Car rental reservation queuing scheduling system and method

Abstract

The invention relates to the technical field of information technology and artificial intelligence, and discloses a car rental reservation queuing scheduling system and method, and a car rental reservation data updating module, a car rental reservation data analysis module, a car rental reservation data processing module and a car rental reservation data reminding module are established. The car rental reservation data updating module is divided into a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit, and the car rental reservation data analysis module calculates a car rental information auditing and artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx and a car rental abnormal index Rx. The car rental reservation data processing module automatically checks and processes problems of the system according to abnormal information of the artificial intelligence registration synchronization index Ex, the artificial intelligence response time Wx and the car rental abnormal index Rx, and the car rental reservation data reminding module reminds the car rental reservation data reminding module according to the processing result of the car rental reservation data processing module. And relevant departments are notified in advance to carry out data repair or fault repair items.

Description

Technical Field

[0001] The present invention relates to the fields of information technology and artificial intelligence technology, and in particular to a car rental reservation queuing scheduling system and method. Background Art

[0002] In today's society where information technology and logistics industries are developing rapidly, traditional offline car rental stores are facing increasing competitive pressure. The emergence of online car rental platforms has brought consumers a more convenient and efficient booking experience with more competitive prices. This change is mainly due to the fact that the car rental reservation queue scheduling system and method has achieved better quality car rental services with the support of background technologies such as intelligent management, logistics chain optimization, and vehicle intelligent scheduling.

[0003] However, the existing technology still has shortcomings, especially poor user experience and imperfect reservation system. Although the intelligent queuing system has been introduced, the response speed and accuracy of the system still need to be improved when handling a large number of reservation requests during peak hours. Users may suffer inconvenience due to untimely updates or improper handling of reservation information, especially during peak hours. Therefore, further optimization of the car rental reservation queuing scheduling system and method has become a key demand for the development of the industry, in order to achieve a more efficient and convenient car rental service experience. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the deficiencies in the prior art, the present invention provides a car rental reservation queuing scheduling system and method, which has the advantage of a perfect reservation system and solves the problem of an imperfect reservation system in the prior art.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a car rental reservation queuing scheduling system and method, including a car rental reservation data updating module, a car rental reservation data analyzing module, a car rental reservation data processing module and a car rental reservation data reminding module;

[0008] The car rental reservation data update module includes a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit. The car rental information entry unit obtains car rental data by connecting to online monitoring equipment and sensors through a network. The artificial intelligence data unit obtains artificial intelligence data through an artificial intelligence Internet terminal. The car rental abnormal data collection unit obtains car rental abnormal data through an artificial intelligence Internet terminal. The car rental data entry unit, the artificial intelligence data unit and the car rental abnormal data collection unit are connected to the car rental reservation data analysis module through a network.

[0009] The car rental reservation data analysis module includes a car rental information review unit, an artificial intelligence auxiliary unit and a car rental abnormality analysis unit. The car rental information review unit calculates the car rental information review and artificial intelligence registration synchronization index Ex according to the car rental data and the artificial intelligence data. The artificial intelligence auxiliary unit calculates the artificial intelligence response time Wx according to the car rental data and the artificial intelligence data. The car rental abnormality analysis unit calculates the car rental abnormality index Rx according to the car rental abnormality data. The car rental information review unit, the artificial intelligence auxiliary unit and the car rental abnormality analysis unit are connected to the car rental reservation data processing module through a network;

[0010] The car rental reservation data processing module automatically troubleshoots and processes system problems based on the abnormal information of the artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx and car rental abnormality index Rx;

[0011] The car rental reservation data reminder module notifies relevant departments in advance to carry out data repair or fault repair matters according to the processing result of the car rental reservation data processing module.

[0012] Preferably, the car rental information entry unit numbers the car rental data input time, the amount of car rental data that has passed the review, and the total amount of car rental data submitted according to the car rental data characteristics, and the car rental data input time, the amount of car rental data that has passed the review, and the total amount of car rental data submitted are numbered t1, m1, and f1, respectively.

