CN112530167A - Control system of vehicle-mounted screen panel based on cloud platform - Google Patents
Control system of vehicle-mounted screen panel based on cloud platform Download PDFInfo
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Abstract
The invention discloses a control system of a vehicle-mounted screen panel based on a cloud platform, which relates to the technical field of control of the vehicle-mounted screen panel and solves the technical problem that the safety performance of a vehicle is reduced because a driver cannot be authenticated in the prior art, the identity of a user is verified by analyzing real-time verification information through an identity verification unit, a coefficient ratio is obtained by dividing the verification coefficient of voice to be verified and the verification coefficient of the voice to be verified, if beta is larger than or equal to 1, the voice verification is successful, if beta is larger than or equal to 1, the voice verification is failed, then a real-time login gesture is compared with a corresponding verification gesture in data, and when the two are consistent, an identity verification success signal is generated, otherwise, an identity verification failure signal is generated; the driver is authenticated, and whether the information in the driver and the information in the database are consistent or not is inquired, so that the safety of the vehicle is improved, and the intelligent performance of the system is enhanced.
Description
Technical Field
The invention relates to the technical field of control of vehicle-mounted screen panels, in particular to a control system of a vehicle-mounted screen panel based on a cloud platform.
Background
With the development of the technology, the vehicle technology is continuously perfected, and the accompanying vehicle-mounted screens are more and more. At present, on the basis of an original instrument screen and a central control screen, a copilot screen and a rear row screen are added to a vehicle-mounted screen. At present, most of vehicle-mounted screens are touch screens, namely, the control of the screens is realized through touch operation, so that information interaction of different screens is realized, and an intelligent vehicle-mounted terminal (also called a satellite positioning intelligent vehicle-mounted terminal) integrates a GPS technology, a mileage positioning technology and an automobile black box technology, and can be used for modern management of transport vehicles, and comprises the following steps: traffic safety monitoring management, operation management, service quality management, intelligent centralized scheduling management, electronic stop board control management and the like.
However, in the prior art, the control system of the vehicle-mounted screen cannot authenticate the identity of the driver, which results in the reduction of the safety performance of the vehicle, and meanwhile, cannot analyze the trip of the driver, which results in the increase of the accident rate of the driver in the severe environment.
Disclosure of Invention
The invention aims to provide a control system of a vehicle-mounted screen panel based on a cloud platform, which analyzes real-time verification information through an identity verification unit so as to verify the identity of a user, obtains real-time login information recorded by the user through the vehicle-mounted screen panel, extracts real-time verification voice in the real-time login information, marks the real-time verification voice as the voice to be verified, obtains the sound pressure and the audio frequency of the voice to be verified, obtains a verification coefficient DY of the voice to be verified through a formula, obtains verification voice in verification information in a database, obtains the sound pressure and the audio frequency of the verification voice, obtains a verification coefficient DYi of the verification voice through the formula, obtains a coefficient ratio of the verification coefficient DY of the voice to be verified and the verification coefficient DYi of the verification voice through division operation, namely, if beta is more than or equal to 1, the voice verification is judged to be successful, if beta is more than 0 and less than, judging that the voice verification fails, generating a verification failure signal and sending the verification failure signal to a mobile phone terminal of a user; acquiring a real-time login gesture through a vehicle-mounted screen face, then comparing the real-time login gesture with a corresponding verification gesture in data, generating an identity verification success signal when the real-time login gesture is consistent with the verification gesture in the data, and generating an identity verification failure signal when the real-time login gesture is inconsistent with the verification gesture in the data; the driver is authenticated, and whether the information in the driver and the information in the database are consistent or not is inquired, so that the safety of the vehicle is improved, and the intelligent performance of the system is enhanced.
