CN116001495A - Tire pressure monitoring processing system based on cloud server - Google Patents
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Abstract
The invention discloses a tire pressure monitoring and processing system based on a cloud server, which comprises a parameter acquisition module, a data analysis module, an environment diagnosis module and the cloud server; the parameter acquisition module acquires the running parameters and the tire behavior parameters of the vehicle and sends the running parameters and the tire behavior parameters of the vehicle to the cloud server; the environment diagnosis module identifies the running environment state of the vehicle, obtains the running environment state parameter of the vehicle, and sends the running environment state parameter of the vehicle to the cloud server; the data analysis module receives the running parameters, the tire behavior parameters and the vehicle running environment state parameters of the vehicle, which are transmitted by the cloud server, completes the comprehensive processing of the tires and the tire pressures of the vehicle, and realizes the real-time feedback of the tire pressure monitoring.
Description
Technical Field
The invention relates to the technical field of tire pressure monitoring, in particular to a tire pressure monitoring processing system based on a cloud server.
Background
The tire pressure monitoring system of the existing automobile has the functions of automatically monitoring the tire pressure in real time in the running process of the automobile and alarming the air leakage and low pressure of the tire so as to ensure the running safety.
Automobiles are very popular in the daily life of modern people, and the air leakage and sudden tire burst of the automobiles are often unexpected, and once the air leakage and tire burst occur, the automobiles can be very dangerous if early warning and reasonable treatment are not available.
The tire pressure monitoring system in the prior art is used for detecting whether the tire leaks or not, the small-amplitude change of the air pressure in the tire is not easy to be found, and the small-amplitude change is usually the pre-occurrence of the air leakage or the tire burst;
secondly, the tire pressure monitoring system in the prior art does not have the early warning effect of the tire pressure in the use process, can not effectively avoid risks, and can not ensure the running safety of the vehicle.
Disclosure of Invention
The invention aims to provide a tire pressure monitoring processing system based on a cloud server, which completes tire pressure monitoring processing from multiple dimensions such as a vehicle running environment, a vehicle running road condition, a vehicle tire pressure state and the like, so that the processing parameters of the tire pressure monitoring processing system based on the cloud server are more matched with the actual running condition of the vehicle, the fitting degree is higher, the risk is effectively avoided, and the running safety of the vehicle is ensured.
The aim of the invention can be achieved by the following technical scheme:
the tire pressure monitoring processing system based on the cloud server comprises a parameter acquisition module, a data analysis module, an environment diagnosis module and the cloud server;
the parameter acquisition module is used for acquiring the running parameters and the tire behavior parameters of the vehicle and sending the running parameters and the tire behavior parameters of the vehicle to the cloud server;
the environment diagnosis module is used for identifying the running environment state of the vehicle, obtaining the running environment state parameter of the vehicle and sending the running environment state parameter of the vehicle to the cloud server;
the data analysis module receives the running parameters, the tire behavior parameters and the vehicle running environment state parameters of the vehicle, which are transmitted by the cloud server, completes the comprehensive processing of the tires and the tire pressures of the vehicle, and realizes the real-time feedback of the tire pressure monitoring.
As a further scheme of the invention: the parameter acquisition module comprises a tire pressure monitoring unit, a vehicle driving unit and a fault counting unit, wherein the driving parameters of the vehicle comprise vehicle mileage, and the tire behavior parameters comprise tire pressure values and fault times;
the tire pressure monitoring unit is used for monitoring the tire pressure of the vehicle tire in real time to obtain tire pressure data;
the vehicle driving unit is used for acquiring the mileage of the vehicle to obtain mileage data;
the fault counting unit is used for obtaining fault data for the number of faults from the start of use to the current node of the tire.
