A log information processing method, system and device, electronic equipment and medium

Abstract

The present disclosure provides a log information processing method, system and device, electronic equipment and medium, relates to the technical field of automatic driving, and particularly relates to the fields of intelligent retrieval and big data technology. The specific implementation scheme is as follows: a target log identifier is obtained from a list database, wherein the target log identifier is an identifier of a target log generated by a target vehicle processing a target order in a target time period requested by a user for query. When the user touches to display the target log, the target log is obtained from a trace center. The order state data of the target order in the target time period is obtained from a vehicle and order information database, and abnormal data reported by the target vehicle in the target time period is searched. The vehicle state data reported by the target vehicle in the target time period is obtained from a vehicle state database, and the obtained data is displayed. Therefore, the data query efficiency is improved.

Description

Technical Field

[0001] This disclosure relates to the field of autonomous driving technology, and in particular to the fields of intelligent retrieval and big data technology. Background Technology

[0002] During the daily operation of vehicles, online transportation orders are received, and operational logs are generated during order processing. If errors occur during order processing, the causes of the errors can be analyzed based on the vehicle's logs, allowing for optimization based on the identified causes. Summary of the Invention

[0003] This disclosure provides a log information processing method, system, device, electronic device, and medium.

[0004] A first aspect of this disclosure provides a log information processing method, including:

[0005] Retrieve the target log identifier from the list database. The target log identifier is the identifier of the target log generated by the target vehicle in processing the target order within the target time period requested by the user.

[0006] When a user triggers the display of the target log, the target log corresponding to the target log identifier is retrieved from the traceability platform;

[0007] Obtain the order status data of the target order within the target time period from the vehicle and order information database, and search for abnormal data reported by the target vehicle within the target time period;

[0008] Obtain the vehicle status data reported by the target vehicle within the target time period from the vehicle status database;

[0009] Display the target log, the order status data, and the vehicle status data, and if abnormal data reported by the target vehicle within the target time period is found, display the abnormal data.

[0010] A second aspect of this disclosure provides a log information processing system, including:

[0011] A terminal for performing the method described in any of the first aspects above;

[0012] A list database used to store log identifiers for logs generated during vehicle order processing;

[0013] The traceability platform is used to store logs generated during the vehicle order processing process;

[0014] The vehicle and order information database is used to store abnormal data reported by vehicles, as well as status data during the order processing process;

[0015] The vehicle status database is used to store the operating status data reported by vehicles.

[0016] A third aspect of this disclosure provides a log information processing apparatus, comprising:

[0017] The acquisition module is used to obtain the target log identifier from the list database. The target log identifier is the identifier of the target log generated by the target vehicle in processing the target order within the target time period requested by the user.

[0018] The acquisition module is further configured to, when receiving a user-triggered display of the target log, acquire the target log corresponding to the target log identifier from the traceability platform;

[0019] The query module is used to retrieve the order status data of the target order within the target time period from the vehicle and order information database, and to find the abnormal data reported by the target vehicle within the target time period.

[0020] The acquisition module is also used to acquire vehicle status data reported by the target vehicle within the target time period from the vehicle status database.

[0021] The display module is used to display the target log, the order status data, and the vehicle status data, and to display the abnormal data if abnormal data reported by the target vehicle within the target time period is found.

[0022] A fourth aspect of this disclosure provides an electronic device, including:

[0023] At least one processor; and

[0024] A memory communicatively connected to the at least one processor; wherein,

[0025] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in any one of the first aspects.

[0026] A fifth aspect of this disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method according to any one of the first aspects.

[0027] A sixth aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, implements the method according to any one of the first aspects.

[0028] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0029] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0030] Figure 1 This is a flowchart of a log information processing method provided in an embodiment of this disclosure;

[0031] Figure 2 This is an exemplary schematic diagram of a display interface provided in an embodiment of this disclosure;

[0032] Figure 3 This is an exemplary schematic diagram of a trace homepage provided in an embodiment of this disclosure;

[0033] Figure 4 This is an exemplary schematic diagram of a log details display interface provided in an embodiment of this disclosure;

[0034] Figure 5 This is an exemplary schematic diagram of a log information display interface provided in an embodiment of this disclosure;

[0035] Figure 6 This is an exemplary schematic diagram of a status display interface provided in an embodiment of this disclosure;

[0036] Figure 7 This is a flowchart of the first method for analyzing the cause of anomalies provided in this embodiment;

[0037] Figure 8 This is a flowchart of the second method for analyzing the cause of anomalies provided in this embodiment of the disclosure;

[0038] Figure 9 This is a flowchart of the third method for analyzing the cause of anomalies provided in this embodiment;

[0039] Figure 10 This is an exemplary schematic diagram of a log information processing procedure provided in an embodiment of this disclosure;

[0040] Figure 11 This is a schematic diagram of the structure of a log information processing system provided in an embodiment of this disclosure;

[0041] Figure 12 This is a schematic diagram of the processing procedure of a log information processing system provided in an embodiment of this disclosure;

[0042] Figure 13 This is a schematic diagram of the structure of a log information processing device provided in an embodiment of this disclosure;

[0043] Figure 14 This is a block diagram of an electronic device used to implement the log information processing method of the embodiments of this disclosure. Detailed Implementation

[0044] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0045] Currently, in the daily operation of vehicles, such as in the operation of autonomous taxis, it is often necessary to quickly query and analyze the reasons for errors in online orders and dispatching, which requires the analysis to be based on the logs corresponding to the orders.

