A data processing method, device and computer readable storage medium

Abstract

The application provides a data processing method and device and a computer readable storage medium. The method is applied to a vehicle and includes receiving a data collection request of a server. The data collection request includes a target state of the vehicle and a data collection range corresponding to the target state. When the state of the vehicle is the target state, vehicle condition data is collected according to the data collection range corresponding to the target state. The current resource usage of the vehicle is obtained. If the resource usage meets a preset data processing condition, the vehicle is used as a node of distributed data processing, and the vehicle condition data is processed through the node of distributed data processing to obtain a processing result. The processing result is uploaded to the server. The method can reduce the transmission and storage cost of vehicle data and improve the data processing efficiency.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more specifically, to a data processing method, apparatus, and computer-readable storage medium in the field of vehicle technology. Background Technology

[0002] During vehicle operation, a large amount of driving data is generated. Collecting and processing this driving data is of great significance for vehicle optimization design and accident analysis. For example, driving data can be used to analyze the control effectiveness of various functions and the usage status of various components, thereby providing support for iterative optimization of control algorithms and design optimization of components.

[0003] In related technologies, data generated by each vehicle is typically uploaded to a data server, which then centrally stores and processes all the data, optimizing the vehicles based on the processing results. This approach results in high data transmission and storage costs, and low processing efficiency.

[0004] Therefore, reducing the cost of vehicle data transmission and storage, and improving data processing efficiency have become urgent problems to be solved. Summary of the Invention

[0005] This application provides a data processing method, apparatus, and vehicle, which can reduce the cost of vehicle data transmission and storage and improve data processing efficiency.

[0006] Firstly, a data processing method is provided, applied to a vehicle. The method includes: receiving a data acquisition request from a server; the data acquisition request includes a target state of the vehicle and a data acquisition range corresponding to the target state; when the vehicle is in the target state, acquiring vehicle condition data according to the data acquisition range corresponding to the target state; obtaining the current resource usage of the vehicle; if the resource usage meets preset data processing conditions, using the vehicle as a node in a distributed data processing system, and processing the vehicle condition data through the distributed data processing node to obtain a processing result; and uploading the processing result to a server.

[0007] Through the above technical solution, by receiving data collection requests from the server, the vehicle can collect data under the target state according to the server's request, ensuring that the collected data is relevant to the target state and avoiding the collection of irrelevant data. This reduces the burden of data transmission and storage, thereby lowering the cost of vehicle data transmission and storage to a certain extent. Furthermore, the server can dynamically adjust the data collection range according to actual needs, improving the flexibility and targeting of data collection. This ensures that data is collected only when the vehicle's state matches the target state, reducing unnecessary data collection and transmission, thus lowering data transmission costs. By obtaining the vehicle's current resource usage, it is possible to assess whether the vehicle has sufficient resources for data processing. The vehicle itself can act as a node in distributed data processing, which is beneficial for fully utilizing the vehicle's local idle resources to process the vehicle's generated vehicle condition data. By distributing data processing tasks to vehicle nodes, the computational pressure on the server is reduced, improving data processing efficiency. The vehicle can send only the processing results to the server, reducing the amount of data uploaded and lowering data transmission costs. Since the vehicle has already processed some vehicle condition data, the server only needs to further process the results, improving data processing efficiency. The server also does not need to store all vehicle condition data; it only needs to save the pre-processed results and the results after further processing, reducing data storage costs.

[0008] In combination with the first aspect and the above implementation methods, in some possible implementation methods, before processing the vehicle condition data to obtain the processing result, the method further includes: determining whether the vehicle condition data is the result data that the server needs to collect, and obtaining the determination result; storing the vehicle condition data according to the determination result and resource usage.

[0009] In the above technical solution, the vehicle condition data stored on the vehicle can serve as a backup of the vehicle condition data on the server. When the server needs the vehicle condition data again, it can upload the vehicle condition data from the vehicle to avoid data loss.

[0010] In conjunction with the first aspect and the above implementation methods, in some possible implementation methods, the resource usage includes the usage of non-volatile storage space. The storage of vehicle condition data based on the judgment result and resource usage includes: if the judgment result is that the vehicle condition data is not the result data that the server needs to collect, then the vehicle condition data is stored using the idle non-volatile storage space; the processing of the vehicle condition data includes: processing the vehicle condition data stored in the non-volatile storage space.

[0011] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the use of idle non-volatile storage space to store vehicle condition data includes: obtaining the first occupancy rate of the non-volatile storage space at the current moment; when the first occupancy rate is lower than a first threshold, storing the vehicle condition data at the current moment in the non-volatile storage space; when the first occupancy rate is greater than or equal to a second threshold, using the vehicle condition data at the current moment to overwrite the oldest historical vehicle condition data stored in the non-volatile storage space, wherein the second threshold is greater than the first threshold.

