Data acquisition method and device, electronic equipment and storage medium

Abstract

The invention discloses a data acquisition method and device, electronic equipment and a storage medium, and relates to the technical field of vehicles, and the main technical scheme comprises the steps: firstly, determining a monitoring mode according to the aging demand of a monitoring project, and configuring a monitoring strategy of the monitoring project according to the monitoring mode; wherein the monitoring strategy is obtained through configuration according to monitoring items, and different monitoring items correspond to different monitoring strategies; secondly, according to the configured monitoring strategy, abnormal information in each target vehicle is collected; and finally, generating statistical information of the abnormal information according to a preset time threshold value, and pushing the statistical information to a specified user according to a preset notification mode. The log data of the vehicle is monitored through the pre-configured monitoring strategy, the abnormal information of the vehicle in the using process can be found in time, the abnormal problem can be found in time, then the abnormal problem is solved in time, the risk of large-area outbreak of the abnormal problem is avoided, and the use experience of a user is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a data collection method and device, an electronic device, and a storage medium. Background Art

[0002] With the continuous advancement of science and technology and the development of intelligence, the application of vehicle software products is becoming more and more extensive. These software products include vehicle operating systems, in-vehicle entertainment systems, navigation systems, vehicle diagnostic systems, etc. They play an important role in improving vehicle performance, providing a better driving experience, and enhancing vehicle safety.

[0003] Due to the complexity and diversity of vehicle software products, functional abnormalities often occur, including software crashes, unresponsive functions, interface freezes, data synchronization errors, etc.; these problems not only affect the user experience, but may also lead to vehicle performance degradation and create safety hazards.

[0004] At present, software product functional anomalies need to rely on active feedback from users. If an abnormal problem is not reported by users or the amount of feedback is small, the abnormal problem will not be known or taken seriously in a timely manner, which will have a negative impact on the user experience. Summary of the Invention

[0005] The present disclosure provides a data collection method, device, electronic device, and storage medium, the main purpose of which is to solve the problem of being unable to promptly obtain notification of software function anomalies.

[0006] According to a first aspect of the present disclosure, a data collection method is provided, comprising:

[0007] Determine a monitoring method based on the timeliness requirements of the monitored items, and configure a monitoring strategy for the monitored items based on the monitoring method; wherein the monitoring strategy is configured based on the monitored items, and different monitoring items correspond to different monitoring strategies;

[0008] Collect abnormal information from each target vehicle according to the configured monitoring strategy;

[0009] Generate statistical information of each abnormal information according to a preset time period, and push the statistical information to a designated user.

[0010] Optionally, the monitoring method includes offline monitoring, the monitoring item corresponds to at least one vehicle model, different monitoring items correspond to different buried events, and different monitoring strategies include different monitoring indicators and monitoring parameters;

[0011] Determining a monitoring method according to the timeliness requirement of the monitoring item, and configuring a monitoring strategy for the monitoring item according to the monitoring method includes:

[0012] Determine the target vehicle according to the vehicle model corresponding to the monitoring item;

[0013] In the case where the monitoring item has no timeliness requirement, determining that the monitoring data source is each historical log data of the target vehicle, and determining the buried event corresponding to the monitoring item in each historical log data;

[0014] According to the monitoring items, monitoring indicators in the monitoring strategy are determined, and monitoring parameters of the monitoring indicators are configured according to the monitoring accuracy requirements of the monitoring items.

[0015] Optionally, the monitoring method includes real-time monitoring,

[0016] The monitoring item corresponds to at least one vehicle model, different monitoring items correspond to different buried events, and different monitoring items correspond to different monitoring indicators and monitoring parameters;

[0017] Determining a monitoring method according to the timeliness requirement of the monitoring item, and configuring a monitoring strategy for the monitoring item according to the monitoring method includes:

[0018] Determine each target vehicle according to the vehicle model corresponding to the monitoring item;

[0019] In the case where the monitoring project has a time limit requirement, determining that the monitoring data source is each real-time log data of each target vehicle, and determining the buried event corresponding to the monitoring project in each real-time log data;

[0020] Determine the monitoring indicators in the monitoring strategy according to the monitoring items, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring items;

[0021] A real-time processing program is configured for each preset exception type respectively; wherein different exception types correspond to different real-time processing programs.