[0013] Preferably, the artificial intelligence data unit numbers the artificial intelligence data processing time, the artificial intelligence result output time, the number of processed car rental reservation requests, the amount of car rental data correctly identified by the artificial intelligence, and the amount of car rental data processed by the artificial intelligence according to the artificial intelligence data characteristics, and the artificial intelligence data processing time, artificial intelligence result output time, the number of processed car rental reservation requests, the amount of car rental data correctly identified by the artificial intelligence, and the amount of car rental data processed by the artificial intelligence are numbered t2, t3, g, m2, and f2, respectively.

[0014] Preferably, the car rental information review unit calculates the car rental information review and artificial intelligence registration synchronization index Ex based on the car rental data and artificial intelligence data, and the calculation formula is:

[0015]

[0016] In the formula, Ex represents the car rental information review and artificial intelligence registration synchronization index, m1 and f1 represent the amount of car rental data that has passed the review and the total amount of car rental data submitted, respectively; m2 and f2 represent the amount of car rental data correctly identified by artificial intelligence and the amount of car rental data processed by artificial intelligence, respectively.

[0017] Preferably, the artificial intelligence auxiliary unit calculates the artificial intelligence response time Wx according to the car rental data and the artificial intelligence data, and the calculation formula is:

[0018]

[0019] In the formula, Wx represents the AI ​​response time, t1 represents the car rental data input time, t2, t3, and g represent the AI ​​data processing time, AI result output time, and the number of processed requests for car rental reservations, respectively, and t1+t2+t3 represents the total processing time.

[0020] Preferably, the car rental abnormality data collection unit numbers the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entries and the number of unqualified car rental reservation information pre-processing identification according to the car rental abnormality data characteristics, and the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entries and the number of unqualified car rental reservation information pre-processing identification are numbered n1, n, n3, and n4.

[0021] Preferably, the car rental abnormality analysis unit calculates the car rental abnormality index Rx according to the car rental abnormality data, and the calculation formula is:

[0022]

[0023] In the formula, Rx represents the car rental anomaly index, and n1, n, n3, and n4 represent the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entry, and the number of unqualified car rental reservation information preprocessing identifications, respectively.

[0024] Preferably, the operations performed by the car rental reservation data processing module according to the artificial intelligence registration synchronization index Ex include: when the artificial intelligence registration synchronization index Ex<1, automatically re-examining the failed data, improving the user interface and providing real-time feedback, manually reviewing the car rental data that has not passed the review, optimizing the user reservation interface, simplifying the operation steps, and providing real-time feedback. After the user submits the reservation, the reservation status and problems are displayed in real time to remind the user to check and correct them in time.

[0025] Preferably, the operations performed by the car rental reservation data processing module according to the artificial intelligence response time Wx include: when the artificial intelligence response time Wx is less than 1 second, regularly performing system performance benchmark tests and implementing load balancing in a multi-server environment;

[0026] The operations performed by the car rental reservation data processing module according to the car rental abnormality index Rx include: when the car rental abnormality index Rx≥0.05, a detailed analysis of the abnormal order data is performed, a real-time data monitoring system is established, an effective user feedback channel is established, and a special emergency response team is set up to quickly handle the user's urgent problems.

[0027] Preferably, a method for scheduling a car rental reservation queue includes the following steps:

[0028] Step 1: Establish a car rental reservation data update module, a car rental reservation data analysis module, a car rental reservation data processing module and a car rental reservation data reminder module;

[0029] Step 2: The car rental reservation data update module is divided into a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit;

[0030] Step 3: The car rental reservation data analysis module is divided into a car rental information review unit, an artificial intelligence auxiliary unit and a car rental abnormality analysis unit, and calculates the car rental information review and artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx and car rental abnormality index Rx;

[0031] Step 4: The car rental reservation data processing module automatically troubleshoots and processes the system based on the abnormal information of the artificial intelligence registration synchronization index Ex, the artificial intelligence response time Wx, and the car rental abnormality index Rx;

[0032] Step 5: The car rental reservation data reminder module notifies the relevant departments in advance to carry out data repair or fault repair according to the processing results of the car rental reservation data processing module.