[0012] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the resource usage includes the memory space usage. The step of storing the vehicle condition data according to the judgment result and the resource usage includes: if the judgment result is that the vehicle condition data is the result data that the server needs to collect, then the vehicle condition data is cached using the free memory space, and the cached vehicle condition data is uploaded to the server.

[0013] In the above technical solution, when the vehicle condition data is not the final result data that the server needs to collect, the vehicle condition data is stored in a non-volatile storage space. Subsequently, when the resource usage of the vehicle meets the preset data processing conditions, it can be processed directly, improving data processing efficiency. Data that does not need to be processed further on the vehicle is cached in memory to avoid frequent reading and writing of vehicle condition data, which would cause resource waste.

[0014] Combining the first aspect and the above implementation methods, in some possible implementation methods, the vehicle condition data is cached using the free memory space, including: obtaining the second occupancy rate of the memory space at the current moment; when the second occupancy rate is lower than the third threshold, storing the vehicle condition data at the current moment in the memory space; when the second occupancy rate is greater than or equal to the fourth threshold, using the vehicle condition data at the current moment to overwrite the oldest historical vehicle condition data stored in the memory space, wherein the fourth threshold is greater than the third threshold.

[0015] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the preset data processing conditions include a first data processing condition and a second data processing condition. The processing of vehicle condition data to obtain a processing result includes: when the resource usage meets the first data processing condition, preprocessing the vehicle condition data to obtain a first processing result, which is the intermediate data required by the server; when the resource usage meets the second data processing condition, fully processing the vehicle condition data to obtain a second processing result, which is the result data required by the server.

[0016] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the method further includes: if the resource usage does not meet the preset data processing conditions, then the vehicle condition data is uploaded to the server for the server to process the vehicle condition data.

[0017] Secondly, a data processing device is provided, comprising: a data acquisition module for receiving a data acquisition request from a server; the data acquisition request includes a target state of the vehicle and a data acquisition range corresponding to the target state; when the vehicle is in the target state, vehicle condition data is acquired according to the data acquisition range corresponding to the target state; an acquisition module for acquiring the current resource usage of the vehicle; a processing module for using the vehicle as a node in a distributed data processing system if the resource usage meets preset data processing conditions, and processing the vehicle condition data through the node in the distributed data processing system to obtain a processing result; and a first upload module for uploading the processing result to a server.

[0018] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, the device further includes: a judgment module, used to judge whether the vehicle condition data is the result data that the server needs to collect, and to obtain a judgment result; and a first storage module, used to store the vehicle condition data according to the judgment result and resource usage.

[0019] In combination with the second aspect and the above implementation methods, in some possible implementation methods, the resource usage includes the usage of non-volatile storage space. The first storage module includes a first storage unit, which is used to store the vehicle condition data using the idle non-volatile storage space if the judgment result is that the vehicle condition data is the result data that the server needs to collect. The processing module is specifically used to process the vehicle condition data stored in the non-volatile storage space.

[0020] In combination with the second aspect and the above implementation methods, in some possible implementation methods, the first storage unit is specifically used to: obtain the first occupancy rate of the non-volatile storage space at the current moment; when the first occupancy rate is lower than the first threshold, store the vehicle condition data at the current moment in the non-volatile storage space; when the first occupancy rate is greater than or equal to the second threshold, use the vehicle condition data at the current moment to overwrite the oldest historical vehicle condition data stored in the non-volatile storage space, wherein the second threshold is greater than the first threshold.

[0021] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, the resource usage includes the memory space usage. The device further includes: a second storage module, used to cache the vehicle condition data using free memory space and upload the cached vehicle condition data to the server if the judgment result is that the vehicle condition data is the result data that the server needs to collect.

[0022] Combining the second aspect and the above implementation methods, in some possible implementation methods, the second storage module is specifically used to obtain the second occupancy rate of the memory space at the current moment; when the second occupancy rate is lower than the third threshold, the vehicle condition data at the current moment is stored in the memory space; when the second occupancy rate is greater than or equal to the fourth threshold, the vehicle condition data at the current moment is used to overwrite the oldest historical vehicle condition data stored in the memory space, wherein the fourth threshold is greater than the third threshold.

[0023] Combining the second aspect and the above implementation methods, in some possible implementation methods, the preset data processing conditions include a first data processing condition and a second data processing condition. The processing module includes a first processing module, which is used to preprocess the vehicle condition data to obtain a first processing result when the resource usage meets the first data processing condition. The first processing result is the intermediate data required by the server. The second processing module is used to fully process the vehicle condition data to obtain a second processing result when the resource usage meets the second data processing condition. The second processing result is the result data required by the server.