[0022] Optionally, collecting abnormal information from each target vehicle according to the configured monitoring strategy further includes:

[0023] In the case of real-time monitoring, after abnormal information is collected from the target vehicle, the abnormal type corresponding to the abnormal information is determined;

[0024] A corresponding real-time processing program is determined based on the exception type, and the exception information is processed based on the real-time processing program.

[0025] Optionally, it is characterized in that the monitoring indicators include at least one of signals and events, and the monitoring parameters include at least one of execution time, execution frequency, abnormal threshold range, and push to designated users.

[0026] Optionally, the statistical information includes at least one of a changing trend and a statistical quantity of abnormal information.

[0027] According to a second aspect of the present disclosure, a data collection device is provided, comprising:

[0028] A determination unit is used to determine the monitoring method according to the timeliness requirement of the monitoring project, and configure the monitoring strategy of the monitoring project according to the monitoring method; wherein the monitoring strategy is configured according to the monitoring project, and different monitoring projects correspond to different monitoring strategies

[0029] A collection unit, configured to collect abnormal information from each target vehicle according to the configured monitoring strategy;

[0030] The generating unit is used to generate statistical information of each abnormal information according to a preset time period and push the statistical information to a designated user.

[0031] Optionally, the monitoring method includes offline monitoring, the monitoring item corresponds to at least one vehicle model, different monitoring items correspond to different buried events, and different monitoring strategies include different monitoring indicators and monitoring parameters;

[0032] The determining unit includes:

[0033] A first determining module is used to determine a target vehicle according to a vehicle model corresponding to the monitoring item;

[0034] A second determination module is configured to determine, when there is no timeliness requirement for the monitoring item, that the monitoring data source is each historical log data of the target vehicle, and to determine the buried event corresponding to the monitoring item in each historical log data;

[0035] The configuration module is used to determine the monitoring indicators in the monitoring strategy according to the monitoring items, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring items.

[0036] Optionally, the monitoring mode includes real-time monitoring, and the determining unit includes:

[0037] The monitoring item corresponds to at least one vehicle model, different monitoring items correspond to different buried events, and different monitoring items correspond to different monitoring indicators and monitoring parameters.

[0038] The first determination module is further configured to determine each target vehicle according to the vehicle model corresponding to the monitoring item;

[0039] The second determination module is further configured to, when the monitoring project has a time limit requirement, determine that the monitoring data source is the real-time log data of each target vehicle, and determine the buried event corresponding to the monitoring project in each real-time log data;

[0040] The configuration module is further configured to determine the monitoring indicators in the monitoring strategy according to the monitoring items, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring items;

[0041] The configuration module is further used to configure a real-time processing program for each preset exception type; wherein different exception types correspond to different real-time processing programs.

[0042] Optionally, the acquisition unit is further configured to:

[0043] In the case of real-time monitoring, after abnormal information is collected from the target vehicle, the abnormal type corresponding to the abnormal information is determined;

[0044] A corresponding real-time processing program is determined based on the exception type, and the exception information is processed based on the real-time processing program.

[0045] Optionally, the monitoring indicator includes at least one of a signal and an event, and the monitoring parameter includes at least one of an execution time, an execution frequency, an abnormal threshold range, and push to a designated user.

[0046] Optionally, the statistical information includes at least one of a changing trend and a statistical quantity of abnormal information.