As a further scheme of the invention: the data analysis module receives tire pressure data transmitted by the cloud server, wherein the tire pressure data comprises tire pressure initial data and tire pressure real-time data;
the tire pressure initial data correspond to the initial tire pressures of four tires, namely Ti1, ti2, ti3 and Ti4;
the tire pressure real-time data corresponds to the real-time tire pressures of the four wheels to be Tj1, tj2, tj3 and Tj4 respectively.
As a further scheme of the invention: the processing steps of the data analysis module based on the tire pressure data are as follows:
the tire pressure initial data and the tire pressure real-time data are processed in a difference mode to obtain four tire pressure reduction values, and the tire pressure reduction values of the four tires are respectively marked as Tij1, tij2, tij3 and Tij4;
calculating to obtain a real-time mean value and a real-time variance of the four tire decompression values, marking the real-time mean value as Tb, and marking the real-time variance as Tf;
the data analysis module receives a preset fluctuation value and a preset variance of the tire pressure stored in the cloud server, marks the preset fluctuation value as Tbc, and marks the preset variance as Tfc;
comparing the real-time variance Tf with a preset variance Tfc;
when the actual variance Tf is more than or equal to the preset variance Tfc, generating an abnormal signal;
when the actual variance Tf is smaller than the preset variance Tfc, generating a normal signal;
after the data analysis module receives the abnormal signal, the obtained abnormal signal and the tire corresponding to the abnormal signal are sent to the cloud server.
As a further scheme of the invention: the processing steps of the data analysis module based on the tire pressure data are as follows:
the tire pressure initial data and the tire pressure real-time data are processed in a difference mode to obtain four tire pressure reduction values, and the tire pressure reduction values of the four tires are respectively marked as Tij1, tij2, tij3 and Tij4;
calculating to obtain a real-time mean value and a real-time variance of the four tire decompression values, marking the real-time mean value as Tb, and marking the real-time variance as Tf;
the data analysis module receives a preset fluctuation value and a preset variance of the tire pressure stored in the cloud server, marks the preset fluctuation value as Tbc, and marks the preset variance as Tfc;
comparing the real-time variance Tf with a preset variance Tfc;
when the actual variance Tf is more than or equal to the preset variance Tfc, generating an abnormal signal;
when the actual variance Tf is smaller than the preset variance Tfc, generating a normal signal;
when the data analysis module obtains normal signals of variance processing, performing difference processing on the tire pressure reduction value and the real-time mean value of each tire, and taking an absolute value of the difference value to obtain a deviation value Tp of the tire; comparing the preset fluctuation value Tb with the deviation value Tp:
when the deviation value Tp is smaller than or equal to the preset fluctuation value Tb, the tire of the current vehicle is free of problems;
when the deviation value Tp is larger than the preset fluctuation value Tb, indicating that the tire of the current vehicle is abnormal, and generating an abnormal signal;
after the data analysis module receives the abnormal signal, the obtained abnormal signal and the tire corresponding to the abnormal signal are sent to the cloud server.
As a further scheme of the invention: the data analysis module receives vehicle running environment state parameters, mileage data and fault data transmitted by the cloud server;
data analysis module vehicleVehicle operating environment status parameter is marked as
Marking the received mileage data as Gi and the received fault data as Bi;
by the formula
Obtaining an early warning coefficient Ri of the tire, wherein a1, a2 and a3 are preset proportional coefficients;
presetting early warning thresholds of vehicle tires as R1 and R2;
when Ri is smaller than R1, indicating that the running state of the vehicle tyre is excellent, and generating a normal signal;
when R1 is less than or equal to Ri and less than R2, the running state of the vehicle tyre is good, and a first-level early warning signal is generated;
when Ri is more than or equal to R2, the running state of the vehicle tire is indicated to be poor, and a secondary early warning signal is generated.
And the data analysis module sends the obtained early warning signal to the cloud server.
As a further scheme of the invention: the cloud server further comprises a prompt module, wherein the prompt module is used for sending the signals of the received data analysis module to an owner of the vehicle.