[0024] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, the device further includes a second upload module, which is used to upload vehicle condition data to the server for the server to process the vehicle condition data if the resource usage does not meet the preset data processing conditions.

[0025] Thirdly, a vehicle is provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, causing the vehicle to perform the methods described in the first aspect or any possible implementation thereof.

[0026] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0027] Fifthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0028] Figure 1 This is a system architecture diagram of a data processing method application provided in an embodiment of this application;

[0029] Figure 2 This is a schematic flowchart illustrating a data processing method provided in an embodiment of this application;

[0030] Figure 3 This is a system architecture diagram of another data processing method provided in the embodiments of this application;

[0031] Figure 4 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application;

[0032] Figure 5 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Detailed Implementation

[0033] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0034] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0035] Remote vehicle data acquisition is crucial for vehicle optimization and accident analysis. It involves wirelessly transmitting data generated during vehicle operation to a data server. Each vehicle generates a series of parameters during operation, including real-time location, driving trajectory, engine start / stop time, engine temperature, engine speed, throttle opening, idling time, continuous engine operating hours, battery voltage, air conditioning status, transmission gear information, transmission shift mode, vehicle speed, driver operating habits, and more. Each vehicle transmits its operational data wirelessly to the server, which centrally stores and processes this data to analyze the control effectiveness of various functions, the usage status of components, and the location and cause of vehicle malfunctions. This provides support for iterative optimization of control algorithms and design optimization of components. However, the amount of vehicle operational data generated is enormous, resulting in high transmission and storage costs and low data processing efficiency.

[0036] Based on the above-mentioned technical problems, this application provides a data processing method that can solve the technical problems of high data transmission and storage costs and low data processing efficiency during the remote acquisition of vehicle data.

[0037] Before describing the data processing method in this application in detail, let's first introduce the system architecture diagram involved in this application.

[0038] Figure 1 This is a system architecture diagram of a data processing method application provided in an embodiment of this application. See also: Figure 1 The system includes multiple vehicles 110 and a server 120, and each vehicle 110 and server 120 are connected to each other via wired or wireless means for communication.

[0039] Among them, vehicle 110 can collect various vehicle condition data generated when the vehicle is running or stationary; and process the collected vehicle condition data according to its own resource usage, send the processed results to server 120, and can also store the collected vehicle condition data according to its own resource usage.

[0040] Server 120 receives the processing results sent by vehicle 110, integrates or further processes them to obtain the required result data, and provides support for subsequent vehicle optimization and improvement based on the result data.

[0041] In some embodiments, server 120 may be a standalone server, or a server cluster or distributed system consisting of multiple physical servers.

[0042] It should be noted that this application does not limit the number of vehicles included in the data processing system; it may include one vehicle or multiple vehicles. In some embodiments, each vehicle serves as both a distributed data processing node and a distributed data storage node. Distributed data processing refers to processing data using distributed computing technology, where each vehicle has its own processor and storage device, distributing the massive computing tasks originally concentrated on a server to vehicles in a distributed network for parallel processing; distributed data storage refers to distributing data across multiple vehicles.

[0043] Figure 2 This is a schematic flowchart illustrating a data processing method provided in an embodiment of this application. This method can be applied to... Figure 1 The vehicle 110 shown is an example. Figure 2 As shown, the method 200 includes:

[0044] S210, Receive data acquisition request from server; the data acquisition request includes the target status of the vehicle and the data acquisition range corresponding to the target status.

[0045] Specifically, the server can send data collection requests to the vehicle. These requests carry the vehicle's target state and the corresponding data collection range. The target state refers to the vehicle's specific state at a given moment, including its own state, controller operating state, driving scenario, and engine operating state. The data collection range includes a time range and / or a data type range. The time range specifies the time interval for data collection, such as data from the last 10 minutes or the previous driving cycle. The data type range specifies the specific data items to be collected, such as speed, acceleration, fuel consumption rate, and GPS location. In other words, the data collection range corresponding to the target state indicates which vehicle condition data within which time periods need to be collected when the vehicle is in the target state, so as to monitor the vehicle's health status and optimize driving behavior analysis based on the collected data.

[0046] It should be understood that different target states can correspond to their own data collection ranges. These ranges may differ or even be similar, allowing for precise control over the content and frequency of data collection based on actual needs, thereby improving data processing efficiency and resource utilization. For example, when the target state is "engine running status," the data type range might focus on engine-related parameters (such as RPM and temperature), and the time range might focus on the first 5 minutes after engine startup. If the target state is "driving in adverse weather conditions," the data type range might include information such as wiper usage frequency, headlight status, and road surface slipperiness, and the time range might cover the entire period of adverse weather. These correspondences can be managed through a pre-defined mapping table to ensure that each target state has a clearly defined data collection range.

