A method and system for intelligent automobile information processing based on Internet of Vehicles technology

Abstract

The present invention belongs to the field of intelligent vehicle management technology, and specifically is an intelligent vehicle information processing method and system based on vehicle networking technology, wherein the intelligent vehicle information processing system includes a vehicle networking platform, an impact detection and analysis module, a real-time scanning monitoring module, a real-time operation detection and analysis module, and a buzzer warning module; the present invention is beneficial to improving the anti-theft performance of the intelligent vehicle by combining the pressure impact condition of the intelligent vehicle body with the unlocking and starting risk condition and accurately judging and feeding back, and during the operation of the intelligent vehicle, the forward risk of the corresponding intelligent vehicle is evaluated to determine its speed range, and it is judged whether to generate a speed warning signal, so that the driver can adjust the speed in time to ensure the forward safety, and when it is judged that the speed is normal, the control performance is analyzed to further ensure the safe forward movement of the corresponding intelligent vehicle.

Description

Technical Field

[0001] The present invention relates to the field of intelligent vehicle management technology, and in particular to an intelligent vehicle information processing method and system based on vehicle networking technology. Background Art

[0002] Smart car refers to a comprehensive system that integrates environmental perception, planning and decision-making, multi-level assisted driving and other functions. It uses computers, modern sensors, information fusion, communications, artificial intelligence and automatic control technologies. It is a typical high-tech complex. The research on smart cars aims to improve the safety and comfort of cars and provide excellent human-vehicle interaction interfaces. In recent years, smart vehicles have become a hot topic in the field of vehicle engineering research and a new driving force for the growth of the automotive industry.

[0003] At present, when processing the information of smart cars, it is difficult to combine the pressure impact condition of the smart car body with the risk condition of unlocking and starting and accurately judge and feedback, which is not conducive to improving the anti-theft performance of smart cars. In addition, it is impossible to reasonably evaluate the forward risk of smart cars during their operation, and it is impossible to analyze their control performance when it is judged that there is no abnormality in the speed of the car, which is not conducive to ensuring the driving safety of smart cars. Improvements are needed;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent vehicle information processing method and system based on vehicle networking technology, which solves the problems that the prior art is difficult to combine the pressure impact condition of the intelligent vehicle body with the unlocking and starting risk condition and accurately judge and feedback, which is not conducive to improving the anti-theft performance of the intelligent vehicle, and cannot reasonably evaluate the forward risk of the intelligent vehicle during its operation, and cannot analyze its control performance when it is judged that the vehicle speed is normal, which is not conducive to ensuring the driving safety of the intelligent vehicle.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for processing intelligent vehicle information based on vehicle networking technology comprises the following steps:

[0008] Step 1: Performing impact detection and analysis on the body of the corresponding smart car, and generating an impact warning signal or a body safety signal accordingly; after the impact warning signal is generated, controlling the buzzer warning module of the corresponding smart car to emit a warning sound, and collecting the real-time monitoring image of the corresponding impact point, and sending the impact warning signal of the corresponding smart car and the corresponding real-time monitoring image to the corresponding user terminal;

[0009] Step 2: When unlocking the corresponding smart car, a real-time monitoring image of the unlocking area is collected, and a facial recognition analysis is performed to generate an identity authentication pass signal or an identity authentication fail signal. The user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" based on the real-time monitoring image;

[0010] Step 3: If the "unlock and start allowed" command is received, the corresponding smart car is allowed to be unlocked and started when the car key is matched; if the "unlock and start not allowed" command is received, the corresponding smart car is not allowed to be unlocked and started when the car key is matched, and the buzzer warning module of the corresponding smart car is controlled to emit a warning sound;

[0011] Step 4. During the operation of the corresponding smart car, the forward risk of the corresponding smart car is evaluated to determine its speed range, and it is judged whether the actual speed of the corresponding smart car meets the requirements, so that the driver can adjust the speed in time.