As a further scheme of the invention: the system also comprises an environment diagnosis module, wherein the environment diagnosis module is used for processing the running environment state of the vehicle to obtain the running environment state parameters of the vehicle in a period;
the environment diagnosis module comprises an environment monitoring unit and a road condition monitoring unit.
As a further scheme of the invention: the environment monitoring unit comprises a temperature monitoring subunit, a humidity monitoring subunit and a rainfall monitoring subunit, wherein the temperature monitoring subunit is used for monitoring the temperature in a vehicle period to obtain temperature monitoring data, the humidity monitoring subunit is used for monitoring the humidity in the vehicle period to obtain humidity monitoring data, the rainfall monitoring subunit is used for monitoring the number of times of rainy days in the vehicle period to obtain rainfall monitoring data, and the environment factor in the vehicle driving period is obtained through integrating the temperature monitoring data, the humidity monitoring data and the rainfall monitoring data.
As a further scheme of the invention: the road condition monitoring unit comprises a vehicle running monitoring subunit and a road condition monitoring subunit, wherein the vehicle running monitoring subunit is used for monitoring running time in a vehicle period to obtain vehicle time data, the road condition monitoring subunit is used for monitoring running road condition indexes in the vehicle period to obtain road condition index data, and road condition factors in the vehicle running period are obtained through integrating the vehicle time data and the road condition index data.
The invention has the beneficial effects that:
the invention combines the running mileage of the vehicle with the running environment of the vehicle, the running environment of the vehicle comprises weather environment and road condition environment, the wear resistance (using state) of the vehicle tyre is converted into the running mileage of the vehicle and the running environment of the vehicle to be replaced, thereby realizing the monitoring of the using state of the vehicle tyre, and when the vehicle tyre has no fault, the monitoring of the using state of the vehicle tyre is completed, and the safety performance is high;
according to the invention, the tire pressure of the vehicle tire is obtained in real time, the real-time tire pressure and the initial tire pressure of the tire are processed, and the tire pressure state of the vehicle tire is identified in a mean value and variance identification processing mode, so that the monitoring of the tire with abnormal tire pressure is realized, the abnormal tire is fed back to the vehicle owner, and the running safety of the vehicle is effectively ensured.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a block diagram of a system of the present invention;
fig. 2 is a schematic diagram of a flow chart of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the invention discloses a tire pressure monitoring processing system based on a cloud server, which comprises a parameter acquisition module, a data analysis module, an environment diagnosis module and the cloud server;
the parameter acquisition module is used for acquiring the running parameters and the tire behavior parameters of the vehicle and sending the running parameters and the tire behavior parameters of the vehicle to the cloud server;
the environment diagnosis module is used for identifying the running environment state of the vehicle, obtaining the running environment state parameter of the vehicle and sending the running environment state parameter of the vehicle to the cloud server;
the data analysis module receives the running parameters, the tire behavior parameters and the vehicle running environment state parameters of the vehicle, which are transmitted by the cloud server, completes the comprehensive processing of the tires and the tire pressures of the vehicle, and realizes the real-time feedback of the tire pressure monitoring.
The running parameters of the vehicle comprise the running mileage of the vehicle, and the tire behavior parameters comprise the tire pressure value and the failure times.