[0047] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0048] at least one processor; and

[0049] a memory communicatively connected to the at least one processor; wherein,

[0050] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0051] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0052] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0053] The data collection method, device, electronic device and storage medium provided by the present disclosure have the following main technical solutions: first, according to the timeliness requirements of the monitoring project, a monitoring method is determined, and a monitoring strategy of the monitoring project is configured according to the monitoring method; wherein the monitoring strategy is obtained by configuring according to the monitoring project, and different monitoring projects correspond to different monitoring strategies; secondly, according to the configured monitoring strategy, abnormal information in each target vehicle is collected; finally, according to a preset time threshold, statistical information of each abnormal information is generated, and the statistical information is pushed to a designated user according to a preset notification method. Compared with the related art, the embodiment of the present application monitors the log data of the vehicle through a pre-configured monitoring strategy, which can timely discover abnormal information of the vehicle during use, can timely discover abnormal problems, and then solve abnormal problems in a timely manner, avoiding the risk of large-scale outbreak of abnormal problems and improving the user experience.

[0054] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings are used to better understand the present invention and do not constitute a limitation of the present invention.

[0056] Figure 1 A flow chart of a data collection method provided by an embodiment of the present disclosure;

[0057] Figure 2 A flow chart of a data collection method provided by an embodiment of the present disclosure;

[0058] Figure 3 A schematic diagram of the structure of a data collection device provided in an embodiment of the present disclosure;

[0059] Figure 4 A schematic diagram of the structure of a data collection device provided in an embodiment of the present disclosure;

[0060] Figure 5 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0061] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0062] The following describes the data collection method, device, electronic device, and storage medium according to the embodiments of the present disclosure with reference to the accompanying drawings.

[0063] Figure 1 A flowchart of a data collection method provided in an embodiment of the present disclosure.

[0064] like Figure 1 As shown, the method comprises the following steps:

[0065] Step 101 : Determine a monitoring method according to the timeliness requirement of a monitoring project, and configure a monitoring strategy for the monitoring project according to the monitoring method; wherein the monitoring strategy is configured according to the monitoring project, and different monitoring projects correspond to different monitoring strategies.

[0066] In one possible implementation method of the embodiment of the present application, the monitoring data can be various functional modules of the vehicle software, such as the navigation system, the car entertainment system, the vehicle diagnostic system, or various indicators of the vehicle, such as the user's operation data, such as the steering wheel rotation angle, the throttle, the brake travel, the vehicle speed, the fuel consumption, the battery status, etc. Specifically, the items that need to be monitored are determined according to specific needs and goals.

[0067] In one possible implementation method of the embodiment of the present application, after determining the monitoring items, a suitable monitoring method can be selected according to the nature and characteristics of the monitoring purpose, such as real-time monitoring, offline monitoring, scheduled monitoring, time-triggered monitoring, etc. Specifically, it can be determined according to actual needs. Specifically, the embodiment of the present application does not limit this.

[0068] Different monitoring items and monitoring methods require corresponding monitoring strategies. In one implementation of the present application, each time a monitoring item is monitored, a monitoring strategy must be configured. This includes setting monitoring indicators, thresholds, and alarm triggering conditions. For example, for navigation system monitoring, indicators such as whether the navigation destination has been successfully reached and whether the navigation route is accurate can be set, along with corresponding thresholds and triggering conditions. When a monitoring indicator exceeds or falls below a set threshold, an abnormality is determined. Specifically, this embodiment of the present application does not limit this.

[0069] Step 102: Collect abnormal information from each target vehicle according to the configured monitoring strategy.

[0070] According to the configured monitoring strategy, the monitoring system collects abnormal information in the vehicle. The abnormal information can be realized through sensors and monitoring equipment inside the vehicle or by communicating with the vehicle system. The monitoring system can collect relevant data of the vehicle regularly or in real time according to the set monitoring method and monitoring strategy, and analyze and process the collected data to determine the abnormal information therein; in one implementable method of the embodiment of the present application, when configuring the monitoring strategy, the data object can be determined. For example, when the monitoring item is the vehicle body posture, the monitored data object is determined to be the vehicle body tilt angle or acceleration value, etc.; specifically, the embodiment of the present application does not limit this.