The purpose of the invention can be realized by the following technical scheme:
a control system of a vehicle-mounted screen panel based on a cloud platform comprises a registration login unit, a database, a cloud control platform, an identity verification unit, a vehicle condition detection unit, a road condition analysis unit and a driving analysis unit;
the identity authentication unit is used for analyzing the real-time authentication information so as to authenticate the identity of the user, and the specific analysis and authentication process is as follows:
the method comprises the steps of firstly, acquiring real-time login information recorded by a user through a vehicle-mounted screen panel, extracting real-time verification voice in the real-time login information, marking the real-time verification voice as voice to be verified, acquiring sound pressure and audio frequency of the voice to be verified, marking the sound pressure and the audio frequency of the voice to be verified as YY and YP respectively, and then acquiring verification coefficients DY of the voice to be verified through a formula, wherein a1 and a2 are proportional coefficients;
step two, acquiring verification voice in verification information in a database, marking the verification information of the database as i, i =1, 2, … …, n, n is a positive integer, acquiring the sound pressure and the audio frequency of the verification voice, respectively marking the sound pressure and the audio frequency of the verification voice as YYi and YPi, and then acquiring a verification coefficient DYi of the verification voice through a formula, wherein a3 and a4 are proportional coefficients;
step three, obtaining a coefficient ratio of a verification coefficient DY of the voice to be verified and a verification coefficient DYi of the verified voice through division operation, namely judging that the voice verification is successful if beta is larger than or equal to 1, entering step four, judging that the voice verification is failed if beta is larger than 0 and smaller than 1, generating a verification failure signal and sending the verification failure signal to a mobile phone terminal of a user;
and step four, acquiring a real-time login gesture through the vehicle-mounted screen face, then comparing the real-time login gesture with a corresponding verification gesture in the data, generating an identity verification success signal when the real-time login gesture is consistent with the verification gesture in the data, entering step five, and generating an identity verification failure signal when the real-time login gesture is inconsistent with the verification gesture in the data.
Further, the vehicle condition detection unit is configured to analyze vehicle condition information to perform safety detection on a vehicle condition, where the vehicle condition information is duration data, frequency data, and frequency data, the duration data is an interval duration between a current use time of the vehicle and a last maintenance time, the frequency data is a failure occurrence frequency of the vehicle within a specified maintenance time, and the frequency data is a ratio between a number of times that the vehicle has a failure and a total number of times that the vehicle has traveled, and a specific analysis and detection process is as follows:
step S1: acquiring the interval duration of the current service time and the last maintenance time of the vehicle, and marking the interval duration of the current service time and the last maintenance time of the vehicle as JG;
step S2: acquiring the fault occurrence frequency of the vehicle in the specified maintenance time, and marking the fault occurrence frequency of the vehicle in the specified maintenance time as PL;
step S3: acquiring the ratio of the number of times of vehicle failure to the total number of times of vehicle trip, and marking the ratio of the number of times of vehicle failure to the total number of times of vehicle trip as BZ;
step S4: obtaining a vehicle condition detection coefficient CK through a formula, wherein b1, b2 and b3 are proportional coefficients, b1 is greater than b2 and is greater than b3 and is greater than 0, and alpha is an error correction factor and is 2.0321546;
step S5: comparing the vehicle condition detection coefficient CK with a vehicle condition detection coefficient threshold value:
if the vehicle condition detection coefficient CK is larger than or equal to the vehicle condition detection coefficient threshold value, judging that the vehicle condition detection coefficient is high, generating a vehicle condition normal signal, and sending the vehicle condition normal signal to a mobile phone terminal of a user;
and if the vehicle condition detection coefficient CK is smaller than the vehicle condition detection coefficient threshold value, judging that the vehicle condition detection coefficient is low, generating a vehicle condition abnormal signal, and sending the vehicle condition abnormal signal to a mobile phone terminal of a user.