[0046] Currently, the existing log provisioning platform consists of a log analysis platform and a trace platform provided by the data visualization tool (Sugar). When a client needs to obtain logs generated during vehicle order processing, it first needs to query the log identifier (logid) link from the log analysis platform. Then, after detecting that the user clicks on that link, it is redirected to the trace platform to retrieve the log corresponding to the logid. This method can only query logs, therefore the amount of data that can be queried is limited, and the query efficiency is low.

[0047] To address the aforementioned problems, this disclosure provides a log information processing method. This method can be applied to terminals, such as mobile phones, tablets, desktop computers, or cloud computing devices. Figure 1 As shown, the method includes the following steps:

[0048] S101. Retrieve the target log identifier from the list database.

[0049] The target log identifier is the identifier of the target log generated by the target vehicle in processing the target order within the target time period requested by the user.

[0050] The target time period, target vehicle, and target order can all be specified by the user. For example, the user can specify to retrieve the logs generated by autonomous vehicle A processing order 001 during the time period from 10:00 to 11:00.

[0051] The list database can be a storage database (click house). The list database can store the logids of the logs generated by each vehicle processing orders within different time periods.

[0052] S102. When a user triggers the display of the target log, the target log corresponding to the target log identifier is obtained from the traceability platform.

[0053] The trace platform can store various log identifiers and logs.

[0054] S103. Obtain the order status data of the target order within the target time period from the vehicle and order information database, and find the abnormal data reported by the target vehicle within the target time period.

[0055] The vehicle and order information database can be a relational database management system (MySQL). The MySQL database can store order status data generated when each order is processed within each time period, as well as abnormal data reported by each vehicle within each time period.

[0056] S104. Obtain the vehicle status data reported by the target vehicle within the target time period from the vehicle status database.

[0057] The vehicle status database can be a data warehouse (harbor), which can store vehicle status data reported by each vehicle in different time periods.

[0058] Vehicles can periodically send vehicle status data to the harbor.

[0059] In this embodiment of the disclosure, in order to improve data acquisition efficiency, data can be acquired in parallel from the traceability platform, the vehicle and order information database, and the vehicle status database.

[0060] S105. Display target logs, order status data, and vehicle status data, and if abnormal data reported by the target vehicle within the target time period is found, display the abnormal data.

[0061] Through the above methods, this embodiment of the present disclosure can not only obtain the target logs generated by the target vehicle in processing the target order within the target time period, but also obtain the vehicle status data and abnormal data reported by the target vehicle within the target time period, as well as the order status data of the target order. Therefore, this embodiment of the present disclosure can obtain more comprehensive data generated by the target vehicle in the process of processing the target order, thereby improving the data query efficiency.

[0062] The log information processing method provided in this disclosure is described in detail below:

[0063] Because the logs generated from vehicle order processing, as well as related vehicle and order information, are very important, to ensure information security, before obtaining the target log identifier from the list database in S101, the electronic device can also verify user permissions, including the following steps:

[0064] Step 1: Receive log query information submitted by logged-in users.

[0065] The log query information includes: target time period, target vehicle identifier (car_id), and target order identifier (schedule_id).

[0066] For example, see Figure 2 , Figure 2 The left box contains the trace homepage. Clicking the "Details" button on the trace homepage will display three boxes on the right, which are the log details display interface, the log information display interface, and the status display interface, respectively. Figure 2 This indicates the positional relationship between the trace homepage and the log details, log information, and status display interfaces. Enlarged views of the trace homepage, log details, log information, and status display interfaces are provided below. Figures 3-6 .

[0067] For a magnified view on the trace homepage, please refer to... Figure 3 Users can enter or select a time period, vehicle ID, and order ID at the top of the trace homepage. Furthermore, as... Figure 3 As shown, users can also enter or select a module, logid, and interface Uniform Resource Locator (URL) on the trace homepage. The module can be represented by its module name. Figure 3 In this code, A or B represents the module name. In practical applications, a module name could be something like "schedule-center" or "orderserver." Different module names correspond to different modules, each providing a different interface URL. Calling different interface URLs enables different functions, generating logs during the process. User-submitted information is used to filter the desired logs. Each module can be deployed in the cloud or on a scheduling server.

[0068] See Figure 3 After detecting that a user clicks the "Query" button on the trace homepage, the information currently selected by the user will be used as the log query information submitted by the user.

[0069] Step 2: Obtain the user information of the logged-in user.

[0070] An electronic device can be equipped with a client for processing log information, which implements the log information processing method provided in this embodiment. Specifically, after logging in to the client, a user can obtain the required target logs, related vehicle information, and order information.

[0071] Before obtaining the target log identifier, such as after the electronic device detects that a user has clicked the "Submit" button on the trace homepage and before retrieving the target log identifier from the list database, the electronic device obtains the username of the logged-in user.

[0072] Step 3: Based on user information, verify whether the logged-in user has query permissions.

[0073] In this embodiment of the disclosure, the electronic device can call the verification interface of the verification server to send the username of the logged-in user to the verification server, requesting the verification server to verify whether the username has query permissions. Afterwards, it receives the verification result from the verification server; wherein the verification result can indicate that the logged-in user has query permissions, or that the logged-in user does not have query permissions.

[0074] Step 4: If the logged-in user has query privileges, then execute the above step S101 to obtain the target log identifier from the list database.

[0075] Conversely, if the logged-in user does not have query privileges, the query will be denied. For example, a message indicating that the user does not have query privileges could be displayed.

[0076] By using the above method, this embodiment of the disclosure can verify whether the logged-in user has query permissions before obtaining logs, vehicle information and order information, and obtain logs, vehicle information and order information only after the verification is passed, thereby ensuring the security of the data stored in the list database, vehicle status database and vehicle and order information database, and reducing the possibility of data being maliciously stolen from these databases.

