Generation method of low-end machine standard of mobile equipment and application program platform

Abstract

The invention provides a mobile equipment low-end machine standard generation method and an application program platform, and relates to the technical field of mobile equipment performance judgment. The method comprises the following steps: a big data center counts online duration, equipment information and lagging data of each client in a preset period every preset period; according to the online duration, the equipment information and the lagging data, generating a lagging frequency report per minute and a low-end machine index parameter proportion; the big data center generates a judgment standard numerical value of each low-end machine index parameter according to the low-end machine index parameter proportion and the report of the number of times of jamming per minute, and pushes the judgment standard numerical value to the server; and the server generates low-end machine standard configuration according to the judgment standard value and a preset judgment rule. According to the method, data collection of model information and operation states and generation of index data statistics are taken as references at regular intervals, the low-end machine judgment standard is generated in combination with the actual condition of APP operation and proportion statistical logic, updating is carried out at regular intervals, and the reasonability of low-end machine judgment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile device performance judgment, and particularly to a method for generating a low-end mobile device standard and an application program platform. Background Art

[0002] Currently, many APPs classify the devices running their own APPs into high-end and low-end devices to provide resources suitable for the device performance. Android mobile devices mainly use the maximum main frequency or the number of cores of the CPU and the value of the memory RAM as indicators to determine whether it is a low-end device. For example, Android devices with a CPU main frequency <1.6 GHz or 2G / 3G memory are classified as low-end devices. Apple mobile devices mainly judge according to the model. For example, older models below iPhone 9 are classified as low-end devices.

[0003] Regarding the existing methods for judging low-end devices, the judgment index dimension of Android mobile devices is relatively small, the low-end device judgment threshold has no actual data support, and the actual operation results of its own APP are not combined as an index for judgment; while the judgment index of Apple mobile devices is not detailed enough. Similarly, the actual operation results of its own APP are not combined as an index for judgment. Summary of the Invention

[0004] The present invention provides a method for generating a low-end mobile device standard and an application program platform, so as to more accurately determine which mobile devices are low-end devices by combining the proportion of actual device parameters in the service and the operation of its own APP, and perform corresponding adaptation for low-end devices.

[0005] The present invention provides a method for generating a low-end mobile device standard, which is applied to an application program platform. The application program platform includes a server, a big data center, and a client. The method includes:

[0006] The big data center statistically counts the online duration, device information, and lag data of each client within the preset period every preset period;

[0007] The big data center generates a report of the number of lags per minute and the proportion of low-end device index parameters based on the online duration, the device information, and the lag data;

[0008] The big data center generates a determination standard value for each low-end device index parameter based on the proportion of low-end device index parameters and the report of the number of lags per minute, and pushes it to the server;

[0009] The server generates a low-end device standard configuration based on the determination standard value and a preset determination rule. The low-end device standard configuration is used to determine whether the device corresponding to the client is a low-end device.

[0010] A method for generating low - end device standards for mobile devices according to the present invention, wherein the device information of Android devices includes: device brand, device model, CPU main frequency, number of CPU cores, running memory, and operating system version number.

[0011] A method for generating low - end device standards for mobile devices according to the present invention, the proportion of low - end device index parameters of Android devices includes: the proportion of the number of each operating system version number, the proportion of the number of each CPU main frequency, the proportion of the number of each CPU core, and the proportion of the number of each running memory.

[0012] A method for generating low - end device standards for mobile devices according to the present invention, the device information of Apple devices includes: device model, generation of operating system, and operating system version number.

[0013] A method for generating low - end device standards for mobile devices according to the present invention, the proportion of low - end device index parameters of Apple devices includes: the proportion of the number of the generation of the operating system and the operating system version number of each device model.

[0014] A method for generating low - end device standards for mobile devices according to the present invention further includes:

[0015] Any one target client sends a low - end device judgment request to the server;

[0016] In response to the low - end device judgment request, the server obtains the real - time online duration and real - time device information of the target client from local, and pulls the lag data statistically calculated within the current preset period of the target client from the big data center;

[0017] The server obtains the low - end device judgment result of the target client according to the low - end device standard configuration of the previous preset period, and the real - time online duration, the online duration, device information, and lag data statistically calculated within the current preset period of the real - time device information;

[0018] The server feeds back the low - end device judgment result to the target client;

[0019] The target client adjusts the resource adaptation configuration of multimedia resources in the application program according to the low - end device judgment result.