Further, the traffic analysis unit is configured to analyze traffic information, so as to perform a safety reminding measure for a driver, where the traffic information includes traffic data, vehicle speed data, and quantity data, the traffic data is a sum of a total quantity of road vehicles and a quantity of vehicles added per hour, the vehicle speed data is an average driving speed of the vehicles on the road, the quantity data is a sum of a quantity of traffic lights on the road and a quantity of pits on the ground, the safety reminding measure is a voice reminding for reducing the vehicle speed and a voice reminding for suggesting a replacement route, and a specific analysis process is as follows:
step SS 1: acquiring the sum of the total number of the road vehicles and the number of the vehicles increased per hour, and marking the sum of the total number of the road vehicles and the number of the vehicles increased per hour as CSL;
step SS 2: acquiring the average running speed of the vehicles on the road, and marking the average running speed of the vehicles on the road as SDV;
step SS 3: acquiring the sum of the number of traffic lights on the road and the number of ground pits, and marking the sum of the number of traffic lights on the road and the number of ground pits as SLH;
step SS 4: acquiring a road condition analysis coefficient LK through a formula, wherein c1, c2 and c3 are proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step SS 5: comparing the road condition analysis coefficient LK with L1 and L2 respectively, wherein L1 and L2 are road condition analysis coefficient threshold values, and L1 is greater than L2:
if the road condition analysis coefficient LK is larger than or equal to L1, judging that the road condition is good, and not taking safety reminding measures for the driver;
if the road condition analysis coefficient L2 is more than LK and less than L1, the road condition is judged to be general, and the speed reduction voice prompt is carried out on the driver;
and if the road condition analysis coefficient LK is less than or equal to L2, judging that the road condition is bad, and carrying out voice prompt for suggesting a route to be changed on the driver.
Further, the driving analysis unit is configured to analyze environmental data, so as to perform safety determination on driving trips of a user, where the environmental data are temperature data, visibility data, and rainfall data, the temperature data is a difference between a morning ground temperature and a morning ground temperature, the visibility data is a sum of a farthest distance visible on a road at night and a farthest distance visible on a road at daytime, and the rainfall data is a ratio of a maximum rainfall all day to a maximum drainage all day of a road drainage device, and a specific analysis determination process is as follows:
step K1: acquiring a difference value between the morning ground temperature and the morning ground temperature, and marking the difference value between the morning ground temperature and the morning ground temperature as CZW;
step K2: acquiring the sum of the farthest distance visible on the night road and the farthest distance visible on the daytime road, and marking the sum of the farthest distance visible on the night road and the farthest distance visible on the daytime road as NJD;
step K3: acquiring the ratio of the maximum rainfall of the whole day to the maximum displacement of the road drainage equipment in the whole day, and marking the ratio of the maximum rainfall of the whole day to the maximum displacement of the road drainage equipment in the whole day as PBZ;
step K4: obtaining an environmental safety factor CX through a formula, wherein v1, v2 and v3 are all proportionality coefficients, and v1 is more than v2 is more than v3 is more than 0;
step K5: acquiring the driving year of a driver and the year of a driver license, respectively marking the driving year of the driver and the year of the driver license as JNX and ZNX, and acquiring a driving coefficient JS (namely the driving coefficient JS by comparing the driving year with the year of the driver license;
step K6: and calculating a ratio of the environmental safety factor CX and the driving coefficient JS to obtain a proper travel coefficient AQ, namely, if the AQ is not less than 1, determining that the driver forbids travel, generating a travel forbidding signal and sending the travel forbidding signal to the cloud control platform, and if the AQ is less than 1, determining that the driver proposes travel, generating a proposed travel signal and sending the proposed travel signal to the cloud control platform.