[0077] The method described above for obtaining the target log identifier from the list database in step S101 can be implemented by sending a list query request to the list database, thereby obtaining the target log identifier from the list database.

[0078] The list query request includes log query information. The list query request is used to request the target log identifier of the target log generated by the target vehicle in processing the target order within the target time period.

[0079] See Figure 3 Once the system detects that a user clicked the "Query" button on the trace homepage and the verification was successful, it sends a list query request to the list database.

[0080] Because multiple logs may be generated by a target vehicle processing a target order within the target time period, the electronic device can retrieve multiple target log identifiers from the list database. See also Figure 3You can display a log list at the bottom of the trace homepage. The log list can include the target log's logid, the time the log was recorded, and the module, interface URL, vehicle ID, and order ID corresponding to the target log. Figure 3 The data in the time, logid, module, interface URL, vehicle ID, and order ID items in the log list are only examples provided in this embodiment of the disclosure; in actual applications, real data can be displayed.

[0081] In this embodiment of the disclosure, the list database can correspond to storage time, module name, logid, interface URL, vehicle ID, and order ID.

[0082] If the user does not select a module name, logid, or interface URL, the system will retrieve all logids corresponding to the other parameters selected by the user from the list database. For example, if the user does not select an interface URL, the system will retrieve logs generated by various interface URLs of the target module during the processing of the target order for the target vehicle within the target time period from the list database. The target module is the module to which the module name submitted by the user belongs.

[0083] See Figure 3 Each line in the log list represents information about a target log, for example... Figure 3 The example illustrates information from six target logs. Each log entry corresponds to a "Details" button. When a user clicks the "Details" button, it is determined that the target log corresponding to that button needs to be displayed. At this point, steps S102-S105 are executed for that target log. It is evident that within the target time period, there may be multiple target logs generated by the target vehicle processing the target order, and at least one of these target logs needs to be displayed. Since the log analysis method for each target log is the same, this embodiment uses one target log as an example for explanation.

[0084] Using the above method, embodiments of this disclosure can search for the logid of the target log required by the user from the list database according to the user's needs, thereby displaying a list of logids of each target log to the user, so that the user can further select the target log to be displayed.

[0085] In some embodiments of this disclosure, the log query information may further include a target log level, a target module identifier, and / or a target interface identifier, wherein the target module is used to provide a specified function for processing orders through the target interface and generate logs. For example, log levels may include: debug, warning, notice, and / or trace, and the target log level is at least one of these levels.

[0086] Correspondingly, a list query request can be used to request the target log identifier of the target log at the target log level generated by the target vehicle in processing the target order within the target time period.

[0087] This embodiment of the disclosure allows users to select the log level required by the user. Compared with directly obtaining logs of various levels, this embodiment of the disclosure can refine the granularity of log acquisition, making the acquired logs more accurate and more convenient for subsequent log analysis.

[0088] Similarly, the above-mentioned method of obtaining the target log corresponding to the target log identifier from the traceability platform in S102 can be implemented as follows: sending a log acquisition request to the traceability platform, wherein the log acquisition request includes the target log identifier, thereby obtaining the target log from the traceability platform.

[0089] After obtaining the target log, see Figure 2 Electronic devices can Figure 2 The middle interface of the three right-hand panes displays the detailed content of the target log. This middle interface can be called the log details display interface; a magnified view of the log details display interface is shown below. Figure 4 As shown, the specific content of the log is displayed. Figure 4 In the "Raw Data" section. For example... Figure 4 As shown, the log details display interface can also display the corresponding time of the log, the module name of the module, etc. Figure 4 The data in the time, module, and raw data items are merely examples provided in this disclosure embodiment; in actual applications, real data may be displayed.

[0090] See Figure 4 The log entries have corresponding "Details" buttons. Clicking the "Details" button will display... Figure 2The bottommost of the three interfaces on the right displays information related to the target log. This bottommost interface can be called the log information display interface. Before clicking the "Details" button, the user can select the data items to be displayed within the log information display interface. For example, the data items selectable in the log details display interface include: request parameters (request_params), response (response), logid, application programming interface (api), status (status), cost (cost), Internet Data Center (IDC), user Internet Protocol address (user_ip), local Internet Protocol address (local_ip), method (method), Uniform Resource Identifier (URI), module (module), vehicle identifier (car_id), order identifier (schedule_id), and instance. Since the logs are generated by the vehicle or passenger using functions provided by the server, user_ip is the IP address of the vehicle or passenger using the function, local_ip is the server IP address, and instance is the device name or device address storing the logs.

[0091] A magnified view of the log information display interface is shown below. Figure 5 As shown, the log information display interface can display various data of the target log, such as... Figure 5 This includes the log's ak, ts, token, response, module, car_id, and schedule_id. Here, ak is the Access Key Id, used to identify the logged-in user. ts is the timestamp, and token is the access token. response is the response information after calling the API URL. module is the module name of the module to which this API URL belongs. Figure 5 The data in the ak, ts, token, response, module, car_id, and schedule_id items are merely examples provided in this embodiment of the disclosure; in actual applications, real data may be displayed.

[0092] Accordingly, the above-mentioned method of obtaining the vehicle status data reported by the target vehicle within the target time period from the vehicle status database in S104 can be implemented as follows: sending a vehicle status acquisition request to the vehicle status database, wherein the vehicle status acquisition request includes the target time period and the target vehicle identifier, thereby obtaining the vehicle status data reported by the target vehicle within the target time period from the vehicle status database.

[0093] The vehicle status data may include the vehicle's network latency and alarm information.