[0033] Compared with the prior art, the present invention provides a car rental reservation queuing scheduling system and method, which has the following beneficial effects:

[0034] 1. The present invention calculates the car rental information review and artificial intelligence registration synchronization index Ex by calculating the car rental data and artificial intelligence data. When the car rental information review and artificial intelligence registration synchronization index Ex is low, the car rental reservation data processing module can automatically re-review the failed data, improve the user interface and provide real-time feedback, and manually review the car rental data that has not passed the review to ensure the accuracy and completeness of the data; optimize the user reservation interface, simplify the operating steps, reduce the probability of users filling in errors and giving up reservations, and provide real-time feedback. After the user submits the reservation, the reservation status and problems are displayed in real time to remind the user to check and correct them in time.

[0035] 2. The present invention calculates the artificial intelligence response time Wx. When the artificial intelligence response time Wx is lower than the system preset response time, the car rental reservation data processing module regularly performs system performance benchmark tests (from once every 15 days to once every 3 days) to ensure that the system can still maintain low latency under high load, thereby improving the artificial intelligence response time and solving the problem of imperfect reservation system in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the structure of the present invention;

[0037] Figure 2 It is a step diagram of the method of the present invention. DETAILED DESCRIPTION

[0038] 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.

[0039] See also Figure 1 , a car rental reservation queuing scheduling system and method, including a car rental reservation data updating module, a car rental reservation data analyzing module, a car rental reservation data processing module and a car rental reservation data reminding module;

[0040] The car rental reservation data update module includes a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit. The car rental information entry unit obtains car rental data through a network connection to online monitoring equipment and sensors. The artificial intelligence data unit obtains artificial intelligence data through an artificial intelligence Internet terminal. The car rental abnormal data collection unit obtains car rental abnormal data through an artificial intelligence Internet terminal. The car rental data entry unit, the artificial intelligence data unit and the car rental abnormal data collection unit are connected to the car rental reservation data analysis module through the network.

[0041] The car rental reservation data analysis module includes a car rental information review unit, an artificial intelligence auxiliary unit and a car rental abnormality analysis unit. The car rental information review unit calculates the car rental information review and artificial intelligence registration synchronization index Ex based on the car rental data and the artificial intelligence data. The artificial intelligence auxiliary unit calculates the artificial intelligence response time Wx based on the car rental data and the artificial intelligence data. The car rental abnormality analysis unit calculates the car rental abnormality index Rx based on the car rental abnormality data. The car rental information review unit, the artificial intelligence auxiliary unit and the car rental abnormality analysis unit are connected to the car rental reservation data processing module through the network;

[0042] The car rental reservation data processing module automatically troubleshoots and processes system problems based on the abnormal information of the artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx, and car rental abnormality index Rx;

[0043] The car rental reservation data reminder module notifies the relevant departments in advance to carry out data repair or fault repair matters according to the processing results of the car rental reservation data processing module.

[0044] The car rental information entry unit numbers the car rental data input time, the amount of car rental data that has been reviewed and approved, and the total amount of car rental data submitted according to the characteristics of the car rental data. The car rental data input time, the amount of car rental data that has been reviewed and approved, and the total amount of car rental data submitted are numbered t1, m1, and f1 respectively.

[0045] The artificial intelligence data unit numbers the artificial intelligence data processing time, the artificial intelligence result output time, the number of processed car rental reservation requests, the amount of car rental data correctly identified by the artificial intelligence, and the amount of car rental data processed by the artificial intelligence according to the characteristics of the artificial intelligence data. The artificial intelligence data processing time, the artificial intelligence result output time, the number of processed car rental reservation requests, the amount of car rental data correctly identified by the artificial intelligence, and the amount of car rental data processed by the artificial intelligence are numbered t2, t3, g, m2, and f2 respectively.