Further, the registration login unit is used for submitting user information through a mobile phone terminal for registration by a user, sending the user information which is successfully registered to a database for storage, wherein the user information comprises the name, age, sex and mobile phone number for authenticating the real name of the user, after the user is successfully registered, the cloud control platform generates a verification information input signal and sends the verification information input signal to the mobile phone terminal of the user, after the user receives the verification information input signal, the verification information is input and added with a name tag, and then the verification information and the corresponding name tag are sent to the database for storage, wherein the verification information comprises verification voice and verification gestures.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, the real-time verification information is analyzed by the identity verification unit, so as to verify the identity of the user and obtain the real-time login information input by the user through the vehicle-mounted screen panel, extracting real-time verification voice in the real-time login information, marking the real-time verification voice as the voice to be verified, acquiring the sound pressure and the audio frequency of the voice to be verified, acquiring the verification coefficient DY of the voice to be verified through a formula, acquiring the verification voice in the verification information in a database, acquiring the sound pressure and the audio frequency of the verification voice, acquiring the verification coefficient DYi of the verification voice through a formula, acquiring a coefficient ratio of the verification coefficient DY of the voice to be verified and the verification coefficient DYi of the verification voice through division operation, if beta is larger than or equal to 1, the voice verification is judged to be successful, if beta is larger than 0 and smaller than 1, the voice verification is judged to be failed, a verification failure signal is generated, and the verification failure signal is sent to the mobile phone terminal of the user; acquiring a real-time login gesture through a vehicle-mounted screen face, then comparing the real-time login gesture with a corresponding verification gesture in data, generating an identity verification success signal when the real-time login gesture is consistent with the verification gesture in the data, and generating an identity verification failure signal when the real-time login gesture is inconsistent with the verification gesture in the data; the driver is authenticated, and whether the information in the driver and the database is consistent or not is inquired, so that the safety of the vehicle is improved, and the intelligent performance of the system is enhanced;
2. according to the method, a driving analysis unit is used for analyzing environmental data, so that driving travel of a user is judged safely, the environmental data are obtained, an environmental safety coefficient CX is obtained through a formula, the driving year of a driver and the year of a driving license are obtained, and a driving coefficient JS is obtained through comparison of the driving year and the year of the driving license; calculating a ratio of the environmental safety coefficient CX and the driving coefficient JS to obtain a proper travel coefficient AQ, namely if AQ is more than or equal to 1, determining that the driver forbids travel, generating a travel forbidding signal and sending the travel forbidding signal to the cloud control platform, and if AQ is less than 1, determining that the driver suggests travel, generating a suggested travel signal and sending the suggested travel signal to the cloud control platform; the driving years of the driver are calculated, so that the traveling analysis is performed for the driver aiming at severe weather, the accident rate of the driver is reduced, and the driving safety is improved, so that the safety performance of the system is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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 derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a control system of a cloud platform-based vehicle-mounted screen panel includes a registration unit, a database, a cloud control platform, an identity verification unit, a vehicle condition detection unit, a road condition analysis unit, and a driving analysis unit;
the system comprises a registration login unit, a database and a cloud control platform, wherein the registration login unit is used for submitting user information through a mobile phone terminal for registration and sending the user information which is successfully registered to the database for storage, the user information comprises the name, age, sex and the mobile phone number for authenticating the real name of a user, after the user registration is successful, the cloud control platform generates a verification information input signal and sends the verification information input signal to the mobile phone terminal of the user, after the user receives the verification information input signal, the verification information is input and added with a name tag, and then the verification information and the corresponding name tag are sent to the database for storage together, and the verification information comprises verification voice and verification gestures;