The environment diagnosis module is used for processing the running environment state of the vehicle so as to obtain the running environment state parameter of the vehicle in a period, wherein the environment diagnosis module comprises an environment monitoring unit and a road condition monitoring unit;
the environment monitoring unit comprises a temperature monitoring subunit, a humidity monitoring subunit and a rainfall monitoring subunit, wherein the temperature monitoring subunit is used for monitoring the temperature in the vehicle period to obtain temperature monitoring data, the humidity monitoring subunit is used for monitoring the humidity in the vehicle period to obtain humidity monitoring data, the rainfall monitoring subunit is used for monitoring the number of times of rainy days in the vehicle period to obtain rainfall monitoring data, and the environment factors in the vehicle driving period are obtained by integrating the temperature monitoring data, the humidity monitoring data and the rainfall monitoring data;
the acquisition process of the environmental factors comprises the following steps:
s1: monitoring the temperature monitoring subunitThe temperature monitoring data is marked as
；
Marking the humidity monitoring data obtained by monitoring the humidity monitoring subunit as
；
Marking the rainfall monitoring data obtained by monitoring the rainfall monitoring subunit as
；
Wherein t1 is a vehicle driving period;
s2: according to the formula
Calculating the environmental factor of the vehicle running in the period>
Wherein alpha, beta and delta are preset proportionality coefficients;
the road condition monitoring unit comprises a vehicle running monitoring subunit and a road condition monitoring subunit, wherein the vehicle running monitoring subunit is used for monitoring running time in a vehicle period to obtain vehicle time data, the road condition monitoring subunit is used for monitoring running road condition indexes in the vehicle period to obtain road condition index data, and road condition factors in the vehicle running period are obtained by integrating the vehicle time data and the road condition index data;
the road condition factor acquisition comprises the following steps:
s3: the road surface condition index is obtained through the following steps:
by the formula
Obtaining the road surface condition index->
，
Wherein i and j are disease types and degrees;
n-total number of disease species;
mi-i disease and number of stages of severity;
DPijk-i diseases and j degrees of weight and k ranges of deduction values;
wij—a number of disease and severity levels, and a deduction value for the k range;
s4: marking the vehicle time data obtained by monitoring the vehicle running monitoring subunit as
；
Wherein the vehicle time data
Index +.>
Travel time of the corresponding road section;
s5: by the formula
Calculating to obtain road condition factor of vehicle running in period>
Wherein ϵ, θ, k are preset scaling factors;
s6: by the formula
Acquiring vehicle running environment state parameters of vehicle in period
ϑ is a specific proportionality coefficient, and a preset vehicle running environment state parameter threshold value is F;
vehicle operating environment state parameters while the vehicle is in a cycle
When the vehicle running environment state parameter threshold value F is larger than or equal to the vehicle running environment state parameter threshold value F, the vehicle running state is good;
vehicle operating ring when vehicle is in cycleEnvironmental status parameters
When the vehicle running environment state parameter is smaller than the vehicle running environment state parameter threshold value F, the vehicle running state is indicated to be poor.
The environment diagnosis module transmits the obtained vehicle running environment state parameters to the cloud server.
The parameter acquisition module comprises a tire pressure monitoring unit, a vehicle running unit and a fault counting unit, wherein the tire pressure monitoring unit is used for monitoring the tire pressure of a vehicle tire in real time to obtain tire pressure data, the vehicle running unit is used for acquiring the mileage number of the vehicle to obtain mileage data, and the fault counting unit is used for obtaining fault data from the time of starting to use the tire to the fault time of a current node;
and the parameter acquisition module transmits the obtained tire pressure data, mileage data and fault data to the cloud server.
In a particular embodiment
The data analysis module receives vehicle running environment state parameters, mileage data and fault data transmitted by the cloud server;
the data analysis module marks the received mileage data as Gi and marks the received fault data as Bi;
by the formula
Obtaining an early warning coefficient Ri of the tire, wherein a1, a2 and a3 are preset proportional coefficients;
presetting early warning thresholds of vehicle tires as R1 and R2;
when Ri is smaller than R1, indicating that the running state of the vehicle tyre is excellent, and generating a normal signal;
when R1 is less than or equal to Ri and less than R2, the running state of the vehicle tyre is good, and a first-level early warning signal is generated;
when Ri is more than or equal to R2, the running state of the vehicle tire is indicated to be poor, and a secondary early warning signal is generated.
The data analysis module sends the obtained early warning signals to the cloud server, and then the early warning signals are transmitted to a vehicle owner through the cloud server to realize early warning and monitoring on vehicle tires;
according to the early warning coefficient formula for obtaining the tire, when the running distance of the vehicle is longer, the number of times of tire faults is more, and the running state of the tire of the vehicle is worse;
conversely, the greater the vehicle operating environment state parameter, the better the operating state of the vehicle tire is explained.
