An internet-based remote device performance evaluation method and related apparatus

Abstract

The application discloses a kind of remote device performance evaluation method and related device based on internet.Therein, method includes: according to the remote device model established in advance, the text monitoring data of remote device based on internet transmission is obtained, and target data extraction is carried out to text monitoring data;The representative value of each target data is calculated, and each target representative value obtained by calculation is combined into evaluation coordinates;According to the remote device evaluation grade table established in advance, establish evaluation area chart;Evaluation coordinates are input into evaluation area chart, and the performance of remote device corresponding evaluation grade is obtained.

Description

Technical Field

[0001] This invention relates to the field of remote device performance evaluation technology, and more specifically, to an Internet-based remote device performance evaluation method and related apparatus. Background Technology

[0002] With digital transformation and upgrading, business demands are experiencing explosive growth. High-end integrated applications such as business convergence and data sharing are developing rapidly. Information system deployment and operation modes are becoming increasingly complex, and users have higher requirements for user experience and business response speed in digital systems. This necessitates monitoring the front-end performance of business systems and continuously optimizing the front-end experience. Currently, data collection for front-end business performance largely relies on external third-party performance collection tools, using methods such as simulating front-end operations or inserting front-end code. However, the collected data samples lack comprehensive coverage and cannot simulate various terminal environments. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a remote device performance evaluation method and related apparatus based on the Internet.

[0004] According to one aspect of the present invention, an Internet-based method for evaluating the performance of remote devices is provided, comprising:

[0005] Based on a pre-established remote device model, text monitoring data of remote devices transmitted via the Internet is obtained, and target data is extracted from the text monitoring data.

[0006] Calculate the representative value of each target data, and combine the calculated representative values ​​of each target into the evaluation coordinates;

[0007] Based on the pre-established remote equipment evaluation level table, create an evaluation area map;

[0008] Input the evaluation coordinates into the evaluation area map to obtain the evaluation level corresponding to the performance of the remote device.

[0009] Optionally, it also includes:

[0010] Construct a remote device model and divide the monitoring area within the remote device model.

[0011] Optionally, the operation of extracting target data from the text monitoring data includes:

[0012] A data retrieval tagging model is built based on a pre-set list of key trees;

[0013] Text monitoring data is retrieved and labeled using a data retrieval and labeling model;

[0014] Data is extracted from the text monitoring data after retrieval and tagged, and the extracted data is integrated into target data in the key tree list according to the corresponding monitoring items.

[0015] Optionally, the operation of integrating the extracted data into various target data in the key tree list according to the corresponding monitoring items includes:

[0016] Identify the key tree list, and set the corresponding standard monitoring item filling template according to the tree arrangement of each monitoring item. The standard monitoring item filling template is marked with the corresponding weight coefficient.

[0017] Obtain the extracted data corresponding to each monitoring item, and fill the extracted data into the standard monitoring item filling template according to the corresponding position to obtain the corresponding target data.

[0018] Optionally, the operation of calculating representative values ​​for each target data point and combining the calculated representative values ​​into evaluation coordinates includes:

[0019] The target data are numerically transformed to determine the target representative value corresponding to each target data.

[0020] The target representative value is compared with the corresponding threshold to obtain a single monitoring result, which includes monitoring qualified and monitoring unqualified. Based on the single monitoring result, the corresponding monitoring area in the remote equipment monitoring model is marked. The marked target representative values ​​are combined to determine the evaluation coordinates, and monitoring unqualified corresponds to multiple unqualified degrees.

[0021] Optionally, the operation of creating an assessment area map based on a pre-established remote equipment assessment level table includes:

[0022] Set a central location point for each evaluation level in the remote equipment evaluation level table;

[0023] Plot the simulated coordinates and center positioning point of the historical monitoring data of the remote equipment obtained in advance onto the coordinate graph, and label the center positioning point with the corresponding evaluation level.

[0024] Based on the remote equipment assessment level table, determine the maximum assessment radius and maximum merging distance for each assessment level;

[0025] Based on the maximum assessment radius and maximum merging distance of each assessment level, and using the center positioning point of each assessment level as the initial center, the simulated coordinates of historical monitoring data are merged to obtain the assessment area;

[0026] Each assessment area is labeled with its corresponding assessment level, and an assessment area map is created.