the identity authentication unit is used for analyzing the real-time authentication information so as to authenticate the identity of the user, and the specific analysis and authentication process is as follows:
the method comprises the steps of firstly, acquiring real-time login information recorded by a user through a vehicle-mounted screen panel, extracting real-time verification voice in the real-time login information, marking the real-time verification voice as voice to be verified, acquiring sound pressure and audio frequency of the voice to be verified, marking the sound pressure and the audio frequency of the voice to be verified as YY and YP respectively, and then acquiring verification coefficients DY of the voice to be verified through a formula, wherein a1 and a2 are proportional coefficients;
step two, acquiring verification voice in verification information in a database, marking the verification information of the database as i, i =1, 2, … …, n, n is a positive integer, acquiring the sound pressure and the audio frequency of the verification voice, respectively marking the sound pressure and the audio frequency of the verification voice as YYi and YPi, and then acquiring a verification coefficient DYi of the verification voice through a formula, wherein a3 and a4 are proportional coefficients;
step three, obtaining a coefficient ratio of a verification coefficient DY of the voice to be verified and a verification coefficient DYi of the verified voice through division operation, namely judging that the voice verification is successful if beta is larger than or equal to 1, entering step four, judging that the voice verification is failed if beta is larger than 0 and smaller than 1, generating a verification failure signal and sending the verification failure signal to a mobile phone terminal of a user;
step four, acquiring a real-time login gesture through the vehicle-mounted screen face, then comparing the real-time login gesture with a corresponding verification gesture in the data, generating an identity verification success signal when the real-time login gesture is consistent with the verification gesture in the data, entering step five, and generating an identity verification failure signal when the real-time login gesture is inconsistent with the verification gesture in the data;
the vehicle condition detection unit is used for analyzing vehicle condition information to perform safety detection on the vehicle condition, the vehicle condition information is duration data, frequency data and frequency data, the duration data is interval duration between current use time and last maintenance time of a vehicle, the frequency data is fault occurrence frequency of the vehicle within specified maintenance time, the frequency data is a ratio of the number of times of fault occurrence of the vehicle to the total number of times of trip of the vehicle, and the specific analysis and detection process is as follows:
step S1: acquiring the interval duration of the current service time and the last maintenance time of the vehicle, and marking the interval duration of the current service time and the last maintenance time of the vehicle as JG;
step S2: acquiring the fault occurrence frequency of the vehicle in the specified maintenance time, and marking the fault occurrence frequency of the vehicle in the specified maintenance time as PL;
step S3: acquiring the ratio of the number of times of vehicle failure to the total number of times of vehicle trip, and marking the ratio of the number of times of vehicle failure to the total number of times of vehicle trip as BZ;
step S4: obtaining a vehicle condition detection coefficient CK through a formula, wherein b1, b2 and b3 are proportional coefficients, b1 is greater than b2 and is greater than b3 and is greater than 0, and alpha is an error correction factor and is 2.0321546;
step S5: comparing the vehicle condition detection coefficient CK with a vehicle condition detection coefficient threshold value:
if the vehicle condition detection coefficient CK is larger than or equal to the vehicle condition detection coefficient threshold value, judging that the vehicle condition detection coefficient is high, generating a vehicle condition normal signal, and sending the vehicle condition normal signal to a mobile phone terminal of a user;
if the vehicle condition detection coefficient CK is smaller than the vehicle condition detection coefficient threshold value, judging that the vehicle condition detection coefficient is low, generating a vehicle condition abnormal signal, and sending the vehicle condition abnormal signal to a mobile phone terminal of a user;
the road condition analysis unit is used for analyzing road condition information so as to carry out safety reminding measures on a driver, the road condition information comprises traffic flow data, speed data and quantity data, the traffic flow data is the sum of the total quantity of road vehicles and the quantity of vehicles increased per hour, the speed data is the average driving speed of the vehicles on the road, the quantity data is the sum of the quantity of traffic lights on the road and the quantity of pits on the ground, the safety reminding measures are voice reminding for reducing the speed of the vehicle and voice reminding for suggesting a replacement route, and the specific analysis process is as follows:
step SS 1: acquiring the sum of the total number of the road vehicles and the number of the vehicles increased per hour, and marking the sum of the total number of the road vehicles and the number of the vehicles increased per hour as CSL;