In another embodiment
The data analysis module receives tire pressure data transmitted by the cloud server, the tire pressure data in the embodiment take a four-wheel vehicle as an example, and the tire pressure data comprises tire pressure initial data and tire pressure real-time data;
the initial tire pressures of the four tires corresponding to the tire pressure initial data are Ti1, ti2, ti3 and Ti4 (1, 2, 3 and 4 correspond to the numbers of the tires respectively);
the tire pressure real-time data corresponds to the real-time tire pressures of four wheels, namely Tj1, tj2, tj3 and Tj4;
the processing steps of the data analysis module based on the tire pressure data are as follows:
w1: the tire pressure initial data and the tire pressure real-time data are processed in a difference mode to obtain four tire pressure reduction values, and the tire pressure reduction values of the four tires are respectively marked as Tij1, tij2, tij3 and Tij4;
w2: calculating to obtain a real-time mean value and a real-time variance of the four tire decompression values, marking the real-time mean value as Tb, and marking the real-time variance as Tf;
the data analysis module receives a preset fluctuation value and a preset variance of the tire pressure stored in the cloud server, marks the preset fluctuation value as Tbc, and marks the preset variance as Tfc;
w4, comparing the real-time variance Tf with a preset variance Tfc;
w41: when the actual variance Tf is more than or equal to the preset variance Tfc, generating an abnormal signal, and entering a step W6;
w42: when the actual variance Tf is smaller than the preset variance Tfc, generating a normal signal, and entering a step W5;
w5: performing difference processing on the tire pressure reduction value and the real-time average value of each tire, and taking an absolute value of the difference value to obtain a deviation value Tp of the tire; comparing the preset fluctuation value Tb with the deviation value Tp:
w51: when the deviation value Tp is smaller than or equal to the preset fluctuation value Tb, the tire of the current vehicle is free of problems;
w52: when the deviation value Tp is larger than the preset fluctuation value Tb, indicating that the tire of the current vehicle is abnormal, generating an abnormal signal, and entering W6;
w6: after the data analysis module receives the abnormal signal, the obtained abnormal signal and the tire corresponding to the abnormal signal are sent to the cloud server.
The cloud server further comprises a prompt module, the prompt module is used for reporting the tire abnormality signal to the vehicle owner, the prompt module comprises a voice broadcasting unit and an information transmission unit, when the cloud server identifies that the vehicle is in the driving process, the voice broadcasting unit is connected with the vehicle-mounted broadcasting terminal and carries out voice broadcasting on the tire abnormality signal to the vehicle owner, and when the cloud server identifies that the vehicle is in the parking process, the information transmission unit transmits the tire abnormality signal to the vehicle owner user terminal through information;
wherein the owner user terminal includes, but is not limited to, a mobile phone terminal.