[0027] According to another aspect of the present invention, an Internet-based remote device performance evaluation apparatus is provided, comprising:

[0028] The extraction module is used to acquire text monitoring data of remote devices transmitted over the Internet based on a pre-established remote device model, and to extract target data from the text monitoring data.

[0029] The calculation module is used to calculate the representative value of each target data and combine the calculated representative values ​​of each target into evaluation coordinates.

[0030] The module is used to create an assessment area map based on a pre-established remote equipment assessment level table.

[0031] The acquisition module is used to input the evaluation coordinates into the evaluation area map and obtain the evaluation level corresponding to the performance of the remote device.

[0032] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0033] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0034] Therefore, this application provides an Internet-based remote device performance evaluation method. By making the monitoring data of the corresponding remote device three-dimensional, relevant personnel can have an intuitive understanding of a single monitoring item within the remote device through the device monitoring model, which does not require high professional knowledge from the relevant personnel. Furthermore, by establishing an evaluation area map and transforming the corresponding data, intelligent judgment of the remote device performance can be achieved, which can greatly reduce the degree of personnel involvement in the later remote device evaluation process. Attached Figure Description

[0035] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0036] Figure 1 This is a flowchart illustrating an exemplary embodiment of the Internet-based remote device performance evaluation method provided by the present invention.

[0037] Figure 2 This is another flowchart illustrating an exemplary embodiment of the Internet-based remote device performance evaluation method provided by the present invention.

[0038] Figure 3This is a schematic diagram of the structure of an Internet-based remote device performance evaluation device provided in an exemplary embodiment of the present invention;

[0039] Figure 4 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. Detailed Implementation

[0040] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0041] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0042] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0043] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0044] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless explicitly defined or given contrary instructions in the context.

[0045] Furthermore, the term "and / or" in this invention 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, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0046] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0047] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0048] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0049] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0050] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0051] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0052] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0053] Exemplary methods

[0054] Figure 1 This is a flowchart illustrating an exemplary embodiment of an Internet-based remote device performance evaluation method provided by the present invention. This embodiment can be applied to electronic devices, such as… Figure 1 As shown, the Internet-based remote device performance evaluation method 100 includes the following steps:

[0055] Step 101: Based on the pre-established remote device model, acquire text monitoring data of the remote device transmitted via the Internet, and extract target data from the text monitoring data.

[0056] Step 102: Calculate the representative value of each target data, and combine the calculated representative values ​​of each target into evaluation coordinates;

[0057] Step 103: Based on the pre-established remote equipment evaluation level table, create an evaluation area map;

[0058] Step 104: Input the evaluation coordinates into the evaluation area map to obtain the evaluation level corresponding to the performance of the remote device.

[0059] For specific details, please refer to the detailed process steps of this solution. Figure 2 As shown:

[0060] Step 1: Establish a remote device data model, mark it as a device monitoring model, and divide the monitoring area within the device monitoring model accordingly;

[0061] The remote device data model is a three-dimensional data model built using existing modeling techniques.

[0062] The method for dividing the monitoring area within the equipment monitoring model is as follows: the area to be monitored is divided manually. For example, if a certain device needs to be monitored and evaluated, the corresponding area is divided into the device area manually. After obtaining the corresponding results, they are displayed in a corresponding form to facilitate intuitive understanding by relevant personnel. The display form refers to using different colors to represent the corresponding single monitoring results, with different single monitoring results corresponding to different colors.

[0063] Step 2: Obtain text monitoring data transmitted over the Internet and extract the corresponding target data;

[0064] The text monitoring data is remote device detection data obtained based on existing monitoring technologies. Because it is remote device monitoring data obtained based on existing technologies, the monitoring process will not be described in detail in this application.

[0065] The methods for extracting the target data include:

[0066] Establish a key item tree list, build a data retrieval and labeling model based on the set key item tree list, perform corresponding retrieval and labeling on the text monitoring data through the data retrieval and labeling model, extract the corresponding data based on the labeled text monitoring data, and integrate the extracted data into target data according to the arrangement of the corresponding monitoring items in the key item tree list.