[0047] For example, the correspondence between target states and data acquisition ranges can be preset. For instance, the correspondence between target states and data acquisition ranges is shown in Table 1 below:

[0048] Table 1

[0049]

[0050] It should be noted that Table 1 above only takes the data collection range corresponding to the target state as an example, including the data type range. In specific implementations, the time range may also be included. This embodiment does not make specific limitations on this.

[0051] S220: When the vehicle's state meets the target state, vehicle condition data is collected according to the data collection range corresponding to the target state.

[0052] Specifically, the vehicle can obtain its current state. If the current state is the same as a target state issued by the server, it can be determined that the vehicle meets the target state. Furthermore, when the vehicle's state meets the target state, the data range to be collected can be determined according to the correspondence shown in Table 1, and the corresponding vehicle condition data can be collected according to the data collection range.

[0053] Referring to Table 1, if the vehicle is currently in a driving state, the data collection scope includes: road conditions, weather, surrounding vehicle traffic conditions, traffic light status, vehicle speed, engine torque, etc. If the vehicle is currently in a fault state, the data collection scope includes: vehicle driving data from 1 to 2 weeks prior to the fault and vehicle condition data at the time of the fault.

[0054] Optionally, the vehicle can collect relevant vehicle condition data based on the data collection request sent by the server in real time, or it can collect relevant vehicle condition data based on the data collection strategy stored on the vehicle. This application does not limit this.

[0055] It should be understood that a data collection request may also include a data collection strategy. The correspondence between the target state and the data collection range mentioned above is an exemplary data collection strategy. This data collection strategy may also include other collection strategies, such as uploading tire pressure data at regular intervals.

[0056] S230: Obtain the current resource usage status of the vehicle.

[0057] The resource usage includes one or any combination of the following: the resource usage of the vehicle's central processing unit (CPU), such as CPU utilization rate; the memory resource usage, such as memory space occupancy rate; and the non-volatile storage resource usage, such as non-volatile storage space occupancy rate.

[0058] In some embodiments, the vehicle includes a resource monitoring module that can monitor the resource usage on the vehicle in real time.

[0059] S240: If the resource usage meets the preset data processing conditions, the vehicle is used as a node for distributed data processing, and the vehicle condition data is processed through the distributed data processing node to obtain the processing result.

[0060] The preset data processing conditions may include: the vehicle's ability to process vehicle condition data must meet CPU resource requirements. If the vehicle's current resource usage meets the preset data processing conditions, it means that the vehicle itself can act as a node in the distributed data processing. Processing the vehicle condition data through these nodes allows for full utilization of the vehicle's local idle resources. By distributing data processing tasks to vehicle nodes, the computational pressure on the server is reduced, and data processing efficiency is improved.

[0061] Optionally, preset data processing conditions may include: the CPU utilization rate on the vehicle is lower than the preset utilization rate, or when the vehicle is running data processing functions, it does not affect the operation of other functions above the data processing function, such as vehicle control functions.

[0062] Furthermore, if the CPU utilization rate on the vehicle is lower than the first utilization rate (e.g., 70%), and / or when the vehicle is running data processing functions, it does not affect the operation of other functions with higher priority than data processing functions, and the vehicle condition data can be processed to obtain the processing result.

[0063] In some embodiments, the preset data processing conditions include a first data processing condition and a second data processing condition.

[0064] Furthermore, when the resource usage meets the first data processing condition, the vehicle condition data is preprocessed to obtain the first processing result, which is the intermediate data required by the server; when the resource usage meets the second data processing condition, the vehicle condition data is fully processed to obtain the second processing result, which is the result data required by the server.

[0065] The first data processing condition can be that the CPU utilization rate is lower than the first utilization rate but higher than the second utilization rate, and the second data processing condition can be that the CPU utilization rate is lower than the third utilization rate. It should be understood that the first utilization rate > the second utilization rate > the third utilization rate.

[0066] For example, when the CPU utilization rate is lower than the first utilization rate (e.g., 70%) and higher than the second utilization rate (e.g., 60%) in the obtained resource usage data, 10% of the CPU resources are used to preprocess the vehicle condition data to obtain intermediate data.

[0067] It should be understood that preprocessing involves partially processing vehicle condition data. Preprocessing methods can include: 1. Cleaning the raw vehicle condition data to remove invalid data; 2. Performing statistical analysis on the raw vehicle condition data to calculate predetermined indicators, such as average speed and speed variance. The specific preprocessing method can be determined based on the intermediate data required by the server or the processing strategy issued by the server.

[0068] When the CPU utilization rate is lower than the third utilization rate (e.g., 30%), it indicates that there may be a large amount of idle CPU resources at this time, which can be used to process all vehicle condition data and obtain the result data.