[0046] The car rental information review unit calculates the car rental information review and artificial intelligence registration synchronization index Ex based on the car rental data and artificial intelligence data. The calculation formula is:

[0047]

[0048] In the formula, Ex represents the car rental information review and artificial intelligence registration synchronization index, m1 and f1 represent the amount of car rental data that has passed the review and the total amount of car rental data submitted, respectively; m2 and f2 represent the amount of car rental data correctly identified by artificial intelligence and the amount of car rental data processed by artificial intelligence, respectively.

[0049] The advantages are: by calculating the car rental data and artificial intelligence data, the car rental information review and artificial intelligence registration synchronization index Ex is calculated. When the value of the car rental information review and artificial intelligence registration synchronization index Ex is low, the car rental reservation data processing module can automatically re-review the failed data, improve the user interface and provide real-time feedback, and manually review the car rental data that has not passed the review to ensure the accuracy and completeness of the data; optimize the user reservation interface, simplify the operation steps, reduce the probability of users filling in errors and giving up reservations, and provide real-time feedback. After the user submits the reservation, the reservation status and problems are displayed in real time to remind the user to check and correct them in time.

[0050] The AI ​​auxiliary unit calculates the AI ​​response time Wx based on the car rental data and AI data. The calculation formula is:

[0051]

[0052] In the formula, Wx represents the AI ​​response time, t1 represents the car rental data input time, t2, t3, and g represent the AI ​​data processing time, AI result output time, and the number of processed requests for car rental reservations, respectively, and t1+t2+t3 represents the total processing time.

[0053] The advantages are: by calculating the artificial intelligence response time Wx, when the artificial intelligence response time Wx is lower than the system preset response time, the car rental reservation data processing module regularly performs system performance benchmark tests (from once every 15 days to once every 3 days) to ensure that the system can still maintain low latency under high load, thereby improving the artificial intelligence response time and solving the problem of imperfect reservation system in the existing technology.

[0054] The car rental abnormality data collection unit numbers the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entries and the number of unqualified car rental reservation information pre-processing identification according to the car rental abnormality data characteristics. The number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entries and the number of unqualified car rental reservation information pre-processing identification are numbered n1, n, n3, and n4.

[0055] The car rental abnormality analysis unit calculates the car rental abnormality index Rx based on the car rental abnormality data, and the calculation formula is:

[0056]

[0057] In the formula, Rx represents the car rental anomaly index, and n1, n, n3, and n4 represent the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entry, and the number of unqualified car rental reservation information preprocessing identifications, respectively.

[0058] The advantages are: by calculating the car rental abnormality index Rx, when the car rental abnormality index Rx is lower than the system preset standard value, the first step is to conduct a detailed analysis of the abnormal order data, the second step is to establish a real-time data monitoring system, the third step is to establish an effective user feedback channel, and the fourth step is to set up a special emergency response team to quickly deal with the user's emergency problems, thereby ensuring that the user experience is not affected.

[0059] The operations performed by the car rental reservation data processing module based on the artificial intelligence registration synchronization index Ex include: when the artificial intelligence registration synchronization index Ex<1, automatically re-examine the failed data, improve the user interface and provide real-time feedback, and manually review the car rental data that has not passed the review to ensure the accuracy and completeness of the data; optimize the user reservation interface, simplify the operating steps, reduce the probability of users filling in errors and abandoning reservations, and provide real-time feedback. After the user submits the reservation, the reservation status and problems are displayed in real time to remind the user to check and correct them in time.

[0060] The operations performed by the car rental reservation data processing module based on the artificial intelligence response time Wx include: when the artificial intelligence response time Wx is less than 1 second, regular system performance benchmark tests are performed to ensure that the system can maintain low latency under high load, and load balancing is implemented in a multi-server environment to ensure that each request is processed quickly.