[0020] A method for generating low - end device standards for mobile devices according to the present invention, the low - end device judgment result includes: model level, resolution level, CPU occupancy threshold, and memory occupancy threshold.

[0021] A method for generating a low - end device standard for a mobile device. The target client adjusts the resource adaptation configuration of the animation resources in the application according to the low - end device determination result, including:

[0022] The target client determines the resource type of the target animation resource;

[0023] The target client determines whether to play the target animation resource according to the resource type, the model level, the CPU occupancy threshold, and the memory occupancy threshold.

[0024] A method for generating a low - end device standard for a mobile device. The target client adjusts the resource adaptation configuration of the animation resources in the application according to the low - end device determination result, further including:

[0025] When the target client determines that the target animation resource is not to be played, it determines the type of static image for alternative playback according to the resolution level.

[0026] The present invention also provides an application platform, which includes a server, a big data center, and a client;

[0027] The big data center is configured to statistically count the online duration, device information, and lag data of each client within a preset period every preset period;

[0028] The big data center is configured to generate a report of the number of lags per minute and the proportion of low - end device index parameters according to the online duration, the device information, and the lag data;

[0029] The big data center is configured to generate the determination standard values of each low - end device index parameter according to the proportion of low - end device index parameters and the report of the number of lags per minute, and push them to the server;

[0030] The server is configured to generate a low - end device standard configuration according to the determination standard values and a preset determination rule, and the low - end device standard configuration is used to determine whether the device corresponding to the client is a low - end device.

[0031] A method for generating a standard for low - end mobile devices and an application program platform provided by the present invention. The client of the application program platform reports the online duration, device information, and lag data. The application program platform regularly counts the online duration, device information, and lag data of each client within a statistical period through a big data center, generates a report of the number of lags per minute and the proportion of low - end device index parameters based on this information and data, and generates a determination standard value for each low - end device index parameter within this period according to the proportion of low - end device index parameters and the report of the number of lags per minute, and pushes it to the server. The server then generates a low - end device standard configuration based on the determination standard value and a preset determination rule. When the client requests to determine whether it is a low - end device, the server determines whether the device with the current performance of the client is a low - end device according to the low - end device standard configuration. The present invention regularly collects data on model information and operating status, generates statistical index data for reference, combines the actual situation of its own APP operation and the proportion statistical logic to generate a low - end device judgment standard, and updates it regularly, which can improve the rationality of low - end device judgment. Applying such an index to the APP can process resources according to the current performance of the device, enabling the resource configuration to be adapted and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0033] Figure 1 It is a schematic structural diagram of an application program platform provided by the present invention;

[0034] Figure 2 It is one of the schematic flowcharts of a method for generating a standard for low - end mobile devices provided by the present invention;

[0035] Figure 3 It is a schematic timing diagram of the client online duration and lag data statistics in an exemplary embodiment of the present invention;

[0036] Figure 4 It is a schematic background configuration diagram of the server low - end device standard configuration in an exemplary embodiment of the present invention;

[0037] Figure 5 It is the second schematic flowchart of a method for generating a standard for low - end mobile devices provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0039] It should be noted that in the description of the embodiments of the present invention, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element. The orientation or positional relationship indicated by terms such as "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present invention. Unless otherwise clearly specified and defined, the terms "mount", "connect" and "couple" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the internal communication of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention may be understood according to specific circumstances.

[0040] The terms "first", "second", etc. in the present invention are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that such data may be interchanged under appropriate circumstances so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same category, and the number of objects is not limited. For example, the first object may be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0041] The following will be combined with Figures 1 - 5 Describe a method for generating a low-end machine standard for a mobile device and an application program platform.