[0012] Furthermore, the present invention also proposes an intelligent automobile information processing system based on the Internet of Vehicles technology, including an Internet of Vehicles platform, a hit detection and analysis module, a real-time scanning and monitoring module, a real-time operation detection and analysis module, and a buzzer warning module; the hit detection and analysis module is used to perform hit detection and analysis on the body of the corresponding intelligent automobile, thereby generating a hit warning signal or a body safety signal, and sending the hit warning signal or the body safety signal to the Internet of Vehicles platform, and after receiving the hit warning signal, the Internet of Vehicles platform controls the buzzer warning module of the corresponding intelligent automobile to emit a warning sound; and after generating the hit warning signal, the real-time scanning and monitoring module collects the real-time monitoring image of the corresponding hit point, and sends the real-time monitoring image to the Internet of Vehicles platform, and the Internet of Vehicles platform sends the hit warning signal of the corresponding intelligent automobile and the corresponding real-time monitoring image to the corresponding user terminal;

[0013] The real-time scanning monitoring module is also used to collect real-time monitoring images of the unlocking area when unlocking the corresponding smart car, and generate an identity authentication signal or an identity authentication failure signal through facial recognition analysis, and send the identity authentication signal or the identity authentication failure signal to the Internet of Vehicles platform, and the Internet of Vehicles platform sends the identity authentication failure signal and the corresponding real-time monitoring image to the user terminal; the user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" to the Internet of Vehicles platform based on the real-time monitoring image, and when the Internet of Vehicles platform receives the "allow unlocking and starting" instruction, it allows it to unlock and start the corresponding smart car when the car key is matched, and when the Internet of Vehicles platform receives the "do not allow unlocking and starting" instruction, it does not allow it to unlock and start the corresponding smart car when the car key is matched, and controls the buzzer warning module of the corresponding smart car to emit a warning sound;

[0014] During the operation of the corresponding smart car, the real-time operation detection and analysis module will evaluate the forward risk of the corresponding smart car, determine its speed range based on this, and send the speed range to the vehicle-mounted terminal of the corresponding smart car via the Internet of Vehicles platform; and obtain the current actual speed of the corresponding smart car, compare the current actual speed with the corresponding speed range, if the current actual speed is not within the corresponding speed range, send a speed warning signal to the vehicle-mounted terminal of the corresponding smart car through the Internet of Vehicles platform, so that the driver can adjust the speed in time; when the speed warning signal is not generated, the control performance of the corresponding smart car will be analyzed, and a qualified control performance signal or an unqualified control performance signal will be generated based on this, and the unqualified control performance signal will be sent to the vehicle-mounted terminal of the corresponding smart car via the Internet of Vehicles platform.

[0015] Furthermore, the specific analysis process of the hit detection analysis module includes:

[0016] A number of detection points are set on the body of the corresponding smart car, and the corresponding detection points are marked as i, i={1,2,…,n}, n represents the number of detection points and n is a natural number greater than 1; the pressure sensor arranged at the detection point i is used to collect the impact force received by it and mark it as an impact value, and an impact set is established by a number of groups of impact values ​​of the detection point i in a unit time, and the impact set is summed and averaged to obtain the impact average value, and the subset with the largest value in the impact set is marked as the instantaneous impact amplitude;

[0017] The impact average value and the instantaneous impulse amplitude are numerically calculated to obtain the impulse performance value, and the impulse performance value is numerically compared with the preset performance threshold; if the impulse performance value exceeds the preset performance threshold, the corresponding detection point i is marked as the impact point; if there is an impact point on the body of the corresponding smart car, an impact warning signal is generated; if there is no impact point on the body of the corresponding smart car at the detection moment, a body safety signal is generated.

[0018] Furthermore, the specific analysis process of facial recognition analysis is as follows:

[0019] Real-time monitoring images of the corresponding smart car unlocking area are collected, all facial images are extracted from the real-time images, and the facial images of the corresponding persons are marked as analysis images p, where p={1,2,…,k}, k represents the number of extracted facial images and m is a natural number greater than or equal to 1; the corresponding analysis images p are compared one by one with the images in the facial image database of the corresponding smart car to obtain several groups of facial overlap data, and the facial overlap data are numerically compared with the preset facial overlap data threshold. If there is facial overlap data exceeding the preset facial overlap data threshold, the corresponding analysis image u is marked as an overlap image; if there is no facial overlap data exceeding the preset facial overlap data threshold, the corresponding analysis image p is marked as an irrelevant image; the person corresponding to the overlap image is marked as a consistency object, and if there is a consistency object in the corresponding smart car unlocking area, an identity authentication qualified signal is generated; if there is no consistency object in the corresponding smart car unlocking area, an identity authentication unqualified signal is generated.