[0061] The operations performed by the car rental reservation data processing module according to the car rental anomaly index Rx include: when the car rental anomaly index Rx ≥ 0.05, a detailed analysis of the abnormal order data is conducted to find out the main causes of the anomaly (input errors and system failures); trend monitoring is conducted, a real-time data monitoring system is established, and changes in the anomaly index are continuously tracked to promptly identify and respond to problems; an effective user feedback channel is established to enable users to promptly report problems encountered and obtain technical support; a special emergency response team is established to quickly handle users' urgent issues to ensure that the user experience is not affected.

[0062] A method for scheduling a car rental reservation queue includes the following steps:

[0063] Step 1: Establish a car rental reservation data update module, a car rental reservation data analysis module, a car rental reservation data processing module and a car rental reservation data reminder module;

[0064] Step 2: The car rental reservation data update module is divided into a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit;

[0065] Step 3: The car rental reservation data analysis module is divided into a car rental information review unit, an artificial intelligence auxiliary unit and a car rental abnormality analysis unit, and calculates the car rental information review and artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx and car rental abnormality index Rx;

[0066] Step 4: The car rental reservation data processing module automatically troubleshoots and processes the system based on the abnormal information of the artificial intelligence registration synchronization index Ex, the artificial intelligence response time Wx, and the car rental abnormality index Rx;

[0067] Step 5: The car rental reservation data reminder module notifies the relevant departments in advance to carry out data repair or fault repair according to the processing results of the car rental reservation data processing module.

[0068] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A car rental reservation queuing scheduling system, characterized in that: It includes a car rental reservation data update module, a car rental reservation data analysis module, a car rental reservation data processing module and a car rental reservation data reminder module; The car rental reservation data update module includes a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit. The car rental information entry unit obtains car rental data by connecting to online monitoring equipment and sensors through a network. The artificial intelligence data unit obtains artificial intelligence data through an artificial intelligence Internet terminal. The car rental abnormal data collection unit obtains car rental abnormal data through an artificial intelligence Internet terminal. The car rental data entry unit, the artificial intelligence data unit and the car rental abnormal data collection unit are connected to the car rental reservation data analysis module through a network. The car rental reservation data analysis module includes a car rental information review unit, an artificial intelligence auxiliary unit and a car rental abnormality analysis unit. The car rental information review unit calculates the car rental information review and artificial intelligence registration synchronization index Ex according to the car rental data and the artificial intelligence data. The artificial intelligence auxiliary unit calculates the artificial intelligence response time Wx according to the car rental data and the artificial intelligence data. The car rental abnormality analysis unit calculates the car rental abnormality index Rx according to the car rental abnormality data. The car rental information review unit, the artificial intelligence auxiliary unit and the car rental abnormality analysis unit are connected to the car rental reservation data processing module through a network; The car rental reservation data processing module automatically troubleshoots and processes system problems based on the abnormal information of the artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx and car rental abnormality index Rx; The car rental reservation data reminder module notifies relevant departments in advance to carry out data repair or fault repair matters according to the processing result of the car rental reservation data processing module.

2. A car rental reservation queuing scheduling system according to claim 1, characterized in that: The car rental information input unit numbers the car rental data input time, the amount of car rental data that has been reviewed and approved, and the total amount of car rental data submitted according to the car rental data characteristics. The car rental data input time, the amount of car rental data that has been reviewed and approved, and the total amount of car rental data submitted are numbered t1, m1, and f1, respectively.

3. A car rental reservation queuing scheduling system according to claim 1, characterized in that: The artificial intelligence data unit numbers the artificial intelligence data processing time, the artificial intelligence result output time, the number of processed car rental reservation requests, the amount of car rental data correctly identified by the artificial intelligence, and the amount of car rental data processed by the artificial intelligence according to the artificial intelligence data characteristics. The artificial intelligence data processing time, the artificial intelligence result output time, the number of processed car rental reservation requests, the amount of car rental data correctly identified by the artificial intelligence, and the amount of car rental data processed by the artificial intelligence are numbered t2, t3, g, m2, and f2, respectively.