[0042] Such as Figure 1As shown in the figure, the present invention provides an application platform, and the application platform includes a server 110, a big data center 120, and a client 130; the server 110, the big data center 120, and the client 130 are communicatively connected. Among them:

[0043] The big data center 120 is configured to statistically count the online duration, device information, and lag data of each of the clients 130 within the preset period every preset period;

[0044] The big data center 120 is configured to generate a report of the number of lags per minute and the proportion of low-end machine index parameters according to the online duration, the device information, and the lag data;

[0045] The big data center 120 is configured to generate a determination standard value for each low-end machine index parameter according to the proportion of low-end machine index parameters and the report of the number of lags per minute, and push it to the server 110;

[0046] The server 110 is configured to generate a low-end machine standard configuration according to the determination standard value and a preset determination rule, and the low-end machine standard configuration is used to determine whether the device corresponding to the client 130 is a low-end machine.

[0047] Correspondingly, as Figure 2 shown in the figure, the present invention provides a method for generating a low-end machine standard for a mobile device, which is applied to an application platform. The application platform includes a server, a big data center, and a client. The method includes:

[0048] Step 210, the big data center statistically counts the online duration, device information, and lag data of each of the clients within the preset period every preset period.

[0049] Specifically, the statistical count of the online duration and device information of the client can be based on the heartbeat report of the client to statistically count the online duration and relevant device information. Among them, the device information of Android devices can include: device brand (such as brands like Xiaomi, Huawei, OPPO, Samsung, etc.), device model (such as HUAWEI EML-AL00, OPPO R11s, etc.), CPU main frequency (such as 2.14GHz, 3.18GHz, etc.), number of CPU cores (such as 8 cores, 6 cores, 4 cores, etc.), operating memory (such as 8GB, 12GB, etc.), and operating system version number (such as Android 12, Android 13, etc.).

[0050] The device information of Apple devices may include: device model (such as iPhone 15, iPad 10, etc.), generation of operating system (such as iOS 18, iOS 15, etc.), and version number of operating system (such as iOS 18.1.1, iOS 10.3.1, etc.).

[0051] Reporting of client-side lag data: When the client monitors that an application lags, it reports the lag event to the big data center. Reporting a single lag event represents one instance of lag on the client side, and when the big data center receives a lag event, it counts it as one instance of lag, thus statistically obtaining the lag data. The lag event may include lag time, CPU main frequency, number of CPU cores, running memory, system version number, and so on. In addition, the client device can also report an activation event when starting an application, which is used to statistically obtain the proportion of each indicator of the actual device for the service.

[0052] As Figure 3 shown, it is a timing diagram of the online duration and lag data statistics of the client in an exemplary embodiment of the present invention. The online duration of the client can be reported to the server via heartbeat for statistics by the server, and the big data center periodically (such as daily) pulls the data from the server for statistics. The lag events of the client are reported to the big data center, and the big data center periodically (such as monthly) statistically obtains the number of lags per minute based on the statistically obtained lag data and pushes it to the server for update.

[0053] Step 220, the big data center generates a report of the number of lags per minute and the proportion of low-end device indicator parameters based on the online duration, the device information, and the lag data.

[0054] Specifically, the big data center generates a report of the number of lags per minute by combining the online duration of the client and the device information with the lag data of the client, and then synchronizes a copy to the server for storage. At the same time, based on the device information, the proportion of low-end device indicator parameters is statistically obtained.

[0055] The proportion of low-end device indicator parameters of Android devices may include: the proportion of the number of each operating system version number, the proportion of the number of each CPU main frequency, the proportion of the number of each CPU core, and the proportion of the number of each running memory.

[0056] As shown in Table 1 - Table 4, it is a table of the proportion of low-end device indicator parameters of Android devices in an exemplary embodiment.

[0057] Table 1 Proportion of low-end device indicator parameters - Proportion of the number of each operating system version number.

[0058] Operating system version number Total proportion in Android models Android 13 26.64％ Android 14 24.76％ Android 12 21.33％

[0059] Table 2 Proportion of low-end device indicator parameters - Proportion of the number of each CPU main frequency.

[0060] CPU main frequency Total proportion in Android models 2.40 GHz 14.47％ 3.18 GHz 13.88％ 2.20 GHz 13.78％

[0061] Table 3 Proportion of Low-end Machine Index Parameters - Proportion of the Quantity of Each CPU Core Count

[0062] Number of CPU cores Total proportion in Android models 8 95.26％ 4 3.95％ 6 0.44％

[0063] Table 4 Proportion of Low-end Machine Index Parameters - Proportion of the Quantity of Each Operating Memory

[0064]

[0065]

[0066] As shown in Table 5, it is a report form of the number of freezes per minute of an Android device in an exemplary embodiment.