[0020] Furthermore, the specific evaluation process for evaluating the forward risk of the corresponding smart car is as follows:

[0021] The environmental visibility and environmental wind speed of the road section ahead of the corresponding smart car are collected, and the environmental visibility and environmental wind speed are numerically compared with the preset environmental visibility threshold and the preset environmental wind speed threshold respectively; if the environmental visibility does not exceed the preset environmental visibility threshold or the environmental wind speed exceeds the preset environmental wind speed threshold, a first-level impact signal is generated; if the environmental visibility exceeds the preset environmental visibility threshold and the environmental wind speed does not exceed the preset environmental wind speed threshold, the average traffic flow and accident frequency of the road section ahead of the corresponding smart car are collected, the average traffic flow and the accident frequency are numerically calculated to obtain a road analysis value, and the road analysis value is numerically compared with the preset road analysis value range;

[0022] If the road analysis value exceeds the maximum value of the preset road analysis value range, a first-level impact signal is generated; if the road analysis value is within the preset forward impact range, a second-level impact signal is generated; if the road analysis value does not exceed the minimum value of the preset forward impact range, a third-level impact signal is generated; if a first-level impact signal is generated, a first-level vehicle speed range is assigned to it; if a second-level impact signal is generated, a second-level vehicle speed range is assigned to it; if a third-level impact signal is generated, a third-level vehicle speed range is assigned to it, and the third-level vehicle speed range > the second-level vehicle speed range > the first-level vehicle speed range.

[0023] Furthermore, the specific analysis process of manipulation performance analysis is as follows:

[0024] The instantaneous swing amplitude and instantaneous swing frequency of the corresponding smart car are collected, and the instantaneous swing amplitude and the instantaneous swing frequency are numerically compared with the preset instantaneous swing amplitude threshold and the preset instantaneous swing frequency threshold respectively. If the instantaneous swing amplitude or the instantaneous swing frequency exceeds the corresponding preset threshold, a control performance unqualified signal is generated; if the instantaneous swing amplitude or the instantaneous swing frequency does not exceed the corresponding preset threshold, the difference between two groups of instantaneous swing amplitudes at adjacent moments is calculated to obtain instantaneous amplitude difference data, and the variance of several groups of instantaneous amplitude difference data within a unit time is calculated to obtain instantaneous amplitude data, and the instantaneous frequency data is obtained in the same way;

[0025] The instantaneous amplitude data and instantaneous frequency data are numerically compared with the preset instantaneous amplitude data threshold and the preset instantaneous data threshold respectively. If the instantaneous amplitude data or the instantaneous frequency data exceeds the corresponding preset threshold, an unqualified control performance signal is generated; if neither the instantaneous amplitude data nor the instantaneous frequency data exceeds the corresponding preset threshold, the temperature, humidity and dust concentration in the cab are collected, and the temperature and the preset suitable control temperature value are numerically calculated to obtain the temperature meter data, and the humidity meter data is obtained similarly; the temperature meter data, humidity meter data and dust concentration are numerically calculated to obtain the control influence value, and the control influence value is numerically compared with the preset control influence threshold. If the control influence value exceeds the preset control influence threshold, an unqualified control performance signal is generated; if the control influence value does not exceed the preset control influence threshold, a qualified control performance signal is generated.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. In the present invention, the body of the corresponding smart car is subjected to impact detection and analysis to generate an impact warning signal or a body safety signal. After the impact warning signal is generated, the buzzer warning module of the corresponding smart car is controlled to emit a warning sound, and the impact warning signal of the corresponding smart car and the corresponding real-time monitoring image are sent to the corresponding user terminal, so that the corresponding user can grasp the safety status of the smart car in detail, and timely report and collect evidence, thereby improving the anti-theft performance of the car; and when the corresponding smart car is unlocked, the real-time monitoring image of the unlocking area is collected by the real-time scanning monitoring module, and the identity authentication signal or the identity authentication signal is generated through facial recognition analysis. When the identity authentication signal is generated, the user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" to the Internet of Vehicles platform based on the real-time monitoring image, which helps prevent the car from being stolen and further improves the anti-theft performance and safety performance of the car;

[0028] 2. In the present invention, the forward risk of the corresponding smart car is evaluated to determine its speed range, and the speed range is sent to the vehicle terminal of the corresponding smart car via the Internet of Vehicles platform, and it is determined whether the current actual speed is within the corresponding speed range. If the current actual speed is not within the corresponding speed range, a speed warning signal is sent to the vehicle terminal of the corresponding smart car, so that the driver can adjust the speed in time to ensure the forward safety; when the speed warning signal is not generated, the control performance of the corresponding smart car is analyzed, and a control performance qualified signal or a control performance unqualified signal is generated accordingly, so that the driver can conduct an investigation in time and perform corresponding adjustment operations as needed, which helps to ensure the safe forward movement of the corresponding smart car. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0030] Figure 1 is a flow chart of the method of the present invention;