4. A car rental reservation queuing and scheduling system according to claim 3, characterized in that: The car rental information review unit calculates the car rental information review and artificial intelligence registration synchronization index Ex based on the car rental data and artificial intelligence data, and the calculation formula is: In the formula, Ex represents the car rental information review and artificial intelligence registration synchronization index, m1 and f1 represent the amount of car rental data that has passed the review and the total amount of car rental data submitted, respectively; m2 and f2 represent the amount of car rental data correctly identified by artificial intelligence and the amount of car rental data processed by artificial intelligence, respectively.

5. A car rental reservation queuing scheduling system according to claim 4, characterized in that: The artificial intelligence auxiliary unit calculates the artificial intelligence response time W x according to the car rental data and the artificial intelligence data, and the calculation formula is: In the formula, Wx represents the AI ​​response time, t1 represents the car rental data input time, t2, t3, and g represent the AI ​​data processing time, AI result output time, and the number of processed requests for car rental reservations, respectively, and t1+t2+t3 represents the total processing time.

6. A car rental reservation queuing and scheduling system according to claim 1, characterized in that: The car rental abnormality data collection unit numbers the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entries and the number of unqualified car rental reservation information pre-processing identification according to the car rental abnormality data characteristics, and the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entries and the number of unqualified car rental reservation information pre-processing identification are numbered n1, n, n3, and n4.

7. A car rental reservation queuing and scheduling system according to claim 6, characterized in that: The car rental abnormality analysis unit calculates the car rental abnormality index Rx according to the car rental abnormality data, and the calculation formula is: In the formula, Rx represents the car rental anomaly index, and n1, n, n3, and n4 represent the number of abnormal car rental reservation orders, the total number of car rental reservation orders, the number of abnormal car rental reservation entry, and the number of unqualified car rental reservation information preprocessing identifications, respectively.

8. A car rental reservation queuing and scheduling system according to claim 4, characterized in that: The operations performed by the car rental reservation data processing module according to the artificial intelligence registration synchronization index Ex include: when the artificial intelligence registration synchronization index Ex<1, automatically re-examining the failed data, improving the user interface and providing real-time feedback, manually reviewing the car rental data that failed the review, optimizing the user reservation interface, simplifying the operation steps, and providing real-time feedback. After the user submits the reservation, the reservation status and problems are displayed in real time to remind the user to check and correct them in time.

9. A car rental reservation queuing and scheduling system according to claim 7, characterized in that: The operations performed by the car rental reservation data processing module according to the artificial intelligence response time Wx include: when the artificial intelligence response time Wx is less than 1 second, regularly performing system performance benchmark tests and implementing load balancing in a multi-server environment; The operations performed by the car rental reservation data processing module according to the car rental abnormality index Rx include: when the car rental abnormality index Rx≥0.05, a detailed analysis of the abnormal order data is performed, a real-time data monitoring system is established, an effective user feedback channel is established, and a special emergency response team is set up to quickly handle the user's urgent problems.

10. A method for scheduling car rental reservation queues, characterized in that: The following steps are involved: Step 1: Establish a car rental reservation data update module, a car rental reservation data analysis module, a car rental reservation data processing module and a car rental reservation data reminder module; Step 2: The car rental reservation data update module is divided into a car rental data entry unit, an artificial intelligence data unit and a car rental abnormal data collection unit; Step 3: The car rental reservation data analysis module is divided into a car rental information review unit, an artificial intelligence auxiliary unit and a car rental abnormality analysis unit, and calculates the car rental information review and artificial intelligence registration synchronization index Ex, artificial intelligence response time Wx and car rental abnormality index Rx; Step 4: The car rental reservation data processing module automatically troubleshoots and processes the system based on the abnormal information of the artificial intelligence registration synchronization index Ex, the artificial intelligence response time Wx, and the car rental abnormality index Rx; Step 5: The car rental reservation data reminder module notifies the relevant departments in advance to carry out data repair or fault repair according to the processing results of the car rental reservation data processing module.

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