target automobile running for hundred kilometers, marking the oil consumption number as an oil consumption value, acquiring the unit price of gasoline filling of the current target automobile in real time, acquiring the oil cost per kilometer according to the product of the oil consumption value and the unit price of gasoline filling, and acquiring the oil cost per kilometer by the product of the oil consumption value and the unit price of gasoline filling to obtain an oil cost mark Gi;
acquiring the total power consumption number of a target automobile running for hundred kilometers, acquiring the power consumption number of the target automobile per kilometer according to the total power consumption number of the target automobile running for hundred kilometers, marking the power consumption number as a power consumption value, acquiring the charging unit price of the current target automobile in real time, acquiring the power cost per kilometer according to the product of the power consumption value and the charging unit price, and acquiring the power cost per kilometer by the product of the power consumption value and the charging unit price to obtain the power cost mark Fi;
the second step: obtaining a tire damage coefficient SZi through a formula, and comparing and analyzing the loss coefficient SHI of each target automobile with the pre-loss coefficient recorded and stored in the target automobile:
if the loss coefficient SHI is larger than or equal to the preset loss coefficient, generating an abnormal signal;
and if the loss coefficient SHI is smaller than the preset tire loss coefficient, generating a normal signal, constructing a set of the loss coefficients SHI smaller than the preset loss coefficient, and sequencing the loss coefficients from small to large in the set.
4. The system of claim 1, wherein the vehicle evaluation analysis unit analyzes the data analysis and the AR technology as follows:
the formula is shown as follows:
obtaining an evaluation performance coefficient, and sending the evaluation performance coefficient Pi, the tire damage coefficient SZi and the loss coefficient SHI to a storage unit for storage;
meanwhile, a set { P1, P2, P3,. And Pi } of the evaluation performance coefficients Pi is constructed, and the subsets in the set are sorted from small to large.
5. The system of claim 1, wherein the vehicle marketing interaction unit viewing analysis process comprises the following steps:
the method comprises the steps of obtaining object scene characteristic images of each target automobile, establishing a rectangular coordinate system by using the middle points of the object scene characteristic images, inputting the length and width threshold values of the preset object scene characteristic images, cutting the preset object scene characteristic images in the corresponding coordinate systems, obtaining the processed object scene characteristic images with the uniform size, marking the processed object scene characteristic images as analysis images, performing compression transcoding processing on the analysis images, namely performing low-resolution and high-resolution compression transcoding processing on the analysis images, storing the low-resolution images and the high-resolution images obtained after the transcoding processing into a folder, and marking the low-resolution images and the high-resolution images as image folders SPi.
6. The automobile marketing management system based on data analysis and AR technology according to claim 1, wherein when the server receives the image folder SPi, the server simultaneously obtains a view loading manner:
when the server checks and loads by adopting a mobile network, a selection instruction is sent to a server screen, when the server screen receives the selection instruction, two selection keys of a low-resolution image and a high-resolution image are loaded, when the low-resolution image is selected, the image content is identified by adopting an image identification algorithm for the low-resolution image in the image folder SPi, and when the high-resolution image is selected, the image content is identified by adopting the image identification algorithm for the high-resolution image in the image folder SPi;
when the server side adopts the Wife to check and load, the image content is directly identified by adopting the image identification algorithm for the high-resolution image in the image folder SPi, and the three-dimensional image corresponding to the image is displayed on the screen of the server side for the image identified by the image identification algorithm.
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| CN117132300A (en) * | 2023-07-28 | 2023-11-28 | 山东方达再生资源利用有限公司 | Image recognition-based scraped car evaluation system |
| CN117132300B (en) * | 2023-07-28 | 2024-03-12 | 山东方达再生资源利用有限公司 | Image recognition-based scraped car evaluation system |
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