[0031] Figure 2 It is the overall system block diagram of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Embodiment 1: Figure 1 As shown, the present invention proposes a smart car information processing method based on the Internet of Vehicles technology, comprising the following steps:

[0034] Step 1: Performing impact detection and analysis on the body of the corresponding smart car, and generating an impact warning signal or a body safety signal accordingly; after the impact warning signal is generated, controlling the buzzer warning module of the corresponding smart car to emit a warning sound, and collecting the real-time monitoring image of the corresponding impact point, and sending the impact warning signal of the corresponding smart car and the corresponding real-time monitoring image to the corresponding user terminal;

[0035] Step 2: When unlocking the corresponding smart car, a real-time monitoring image of the unlocking area is collected, and a facial recognition analysis is performed to generate an identity authentication pass signal or an identity authentication fail signal. The user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" based on the real-time monitoring image;

[0036] Step 3: If the "unlock and start allowed" command is received, the corresponding smart car is allowed to be unlocked and started when the car key is matched; if the "unlock and start not allowed" command is received, the corresponding smart car is not allowed to be unlocked and started when the car key is matched, and the buzzer warning module of the corresponding smart car is controlled to emit a warning sound;

[0037] Step 4. During the operation of the corresponding smart car, the forward risk of the corresponding smart car is evaluated to determine its speed range, and it is judged whether the actual speed of the corresponding smart car meets the requirements, so that the driver can adjust the speed in time.

[0038] Embodiment 2: Figure 2 As shown, the difference between this embodiment and embodiment 1 is that an intelligent automobile information processing system based on the Internet of Vehicles technology includes an Internet of Vehicles platform, an impact detection and analysis module, a real-time scanning and monitoring module, a real-time operation detection and analysis module, and a buzzer warning module; the impact detection and analysis module is used to perform impact detection and analysis on the body of the corresponding intelligent automobile, thereby generating an impact warning signal or a body safety signal, and sending the impact warning signal or the body safety signal to the Internet of Vehicles platform. After receiving the impact warning signal, the Internet of Vehicles platform controls the buzzer warning module of the corresponding intelligent automobile to emit a warning sound, thereby significantly improving the anti-theft performance of the automobile; and after generating the impact warning signal, the real-time scanning and monitoring module collects the real-time monitoring image of the corresponding impact point, and sends the real-time monitoring image to the Internet of Vehicles platform. The Internet of Vehicles platform sends the impact warning signal and the corresponding real-time monitoring image of the corresponding intelligent automobile to the corresponding user terminal, so that the corresponding user can grasp the safety status of the intelligent automobile in detail, and promptly alarm and collect evidence, thereby further improving the anti-theft performance of the automobile; the specific analysis process of the impact detection and analysis module is as follows:

[0039] A number of detection points are set on the body of the corresponding smart car, and the corresponding detection points are marked as i, i={1,2,…,n}, n represents the number of detection points and n is a natural number greater than 1; the pressure sensor arranged at the detection point i is used to collect the impact force received by it and mark it as an impulse value, and an impulse set is established by a number of groups of impulse values ​​of the detection point i in a unit time, and the impulse set is summed and averaged to obtain the impact average value, and the subset with the largest value in the impulse set is marked as the instantaneous impulse amplitude; the impact average value CPi and the instantaneous impulse amplitude SPi are numerically calculated by the formula CBi=bp1*CPi+bp2*SPi to obtain the impulse performance value CBi, wherein bp1 and bp2 are preset weight coefficients, and bp1>bp2>0;

[0040] Moreover, the numerical value of the impulse performance value CBi is positively proportional to the impact average value CPi and the instantaneous impulse amplitude SPi. The larger the numerical value of the impulse performance value CBi, the greater the impact degree of the corresponding detection point i. The impulse performance value CBi of the corresponding detection point i is numerically compared with the preset performance threshold. If the impulse performance value CBi exceeds the preset performance threshold, it indicates that the corresponding detection point i is seriously impacted, and the corresponding detection point i is marked as a hit point. If there is a hit point on the body of the corresponding smart car, it indicates that the corresponding smart car is more likely to be stolen by knocking, and a hit warning signal is generated. If there is no hit point on the body of the corresponding smart car at the detection moment, it indicates that the corresponding smart car is less likely to be stolen by knocking, and a body safety signal is generated.