[0067] Table 5 Report Form of the Number of Freezes per Minute of an Android Device

[0068] Device brand Device model Number of freezes per minute Sorting OPPO PFFM10 2.03 1 OPPO OPPO R11s 1.89 2 HUAWEI EML-AL00 1.64 3

[0069] The proportion of low-end machine index parameters of Apple devices may include: the proportion of the quantity of the generation number of the operating system and the operating system version number of each device model.

[0070] Step 230, the big data center generates the determination standard values of each low-end machine index parameter according to the proportion of the low-end machine index parameters and the report form of the number of freezes per minute, and pushes them to the server.

[0071] Specifically, for Android devices, in combination with the proportion of the quantity of each operating system version number, the proportion of the quantity of each CPU main frequency, the proportion of the quantity of each CPU core count, the proportion of the quantity of each operating memory, and the report form of the number of freezes per minute, the determination standard values that conform to the operation situation of its own application program are formulated. The big data center pushes the determination standard values of each low-end machine index parameter to the server.

[0072] Step 240, the server generates a low-end machine standard configuration according to the determination standard values and the preset determination rules, and the low-end machine standard configuration is used to determine whether the device corresponding to the client is a low-end machine.

[0073] Specifically, the determination standard values and the preset determination rules provided by the server are for the background of configuring the low-end machine standard. The standard values of the low-end machine are configured to generate a low-end machine standard configuration. The preset determination rules are the rules for determining a low-end machine. In some embodiments, each low-end machine index parameter that makes up the standard can be divided into combined conditions and sufficient conditions. The preset determination rules can be that hitting any sufficient condition is determined as a low-end machine or hitting multiple combined conditions is determined as a low-end machine. The server can also make flexible adjustments.

[0074] Such as Figure 4As shown, if the internal version number of the hit sufficient condition is ≤ 27, it is determined as a low-end device. If 3 combined conditions are hit, it is determined as a low-end device. For example, if the CPU main frequency ≤ 2.2 GHz, the number of CPU cores ≤ 4, and the running memory size ≤ 4 GB are hit, it is determined as a low-end device.

[0075] For Apple devices, combined with the operating system generation and the proportion of the number of operating system version numbers of each device model and the report of the number of freezes per minute, the standard numerical values for determination that conform to the running situation of their own application programs are formulated. For example: iPhone ≤ n generations and m versions, iPad ≤ n generations and m versions can be determined as low-end devices. For example, in the operating system generation iOS 15, 15 is n, and in the operating system version number iOS 15.2.1, 2 is m. As Figure 3 shown, iPhone ≤ 15 generations and 2 versions is determined as a low-end device, and iPad ≤ 15 generations and 2 versions is determined as a low-end device.

[0076] The above low-end device standard configuration can be used to determine whether the device corresponding to the client is a low-end device. Specifically, the client requests the server through the low-end device judgment interface. The server calculates the low-end device determination result of the current device based on the low-end device standard configuration and returns it to the client for use.

[0077] In some embodiments, the method further includes:

[0078] Any one target client sends a low-end device judgment request to the server;

[0079] The server, in response to the low-end device judgment request, obtains the real-time online duration and real-time device information of the target client from local, and pulls the freeze data statistically counted within the current preset period of the target client from the big data center;

[0080] The server obtains the low-end device determination result of the target client according to the low-end device standard configuration of the previous preset period, and the real-time online duration, the real-time device information, the online duration, device information, and freeze data statistically counted within the current preset period;

[0081] The server feeds back the low-end device determination result to the target client;

[0082] The target client adjusts the resource adaptation configuration of the multimedia resources in the application program according to the low-end device determination result.

[0083] Specifically, the server can obtain the real-time online duration, real-time device information of the target client, and the lag data of the target client statistically counted within the current preset period according to the low-end device of the target client, and make a judgment based on the latest low-end device standard configuration (i.e., obtained according to the relevant data of the previous preset period), and return the low-end device judgment result to the target client. Among them, the low-end device determination result can include: model level, resolution level, CPU occupancy threshold, and memory occupancy threshold. The model level is used to determine whether it is a low-end device, and the resolution level is used to select an appropriate resolution for static images. The CPU occupancy threshold and the memory occupancy threshold are respectively used to determine in real time whether the current running state of the device of the target client is normal.