[0094] After obtaining the vehicle status data, see Figure 2Electronic devices can Figure 2 The top screen of the three screens on the right displays vehicle status data. This top screen can be called the status display screen; see [link / reference]. Figure 6 , Figure 6 This is a magnified view of the status display interface. Figure 6 The line graph in the image represents time on the horizontal axis and network latency on the vertical axis. Figure 6 The line graph represents the vehicle's network latency as a function of time within a target time period, allowing users to more intuitively view the vehicle's network status during that period. The horizontal axis represents different times, with each XXXX-XX-XX XX:XX:XX representing a specific moment, increasing sequentially to the right; in practical applications, actual times can be displayed. The vertical axis represents different network latencies, increasing sequentially upwards; in practical applications, preset network latencies can be displayed. The status display interface can also show alarm information reported by the vehicle within the target time period. Figure 6 Not shown in the image.

[0095] The above-mentioned method of obtaining the order status data of the target order within the target time period from the vehicle and order information database and searching for the abnormal data reported by the target vehicle within the target time period in S103 can be implemented as follows: sending a query request to the vehicle and order information database, wherein the query request includes the target time period, the target vehicle identifier, and the target order identifier, thereby obtaining the order status data of the target order within the target time period from the vehicle and order information database, and if the vehicle and order information database stores the abnormal data reported by the target vehicle within the target time period, obtaining the abnormal data from the vehicle and order information database.

[0096] After obtaining the order status data of the target orders within the target time period, see [link / reference]. Figure 2 Electronic devices can Figure 2 The order status data is displayed at the top right of the screen. See also... Figure 6 The status display interface can also show the order timeline, which shows the status changes of the target order within the target time period. Figure 6 In the order timeline, each XXXX-XX-XXXX:XX:XX represents a different moment, increasing sequentially from bottom to top. Each moment corresponds to an order status. The moments and statuses in the order timeline are examples provided in this embodiment of the disclosure; in actual applications, real data can be displayed.

[0097] from Figures 2-6As can be seen from the present invention, the embodiments can integrate logs, vehicle information and order information from multiple channels, and process the acquired information to display the complex raw data in a visual way, thereby displaying the relevant data of the logs in a more detailed and intuitive way, and helping to analyze the reasons for order anomalies.

[0098] Currently, existing technologies only acquire logs generated by vehicle order processing, and rely solely on manual analysis of the reasons for order anomalies from these logs. However, analyzing the reasons for order anomalies from logs is quite difficult, thus placing too high a barrier to entry for analysts.

[0099] The embodiments disclosed herein can not only acquire logs, but also acquire vehicle status data and abnormal data reported by the target vehicle within the target time period, as well as order status data of the target order. By using the acquired data to assist log analysis, it is easier and more accurate to locate the cause of order anomalies, reducing the difficulty of log analysis, improving the efficiency of log analysis, and making it easier to optimize the cause of anomalies in the future.

[0100] The following explains how to use the acquired information to assist in analyzing the causes of order anomalies:

[0101] In this embodiment of the disclosure, after obtaining the order status data of the target order within the target time period in S104, the electronic device can further determine whether the statuses included in the order status data match the statuses included in the standard order cycle.

[0102] If there is no match, the abnormal time period of the target order is determined based on the various states included in the order status data, and the abnormal type of the order during the abnormal time period is determined, and then the abnormal type of the order is displayed.

[0103] If a match is found, it confirms that there were no abnormalities in the processing of target orders for the target vehicle within the target time period.

[0104] If the order of the statuses in the order status data is the same as the order of the statuses in the standard order cycle, then it is considered a match; otherwise, it is considered a mismatch.

[0105] A standard order cycle refers to the various stages an order goes through from its creation to completion. For example, a standard order cycle includes the following states: Pending Scheduling, Pending Order Acceptance, Order Accepted, Departure to Pick Up Passengers, Arrival at Origin, Start of Trip, Arrival at Destination, and Completed. Suppose the order status data includes the states: Order Accepted, Departure to Pick Up Passengers, and Pending Order Acceptance; since in a standard order cycle, after Departure to Pick Up Passengers, the order should be in the Arrival at Origin state, this order status data does not match the standard order cycle.

[0106] In cases of mismatch, two adjacent states in the order status data that differ from the standard order cycle's status order can be identified. The time interval between these two states is considered an abnormal time interval. Based on a pre-defined correspondence between order status and abnormal type, the abnormal type corresponding to these two adjacent states is determined. For example, among the three states "Order Accepted," "Departure to Pick Up Passengers," and "Pending Order Acceptance," the states that differ from the standard order cycle's status order are "Departure to Pick Up Passengers" and "Pending Order Acceptance." The time interval between "Departure to Pick Up Passengers" and "Pending Order Acceptance" is considered an abnormal time interval, and based on the pre-defined correspondence between order status and abnormal type, the abnormal type is determined to be "Order Reassignment."

[0107] Abnormal time periods and abnormal types can also be determined by other methods, and this disclosure does not specifically limit them.

[0108] Using the above method, this embodiment of the disclosure can obtain the complete status flow of the target order within the target time period, thereby analyzing the abnormal type of the target order based on the changes in the status of the target order, realizing automated analysis of abnormal types. Compared with manual log analysis, it is more convenient and faster, and reduces the workload of manual analysis.

[0109] In some embodiments of this disclosure, if an anomaly is determined in the target order, the cause of the anomaly can be further analyzed. The analysis of the cause of the anomaly is explained below:

[0110] See Figure 7 After acquiring vehicle status data in S104, the electronic device can also perform the following steps:

[0111] S701. Obtain the network latency of the target vehicle at each time point during the abnormal time period from the vehicle status data.