The invention is characterized in that: the running mileage of the vehicle is combined with the running environment of the vehicle, the running environment of the vehicle comprises weather environment and road condition environment, the wear resistance (using state) of the vehicle tyre is converted into the running mileage of the vehicle and the running environment of the vehicle to be replaced, so that the monitoring of the using state of the vehicle tyre is realized, and when the vehicle tyre is in a fault-free condition, the monitoring of the using state of the vehicle tyre is completed, and the safety performance is high;
the invention is characterized in that: the tire pressure of the vehicle tire is obtained in real time, the real-time tire pressure of the tire and the initial tire pressure of the tire are processed, the tire pressure state of the vehicle tire is identified in a mean value and variance identification processing mode, so that the monitoring of the tire with abnormal tire pressure is realized, the abnormal tire is fed back to the vehicle owner, and the running safety of the vehicle is effectively ensured;
the invention is characterized in that: the tire pressure monitoring processing is completed from multiple dimensions such as the vehicle running environment, the vehicle running road condition, the vehicle tire pressure state and the like, so that the processing parameters of the tire pressure monitoring processing system based on the cloud server are more matched with the actual running condition of the vehicle, and the laminating degree is higher.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (10)
1. The tire pressure monitoring and processing system based on the cloud server is characterized by comprising a parameter acquisition module, a data analysis module, an environment diagnosis module and the cloud server;
the parameter acquisition module is used for acquiring the running parameters and the tire behavior parameters of the vehicle and sending the running parameters and the tire behavior parameters of the vehicle to the cloud server;
the environment diagnosis module is used for identifying the running environment state of the vehicle, obtaining the running environment state parameter of the vehicle and sending the running environment state parameter of the vehicle to the cloud server;
the data analysis module receives the running parameters, the tire behavior parameters and the vehicle running environment state parameters of the vehicle, which are transmitted by the cloud server, completes the comprehensive processing of the tires and the tire pressures of the vehicle, and realizes the real-time feedback of the tire pressure monitoring.
2. The cloud server-based tire pressure monitoring processing system of claim 1, wherein the parameter acquisition module comprises a tire pressure monitoring unit, a vehicle driving unit and a failure counting unit, the driving parameters of the vehicle comprise a vehicle mileage, and the tire behavior parameters comprise a tire pressure value and a failure number;
the tire pressure monitoring unit is used for monitoring the tire pressure of the vehicle tire in real time to obtain tire pressure data;
the vehicle driving unit is used for acquiring the mileage of the vehicle to obtain mileage data;
the fault counting unit is used for obtaining fault data for the number of faults from the start of use to the current node of the tire.
3. The cloud server-based tire pressure monitoring processing system of claim 1, wherein the data analysis module receives tire pressure data transmitted by the cloud server, the tire pressure data comprising tire pressure start data and tire pressure real-time data;
the tire pressure initial data correspond to the initial tire pressures of four tires, namely Ti1, ti2, ti3 and Ti4;
the tire pressure real-time data corresponds to the real-time tire pressures of the four wheels to be Tj1, tj2, tj3 and Tj4 respectively.
4. The cloud server-based tire pressure monitoring processing system of claim 3, wherein the processing steps of the data analysis module based on the tire pressure data are as follows:
the tire pressure initial data and the tire pressure real-time data are processed in a difference mode to obtain four tire pressure reduction values, and the tire pressure reduction values of the four tires are respectively marked as Tij1, tij2, tij3 and Tij4;
calculating to obtain a real-time mean value and a real-time variance of the four tire decompression values, marking the real-time mean value as Tb, and marking the real-time variance as Tf;
the data analysis module receives a preset fluctuation value and a preset variance of the tire pressure stored in the cloud server, marks the preset fluctuation value as Tbc, and marks the preset variance as Tfc;
comparing the real-time variance Tf with a preset variance Tfc;
when the actual variance Tf is more than or equal to the preset variance Tfc, generating an abnormal signal;
when the actual variance Tf is smaller than the preset variance Tfc, generating a normal signal;
after the data analysis module receives the abnormal signal, the obtained abnormal signal and the tire corresponding to the abnormal signal are sent to the cloud server.