[0067] The key item tree list is created manually. This involves identifying which monitoring items are included, their sub-items, and assigning weight coefficients to each sub-item within the monitoring item. This is confirmed by combining the monitoring technology of the corresponding remote equipment. For example, if a remote equipment monitoring facility includes sub-items such as temperature and humidity, the corresponding weight coefficients are set to 0.7 and 0.3, respectively. The list is then drawn and labeled level by level according to the corresponding tree diagram method. All these settings can be configured manually.

[0068] The data retrieval labeling model is built on a neural network model, or it can directly obtain an existing model with the same function, or it can be adapted based on the existing model. For example, based on the existing retrieval model, the corresponding retrieval data is obtained according to the retrieval keywords of the corresponding monitoring items and sub-items, and then the corresponding labeling is performed. The specific establishment and training process is common knowledge in this field, so it will not be described in detail.

[0069] Methods for integrating extracted data into target data according to the arrangement of corresponding monitoring items in the key item tree list include:

[0070] Identify the key item tree list, set the corresponding standard monitoring item filling template according to the tree arrangement of each monitoring item, obtain the corresponding extracted data, and fill the standard monitoring item filling template with the extracted data according to the corresponding position to obtain the corresponding target data.

[0071] The standard monitoring item filling template is marked with the corresponding weight coefficient.

[0072] Step 3: Calculate the representative value of each target data, mark it as the target representative value, compare the target representative value with the corresponding threshold to obtain a single monitoring result; mark the corresponding area in the equipment monitoring model according to the obtained single monitoring result.

[0073] Methods for calculating representative values ​​for each target data point include:

[0074] Perform numerical transformation of the target data, labeled as Pi, where i = 1, 2, ..., n, n is a positive integer; i represents the sub-item in the corresponding monitoring item; obtain the corresponding weight coefficient, labeled as βi, and calculate the representative value according to the formula.

[0075] Numerical transformation of target data refers to converting non-numerical data into numerical data. Specifically, the expert group can set corresponding numerical values ​​based on the available data, form a numerical transformation table, and then perform the appropriate matching to obtain the corresponding numerical values.

[0076] A single monitoring result includes whether the monitoring is qualified or unqualified, as well as the degree of unqualified monitoring, which is the difference exceeding the corresponding threshold. Then, it is matched with the corresponding manifestation degree. For example, different color depths of the same color can be matched by manually establishing a corresponding matching table.

[0077] The corresponding area in the equipment monitoring model is marked according to the obtained single monitoring result. That is, the corresponding display form is matched according to the single monitoring result, such as different colors, and the corresponding area is marked according to the matched display form.

[0078] Methods for comparing a target representative value with a corresponding threshold include:

[0079] The expert group establishes a corresponding threshold table. Based on the monitoring item corresponding to the representative value, the corresponding threshold is matched from the threshold table. When the representative value is within the threshold range, the single monitoring result is qualified; when the representative value exceeds the threshold range, the single monitoring result is qualified or unqualified, and the corresponding difference is calculated.

[0080] Step 4: Combine the representative values ​​of each monitoring item into an evaluation coordinate system;

[0081] Step 5: Establish an evaluation level table for remote equipment, and create an evaluation area map based on the evaluation level table;

[0082] The assessment grading table is compiled manually, with grading based on the user's assessment needs, and different assessment grades are supplemented with corresponding assessment criteria.

[0083] Methods for creating assessment area maps based on assessment rating scales include:

[0084] Set a central location point for each assessment level, plot the central location point on the coordinate graph, and label it with the corresponding assessment level. Obtain a large amount of historical monitoring data on the performance of remote devices, convert the obtained historical monitoring data into several simulated coordinates, and input the simulated coordinates into the coordinate graph.

[0085] The maximum assessment radius and the maximum merging distance are set according to the assessment level. The maximum assessment radius and the maximum merging distance are both set by the expert group through discussion. The maximum merging distance is set manually based on the difference between the corresponding assessment levels. The simulated coordinates are merged with the central positioning point as the initial center to obtain the assessment area. The assessment area is labeled with the corresponding assessment level, and the current coordinate map is marked as the assessment area map.