step SS 2: acquiring the average running speed of the vehicles on the road, and marking the average running speed of the vehicles on the road as SDV;
step SS 3: acquiring the sum of the number of traffic lights on the road and the number of ground pits, and marking the sum of the number of traffic lights on the road and the number of ground pits as SLH;
step SS 4: acquiring a road condition analysis coefficient LK through a formula, wherein c1, c2 and c3 are proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step SS 5: comparing the road condition analysis coefficient LK with L1 and L2 respectively, wherein L1 and L2 are road condition analysis coefficient threshold values, and L1 is greater than L2:
if the road condition analysis coefficient LK is larger than or equal to L1, judging that the road condition is good, and not taking safety reminding measures for the driver;
if the road condition analysis coefficient L2 is more than LK and less than L1, the road condition is judged to be general, and the speed reduction voice prompt is carried out on the driver;
if the road condition analysis coefficient LK is less than or equal to L2, judging that the road condition is bad, and carrying out voice prompt on the recommended replacement route for the driver;
the driving analysis unit is used for analyzing environmental data so as to perform safety judgment on driving travel of a user, the environmental data are temperature data, visibility data and rainfall data, the temperature data are difference values of the ground temperature in the morning and the ground temperature in the morning, the visibility data are sum of the farthest distance visible on a road at night and the farthest distance visible on a road in the daytime, the rainfall data are ratio of the maximum rainfall and the maximum drainage of the road drainage equipment all day, and the specific analysis and judgment process is as follows:
step K1: acquiring a difference value between the morning ground temperature and the morning ground temperature, and marking the difference value between the morning ground temperature and the morning ground temperature as CZW;
step K2: acquiring the sum of the farthest distance visible on the night road and the farthest distance visible on the daytime road, and marking the sum of the farthest distance visible on the night road and the farthest distance visible on the daytime road as NJD;
step K3: acquiring the ratio of the maximum rainfall of the whole day to the maximum displacement of the road drainage equipment in the whole day, and marking the ratio of the maximum rainfall of the whole day to the maximum displacement of the road drainage equipment in the whole day as PBZ;
step K4: obtaining an environmental safety factor CX through a formula, wherein v1, v2 and v3 are all proportionality coefficients, and v1 is more than v2 is more than v3 is more than 0;
step K5: acquiring the driving year of a driver and the year of a driver license, respectively marking the driving year of the driver and the year of the driver license as JNX and ZNX, and acquiring a driving coefficient JS (namely the driving coefficient JS by comparing the driving year with the year of the driver license;
step K6: and calculating a ratio of the environmental safety factor CX and the driving coefficient JS to obtain a proper travel coefficient AQ, namely, if the AQ is not less than 1, determining that the driver forbids travel, generating a travel forbidding signal and sending the travel forbidding signal to the cloud control platform, and if the AQ is less than 1, determining that the driver proposes travel, generating a proposed travel signal and sending the proposed travel signal to the cloud control platform.
The working principle of the invention is as follows:
a control system of a vehicle-mounted screen panel based on a cloud platform is characterized in that during work, real-time verification information is analyzed through an identity verification unit, so that the identity of a user is verified, real-time login information input by the user through the vehicle-mounted screen panel is obtained, real-time verification voice in the real-time login information is extracted and marked as voice to be verified, the sound pressure and the audio frequency of the voice to be verified are obtained, the sound pressure and the audio frequency of the voice to be verified are marked as YY and YP respectively, then a verification coefficient DY of the voice to be verified is obtained through a formula, verification voice in verification information in a database is obtained, the sound pressure and the audio frequency of the verification voice are marked as YYi and YPi respectively, then a verification coefficient DYi of the verification voice is obtained through the formula, and a coefficient ratio of the verification coefficient DY of the voice to be verified and the verification coefficient DY, if beta is larger than or equal to 1, the voice verification is judged to be successful, if beta is larger than 0 and smaller than 1, the voice verification is judged to be failed, a verification failure signal is generated, and the verification failure signal is sent to the mobile phone terminal of the user; acquiring a real-time login gesture through a vehicle-mounted screen face, then comparing the real-time login gesture with a corresponding verification gesture in data, generating an identity verification success signal when the real-time login gesture is consistent with the verification gesture in the data, and generating an identity verification failure signal when the real-time login gesture is inconsistent with the verification gesture in the data; the driver is authenticated, and whether the information in the driver and the information in the database are consistent or not is inquired, so that the safety of the vehicle is improved, and the intelligent performance of the system is enhanced.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A control system of a vehicle-mounted screen panel based on a cloud platform is characterized by comprising a registration login unit, a database, a cloud control platform, an identity verification unit, a vehicle condition detection unit, a road condition analysis unit and a driving analysis unit;