5. The cloud server-based tire pressure monitoring processing system of claim 3, wherein the processing steps of the data analysis module based on the tire pressure data are as follows:
the tire pressure initial data and the tire pressure real-time data are processed in a difference mode to obtain four tire pressure reduction values, and the tire pressure reduction values of the four tires are respectively marked as Tij1, tij2, tij3 and Tij4;
calculating to obtain a real-time mean value and a real-time variance of the four tire decompression values, marking the real-time mean value as Tb, and marking the real-time variance as Tf;
the data analysis module receives a preset fluctuation value and a preset variance of the tire pressure stored in the cloud server, marks the preset fluctuation value as Tbc, and marks the preset variance as Tfc;
comparing the real-time variance Tf with a preset variance Tfc;
when the actual variance Tf is more than or equal to the preset variance Tfc, generating an abnormal signal;
when the actual variance Tf is smaller than the preset variance Tfc, generating a normal signal;
when the data analysis module obtains normal signals of variance processing, performing difference processing on the tire pressure reduction value and the real-time mean value of each tire, and taking an absolute value of the difference value to obtain a deviation value Tp of the tire; comparing the preset fluctuation value Tb with the deviation value Tp:
when the deviation value Tp is smaller than or equal to the preset fluctuation value Tb, the tire of the current vehicle is free of problems;
when the deviation value Tp is larger than the preset fluctuation value Tb, indicating that the tire of the current vehicle is abnormal, and generating an abnormal signal;
after the data analysis module receives the abnormal signal, the obtained abnormal signal and the tire corresponding to the abnormal signal are sent to the cloud server.
6. The cloud server-based tire pressure monitoring processing system of claim 2, wherein the data analysis module receives vehicle operating environment status parameters, mileage data, and fault data transmitted by the cloud server;
data analysis module vehicle operating environment state parameter is marked as
Marking the received mileage data as Gi and the received fault data as Bi;
by the formula
Obtaining an early warning coefficient Ri of the tire, wherein a1, a2 and a3 are preset proportional coefficients;
presetting early warning thresholds of vehicle tires as R1 and R2;
when Ri is smaller than R1, indicating that the running state of the vehicle tyre is excellent, and generating a normal signal;
when R1 is less than or equal to Ri and less than R2, the running state of the vehicle tyre is good, and a first-level early warning signal is generated;
when Ri is more than or equal to R2, representing that the running state of the vehicle tyre is poor, and generating a secondary early warning signal;
and the data analysis module sends the obtained early warning signal to the cloud server.
7. The cloud server-based tire pressure monitoring processing system of claim 5 or 6, wherein the cloud server further comprises a prompting module for sending a signal of the received data analysis module to a vehicle owner.
8. The cloud server-based tire pressure monitoring and processing system according to claim 6, wherein the environment diagnosis module is further configured to process an operating environment state of the vehicle to obtain a vehicle operating environment state parameter of the vehicle in a period;
the environment diagnosis module comprises an environment monitoring unit and a road condition monitoring unit.
9. The cloud server-based tire pressure monitoring processing system of claim 8, wherein the environment monitoring unit comprises a temperature monitoring subunit, a humidity monitoring subunit and a rainfall monitoring subunit, the temperature monitoring subunit is used for monitoring the temperature in the vehicle period to obtain temperature monitoring data, the humidity monitoring subunit is used for monitoring the humidity in the vehicle period to obtain humidity monitoring data, the rainfall monitoring subunit is used for monitoring the number of times of rainy days in the vehicle period to obtain rainfall monitoring data, and the environment factor in the vehicle driving period is obtained by integrating the temperature monitoring data, the humidity monitoring data and the rainfall monitoring data.
10. The cloud server-based tire pressure monitoring processing system according to claim 8, wherein the road condition monitoring unit comprises a vehicle running monitoring subunit and a road condition monitoring subunit, the vehicle running monitoring subunit is configured to monitor running time in a vehicle period to obtain vehicle time data, the road condition monitoring subunit is configured to monitor running road condition index in the vehicle period to obtain road condition index data, and the road condition factor in the vehicle running period is obtained by integrating the vehicle time data and the road condition index data.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116342014A (en) * | 2023-05-24 | 2023-06-27 | 西南医科大学附属医院 | Anesthetic transportation management system based on data analysis |
| CN117589367A (en) * | 2023-11-07 | 2024-02-23 | 苏州紫联汽车科技有限公司 | Tire pressure detecting system |
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| CN117589367B (en) * | 2023-11-07 | 2024-05-17 | 苏州紫联汽车科技有限公司 | Tire pressure detecting system |
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