[0112] Vehicles periodically report network latency to the harbor, so electronic devices can obtain the vehicle's network latency at each moment during abnormal periods from the harbor.

[0113] S702. If the network latency is higher than the latency threshold at any time during the abnormal period, the cause of the abnormal period is determined to be that the target vehicle has a network abnormality.

[0114] Since the order status flow was abnormal during the abnormal period, and the network latency was high during this period, it can be determined that the abnormality during the abnormal period was due to network abnormalities in the target vehicle.

[0115] Conversely, if the network latency at each moment within the abnormal time period is lower than or equal to the latency threshold, then the cause of the abnormal time period is determined to be unrelated to vehicle network latency.

[0116] S703, Display the cause of the error.

[0117] Using the above method, the embodiments of this disclosure can automatically analyze whether order anomalies are related to vehicle network latency. Compared with manual log analysis, this method is more convenient and faster, and reduces the workload of manual analysis.

[0118] See Figure 8 After acquiring vehicle status data in S104, the electronic device can also perform the following steps:

[0119] S801. Determine whether the vehicle status data within the abnormal time period includes vehicle alarm information; if it includes vehicle alarm information, proceed to S802; if it does not include vehicle alarm information, proceed to S804.

[0120] Vehicle alarm information is used to indicate that there is a hardware malfunction in the target vehicle. For example, vehicle alarm information may include: the seat belt has been opened abnormally, the seat has detected that the user has left the seat, or the vehicle battery is low.

[0121] S802. Determine the alarm cause corresponding to the vehicle alarm information, and determine the abnormal cause during the abnormal time period, including the alarm cause.

[0122] Based on a preset correspondence between vehicle alarm information and alarm causes, the alarm causes corresponding to the vehicle alarm information included in the vehicle status data can be determined. For example, if the vehicle alarm information is "low battery," the corresponding alarm cause could be "low battery prevents further order processing." Or, if the vehicle alarm information is "seatbelt abnormally opened," the corresponding alarm cause could be "passenger exits prematurely."

[0123] S803, Display the cause of the error.

[0124] S804. The cause of the abnormality during the abnormal time period is determined to be unrelated to the vehicle alarm.

[0125] Using the above method, this embodiment of the disclosure can automatically analyze whether order anomalies are related to vehicle anomaly alarms. Compared with manual log analysis, this method is more convenient and faster, and reduces the workload of manual analysis.

[0126] See Figure 9 After S103 locates the abnormal data reported by the vehicle, the electronic device can also perform the following steps:

[0127] S901. Determine whether the abnormal data reported by the target vehicle within the target time period includes target abnormal data. Target abnormal data refers to abnormal data within the abnormal time period. If target abnormal data is included, proceed to S902; if target abnormal data is not included, proceed to S904.

[0128] The abnormal data reported by the target vehicle can include: cloud routing, map upgrade failure, or vehicle-side system malfunction. Among these, cloud routing indicates an abnormal communication between the vehicle and the cloud, and map upgrade failure indicates that the electronic map used in the vehicle failed to upgrade.

[0129] S902. Determine the vehicle anomaly type corresponding to the target anomaly data, and determine the anomaly cause, including the vehicle anomaly type, for the anomaly time period.

[0130] Specifically, the vehicle exception type refers to the exception type of the software in the target vehicle that processes the target order. In other words, the vehicle exception type is the exception type of the client running in the target vehicle that processes the order.

[0131] Based on a preset correspondence between abnormal data and vehicle abnormality types, the vehicle abnormality type corresponding to the target abnormal data can be determined. For example, if the abnormal data is cloud routing, the vehicle abnormality type can be determined as communication abnormality between the vehicle and the cloud.

[0132] S903, Display the cause of the error.

[0133] S904. The cause of the abnormal time period is determined to be unrelated to vehicle abnormalities.

[0134] Using the above method, the embodiments of this disclosure can automatically analyze whether the abnormality of an order is related to the abnormal operation of the client running in the vehicle to process the order. Compared with the method of manually analyzing logs, it is more convenient and faster, and reduces the workload of manual analysis.

[0135] In some embodiments of this disclosure, the target log records the device address where the target log is located, and the electronic device can display the device name to the user based on the device address in the target log.

[0136] That is, after obtaining the target log in S102 above, the electronic device can also obtain the target device address that records the target log from the target log, find the target device name corresponding to the target device address from the preset correspondence between the device address and the device name, and then display the target device name.

[0137] The target device address can be the IP address of the target device. Electronic devices can find the target device name corresponding to the IP address of the target device based on the preset correspondence between each IP address and device name.

[0138] Using the above method, embodiments of this disclosure can display the name of the device that records the target log, thereby facilitating the tracing of the log's source so that the target log can be subsequently obtained or processed from the target device.

[0139] See Figure 10The following describes the overall process of the log information processing method provided in this embodiment, taking into account practical application scenarios:

[0140] S1001, The terminal receives log query information submitted by the user on the trace homepage.

[0141] S1002. The terminal sends a list query request to the click house to obtain the logid and interface URL from the click house.

[0142] The list query request includes log query information.

[0143] S1003, The terminal displays the login ID and the interface URL.

[0144] S1004. When the terminal detects that the user clicks the details button corresponding to the logid, it sends a log retrieval request to the trace middleware to retrieve the target log corresponding to the logid from the trace middleware.

[0145] The log retrieval request includes the logid.

[0146] S1005. The terminal sends a vehicle status acquisition request to the harbor, thereby obtaining the network latency and vehicle alarm information reported by the target vehicle within the target time period from the harbor.