[0041] The real-time scanning monitoring module is also used to collect real-time monitoring images of the unlocking area when unlocking the corresponding smart car, and generate an identity authentication signal or an identity authentication failure signal through facial recognition analysis, and send the identity authentication signal or the identity authentication failure signal to the Internet of Vehicles platform, and the Internet of Vehicles platform sends the identity authentication failure signal and the corresponding real-time monitoring image to the user terminal; the user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" to the Internet of Vehicles platform based on the real-time monitoring image. When the Internet of Vehicles platform receives the "allow unlocking and starting" instruction, it allows it to unlock and start the corresponding smart car when the car key matches. When the Internet of Vehicles platform receives the "do not allow unlocking and starting" instruction, it does not allow it to unlock and start the corresponding smart car when the car key matches, and controls the buzzer warning module of the corresponding smart car to emit a warning sound, which helps prevent the car from being stolen and further improves the car's anti-theft performance and safety performance; the specific analysis process of facial recognition analysis is as follows:

[0042] Real-time monitoring images of the corresponding smart car unlocking area are collected, all facial images are extracted from the real-time images, and the facial images of the corresponding persons are marked as analysis images p, where p={1,2,…,k}, k represents the number of extracted facial images and m is a natural number greater than or equal to 1; the corresponding analysis images p are compared one by one with the images in the facial image database of the corresponding smart car to obtain several groups of facial overlap data, and the facial overlap data are numerically compared with the preset facial overlap data threshold. If there is facial overlap data exceeding the preset facial overlap data threshold, the corresponding analysis image u is marked as an overlap image; if there is no facial overlap data exceeding the preset facial overlap data threshold, the corresponding analysis image p is marked as an irrelevant image; the person corresponding to the overlap image is marked as a consistency object, and if there is a consistency object in the corresponding smart car unlocking area, an identity authentication qualified signal is generated; if there is no consistency object in the corresponding smart car unlocking area, an identity authentication unqualified signal is generated.

[0043] During the operation of the corresponding smart car, the real-time operation detection and analysis module will evaluate the forward risk of the corresponding smart car, determine its speed range based on this, and send the speed range to the vehicle terminal of the corresponding smart car through the Internet of Vehicles platform; and obtain the current actual speed of the corresponding smart car, compare the current actual speed with the corresponding speed range, if the current actual speed is not within the corresponding speed range, send a speed warning signal to the vehicle terminal of the corresponding smart car through the Internet of Vehicles platform, so that the driver can adjust the speed in time to ensure the forward safety; the specific evaluation process of evaluating the forward risk of the corresponding smart car is as follows:

[0044] The environmental visibility and environmental wind speed of the road section ahead of the corresponding smart car are collected. It should be noted that the smaller the value of the environmental visibility and the larger the value of the environmental wind speed, the greater the risk of moving forward, and the more cautious and slow the corresponding smart car needs to move forward; the environmental visibility and environmental wind speed are numerically compared with the preset environmental visibility threshold and the preset environmental wind speed threshold, respectively. If the environmental visibility does not exceed the preset environmental visibility threshold or the environmental wind speed exceeds the preset environmental wind speed threshold, indicating that the environmental risk level is large, a first-level impact signal is generated; if the environmental visibility exceeds the preset environmental visibility threshold and the environmental wind speed does not exceed the preset environmental wind speed threshold, the average traffic flow and accident frequency of the road section ahead of the corresponding smart car are collected, and the average traffic flow HT and the accident frequency HD are numerically calculated by the formula LX=vy1*HT+vy2*HD to obtain the road analysis value LX;

[0045] Among them, vy1 and vy2 are preset weight coefficients, and the values ​​of vy1 and vy2 are both greater than zero; and the numerical value of the road analysis value LX is positively proportional to the average traffic volume HT and the accident frequency HD. The larger the numerical value of the road analysis value LX is, the more cautious the driver needs to be. The road analysis value LX is numerically compared with the preset road analysis value range; if the road analysis value LX exceeds the maximum value of the preset road analysis value range, it indicates that the risk level of the road ahead is relatively high, and a first-level impact signal is generated;

[0046] If the road analysis value LX is within the preset forward influence range, indicating that the degree of forward risk is general, a secondary influence signal is generated; if the road analysis value LX does not exceed the minimum value of the preset forward influence range, indicating that the degree of forward risk is small, a tertiary influence signal is generated; if a first-level influence signal is generated, a first-level vehicle speed range is assigned to it; if a second-level influence signal is generated, a second-level vehicle speed range is assigned to it; if a third-level influence signal is generated, a third-level vehicle speed range is assigned to it, and the third-level vehicle speed range > the second-level vehicle speed range > the first-level vehicle speed range.