[0086] A central location point is set for each assessment level manually, in the same way as setting the assessment coordinates in steps two to four. A central location point that can represent the corresponding assessment level is set manually.

[0087] Based on the acquired historical monitoring data, several simulated coordinates are converted and set up according to steps two through four.

[0088] Methods for merging simulated coordinates using the central positioning point as the initial center include:

[0089] Step SA1: Calculate the Euclidean distance between each simulated coordinate and the initial center. Sort the calculated Euclidean distances in ascending order and mark them as the first sequence. Set a fixed-point distance, which is discussed and set by the expert group to speed up the merging process. Mark the simulated coordinates in the first sequence that are smaller than the fixed-point distance. Identify the simulated coordinates corresponding to the largest marked Euclidean distance in the first sequence and mark it as the first merging point. Draw a circle with the distance between the initial coordinates and the first merging point as the radius and the initial coordinates as the center to obtain the first circle. Merge the simulated coordinates, initial coordinates, and the first merging point within the first circle, identify the corresponding merging region, and mark it as the first region. Mark all simulated points within the first region as merging points.

[0090] Step SA2: Identify the center point of the first region and mark it as the second center. Calculate the merging radius of the merged region based on the second center.

[0091] The merging center is set according to the density of the simulated coordinates. The neural network model is trained manually, and the trained model is used for analysis and settings.

[0092] Step SA3: Compare the merge radius with the maximum evaluation radius. If the merge radius is not greater than the maximum evaluation radius, perform cyclic merging until the merge radius is greater than the maximum evaluation radius, then proceed to step SA4.

[0093] Methods for performing cyclic merging include:

[0094] Identify the merging point on the boundary of the first region and mark it as the second center. There are multiple merging points on the boundary. Calculate the Euclidean distance between the remaining simulated coordinates and the second center. Sort the calculated Euclidean distances in ascending order and mark them as the second sequence. Mark the distances in the second sequence that are less than the fixed point distance. Identify the simulated coordinates corresponding to the largest marked Euclidean distance in the second sequence and mark it as the second merging point. Draw a circle with the distance between the corresponding second center and the second merging point as the radius and the second center as the center to obtain the second circle. Merge the simulated coordinates within the second circle with the first region and identify the corresponding merging region, marking it as the second region. Mark all simulated points within the second region as merging points. Identify the center point of the second region and mark it as the third center. Calculate the merging radius of the merging region based on the third center. Compare the merging radius with the maximum evaluation radius, and so on, until the merging radius is greater than the maximum evaluation radius, at which point the loop stops.

[0095] Step SA4: Perform priority deordering until the merge radius is no greater than the maximum evaluation radius, then mark the corresponding region as the evaluation region.

[0096] Priority deordering refers to removing corresponding merge points one by one based on their distance from the merge center.

[0097] Step 6: Input the evaluation coordinates into the evaluation area map to obtain the evaluation level corresponding to the performance of the remote equipment.

[0098] This method is based on a browser client. The browser serves as the access point for the business system, responsible for resource loading and page rendering. It can collect data on the entire front-end business process and the response time of all resources when users are using the business system. With browsers distributed across various office terminals, a distributed performance monitoring and analysis system can be established based on the browser client. In a silent state, it can simulate manual operation and collect data on the front-end performance of the business system.

[0099] Therefore, by making the monitoring data of the corresponding remote devices three-dimensional, relevant personnel can have an intuitive understanding of a single monitoring item within the remote device through the device monitoring model, which does not require high professional knowledge from the relevant personnel. Furthermore, by establishing an evaluation area map and transforming the corresponding data, intelligent judgment of the performance of the remote device can be achieved, which can greatly reduce the degree of personnel involvement in the later evaluation process of the remote device.

[0100] Exemplary device

[0101] Figure 3 This is a schematic diagram of the structure of an Internet-based remote device performance evaluation device provided in an exemplary embodiment of the present invention. Figure 3 As shown, the device 300 includes:

[0102] The extraction module 310 is used to acquire text monitoring data of remote devices transmitted via the Internet based on a pre-established remote device model, and to extract target data from the text monitoring data.