[0084] In some embodiments, the model level includes: high-end device, mid-end device, low-end device; the resolution level includes: high resolution, normal resolution.

[0085] The target client can adjust the resource adaptation configuration of the multimedia resources in the APP according to the low-end device determination result. For example, when the client executes the special effect playback logic, it can determine whether to play the dynamic effect or display the corresponding static image according to the low-end device determination result.

[0086] In some embodiments, the target client adjusts the resource adaptation configuration of the dynamic effect resources in the application program according to the low-end device determination result, including:

[0087] The target client determines the resource type of the target dynamic effect resource;

[0088] The target client determines whether to play the target dynamic effect resource according to the resource type, the model level, the CPU occupancy threshold, and the memory occupancy threshold.

[0089] Specifically, the resource type of the target dynamic effect resource can include the first type of dynamic effect resource, the second type of dynamic effect resource, and the third type of dynamic effect resource. Among them, the first type of dynamic effect resource is a dynamic effect resource whose display area exceeds half of the screen size, such as a full-screen dynamic effect; the second type of dynamic effect resource is a dynamic effect resource that appears and refreshes frequently and whose display area exceeds one-eighth of the screen size; the third type of dynamic effect resource is the remaining dynamic effect resources after removing the first two types (the first type of dynamic effect resource, the second type of dynamic effect resource).

[0090] It should be noted that the first type of dynamic effect resource requires the device to have higher performance so that the playback is smoother. If a low-end device plays the first type of dynamic effect resource, it will not only be stuck but also occupy device resources, affecting the device usage and the user experience is poor. The second type of dynamic effect resource can be played by medium-performance devices, but when the running state of the device is poor, it can be avoided as much as possible to avoid affecting the device usage; the third type of dynamic effect resource is a dynamic effect resource with a relatively low correlation with the device performance.

[0091] In some embodiments, as Figure 5 shown, the target client determines whether to play the target animation resource according to the resource type, model level, CPU occupancy threshold, and memory occupancy threshold. Specifically, it includes:

[0092] (1) The first type of animation resource

[0093] When the target client determines that the target animation resource is the first type of animation resource, it determines whether the current device of the target client is a low-end device according to the model level;

[0094] If it is a low-end device, the target animation resource is not played; otherwise (i.e., a high-end device or a mid-end device), it determines whether the running state of the current device of the target client is poor according to the CPU occupancy threshold and the memory occupancy threshold;

[0095] If the running state is poor, the target animation resource is not played; otherwise, the target animation resource is played.

[0096] (2) The second type of animation resource

[0097] When the target client determines that the target animation resource is the second type of animation resource, it determines whether the running state of the current device of the target client is poor according to the CPU occupancy threshold and the memory occupancy threshold;

[0098] If the running state is poor, the target animation resource is not played; otherwise, the target animation resource is played.

[0099] (3) The third type of animation resource

[0100] When the target client determines that the target animation resource is the third type of animation resource, the target animation resource is played.

[0101] In some embodiments, the target client adjusts the resource adaptation configuration of the animation resources in the application according to the low-end device determination result, and further includes:

[0102] When the target client determines that the target animation resource is not played, it determines the type of static image for alternative playback according to the resolution level.

[0103] Specifically, when it is determined that the target animation resource is not played, the type of static image for alternative playback is determined according to the resolution level of the target client. If the resolution level is high resolution, a high-definition static image for replacing the playback of the target animation resource is used; if the resolution level is normal resolution, a static image with normal resolution for replacing the playback of the target animation resource is used. In this way, the lack of animation can be avoided, and the user can still perceive that the animation has been played, improving the user experience.