[0047] Embodiment 3: The difference between this embodiment and Embodiment 1 and Embodiment 2 is that the real-time operation detection and analysis module performs a control performance analysis on the corresponding smart car when the vehicle speed warning signal is not generated, and generates a control performance qualified signal or a control performance unqualified signal accordingly, and sends the control performance unqualified signal to the vehicle terminal of the corresponding smart car via the Internet of Vehicles platform, so that the driver can conduct timely investigation and perform corresponding control operations as needed, thereby helping to ensure the safe driving of the corresponding smart car; the specific analysis process of the control performance analysis is as follows:

[0048] The instantaneous swing amplitude and instantaneous swing frequency of the corresponding smart car are collected. It should be noted that the larger the values ​​of the instantaneous swing amplitude and the instantaneous swing frequency are, the worse the operating condition of the corresponding smart car is and the greater the operating risk is; the instantaneous swing amplitude and the instantaneous swing frequency are numerically compared with the preset instantaneous swing amplitude threshold and the preset instantaneous swing frequency threshold respectively. If the instantaneous swing amplitude or the instantaneous swing frequency exceeds the corresponding preset threshold, it indicates that the operating condition of the corresponding smart car is poor, and a control performance unqualified signal is generated; if the instantaneous swing amplitude or the instantaneous swing frequency does not exceed the corresponding preset threshold, the difference between two groups of instantaneous swing amplitudes at adjacent moments is calculated to obtain instantaneous amplitude difference data, and the variance of several groups of instantaneous amplitude difference data in unit time is calculated to obtain instantaneous amplitude data, and the instantaneous frequency data is obtained in the same way;

[0049] The instantaneous amplitude data and the instantaneous frequency data are numerically compared with the preset instantaneous amplitude data threshold and the preset instantaneous data threshold, respectively. If the instantaneous amplitude data or the instantaneous frequency data exceeds the corresponding preset threshold, it indicates that the stability of the swing condition is poor, and a control performance unqualified signal is generated; if the instantaneous amplitude data or the instantaneous frequency data does not exceed the corresponding preset threshold, it indicates that the stability of the swing condition is good, then the temperature, humidity and dust concentration in the cab are collected, and the temperature and the preset control suitable temperature value are numerically calculated to obtain the temperature meter data, and the wet meter data is obtained in the same way; the temperature meter data QW, the wet meter data PW and the dust concentration FW are numerically calculated by the formula CX=a1*QW+a2*PW+a3*FW to obtain the control influence value CX;

[0050] Among them, a1, a2, and a3 are preset weight coefficients, and the values ​​of a1, a2, and a3 are all greater than zero; and the numerical value of the control influence value CX is directly proportional to the temperature meter data QW, the humidity meter data PW, and the dust concentration FW. The larger the numerical value of the control influence value CX, the greater the influence of the current cab environment on the driver's control, the more unfavorable it is for the driver's safe driving, and the more timely the cab environment needs to be adjusted; the control influence value CX is numerically compared with the preset control influence threshold. If the control influence value CX exceeds the preset control influence threshold, a control performance unqualified signal is generated; if the control influence value CX does not exceed the preset control influence threshold, a control performance qualified signal is generated.

[0051] The working principle of the present invention is as follows: when in use, the body of the corresponding smart car is subjected to impact detection and analysis through the impact detection and analysis module, and an impact warning signal or a body safety signal is generated accordingly. After the impact warning signal is generated, the buzzer warning module of the corresponding smart car is controlled to emit a warning sound, and the real-time monitoring image of the corresponding impact point is collected through the real-time scanning monitoring module, and the impact warning signal of the corresponding smart car and the corresponding real-time monitoring image are sent to the corresponding user terminal, so that the corresponding user can grasp the safety status of the smart car in detail, and make an alarm and collect evidence in time, thereby improving the anti-theft performance of the car; and when unlocking the corresponding smart car, the real-time monitoring image of the unlocking area is collected through the real-time scanning monitoring module, and a qualified identity authentication signal or an identity authentication signal is generated through facial recognition analysis. When the identity verification failure signal is generated, the user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" to the Internet of Vehicles platform based on the real-time monitoring image, which helps prevent the car from being stolen and further improves the car's anti-theft and safety performance; during the operation of the corresponding smart car, the real-time operation detection and analysis module will evaluate the forward risk of the corresponding smart car, and determine its speed range based on this. The speed range will be sent to the corresponding smart car's on-board terminal via the Internet of Vehicles platform, and it will be determined whether the current actual speed is within the corresponding speed range. If the current actual speed is not within the corresponding speed range, a speed warning signal will be sent to the on-board terminal of the corresponding smart car, so that the driver can adjust the speed in time to ensure the safety of moving forward.