[0069] It should be understood that the above examples of 70% first usage rate, 60% second usage rate, and 30% third usage rate are merely examples, and the specific values ​​can be set according to the actual situation.

[0070] By using the technical solutions in the above example embodiments, preprocessing or fully processing vehicle condition data on the vehicle side can save on the computational and analytical costs of the server later.

[0071] In one possible implementation, whether vehicle condition data is fully processed depends not only on the resource usage mentioned above, but also on whether the vehicle meets the hard conditions for full processing. For example, if full processing of vehicle data requires the combination of other parameters or data, and the vehicle cannot meet this condition, then the vehicle condition data or pre-processed intermediate data needs to be uploaded to the data server for processing.

[0072] In some embodiments, if the resource usage on the vehicle does not meet the preset data processing conditions, the vehicle condition data is uploaded to the server for the server to process the vehicle condition data.

[0073] In one possible implementation, when the CPU utilization rate is higher than the first utilization rate (70%), the vehicle condition data is uploaded to the server for the server to process the vehicle condition data.

[0074] In another possible implementation, when the data processing function is running, it will affect the operation of other functions with higher priority than the data processing function. In this case, the vehicle condition data is uploaded to the server for the server to process the vehicle condition data.

[0075] In some embodiments, vehicle condition data is processed according to the data processing strategy issued by the server and the resource usage of the vehicle terminal.

[0076] The data processing strategy may include the aforementioned vehicle condition data preprocessing methods and the parameters required during the vehicle condition data processing.

[0077] S250 uploads the processing results to the server.

[0078] Since the server needs to perform comprehensive analysis based on the vehicle condition data of multiple vehicles, the vehicle-side needs to upload the data processing results to the server.

[0079] In some embodiments, if the vehicle only preprocesses the vehicle condition data, the intermediate preprocessing result is uploaded to the server; if the vehicle processes all the vehicle condition data, the result data is uploaded to the server; if the vehicle processes only a portion of the vehicle condition data, the unprocessed vehicle condition data and the partially processed result data are uploaded to the server.

[0080] By using the technical solutions in the above example embodiments, the vehicle condition data generated by the vehicle, combined with the vehicle's resource usage, is partially processed on the vehicle side, which acts as a node for distributed data processing. Only the processing results are sent to the server, reducing the amount of data uploaded and lowering data transmission costs. At the same time, since the vehicle side has already processed part of the vehicle condition data, the server only needs to further process the processing results, improving data processing efficiency. The server also does not need to store all the vehicle condition data; it only needs to save the pre-processed results and the results after further processing, reducing data storage costs.

[0081] In some embodiments, before processing the vehicle condition data, the method further includes: determining whether the vehicle condition data is result data that the server needs to collect, and obtaining a determination result; and storing the vehicle condition data according to the determination result and resource usage.

[0082] In some embodiments, there are at least two ways to determine whether vehicle condition data is the result data that the server needs to collect:

[0083] 1. Based on the data upload strategy pre-stored on the vehicle or issued by the server, determine whether the vehicle condition data is the result data that the server needs to collect. It should be understood that the data upload strategy includes vehicle condition data that needs to be uploaded in specific scenarios. For example, when a vehicle malfunctions, data such as the current average speed and maximum tire pressure need to be uploaded. If the vehicle condition data when a malfunction occurs is the current speed, tire pressure, etc., then it is determined that the vehicle condition data is not the result data that the server needs to collect and further processing is required.

[0084] 2. Based on the server's request, determine whether the vehicle condition data is the result data that the server needs to collect. Specifically, if the server sends a request to upload the current tire pressure data, and the vehicle condition data is the current tire pressure, then it is determined that the vehicle condition data is the result data that the server needs to collect, and no further processing is required.

[0085] Furthermore, after obtaining the judgment result, the vehicle condition data is stored according to the judgment result and resource usage. The implementation process of this step can be as follows: if the judgment result is that the vehicle condition data is not the result data that the server needs to collect, then the vehicle condition data is stored using the idle non-volatile storage space.

[0086] Furthermore, when the vehicle's resource usage meets the preset data processing conditions, the vehicle condition data stored in the non-volatile storage space is processed, and the processed result data is uploaded to the server.

[0087] In other words, if the vehicle condition data is not the final result data that the server needs to collect, that is, if the vehicle condition data is data that needs to be processed later, then the vehicle condition data is stored using the available non-volatile storage space.

[0088] In some embodiments, the process of storing vehicle condition data using idle non-volatile storage space can be as follows: obtaining the first occupancy rate of the non-volatile storage space at the current moment; when the first occupancy rate is lower than a first threshold, storing the vehicle condition data at the current moment in the non-volatile storage space; when the first occupancy rate is greater than or equal to a second threshold, using the vehicle condition data at the current moment to overwrite the oldest historical vehicle condition data stored in the non-volatile storage space.