[0104] The method for generating the standard of low-end mobile devices and the application program platform provided by the present invention. The client of the application program platform reports the online duration, device information, and lag data. The application program platform regularly counts the online duration, device information, and lag data of each client within a statistical period through the big data center, generates a report of the number of lags per minute and the proportion of low-end device index parameters based on this information and data, and generates the determination standard values of each low-end device index parameter within this period according to the proportion of low-end device index parameters and the report of the number of lags per minute, and pushes them to the server. The server then generates the low-end device standard configuration according to the determination standard values and the preset determination rules. When the client requests to determine whether it is a low-end device, the server determines whether the device with the current performance of the client is a low-end device according to the low-end device standard configuration. The present invention regularly collects data on model information and operating status, generates statistical index data for reference, combines the actual situation of its own APP operation and the proportion statistical logic to generate the low-end device judgment standard, and updates it regularly, which can improve the rationality of low-end device judgment. Applying such an index to the APP can process resources according to the current performance of the device, making the resource configuration adaptable and improving the user experience.

[0105] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0106] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating a low-end mobile device standard, characterized in that: Applied to an application platform, the application platform includes a server, a big data center and a client, and the method includes: The big data center counts the online duration, device information and freeze data of each client within the preset period once every preset period; The big data center generates a report on the number of freezes per minute and a proportion of low-end machine indicator parameters according to the online time, the device information and the freeze data; The big data center generates a judgment standard value of each low-end machine indicator parameter according to the proportion of the low-end machine indicator parameter and the report of the number of freezes per minute, and pushes it to the server; The server generates a low-end machine standard configuration according to the judgment standard value and a preset judgment rule, and the low-end machine standard configuration is used to determine whether the device corresponding to the client is a low-end machine.

2. The method for generating a low-end mobile device standard according to claim 1, characterized in that: in, The device information of the Android device includes: device brand, device model, CPU main frequency, number of CPU cores, running memory, and operating system version number.

3. The method for generating a low-end mobile device standard according to claim 2, characterized in that: The proportion of the low-end indicator parameters of Android devices includes: the proportion of the number of each operating system version number, the proportion of the number of each CPU main frequency, the proportion of the number of each CPU core, and the proportion of the number of each running memory.

4. The method for generating a low-end mobile device standard according to claim 1, characterized in that: The device information of Apple devices includes: device model, operating system generation, and operating system version number.

5. The method for generating a low-end mobile device standard according to claim 1, characterized in that: The proportion of low-end index parameters of Apple devices includes: the proportion of operating system generations and operating system version numbers of each device model.

6. The method for generating a low-end mobile device standard according to claim 1, characterized in that: Also includes: Any target client sends a low-end machine determination request to the server; The server side responds to the judgment request of the low-end machine, obtains the real-time online duration and real-time device information of the target client locally, and pulls the statistical jamming data of the target client in the current preset period from the big data center; The server obtains the low-end machine determination result of the target client according to the low-end machine standard configuration of the last preset period, the real-time online time, the online time, device information and freeze data counted in the current preset period of the real-time device information; The server feeds back the low-end machine determination result to the target client; The target client adjusts the resource adaptation configuration of the multimedia resources in the application program according to the determination result of the low-end machine.

7. The method for generating a low-end mobile device standard according to claim 6, characterized in that: The low-end machine determination result includes: machine model level, resolution level, CPU occupancy threshold, and memory occupancy threshold.

8. The method for generating a low-end mobile device standard according to claim 7, characterized in that: The target client adjusts the resource adaptation configuration of the motion effect resource in the application according to the low-end machine determination result, including: The target client determines the resource type of the target motion effect resource; The target client determines whether to play the target motion effect resource according to the resource type, the machine model level, the CPU occupancy threshold and the memory occupancy threshold.

9. The method for generating a low-end mobile device standard according to claim 8, characterized in that: The target client adjusts the resource adaptation configuration of the dynamic effect resource in the application according to the low-end machine determination result, and further includes: When the target client determines that the target motion effect resource is not played, the target client determines a static image type to be played in place of the target motion effect resource according to the resolution level.

10. An application platform, characterized in that: The application platform includes a server, a big data center and a client; The big data center is configured to count the online duration, device information and freeze data of each client within the preset period once every preset period; The big data center is configured to generate a report on the number of freezes per minute and a proportion of low-end machine indicator parameters according to the online duration, the device information and the freeze data; The big data center is configured to generate a judgment standard value of each low-end machine indicator parameter according to the proportion of the low-end machine indicator parameter and the report of the number of freezes per minute, and push it to the server; The server is configured to generate a low-end machine standard configuration according to the judgment standard value and a preset judgment rule, and the low-end machine standard configuration is used to determine whether the device corresponding to the client is a low-end machine.

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