the identity authentication unit is used for analyzing the real-time authentication information so as to authenticate the identity of the user, and the specific analysis and authentication process is as follows:
the method comprises the steps of firstly, acquiring real-time login information recorded by a user through a vehicle-mounted screen panel, extracting real-time verification voice in the real-time login information, marking the real-time verification voice as voice to be verified, acquiring sound pressure and audio frequency of the voice to be verified, marking the sound pressure and the audio frequency of the voice to be verified as YY and YP respectively, and then acquiring verification coefficients DY of the voice to be verified through a formula, wherein a1 and a2 are proportional coefficients;
step two, acquiring verification voice in verification information in a database, marking the verification information of the database as i, i =1, 2, … …, n, n is a positive integer, acquiring the sound pressure and the audio frequency of the verification voice, respectively marking the sound pressure and the audio frequency of the verification voice as YYi and YPi, and then acquiring a verification coefficient DYi of the verification voice through a formula, wherein a3 and a4 are proportional coefficients;
step three, obtaining a coefficient ratio of a verification coefficient DY of the voice to be verified and a verification coefficient DYi of the verified voice through division operation, namely judging that the voice verification is successful if beta is larger than or equal to 1, entering step four, judging that the voice verification is failed if beta is larger than 0 and smaller than 1, generating a verification failure signal and sending the verification failure signal to a mobile phone terminal of a user;
step four, acquiring a real-time login gesture through the vehicle-mounted screen face, then comparing the real-time login gesture with a corresponding verification gesture in the data, generating an identity verification success signal when the real-time login gesture is consistent with the verification gesture in the data, entering step five, and generating an identity verification failure signal when the real-time login gesture is inconsistent with the verification gesture in the data;
the driving analysis unit is used for analyzing the environmental data so as to perform safety judgment on the driving trip of the user.
2. The cloud platform-based control system for the vehicle-mounted screen panel according to claim 1, wherein the vehicle condition detection unit is configured to analyze vehicle condition information to perform safety detection on the vehicle condition, the vehicle condition information is duration data, frequency data and number data, the duration data is an interval duration between a current use time of the vehicle and a last maintenance time, the frequency data is a fault occurrence frequency of the vehicle within a specified maintenance time, the number data is a ratio between the number of times of the vehicle that the vehicle has a fault and a total number of times of vehicle traveling, and the specific analysis and detection process is as follows:
step S1: acquiring the interval duration of the current service time and the last maintenance time of the vehicle, and marking the interval duration of the current service time and the last maintenance time of the vehicle as JG;
step S2: acquiring the fault occurrence frequency of the vehicle in the specified maintenance time, and marking the fault occurrence frequency of the vehicle in the specified maintenance time as PL;
step S3: acquiring the ratio of the number of times of vehicle failure to the total number of times of vehicle trip, and marking the ratio of the number of times of vehicle failure to the total number of times of vehicle trip as BZ;
step S4: obtaining a vehicle condition detection coefficient CK through a formula, wherein b1, b2 and b3 are proportional coefficients, b1 is greater than b2 and is greater than b3 and is greater than 0, and alpha is an error correction factor and is 2.0321546;
step S5: comparing the vehicle condition detection coefficient CK with a vehicle condition detection coefficient threshold value:
if the vehicle condition detection coefficient CK is larger than or equal to the vehicle condition detection coefficient threshold value, judging that the vehicle condition detection coefficient is high, generating a vehicle condition normal signal, and sending the vehicle condition normal signal to a mobile phone terminal of a user;
and if the vehicle condition detection coefficient CK is smaller than the vehicle condition detection coefficient threshold value, judging that the vehicle condition detection coefficient is low, generating a vehicle condition abnormal signal, and sending the vehicle condition abnormal signal to a mobile phone terminal of a user.