[0103] The calculation module 320 is used to calculate the representative value of each of the target data and combine the calculated target representative values ​​into evaluation coordinates;

[0104] Module 330 is used to create an assessment area map based on a pre-established remote equipment assessment level table.

[0105] The acquisition module 340 is used to input the evaluation coordinates into the evaluation area map to obtain the evaluation level corresponding to the performance of the remote device.

[0106] Optionally, the device 300 further includes:

[0107] A construction module is used to build a remote device model and divide the monitoring area within the remote device model.

[0108] Optionally, the extraction module 310 includes:

[0109] The first submodule is used to build a data retrieval tagging model based on a pre-set list of key trees.

[0110] The tagging submodule is used to retrieve and tag text monitoring data using a data retrieval tagging model.

[0111] The extraction submodule is used to extract data from the text monitoring data after retrieval and marking, and integrate the extracted data into various target data in the key tree list according to the corresponding monitoring items.

[0112] Optionally, extract submodules, including:

[0113] The identification unit is used to identify the key tree list and set the corresponding standard monitoring item filling template according to the tree arrangement of each monitoring item. The standard monitoring item filling template is marked with the corresponding weight coefficient.

[0114] The acquisition unit is used to obtain the extracted data corresponding to each monitoring item, and fill the extracted data into the standard monitoring item filling template according to the corresponding position to obtain the corresponding target data.

[0115] Optionally, the computing module 320 includes:

[0116] The first determination submodule is used to convert the target data into numerical values ​​and determine the target representative value corresponding to each target data.

[0117] The second determination submodule is used to compare the target representative value with the corresponding threshold to obtain a single monitoring result, wherein the single monitoring result includes monitoring qualified and monitoring unqualified. Based on the single monitoring result, the corresponding monitoring area in the remote equipment monitoring model is marked, and the marked target representative values ​​are combined to determine the evaluation coordinates. Furthermore, monitoring unqualified corresponds to multiple unqualified degrees.

[0118] Optionally, module 330 is established, including:

[0119] The configuration submodule is used to set a central location point for each evaluation level in the remote device evaluation level table.

[0120] The drawing submodule is used to draw the simulated coordinates and center positioning point of the historical monitoring data of the pre-acquired remote equipment onto the coordinate graph, and to label the center positioning point with the corresponding evaluation level label.

[0121] The third determination submodule is used to determine the maximum evaluation radius and maximum merging distance for each evaluation level based on the remote equipment evaluation level table;

[0122] The submodule is used to merge simulated coordinates of historical monitoring data based on the maximum assessment radius and maximum merging distance of each assessment level, with the center positioning point of each assessment level as the initial center, to obtain the assessment area;

[0123] The second sub-module is used to label each assessment area with a corresponding assessment level and create an assessment area map.

[0124] Exemplary electronic devices

[0125] Figure 4 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. For example... Figure 4 As shown, the electronic device 40 includes one or more processors 41 and memory 42.

[0126] The processor 41 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0127] The memory 42 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 41 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above, and / or other desired functions. In one example, the electronic device may also include an input device 43 and an output device 44, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0128] In addition, the input device 43 may also include, for example, a keyboard, a mouse, etc.

[0129] The output device 44 can output various information to the outside. The output device 44 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0130] Of course, for the sake of simplicity, Figure 4 Only some of the components of the electronic device relevant to the present invention are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0131] Exemplary computer program products and computer-readable storage media

[0132] In addition to the methods and apparatus described above, embodiments of the present invention may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0133] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of the present invention. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0134] Furthermore, embodiments of the present invention may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the methods for information mining of historical change records according to various embodiments of the present invention as described in the "Exemplary Methods" section above.

[0135] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0136] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0137] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0138] The block diagrams of devices, systems, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0139] The methods and systems of the present invention may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of the present invention are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, the present invention may also be implemented as a program recorded on a recording medium, the program comprising machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers recording media storing programs for performing the methods according to the present invention.