[0089] The second threshold is greater than the first threshold. The first threshold can be set according to specific circumstances, such as 20%. The second threshold is the upper limit of non-volatile storage space occupancy, which can be dynamically determined based on the current non-volatile storage usage and the set non-volatile storage space available for data storage. For example, if the current non-volatile storage space occupancy is 50% and the set storage space available for storing vehicle condition data is 20%, then the second threshold is 70%.

[0090] Furthermore, when the current non-volatile storage space occupancy rate is lower than the first threshold (20%), the vehicle condition data at the current moment is stored in the non-volatile storage space. When the non-volatile storage space occupancy rate is greater than or equal to the second threshold (70%), the vehicle condition data at the current moment is used to overwrite the oldest stored vehicle condition data.

[0091] In some embodiments, resource usage includes memory space usage. The above-mentioned storage of vehicle condition data based on the judgment result and resource usage includes: if the judgment result is that the vehicle condition data is the result data that the server needs to collect, then the vehicle condition data is cached using free memory space, and the cached vehicle condition data is uploaded to the server.

[0092] If the vehicle condition data is the final result data that the server needs to collect, that is, the vehicle condition data does not need to be processed further, then the vehicle condition data is cached using the free memory space.

[0093] It should be understood that storing the vehicle condition data that the server needs to collect in non-volatile storage allows for direct processing when the vehicle's resource usage meets the preset data processing conditions, thereby improving data processing efficiency. Data that does not require further processing on the vehicle side is cached in memory to avoid frequent reading and writing of vehicle condition data, which would otherwise waste resources.

[0094] In some embodiments, the process of caching vehicle condition data using free memory space can be as follows: obtaining the second occupancy rate of the memory space at the current moment; when the second occupancy rate is lower than the third threshold, storing the vehicle condition data at the current moment in the memory space; when the second occupancy rate is greater than or equal to the fourth threshold, using the vehicle condition data at the current moment to overwrite the oldest historical vehicle condition data stored in the memory space.

[0095] The fourth threshold is greater than the third threshold, the third threshold can be the same as the first threshold, and the fourth threshold can be the same as the second threshold. The fourth threshold is the upper limit of memory space occupancy, and its specific value can be dynamically determined based on the current memory space usage and the set memory space available for data storage.

[0096] In some embodiments, data can be stored according to the data storage policy issued by the server in conjunction with the resource usage described above.

[0097] The data storage strategy may include the non-volatile storage space and memory space that can be used to store data, as well as the different storage spaces allocated to different vehicle condition data, etc.

[0098] It should be understood that since the vehicle condition data stored in the non-volatile storage space is the data that the server needs to collect, the vehicle condition data stored in the non-volatile storage space will be processed when the resource usage on the vehicle meets the above-mentioned preset data processing conditions.

[0099] Through the technical solutions in the above example embodiments, the vehicle condition data stored on the vehicle can serve as a backup of the vehicle condition data on the server. When the server needs the vehicle condition data again, it can upload the vehicle condition data on the vehicle again to avoid data loss.

[0100] Figure 3 This is a system architecture diagram of another data processing method provided in the embodiments of this application. The specific implementation of this system will be described accordingly.

[0101] like Figure 3 As shown, the system includes a vehicle controller 310, a main server 320, and a data server 330. When the vehicle starts, the vehicle controller 310 establishes a communication connection with the main server 320 and the data server 330.

[0102] The vehicle-side controller 310 includes a data acquisition module, a resource monitoring module, a storage module, and a processing module. The vehicle-side controller 310 can be a system-on-a-chip (SOC) controller. An SOC controller integrates key system components onto a single chip. The SOC can consist of a SOC control logic module, a microprocessor / microcontroller CPU core module, a digital signal processing (DSP) module, an embedded memory module, an interface module for external communication, an analog front-end module containing an analog-to-digital converter (ADC) / digital-to-analog converter (DAC), a power supply and power management module, and for a wireless SOC, a radio frequency (RF) front-end module, user-defined logic (which can be implemented using a field-programmable gate array (FPGA) or application-specific integrated circuit (ASIC)), and a microelectromechanical (MEMS) module. More importantly, an SOC chip embeds basic software (a real-time disk operating system (RDOS) or an on-chip operating system). System (COS) and other application software modules or loadable user software, etc.

[0103] The data acquisition module is used to collect vehicle condition data and upload it to the data server; the resource monitoring module is used to monitor the resource usage of the vehicle; the storage module is used to store vehicle condition data; and the processing module is used to process vehicle condition data.

[0104] The main server 320 has functions of acquisition control, storage control, and processing control, and these functions can be implemented in the following ways:

[0105] 1. Send data containing configurable parameters from the acquisition strategy, storage strategy, and processing strategy to the vehicle terminal, and adjust the acquisition, storage, and processing functions by changing these parameters.