[0071] Through the steps of collection, identification, recording and alarm, abnormal problems in the vehicle can be discovered and solved in a timely manner, and the stability and safety of the vehicle software can be improved.

[0072] Step 103: Generate statistical information of each abnormal information according to a preset time period, and push the statistical information to a designated user.

[0073] In one possible implementation of the embodiment of the present application, serious abnormal information, such as changes in vehicle body posture or other abnormal information that may affect vehicle driving safety, can be promptly notified to relevant personnel through an alarm mechanism; the alarm can be in the form of sound, text message, email, etc., so that relevant personnel can take timely action to discover and resolve abnormal situations as soon as possible to reduce potential risks and losses.

[0074] According to the preset time period, the monitoring system will collect statistics and analyze the abnormal information collected, including statistical information such as the number, frequency, duration, vehicles and locations of the abnormal information. The generated statistical information can be pushed to the designated user in a variety of ways. This can include pushing through email, text messages, mobile applications, etc.; in one possible implementation method of the embodiment of the present application, the designated user can be specified when configuring the monitoring strategy. For example, if there is abnormal information in the vehicle interactive voice system, the designated user can be set as the developer of the vehicle interactive voice system, and the developer can solve the problem; specifically, the embodiment of the present application does not limit this.

[0075] In one possible implementation method of the embodiment of the present application, in order to better display statistical information, charts, reports, dashboards, etc. can be generated to allow users to intuitively understand the situation of abnormal information. This method can help users better understand and analyze data, and thus make better decisions.

[0076] The data collection method provided by the present disclosure has the following main technical solutions: first, according to the timeliness requirements of the monitoring project, a monitoring method is determined, and a monitoring strategy for the monitoring project is configured according to the monitoring method; wherein the monitoring strategy is obtained by configuring according to the monitoring project, and different monitoring projects correspond to different monitoring strategies; second, according to the configured monitoring strategy, abnormal information in each target vehicle is collected; finally, according to a preset time threshold, statistical information of each abnormal information is generated, and the statistical information is pushed to a designated user according to a preset notification method. Compared with related technologies, the embodiment of the present application monitors the log data of the vehicle through a pre-configured monitoring strategy, which can timely discover abnormal information of the vehicle during use, can timely discover abnormal problems, and then solve abnormal problems in a timely manner, avoiding the risk of large-scale outbreak of abnormal problems and improving the user experience.

[0077] In one possible implementation of the embodiment of the present application, when executing step 101, there are two monitoring modes: real-time monitoring and offline monitoring. The monitoring items correspond to at least one vehicle model, different monitoring items correspond to different buried events, and different monitoring strategies include different monitoring indicators and monitoring parameters. Please refer to the following implementation method; please refer to Figure 2 , Figure 2 A flow chart of a data collection method provided in an embodiment of the present application includes:

[0078] Step 201: Determine a target vehicle based on the vehicle model corresponding to the monitoring item.

[0079] In one possible implementation of the embodiment of the present application, different vehicle models and different vehicle configurations of the same vehicle model may have some differences in their sensors or vehicle-machine systems, so the abnormal information existing in vehicles of different models may also be different, and the monitoring strategies for abnormal information under different vehicle models may also be different.

[0080] In step 202, when there is no timeliness requirement for the monitoring item, the monitoring data source is determined to be each historical log data of the target vehicle, and the buried event corresponding to the monitoring item is determined in each historical log data.

[0081] Tracking events refers to inserting code at specific locations or operation points in an application or website to record data on user behavior or system events. By adding tracking code to an application or website, you can collect data on user behavior, application performance, and other key indicators.

[0082] In one possible implementation of the embodiment of the present application, different monitoring items may correspond to different buried point events. For example, if the monitoring item is vehicle collision detection, then the corresponding buried point event may be an event in which a collision is detected in the log data; if the monitoring item is vehicle tilt detection, then the corresponding buried point event may be an event in which the vehicle tilt angle exceeds a preset threshold value in the log data; in one possible implementation of the embodiment of the present application, log data related to the item can be filtered out according to the needs of the monitoring item. For example, if the monitoring item is collision detection, then log data related to collisions can be filtered out.