3. The control system of the cloud platform-based vehicle-mounted screen panel as claimed in claim 1, wherein the road condition analysis unit is configured to analyze road condition information to perform a safety reminding measure for a driver, the road condition information includes traffic data, vehicle speed data and quantity data, the traffic data is a sum of a total quantity of road vehicles and a quantity of vehicles added per hour, the vehicle speed data is an average driving speed of the vehicles on the road, the quantity data is a sum of a number of traffic lights on the road and a number of pits on the ground, the safety reminding measure is a voice reminding for reducing the vehicle speed and a voice reminding for suggesting a replacement route, and a specific analysis process is as follows:
step SS 1: acquiring the sum of the total number of the road vehicles and the number of the vehicles increased per hour, and marking the sum of the total number of the road vehicles and the number of the vehicles increased per hour as CSL;
step SS 2: acquiring the average running speed of the vehicles on the road, and marking the average running speed of the vehicles on the road as SDV;
step SS 3: acquiring the sum of the number of traffic lights on the road and the number of ground pits, and marking the sum of the number of traffic lights on the road and the number of ground pits as SLH;
step SS 4: acquiring a road condition analysis coefficient LK through a formula, wherein c1, c2 and c3 are proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step SS 5: comparing the road condition analysis coefficient LK with L1 and L2 respectively, wherein L1 and L2 are road condition analysis coefficient threshold values, and L1 is greater than L2:
if the road condition analysis coefficient LK is larger than or equal to L1, judging that the road condition is good, and not taking safety reminding measures for the driver;
if the road condition analysis coefficient L2 is more than LK and less than L1, the road condition is judged to be general, and the speed reduction voice prompt is carried out on the driver;
and if the road condition analysis coefficient LK is less than or equal to L2, judging that the road condition is bad, and carrying out voice prompt for suggesting a route to be changed on the driver.
4. The control system of the vehicle-mounted screen panel based on the cloud platform as claimed in claim 1, wherein the driving analysis unit is configured to analyze environmental data to perform safety judgment on driving trip of a user, the environmental data are temperature data, visibility data and rainfall data, the temperature data is a difference value between a morning ground temperature and a morning ground temperature, the visibility data is a sum of a farthest distance visible on a road at night and a farthest distance visible on a road at day, the rainfall data is a ratio of a maximum rainfall all day to a maximum displacement of road drainage equipment all day, and a specific analysis and judgment process is as follows:
step K1: acquiring a difference value between the morning ground temperature and the morning ground temperature, and marking the difference value between the morning ground temperature and the morning ground temperature as CZW;
step K2: acquiring the sum of the farthest distance visible on the night road and the farthest distance visible on the daytime road, and marking the sum of the farthest distance visible on the night road and the farthest distance visible on the daytime road as NJD;
step K3: acquiring the ratio of the maximum rainfall of the whole day to the maximum displacement of the road drainage equipment in the whole day, and marking the ratio of the maximum rainfall of the whole day to the maximum displacement of the road drainage equipment in the whole day as PBZ;
step K4: obtaining an environmental safety factor CX through a formula, wherein v1, v2 and v3 are all proportionality coefficients, and v1 is more than v2 is more than v3 is more than 0;
step K5: acquiring the driving year of a driver and the year of a driver license, respectively marking the driving year of the driver and the year of the driver license as JNX and ZNX, and acquiring a driving coefficient JS (namely the driving coefficient JS by comparing the driving year with the year of the driver license;
step K6: and calculating a ratio of the environmental safety factor CX and the driving coefficient JS to obtain a proper travel coefficient AQ, namely, if the AQ is not less than 1, determining that the driver forbids travel, generating a travel forbidding signal and sending the travel forbidding signal to the cloud control platform, and if the AQ is less than 1, determining that the driver proposes travel, generating a proposed travel signal and sending the proposed travel signal to the cloud control platform.
5. The cloud platform-based control system for the vehicle-mounted screen panel is characterized in that the registration login unit is used for a user to submit user information through a mobile phone terminal for registration and send the user information which is successfully registered to the database for storage, the user information comprises the name, age, sex and mobile phone number of the user for real name authentication, after the user is successfully registered, the cloud control platform generates a verification information entry signal and sends the verification information entry signal to the mobile phone terminal of the user, after the user receives the verification information entry signal, the verification information is entered and added with a name tag, and then the verification information and the corresponding name tag are sent to the database for storage, and the verification information comprises verification voice and verification gestures.
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