[0106] 2. Update the vehicle's data acquisition module, resource monitoring module, storage module, and processing module software via OTA (Over-the-Air Technology).

[0107] 3. Directly send collection, storage, and processing requests to the vehicle terminal.

[0108] The data server 330 has data storage and data parsing functions, and is used to store and parse vehicle condition data uploaded by the vehicle terminal.

[0109] In some embodiments, the acquisition module in the vehicle controller 310 determines the range of vehicle condition data to be collected based on the data acquisition request sent by the master server 320. The range of vehicle condition data includes the range of data types and the time range. The resource monitoring module monitors the current resource usage of the vehicle. The storage module caches or persistently stores the data using idle memory and non-volatile storage space based on the current resource usage and the storage policy issued by the master server 320. The vehicle condition data stored in the non-volatile storage space can serve as a backup of the vehicle condition data in the data server, and the master server 320 can request to re-upload this vehicle condition data. When the current resource usage of the vehicle meets the preset data processing conditions, the processing module preprocesses or fully processes the original vehicle condition data based on the processing policy. The acquisition module uploads the processing results to the data server 330, which further processes or integrates the results.

[0110] Figure 4 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application.

[0111] For example, such as Figure 4 As shown, the data processing device 400 may include:

[0112] The acquisition module 410 is used to receive data acquisition requests from the server; the data acquisition request includes the target state of the vehicle and the data acquisition range corresponding to the target state; when the state of the vehicle is the target state, the vehicle condition data is acquired according to the data acquisition range corresponding to the target state.

[0113] The acquisition module 420 is used to acquire the current resource usage of the vehicle.

[0114] The processing module 430 is used to treat the vehicle as a node in a distributed data processing system if the resource usage meets preset data processing conditions, and to process the vehicle condition data through the distributed data processing node to obtain the processing result.

[0115] The first upload module 440 is used to upload the processing results to the server.

[0116] In some embodiments, the device further includes: a judgment module for judging whether the vehicle condition data is the result data that the server needs to collect, and obtaining a judgment result; and a first storage module for storing the vehicle condition data according to the judgment result and resource usage.

[0117] In some embodiments, resource usage includes the usage of non-volatile storage space. The first storage module includes a first storage unit, which is used to store the vehicle condition data using the idle non-volatile storage space if the determination result is that the vehicle condition data is not the result data that the server needs to collect. The processing module is specifically used to process the vehicle condition data stored in the non-volatile storage space.

[0118] In some embodiments, the first storage unit is specifically used to: obtain a first occupancy rate of the non-volatile storage space at the current moment; when the first occupancy rate is lower than a first threshold, store the vehicle condition data at the current moment in the non-volatile storage space; when the first occupancy rate is greater than or equal to a second threshold, use the vehicle condition data at the current moment to overwrite the historical vehicle condition data stored in the non-volatile storage space with the oldest data, wherein the second threshold is greater than the first threshold.

[0119] In some embodiments, the resource usage includes memory space usage. The device further includes a second storage module, configured to cache the vehicle condition data using free memory space and upload the cached vehicle condition data to the server if the determination result indicates that the vehicle condition data is result data that the server needs to collect.

[0120] In some embodiments, the second storage module is specifically used to obtain the second occupancy rate of the memory space at the current moment; when the second occupancy rate is lower than the third threshold, the vehicle condition data at the current moment is stored in the memory space; when the second occupancy rate is greater than or equal to the fourth threshold, the vehicle condition data at the current moment is used to overwrite the oldest historical vehicle condition data stored in the memory space, wherein the fourth threshold is greater than the third threshold.

[0121] In some embodiments, the preset data processing conditions include a first data processing condition and a second data processing condition. The processing module 430 includes a first processing module, which is used to preprocess the vehicle condition data to obtain a first processing result when the resource usage meets the first data processing condition. The first processing result is the intermediate data required by the server. The second processing module is used to fully process the vehicle condition data to obtain a second processing result when the resource usage meets the second data processing condition. The second processing result is the result data required by the server.

[0122] In some embodiments, the device further includes a second upload module, configured to upload vehicle condition data to a server for processing if the resource usage does not meet preset data processing conditions.

[0123] Figure 5 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application.

[0124] For example, such as Figure 5 As shown, the vehicle 500 includes a memory 510 and a processor 520, wherein the memory 510 stores executable program code 511, and the processor 520 is used to call and execute the executable program code 511 to perform a data processing method.

[0125] This embodiment can divide the vehicle into functional modules according to the above method example. For example, each function can be assigned to a separate module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0126] When each function is divided into modules corresponding to its specific function, the vehicle may include: a data collection module, an acquisition module, a processing module, an upload module, etc. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional descriptions of the corresponding modules, and will not be repeated here.