[0140] It should also be noted that in the systems, apparatus, and methods of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0141] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for remote device performance evaluation based on the Internet, characterized in that, include: Based on a pre-established remote device model, text monitoring data of remote devices transmitted via the Internet is acquired, and target data is extracted from the text monitoring data. Calculate the representative value of each of the target data, and combine the calculated representative values ​​of each target into evaluation coordinates; Based on the pre-established remote equipment evaluation level table, create an evaluation area map; Input the evaluation coordinates into the evaluation area map to obtain the evaluation level corresponding to the performance of the remote device; The operation of calculating representative values ​​for each of the target data and combining the calculated representative values ​​into evaluation coordinates includes: The target data are numerically transformed to determine the target representative value corresponding to each target data. The target representative value is compared with the corresponding threshold to obtain a single monitoring result, wherein the single monitoring result includes monitoring qualified and monitoring unqualified. The corresponding monitoring area in the remote equipment monitoring model is marked according to the single monitoring result. The marked target representative values ​​are combined to determine the evaluation coordinates. The monitoring unqualified corresponds to multiple unqualified degrees. The operation of creating an assessment area map based on a pre-established remote equipment assessment level table includes: Set a central location point for each evaluation level in the remote equipment evaluation level table; The simulated coordinates of the historical monitoring data of the remote device obtained in advance and the central positioning point are plotted on the coordinate graph, and the central positioning point is labeled with the corresponding evaluation level. Based on the remote equipment evaluation level table, determine the maximum evaluation radius and maximum merging distance for each evaluation level; Based on the maximum assessment radius and the maximum merging distance for each assessment level, and using the central positioning point of each assessment level as the initial center, the simulated coordinates of the historical monitoring data are merged to obtain the assessment area; Each of the assessment areas is labeled with a corresponding assessment level, and an assessment area map is created.

2. The method according to claim 1, characterized in that, Also includes: Construct a remote device model and divide the monitoring area within the remote device model.

3. The method according to claim 1, characterized in that, The operation of extracting target data from the text monitoring data includes: A data retrieval tagging model is built based on a pre-set list of key trees; The text monitoring data is retrieved and labeled using the data retrieval and labeling model. Data is extracted from the text monitoring data after retrieval and tagged, and the extracted data is integrated into the target data in the key tree list according to the corresponding monitoring items.

4. The method according to claim 3, characterized in that, The operation of integrating the extracted data into the target data according to the corresponding monitoring items in the key tree list includes: Identify the key tree list, and set the corresponding standard monitoring item filling template according to the tree arrangement of each monitoring item, wherein the standard monitoring item filling template is marked with the corresponding weight coefficient; The extracted data corresponding to each monitoring item is obtained, and the extracted data is filled into the standard monitoring item filling template according to the corresponding position to obtain the corresponding target data.

5. An Internet-based remote device performance evaluation apparatus, used to implement the method described in any one of claims 1-4, characterized in that, include: The extraction module is used to acquire text monitoring data of remote devices transmitted via the Internet based on a pre-established remote device model, and to extract target data from the text monitoring data. The calculation module is used to calculate the representative value of each of the target data, and combine the calculated target representative values ​​into evaluation coordinates; The module is used to create an assessment area map based on a pre-established remote equipment assessment level table; The acquisition module is used to input the evaluation coordinates into the evaluation area map to obtain the evaluation level corresponding to the performance of the remote device.

6. The apparatus according to claim 5, characterized in that, Also includes: A construction module is used to build a remote device model and divide the monitoring area within the remote device model.

7. The apparatus according to claim 5, characterized in that, The operation of extracting target data from the text monitoring data includes: A data retrieval tagging model is built based on a pre-set list of key trees; The text monitoring data is retrieved and labeled using the data retrieval and labeling model. Data is extracted from the text monitoring data after retrieval and tagged, and the extracted data is integrated into the target data in the key tree list according to the corresponding monitoring items.

8. The apparatus according to claim 7, characterized in that, The calculation module includes: Identify the key tree list, and set the corresponding standard monitoring item filling template according to the tree arrangement of each monitoring item, wherein the standard monitoring item filling template is marked with the corresponding weight coefficient; The extracted data corresponding to each monitoring item is obtained, and the extracted data is filled into the standard monitoring item filling template according to the corresponding position to obtain the corresponding target data.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-4.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-4.

Images