[0052] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A smart car information processing method based on Internet of Vehicles technology, characterized in that: The following steps are involved: Step 1: Performing impact detection and analysis on the body of the corresponding smart car, thereby generating an impact warning signal or a body safety signal; After generating the strike warning signal, the buzzer warning module of the corresponding smart car is controlled to emit a warning sound, and the real-time monitoring image of the corresponding strike point is collected, and the strike warning signal of the corresponding smart car and the corresponding real-time monitoring image are sent to the corresponding user terminal; Step 2: When unlocking the corresponding smart car, a real-time monitoring image of the unlocking area is collected, and a facial recognition analysis is performed to generate an identity authentication pass signal or an identity authentication fail signal. The user terminal sends an instruction of "allow unlocking and starting" or "do not allow unlocking and starting" based on the real-time monitoring image; Step 3: If the "unlock and start allowed" command is received, the corresponding smart car is allowed to be unlocked and started when the car key is matched; if the "unlock and start not allowed" command is received, the corresponding smart car is not allowed to be unlocked and started when the car key is matched, and the buzzer warning module of the corresponding smart car is controlled to emit a warning sound; Step 4: During the operation of the corresponding smart car, the forward risk of the corresponding smart car is evaluated to determine its speed range, and whether the actual speed of the corresponding smart car meets the requirements is judged, so that the driver can adjust the speed in time; The intelligent automobile information processing system based on the Internet of Vehicles technology includes an Internet of Vehicles platform, an impact detection and analysis module, a real-time scanning monitoring module, a real-time operation detection and analysis module, and a buzzer warning module; the impact detection and analysis module is used to perform impact detection and analysis on the body of the corresponding intelligent automobile, thereby generating an impact warning signal or a body safety signal, and sending the impact warning signal or the body safety signal to the Internet of Vehicles platform. After receiving the impact warning signal, the Internet of Vehicles platform controls the buzzer warning module of the corresponding intelligent automobile to emit a warning sound; After the strike warning signal is generated, the real-time scanning monitoring module collects the real-time monitoring image of the corresponding strike point, and sends the real-time monitoring image to the Internet of Vehicles platform, and the Internet of Vehicles platform sends the strike warning signal of the corresponding smart car and the corresponding real-time monitoring image to the corresponding user terminal; The real-time scanning monitoring module is also used to collect real-time monitoring images of the unlocking area when unlocking the corresponding smart car, and generate an identity authentication signal or an identity authentication failure signal through facial recognition analysis, and send the identity authentication signal or the identity authentication failure signal to the car networking platform, and the car networking platform sends the identity authentication failure signal and the corresponding real-time monitoring image to the user terminal; the user terminal sends an "allow unlocking and starting" or "do not allow unlocking and starting" instruction to the car networking platform based on the real-time monitoring image, and when the car networking platform receives the "allow unlocking and starting" instruction, it allows it to unlock and start the corresponding smart car when the car key is matched, and when the car networking platform receives the "do not allow unlocking and starting" instruction, it does not allow it to unlock and start the corresponding smart car when the car key is matched, and controls the buzzer warning module of the corresponding smart car to emit a warning sound; During the operation of the corresponding smart car, the real-time operation detection and analysis module will evaluate the forward risk of the corresponding smart car, determine its speed range accordingly, and send the speed range to the vehicle-mounted terminal of the corresponding smart car via the Internet of Vehicles platform; and obtain the current actual speed of the corresponding smart car, compare the current actual speed with the corresponding speed range, and if the current actual speed is not within the corresponding speed range, send a speed warning signal to the vehicle-mounted terminal of the corresponding smart car via the Internet of Vehicles platform, so that the driver can adjust the speed in time; when the speed warning signal is not generated, the control performance of the corresponding smart car will be analyzed, and a control performance qualified signal or a control performance unqualified signal will be generated accordingly, and the control performance unqualified signal will be sent to the vehicle-mounted terminal of the corresponding smart car via the Internet of Vehicles platform; The specific analysis process of facial recognition analysis is as follows: Collect real-time monitoring images of the corresponding smart car unlocking area, extract all facial images from the real-time images, mark the facial images of the corresponding persons as analysis images p, p={1,2,…,k}, k represents the number of extracted facial images and k is a natural number greater than or equal to 1; compare the corresponding analysis images p with the images in the facial image database of the corresponding smart car one by one to obtain several groups of facial overlap data, compare the facial overlap data with the preset facial overlap data threshold, if there is facial overlap data exceeding the preset facial overlap data threshold, mark the corresponding analysis image p as an overlap image; if