[0083] In one possible implementation of an embodiment of the present application, when the monitoring mode is offline monitoring, the data target is the historical log data of the vehicle, such as the log data of the past 24 hours or the log data of the past 48 hours. Specifically, the embodiment of the present application does not limit this.

[0084] Step 203: Determine the monitoring indicators in the monitoring strategy according to the monitoring item, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring item.

[0085] The purpose of configuring monitoring indicators and monitoring parameters is to achieve effective monitoring and analysis of different monitoring items. Different monitoring items have different monitoring indicators and monitoring parameters to measure and evaluate their performance, status and behavior. The monitoring indicators include at least one of signals and events, and the monitoring parameters include at least one of execution time, execution frequency, abnormal threshold range, and push to designated users.

[0086] In this application, which is a private and implementable method, the configuration of monitoring indicators and monitoring parameters needs to be customized according to specific monitoring projects and business needs. The configuration of monitoring indicators and parameters can be achieved through monitoring tools, platforms or custom development. During the configuration process, factors such as monitoring objectives, expected results, threshold settings and alarm mechanisms need to be considered to ensure the accuracy and effectiveness of monitoring; specifically, the embodiments of this application do not limit this.

[0087] In one implementation of the embodiment of the present application, when the monitoring mode is real-time monitoring, step 101 may refer to the following execution steps, including:

[0088] Determine each target vehicle according to the vehicle model corresponding to the monitoring item;

[0089] In the case where the monitoring project has a time limit requirement, determining that the monitoring data source is each real-time log data of each target vehicle, and determining the buried event corresponding to the monitoring project in each real-time log data;

[0090] Determine the monitoring indicators in the monitoring strategy according to the monitoring items, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring items;

[0091] For the detailed implementation process of the above steps, please refer to steps 201 to 203, and the embodiments of this application will not be described one by one here.

[0092] A real-time processing program is configured for each preset exception type respectively; wherein different exception types correspond to different real-time processing programs.

[0093] Configuring a real-time processing program requires customization based on specific exception information and business requirements. During the configuration process, factors such as the exception type, severity, processing priority, and response time must be considered to ensure timely handling of the exception and resolution of the problem. For example, after detecting an anomaly in vehicle posture data or a vehicle collision, manual customer service can contact the driver and passengers by phone to determine whether an accidental collision has occurred and whether there have been any injuries. This is not specifically limited in the present embodiments.

[0094] In one possible implementation of the embodiment of the present application, when the monitoring mode is real-time monitoring, after abnormal information is collected in the target vehicle, the abnormal type corresponding to the abnormal information is determined; the corresponding real-time processing program is determined based on the abnormal type, and the abnormal information is processed based on the real-time processing program.

[0095] By configuring different real-time processing programs for different exception information, appropriate measures can be taken according to the specific situation to solve the problem, improve the stability and reliability of the system, respond to abnormal situations in a timely manner, improve user experience, and support the ability to discover and solve problems in a timely manner.

[0096] In one possible implementation of the embodiment of the application, when generating statistical data in step 103, the statistical information includes at least one of a changing trend of abnormal information and a statistical quantity.

[0097] Corresponding to the above-mentioned data collection method, the present invention also provides a data collection device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment and will not be repeated in the present invention.

[0098] Figure 3 A schematic diagram of the structure of a data collection device provided in an embodiment of the present disclosure is shown in FIG. Figure 3 Shown, including:

[0099] A determining unit 31 is configured to determine a monitoring method according to a timeliness requirement of a monitoring item, and configure a monitoring strategy for the monitoring item according to the monitoring method; wherein the monitoring strategy is configured according to the monitoring item, and different monitoring items correspond to different monitoring strategies;

[0100] The collection unit 32 is used to collect abnormal information from each target vehicle according to the configured monitoring strategy;

[0101] The generating unit 33 is configured to generate statistical information of each abnormal information according to a preset time period, and push the statistical information to a designated user.