[0147] The vehicle status retrieval request includes the target time period and the target vehicle ID.

[0148] S1006. The terminal sends a query request to MySQL to obtain the abnormal data reported by the target vehicle within the target time period, as well as the order status data of the target order within the target time period from MySQL.

[0149] The query request includes the target time period, the target vehicle ID, and the target order ID.

[0150] S1007. The terminal displays target logs, network latency, vehicle alarm information, order status data, and abnormal data.

[0151] Figure 10 The specific implementation methods for each step can be found in the above description, and will not be repeated here.

[0152] The log information processing method provided in this disclosure can simultaneously acquire logs, vehicle information, and order information, greatly improving data acquisition efficiency, simplifying the log query process, and enhancing the efficiency of locating the cause of order anomalies. It can provide a reference for analysts to locate the cause of anomalies and optimize order assignment and scheduling, thus facilitating an increase in the success rate of order dispatch.

[0153] Based on the same inventive concept, corresponding to the above method embodiments, this disclosure also provides a log information processing system, see [link to relevant documentation]. Figure 11 The system includes: terminal 1101, list database 1102, traceability platform 1103, vehicle and order information database 1104, and vehicle status database 1105;

[0154] Terminal 1101 is used to execute the above-mentioned log information processing method;

[0155] List database 1102 is used to store log identifiers for logs generated during vehicle order processing;

[0156] The traceability platform 1103 is used to store logs generated by each vehicle's order processing.

[0157] The vehicle and order information database 1104 is used to store abnormal data reported by vehicles and status data during the order processing process;

[0158] Vehicle status database 1105 is used to store the operating status data reported by vehicles.

[0159] Through the above system, in this embodiment of the present disclosure, the terminal can not only obtain the target log generated by the target vehicle in processing the target order within the target time period, but also obtain the vehicle status data and abnormal data reported by the target vehicle within the target time period, as well as the order status data of the target order. Therefore, this embodiment of the present disclosure can obtain more comprehensive data generated during the process of the target vehicle processing the target order, thereby improving the data query efficiency.

[0160] See Figure 12 The following describes the processing procedure of the log information processing system provided in this embodiment, based on practical application scenarios:

[0161] The terminal is equipped with a client that provides trace front-end services and back-end API services. The trace front-end service is used to obtain log query information such as the timestamp of the target time period submitted by the user, the car_id of the target vehicle, the module name, and the schedule_id of the target order.

[0162] The backend API service verifies whether the logged-in user has query permissions. After confirming that the logged-in user has query permissions, it sends a list query request to the click house. The list query request includes log query information, thereby obtaining the logid and interface URL from the click house.

[0163] When the trace frontend service detects that a user clicks the log details button, it sends a log retrieval request to the trace middleware through the backend API service. The log retrieval request includes the logid, thereby retrieving the log corresponding to the logid from the trace middleware.

[0164] The backend API service sends a vehicle status retrieval request to the harbor, which includes the target time period and the target vehicle ID, thereby retrieving the network latency and vehicle alarm information reported by the target vehicle within the target time period from the harbor.

[0165] The backend API service sends a query request to MySQL, which includes the target time period, target vehicle ID, and target order ID, in order to retrieve the abnormal data reported by the target vehicle within the target time period and the order status data of the target order within the target time period from MySQL.

[0166] The trace front-end service displays the received target logs, network latency, vehicle alarm information, order status data, and abnormal data.

[0167] Based on the same inventive concept, and corresponding to the above method embodiments, this disclosure provides a log information processing apparatus, such as... Figure 13 As shown, the device includes: an acquisition module 1301, a query module 1302, and a display module 1303;

[0168] The acquisition module 1301 is used to obtain the target log identifier from the list database. The target log identifier is the identifier of the target log generated by the target vehicle in processing the target order within the target time period requested by the user.

[0169] The acquisition module 1301 is also used to obtain the target log corresponding to the target log identifier from the traceability platform when it receives a user trigger to display the target log;

[0170] The query module 1302 is used to retrieve the order status data of the target order within the target time period from the vehicle and order information database, and to find the abnormal data reported by the target vehicle within the target time period.

[0171] The acquisition module 1301 is also used to acquire vehicle status data reported by the target vehicle within the target time period from the vehicle status database.

[0172] The display module 1303 is used to display target logs, order status data, and vehicle status data, and to display abnormal data if abnormal data reported by the target vehicle within the target time period is found.

[0173] In some embodiments of this disclosure, the device may further include:

[0174] The determination module is used to determine, after obtaining the order status data of the target order within the target time period, whether the statuses included in the order status data match the statuses included in the standard order cycle.

[0175] The determination module is also used to determine the abnormal time period of the target order based on the various states included in the order status data if there is a mismatch, and to determine the abnormal type of the order during the abnormal time period.

[0176] Display module 1303 is also used to display order exception types.

[0177] In some embodiments of this disclosure,

[0178] The acquisition module 1301 is also used to acquire the network latency of the target vehicle at each moment during the abnormal time period from the vehicle status data reported by the target vehicle within the target time period after acquiring the vehicle status data reported by the target vehicle within the target time period from the vehicle status database.

[0179] The determination module is also used to determine the cause of the abnormality during the abnormal time period if the network latency at any moment within the abnormal time period is higher than the latency threshold, including the target vehicle having a network abnormality.

[0180] Display module 1303 is also used to display the cause of the error.

[0181] In some embodiments of this disclosure,

[0182] The determination module is also used to determine whether the vehicle status data in the abnormal time period includes vehicle alarm information after obtaining the vehicle status data reported by the target vehicle within the target time period from the vehicle status database. The vehicle alarm information is used to indicate that the target vehicle has a hardware abnormality.