there is no facial overlap data exceeding the preset facial overlap data threshold, mark the corresponding analysis image p as an irrelevant image; mark the person corresponding to the overlap image as a consistency object, and generate a qualified identity authentication signal if there is a consistency object in the corresponding smart car unlocking area; If there is no consistent object in the corresponding smart car unlocking area, an identity authentication failure signal is generated; The specific analysis process of the hit detection analysis module includes: A number of detection points are set on the body of the corresponding smart car, and the corresponding detection points are marked as i, i={1,2,…,n}, n represents the number of detection points and n is a natural number greater than 1; the pressure sensor arranged at the detection point i is used to collect the impact force received by it and mark it as an impact value, and an impact set is established by a number of groups of impact values ​​of the detection point i in a unit time, and the impact set is summed and averaged to obtain the impact average value, and the subset with the largest value in the impact set is marked as the instantaneous impact amplitude; The impact average value and the instantaneous impulse amplitude are numerically calculated to obtain an impulse performance value, and the impulse performance value is numerically compared with a preset performance threshold; if the impulse performance value exceeds the preset performance threshold, the corresponding detection point i is marked as a hit point; if there is a hit point on the body of the corresponding smart car, a hit warning signal is generated; if there is no hit point on the body of the corresponding smart car at the detection moment, a body safety signal is generated; The specific evaluation process for evaluating the forward risk of the corresponding smart car is as follows: The environmental visibility and environmental wind speed of the road section ahead of the corresponding smart car are collected, and the environmental visibility and environmental wind speed are numerically compared with the preset environmental visibility threshold and the preset environmental wind speed threshold respectively; if the environmental visibility does not exceed the preset environmental visibility threshold or the environmental wind speed exceeds the preset environmental wind speed threshold, a first-level impact signal is generated; if the environmental visibility exceeds the preset environmental visibility threshold and the environmental wind speed does not exceed the preset environmental wind speed threshold, the average traffic flow and accident frequency of the road section ahead of the corresponding smart car are collected, the average traffic flow and the accident frequency are numerically calculated to obtain a road analysis value, and the road analysis value is numerically compared with the preset road analysis value range; If the road analysis value exceeds the maximum value of the preset road analysis value range, a first-level influence signal is generated; if the road analysis value is within the preset forward influence range, a second-level influence signal is generated; if the road analysis value does not exceed the minimum value of the preset forward influence range, a third-level influence signal is generated; if a first-level influence signal is generated, a first-level vehicle speed range is allocated to it; if a second-level influence signal is generated, a second-level vehicle speed range is allocated to it; if a third-level influence signal is generated, a third-level vehicle speed range is allocated to it, and the third-level vehicle speed range>the second-level vehicle speed range>the first-level vehicle speed range; The specific analysis process of control performance analysis is as follows: The instantaneous swing amplitude and instantaneous swing frequency of the corresponding smart car are collected, and the instantaneous swing amplitude and the instantaneous swing frequency are numerically compared with the preset instantaneous swing amplitude threshold and the preset instantaneous swing frequency threshold respectively. If the instantaneous swing amplitude or the instantaneous swing frequency exceeds the corresponding preset threshold, a control performance unqualified signal is generated; if the instantaneous swing amplitude or the instantaneous swing frequency does not exceed the corresponding preset threshold, the difference between two groups of instantaneous swing amplitudes at adjacent moments is calculated to obtain instantaneous amplitude difference data, and the variance of several groups of instantaneous amplitude difference data within a unit time is calculated to obtain instantaneous amplitude data, and the instantaneous frequency data is obtained in the same way; The instantaneous amplitude data and instantaneous frequency data are numerically compared with the preset instantaneous amplitude data threshold and the preset instantaneous data threshold respectively. If the instantaneous amplitude data or the instantaneous frequency data exceeds the corresponding preset threshold, an unqualified control performance signal is generated; if neither the instantaneous amplitude data nor the instantaneous frequency data exceeds the corresponding preset threshold, the temperature, humidity and dust concentration in the cab are collected, and the temperature and the preset suitable control temperature value are numerically calculated to obtain the temperature meter data, and the humidity meter data is obtained similarly; the temperature meter data, humidity meter data and dust concentration are numerically calculated to obtain the control influence value, and the control influence value is numerically compared with the preset control influence threshold. If the control influence value exceeds the preset control influence threshold, an unqualified control performance signal is generated; if the control influence value does not exceed the preset control influence threshold, a qualified control performance signal is generated.

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