[0127] The vehicle provided in this embodiment is used to execute the above-described data processing method, and therefore can achieve the same effect as the above-described implementation method.

[0128] When using integrated units, the vehicle may include a processing module and a storage module. The processing module is used to control and manage the vehicle's actions. The storage module supports the vehicle in executing program code and data.

[0129] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as disclosed in this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a digital signal processing unit (DSP), and a microprocessor, etc., and the storage module may be a memory.

[0130] This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned method steps to implement a data processing method described in the above embodiment.

[0131] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement a data processing method described in the above embodiment.

[0132] In addition, the vehicle provided in the embodiments of this application may specifically be a chip, component or module. The vehicle may include a connected processor and a memory. The memory is used to store instructions. When the vehicle is running, the processor may call and execute the instructions to make the chip execute a data processing method in the above embodiments.

[0133] In this embodiment, the vehicle, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0134] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0135] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0136] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data processing method, characterized in that, The method is applied to a vehicle, and the method includes: Receive a data collection request from the server; the data collection request includes the target state of the vehicle and the data collection range corresponding to the target state. When the vehicle is in the target state, vehicle condition data is collected according to the data collection range corresponding to the target state. Obtain the current resource usage of the vehicle; If the resource usage meets the preset data processing conditions, the vehicle is used as a node in the distributed data processing, and the vehicle condition data is processed through the distributed data processing node to obtain the processing result. The processing results are then uploaded to the server.

2. The method according to claim 1, characterized in that, Before processing the vehicle condition data to obtain the processing result, the method further includes: Determine whether the vehicle condition data is the result data that the server needs to collect, and obtain the determination result; The vehicle condition data is stored based on the judgment result and the resource usage.

3. The method according to claim 2, characterized in that, The resource usage information includes the usage of non-volatile storage space. The step of storing the vehicle condition data based on the judgment result and the resource usage information includes: If the judgment result is that the vehicle condition data is not the result data that the server needs to collect, then the vehicle condition data is stored using the available non-volatile storage space; The processing of the vehicle condition data includes: The vehicle condition data stored in the non-volatile storage space is processed.

4. The method according to claim 3, characterized in that, The method of storing the vehicle condition data using idle non-volatile storage space includes: Get the current occupancy rate of non-volatile memory; When the first occupancy rate is lower than the first threshold, the vehicle condition data at the current moment is stored in non-volatile storage space; When the first occupancy rate is greater than or equal to the second threshold, the vehicle condition data at the current moment is used to overwrite the historical vehicle condition data with the earliest storage time in the non-volatile storage space, wherein the second threshold is greater than the first threshold.

5. The method according to claim 2, characterized in that, The resource usage information includes memory space usage. The step of storing the vehicle condition data based on the judgment result and the resource usage information includes: If the determination result indicates that the vehicle condition data is the result data that the server needs to collect, then the vehicle condition data is cached using free memory space, and the cached vehicle condition data is uploaded to the server.

6. The method according to claim 5, characterized in that, The method of caching vehicle condition data using free memory space includes: Get the second memory space occupancy rate at the current moment; When the second occupancy rate is lower than the third threshold, the vehicle status data at the current moment is stored in the memory space; When the second occupancy rate is greater than or equal to the fourth threshold, the vehicle condition data at the current moment is used to overwrite the historical vehicle condition data stored in the memory space with the earliest data. The fourth threshold is greater than the third threshold.

7. The method according to any one of claims 1 to 6, characterized in that, The preset data processing conditions include a first data processing condition and a second data processing condition. The process of processing the vehicle condition data to obtain the processing result includes: When the resource usage meets the first data processing condition, the vehicle condition data is preprocessed to obtain a first processing result, which is the intermediate data required by the server. When the resource usage meets the second data processing condition, the vehicle condition data is fully processed to obtain the second processing result, which is the result data required by the server.

8. The method according to any one of claims 1 to 6, characterized in that, The method further includes: If the resource usage does not meet the preset data processing conditions, the vehicle condition data is uploaded to the server for processing.

9. A data processing apparatus, characterized in that, The device includes: The data acquisition module is used to receive data acquisition requests from the server; the data acquisition request includes the target state of the vehicle and the data acquisition range corresponding to the target state; when the vehicle is in the target state, the vehicle condition data is acquired according to the data acquisition range corresponding to the target state. The acquisition module is used to acquire the current resource usage status of the vehicle; The processing module is used to, if the resource usage meets the preset data processing conditions, use the vehicle as a node of distributed data processing, and process the vehicle condition data through the node of distributed data processing to obtain the processing result. The first upload module is used to upload the processing results to the server.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the method as described in any one of claims 1 to 8.

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