[0102] The data collection device provided by the present disclosure has the following main technical solutions: first, according to the timeliness requirements of the monitoring project, a monitoring method is determined, and a monitoring strategy of the monitoring project is configured according to the monitoring method; wherein the monitoring strategy is obtained by configuring according to the monitoring project, and different monitoring projects correspond to different monitoring strategies; second, according to the configured monitoring strategy, abnormal information in each target vehicle is collected; finally, according to a preset time threshold, statistical information of each abnormal information is generated, and the statistical information is pushed to a designated user according to a preset notification method. Compared with related technologies, the embodiment of the present application monitors the log data of the vehicle through a pre-configured monitoring strategy, which can timely discover abnormal information of the vehicle during use, can timely discover abnormal problems, and then solve abnormal problems in a timely manner, avoiding the risk of large-scale outbreak of abnormal problems and improving the user experience.

[0103] Furthermore, in a possible implementation of this embodiment, as Figure 4 As shown, the monitoring mode includes offline monitoring, and the determining unit 31 includes:

[0104] A first determining module 311 is configured to determine a target vehicle based on a vehicle model corresponding to the monitoring item;

[0105] The second determining module 312 is configured to determine, when the monitoring item has no timeliness requirement, that the monitoring data source is each historical log data of the target vehicle, and determine the buried event corresponding to the monitoring item in each historical log data;

[0106] The configuration module 313 is configured to determine the monitoring indicators in the monitoring strategy according to the monitoring items, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring items.

[0107] Furthermore, in a possible implementation of this embodiment, the monitoring method includes real-time monitoring, and the determining unit includes:

[0108] The first determination module 311 is further configured to determine each target vehicle according to the vehicle model corresponding to the monitoring item;

[0109] The second determining module 312 is further configured to determine, when the monitoring project has a time-sensitive requirement, that the monitoring data source is the real-time log data of each target vehicle, and determine the buried event corresponding to the monitoring project in each real-time log data;

[0110] The configuration module 313 is further configured to determine the monitoring indicators in the monitoring strategy according to the monitoring items, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring items;

[0111] The configuration module 313 is further configured to configure a real-time processing program for each preset exception type; wherein different exception types correspond to different real-time processing programs.

[0112] Furthermore, in a possible implementation of this embodiment, the collection unit 32 is further configured to:

[0113] In the case of real-time monitoring, after abnormal information is collected from the target vehicle, the abnormal type corresponding to the abnormal information is determined;

[0114] A corresponding real-time processing program is determined based on the exception type, and the exception information is processed based on the real-time processing program.

[0115] Furthermore, in a possible implementation of this embodiment, the monitoring indicator includes at least one of a signal and an event, and the monitoring parameter includes at least one of an execution time, an execution frequency, an abnormal threshold range, and push to a designated user.

[0116] Furthermore, in a possible implementation of this embodiment, the statistical information includes at least one of a changing trend and a statistical quantity of the abnormal information.

[0117] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principles are the same, which is not limited in this embodiment.

[0118] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0119] Figure 5A schematic block diagram of an example electronic device 400 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 can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0120] like Figure 5 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 into a RAM (Random Access Memory) 403. Various programs and data required for the operation of the device 400 can also be stored in the RAM 403. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0121] Various components in device 400 are connected to I / O interface 405, including an input unit 406, such as a keyboard, mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, optical disk, etc.; and a communication unit 409, such as a network card, modem, wireless communication transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0122] Computing unit 401 can be various general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphic Processing Units), various specialized AI (Artificial Intelligence) computing chips, various computing units that run machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processors, controllers, microcontrollers, etc. Computing unit 401 performs the various methods and processes described above, such as the data collection method. For example, in some embodiments, the data collection method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by computing unit 401, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned data collection method in any other appropriate manner (for example, by means of firmware).

[0123] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System on Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0124] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0125] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0126] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the 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 acoustic input, voice input, or tactile input).