[0183] The determination module is also used to determine the alarm cause corresponding to the vehicle alarm information if vehicle alarm information is included, and to determine the abnormal cause of the abnormal time period, including the alarm cause.

[0184] Display module 1303 is also used to display the cause of the error.

[0185] In some embodiments of this disclosure,

[0186] The determination module is also used to determine, after finding the abnormal data reported by the target vehicle within the target time period, whether the abnormal data reported by the target vehicle within the target time period includes the target abnormal data; the target abnormal data is the abnormal data within the abnormal time period.

[0187] The determination module is also used to determine the vehicle anomaly type corresponding to the target anomaly data if the target anomaly data is included, and to determine the anomaly cause of the anomaly time period, including the vehicle anomaly type, wherein the vehicle anomaly type is the anomaly type of the software that processes the target order in the target vehicle.

[0188] Display module 1303 is also used to display the cause of the error.

[0189] In some embodiments of this disclosure, the device may further include:

[0190] The receiving module is used to receive log query information submitted by the logged-in user before obtaining the target log identifier from the list database. The log query information includes the target time period, the target vehicle identifier, and the target order identifier.

[0191] The acquisition module 1301 is also used to acquire the user information of the logged-in user after receiving the log query information submitted by the logged-in user;

[0192] The verification module is used to verify whether a logged-in user has query permissions based on user information.

[0193] The return module is used to trigger the retrieval module 1301 to perform the step of retrieving the target log identifier from the list database if the logged-in user has query permissions.

[0194] In some embodiments of this disclosure, the log query information further includes: a target log level, a target module identifier, and / or a target interface identifier, wherein the target module is used to provide specified functions for processing orders and generating logs through the target interface.

[0195] In some embodiments of this disclosure,

[0196] The acquisition module 1301 is also used to obtain the target device address that records the target log from the target log after obtaining the target log corresponding to the target log identifier from the traceability platform;

[0197] The query module 1302 is also used to find the target device name corresponding to the target device address from the preset correspondence between device address and device name;

[0198] Display module 1303 is also used to display the name of the target device.

[0199] The technical solutions disclosed herein involve the collection, storage, use, processing, transmission, provision, and disclosure of logs, vehicle information, and order information, all of which comply with relevant laws and regulations and do not violate public order and good morals.

[0200] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0201] Figure 14 A schematic block diagram of an example electronic device 1400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0202] like Figure 14 As shown, the electronic device 1400 includes a computing unit 1401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1402 or a computer program loaded from a storage unit 1408 into a random access memory (RAM) 1403. The RAM 1403 may also store various programs and data required for the operation of the electronic device 1400. The computing unit 1401, ROM 1402, and RAM 1403 are interconnected via a bus 1404. An input / output (I / O) interface 1405 is also connected to the bus 1404.

[0203] Multiple components in electronic device 1400 are connected to I / O interface 1405, including: input unit 1406, such as keyboard, mouse, etc.; output unit 1407, such as various types of monitors, speakers, etc.; storage unit 1408, such as disk, optical disk, etc.; and communication unit 1409, such as network card, modem, wireless transceiver, etc. Communication unit 1409 allows electronic device 1400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0204] The computing unit 1401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1401 performs the various methods and processes described above, such as the log information processing method. For example, in some embodiments, the log information processing method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 1408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 1400 via ROM 1402 and / or communication unit 1409. When the computer program is loaded into RAM 1403 and executed by the computing unit 1401, one or more steps of the log information processing method described above may be performed. Alternatively, in other embodiments, the computing unit 1401 may be configured to perform a log information processing method by any other suitable means (e.g., by means of firmware).

[0205] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0206] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0207] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0208] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0209] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0210] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0211] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0212] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A log information processing method, comprising: Retrieve the target log identifier from the list database. The target log identifier is the identifier of the target log generated by the target vehicle in processing the target order within the target time period requested by the user. When a user triggers the display of the target log, the target log corresponding to the target log identifier is retrieved from the traceability platform; Obtain the order status data of the target order within the target time period from the vehicle and order information database, and search for abnormal data reported by the target vehicle within the target time period; Obtain the vehicle status data reported by the target vehicle within the target time period from the vehicle status database; Display the target log, the order status data, and the vehicle status data, and if abnormal data reported by the target vehicle within the target time period is found, display the abnormal data. After obtaining the order status data of the target order within the target time period, the method further includes: Determine whether the order of the statuses included in the order status data is the same as the order of the statuses included in the standard order cycle; If they are different, then identify two adjacent states in the order status data that are different from the status order in the standard order cycle, take the time period between the two adjacent states as the abnormal time period, and determine the abnormal type corresponding to the two adjacent states according to the preset correspondence between order status and abnormal type. Display order exception types; Determine whether the abnormal data reported by the target vehicle within the target time period includes target abnormal data; the target abnormal data refers to the abnormal data within the abnormal time period. If the target abnormal data is included, then the vehicle abnormality type corresponding to the target abnormal data is determined, and the abnormality cause of the abnormal time period is determined to include the vehicle abnormality type, wherein the vehicle abnormality type is the abnormality type of the software in the target vehicle that processes the target order. The cause of the aforementioned anomaly is explained.

2. The method according to claim 1, after obtaining the vehicle status data reported by the target vehicle within the target time period from the vehicle status database, the method further includes: From the vehicle status data, obtain the network latency of the target vehicle at each time point during the abnormal time period; If the network latency is higher than the latency threshold at any moment during the abnormal time period, then the cause of the abnormality during the abnormal time period is determined to include the target vehicle having a network abnormality. The cause of the aforementioned anomaly is explained.

3. The method according to claim 1, after obtaining the vehicle status data reported by the target vehicle within the target time period from the vehicle status database, the method further includes: Determine whether the vehicle status data within the abnormal time period includes vehicle alarm information, wherein the vehicle alarm information is used to indicate that the target vehicle has a hardware abnormality; If vehicle alarm information is included, then the alarm reason corresponding to the vehicle alarm information is determined, and the abnormal reason of the abnormal time period is determined to include the alarm reason; The cause of the aforementioned anomaly is explained.

4. The method according to any one of claims 1-3, wherein before obtaining the target log identifier from the list database, the method further comprises: Receive log query information submitted by the logged-in user, the log query information including the target time period, target vehicle identifier, and target order identifier; Obtain the user information of the logged-in user; Based on the user information, verify whether the logged-in user has query permissions; If the logged-in user has query privileges, then the step of retrieving the target log identifier from the list database is executed.

5. The method according to claim 4, wherein, The log query information also includes: target log level, target module identifier and / or target interface identifier, wherein the target module is used to provide specified functions for processing orders and generate logs through the target interface.

6. The method according to any one of claims 1-3, after obtaining the target log corresponding to the target log identifier from the traceability platform, the method further includes: Obtain the target device address that records the target log from the target log; Find the target device name corresponding to the target device address from the preset correspondence between device address and device name; Display the name of the target device.

7. A log information processing system, comprising: A terminal for performing the method described in any one of claims 1-6; A list database used to store log identifiers for logs generated during vehicle order processing; The traceability platform is used to store logs generated during the vehicle order processing process; The vehicle and order information database is used to store abnormal data reported by vehicles, as well as status data during the order processing process; The vehicle status database is used to store the operating status data reported by vehicles.

8. A log information processing device, comprising: The acquisition module is used to obtain the target log identifier from the list database. The target log identifier is the identifier of the target log generated by the target vehicle in processing the target order within the target time period requested by the user. The acquisition module is further configured to, when receiving a user-triggered display of the target log, acquire the target log corresponding to the target log identifier from the traceability platform; The query module is used to retrieve the order status data of the target order within the target time period from the vehicle and order information database, and to find the abnormal data reported by the target vehicle within the target time period. The acquisition module is also used to acquire vehicle status data reported by the target vehicle within the target time period from the vehicle status database. The display module is used to display the target log, the order status data, and the vehicle status data, and to display the abnormal data if abnormal data reported by the target vehicle within the target time period is found. The device further includes: The determining module is used to determine, after obtaining the order status data of the target order within the target time period, whether the order order status data includes the same order as the order of the status in the standard order cycle. The determining module is further configured to, if different, determine two adjacent states in the order status data that are different from the status order in the standard order cycle, take the time period between the two adjacent states as the abnormal time period, and determine the abnormal type corresponding to the two adjacent states according to the preset correspondence between order status and abnormal type. The display module is also used to display order exception types; The determining module is further configured to, after searching for abnormal data reported by the target vehicle within the target time period from the vehicle and order information database, determine whether the abnormal data reported by the target vehicle within the target time period includes target abnormal data; the target abnormal data is abnormal data within the abnormal time period. The determining module is further configured to, if the target abnormal data is included, determine the vehicle abnormality type corresponding to the target abnormal data, and determine that the abnormality cause of the abnormal time period includes the vehicle abnormality type, wherein the vehicle abnormality type is the abnormality type of the software in the target vehicle that processes the target order. The display module is also used to display the cause of the anomaly.

9. The apparatus according to claim 8, The acquisition module is further configured to, after acquiring the vehicle status data reported by the target vehicle within the target time period from the vehicle status database, acquire the network latency of the target vehicle at each moment within the abnormal time period from the vehicle status data. The determining module is further configured to determine that if the network latency is higher than the latency threshold at any moment during the abnormal time period, the cause of the abnormality during the abnormal time period includes the target vehicle having a network abnormality. The display module is also used to display the cause of the anomaly.

10. The apparatus according to claim 8, The determining module is further configured to, after obtaining the vehicle status data reported by the target vehicle within the target time period from the vehicle status database, determine whether the vehicle status data within the abnormal time period includes vehicle alarm information, wherein the vehicle alarm information is used to indicate that the target vehicle has a hardware abnormality. The determining module is further configured to, if vehicle alarm information is included, determine the alarm cause corresponding to the vehicle alarm information, and determine that the abnormal cause of the abnormal time period includes the alarm cause; The display module is also used to display the cause of the anomaly.

11. The apparatus according to any one of claims 8-10, further comprising: The receiving module is configured to receive log query information submitted by the logged-in user before obtaining the target log identifier from the list database. The log query information includes the target time period, the target vehicle identifier, and the target order identifier. The acquisition module is also used to acquire the user information of the logged-in user; The verification module is used to verify whether the logged-in user has query permissions based on the user information. The return module is used to trigger the acquisition module to perform the step of obtaining the target log identifier from the list database if the logged-in user has query permissions.

12. The apparatus according to claim 11, wherein, The log query information also includes: target log level, target module identifier and / or target interface identifier, wherein the target module is used to provide specified functions for processing orders and generate logs through the target interface.

13. The apparatus according to any one of claims 8-10, The acquisition module is further configured to, after acquiring the target log corresponding to the target log identifier from the traceability platform, acquire the target device address that records the target log from the target log; The query module is also used to find the target device name corresponding to the target device address from the preset correspondence between device address and device name; The display module is also used to display the name of the target device.

14. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

15. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

16. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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