[0127] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0128] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. This client-server relationship is established by computer programs running on the respective computers, establishing a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosts and VPS services ("Virtual Private Servers" or simply "VPS"). The server may also be a server in a distributed system or a server integrated with blockchain.

[0129] It's important to note that artificial intelligence (AI) is the study of how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). This encompasses both hardware and software technologies. AI hardware technologies generally include sensors, specialized AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily encompass computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graphs.

[0130] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0131] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A data collection method, characterized in that: include: Determine a monitoring method according to the timeliness requirement of the monitoring project, and configure a monitoring strategy for the monitoring project according to the monitoring method; wherein the monitoring strategy is obtained by configuring according to the monitoring project, and different monitoring projects correspond to different monitoring strategies; According to the configured monitoring strategy, collect abnormal information from each target vehicle; According to a preset time period, statistical information of each abnormal information is generated, and the statistical information is pushed to a designated user.

2. The method according to claim 1, characterized in that The monitoring method includes offline monitoring, the monitoring items correspond to at least one vehicle model, different monitoring items correspond to different buried point events, and different monitoring strategies include different monitoring indicators and monitoring parameters; Determining the monitoring method according to the timeliness requirement of the monitoring item, and configuring the monitoring strategy of the monitoring item according to the monitoring method includes: Determine the target vehicle according to the vehicle model corresponding to the monitoring item; In the case where the monitoring item has no timeliness requirement, determining that the monitoring data source is each historical log data of the target vehicle, and determining the buried event corresponding to the monitoring item in each historical log data; According to the monitoring project, the monitoring indicators in the monitoring strategy are determined, and the monitoring parameters of the monitoring indicators are configured according to the monitoring accuracy requirements of the monitoring project.

3. The method according to claim 1, characterized in that The monitoring method includes real-time monitoring, The monitoring item corresponds to at least one vehicle model, different monitoring items correspond to different buried point events, and different monitoring items correspond to different monitoring indicators and monitoring parameters; Determining the monitoring method according to the timeliness requirement of the monitoring item, and configuring the monitoring strategy of the monitoring item according to the monitoring method includes: Determine each target vehicle according to the vehicle model corresponding to the monitoring item; In the case where the monitoring project has a time limit requirement, determining that the monitoring data source is each real-time log data of each target vehicle, and determining the buried event corresponding to the monitoring project in each real-time log data; Determine the monitoring indicators in the monitoring strategy according to the monitoring project, and configure the monitoring parameters of the monitoring indicators according to the monitoring accuracy requirements of the monitoring project; A real-time processing program is configured for each preset exception type respectively; wherein different exception types correspond to different real-time processing programs.

4. The method according to claim 3, characterized in that According to the configured monitoring strategy, collecting abnormal information from each target vehicle also includes: In the case where the monitoring mode is real-time monitoring, after abnormal information is collected from the target vehicle, the abnormal type corresponding to the abnormal information is determined; A corresponding real-time processing program is determined based on the exception type, and the exception information is processed based on the real-time processing program.

5. The method according to any one of claims 1 to 4, characterized in that The monitoring indicator includes at least one of a signal and an event, and the monitoring parameter includes at least one of an execution time, an execution frequency, an abnormal threshold range, and push to a designated user.

6. The method according to claim 1, characterized in that The statistical information includes at least one of a changing trend and a statistical quantity of abnormal information.

7. A data collection device, characterized in that: include: A determination unit, configured to determine a monitoring method according to a timeliness requirement of a monitoring project, and configure a monitoring strategy of the monitoring project according to the monitoring method; wherein the monitoring strategy is obtained by configuring according to the monitoring project, and different monitoring projects correspond to different monitoring strategies; A collection unit, used to collect abnormal information from each target vehicle according to the configured monitoring strategy; The generating unit is used to generate statistical information of each abnormal information according to a preset time period, and push the statistical information to a designated user.

8. An electronic device, characterized in that: include: 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, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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