System and method for automatically tracking distribution network log of intelligent equipment

Abstract

The invention discloses a system and a method for automatically tracking a distribution network log of intelligent equipment, relates to the technical field of log management of the intelligent equipment, and solves the problems that when a log management system of the intelligent equipment analyzes a large number of log files, the log files are difficult to clean in time, so that abnormal problems cannot be processed in time; and the experience feeling of a user is influenced. Comprising a data acquisition module used for acquiring abnormal log data; the data processing module is used for generating a cleaning signal according to the storage space and the storage time of each abnormal log data when the used storage space of the storage module is greater than a space cleaning threshold value; the network module is used for transmitting the abnormal storage data to the cloud server according to the network transmission quality; the storage module is used for cleaning the abnormal log data according to the cleaning signal; storing the abnormal log data; the cloud server is used for generating an abnormal data packet and an alarm signal according to the error code; the log management efficiency of the intelligent equipment is enhanced, and the experience feeling of a user of the intelligent equipment is improved.

Description

Technical Field

[0001] The present application belongs to the field of smart device log management technology, and relates to smart device log management technology, and specifically to a system and method for automatically tracking smart device network configuration logs. Background Art

[0002] Smart device logs are records of various important data generated by smart devices during operation, including the device's operating status, operation history, error information, etc. These logs are of great significance for device monitoring, troubleshooting, performance optimization, and security auditing.

[0003] The prior art (the patent for invention with announcement number CN112948341B) discloses a method and apparatus for identifying abnormal network device logs. The specific implementation of the method includes: obtaining a set of network device logs to be identified; matching using at least one type of preset network device log template to generate the number of network device logs that match each type of network device log template within a preset time period; and generating prompt information indicating whether there are abnormal network device logs based on the match between the number and the corresponding historical log number distribution, wherein the historical log number distribution is generated based on the match between the set of network device logs within the previous preset time period and the preset at least one type of network device log template. This implementation improves the recognition efficiency and accuracy of abnormal network device logs.

[0004] The above-mentioned method for identifying network device log anomalies solves the problem of analyzing large-scale logs and identifying abnormal network device logs. However, the capacity of the storage module of the smart device is limited. When storing a large number of logs, the storage module may be full, which will affect the storage of abnormal logs, resulting in the inability of relevant business personnel to handle abnormal problems in a timely manner, affecting the user experience of the smart device; at the same time, the log management efficiency of the smart device is reduced; therefore, a system and method for automatically tracking the network configuration logs of smart devices is needed. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes a system and method for automatically tracking smart device network configuration logs, which is used to solve the technical problem that when the existing smart device log management system analyzes a large number of log files, the storage module is difficult to clean up the log files in a timely and effective manner, resulting in the inability of relevant business personnel to handle abnormal problems in a timely manner, affecting the user experience of the smart device.

[0006] To achieve the above-mentioned purpose, the first aspect of the present application provides a system for automatically tracking network configuration logs of intelligent devices, including: a data acquisition module, a data processing module, a cloud server, a network module, an internal storage module and an alarm module;

[0007] The data acquisition module: when a program processing exception occurs in the smart device, obtains the log record of the smart device and records it as abnormal log data;

[0008] The data processing module: obtains the used storage space of the storage module, and when the used storage space is greater than the space cleaning threshold, obtains the storage time of each abnormal log data stored in the storage module; generates a cleaning signal according to the storage space and the storage time of each abnormal log data; and obtains the abnormal log data through the data acquisition module connected thereto; and stores the abnormal log data in the storage module;

[0009] The network module: obtains the network transmission quality; transmits the abnormal storage data in the storage module to the cloud server according to the network transmission quality;

[0010] The storage module: obtains a cleaning signal and cleans up the stored abnormal log data; and obtains the abnormal log data and stores it;

[0011] The cloud server extracts error codes from abnormal log data and generates abnormal data packets and alarm signals according to the error codes;

[0012] The alarm module obtains the alarm signal and the abnormal data packet, and sends the alarm signal and the abnormal data packet to the business personnel.

[0013] The present application obtains the log records of the smart device and records them as abnormal log data when a program processing exception occurs in the smart device; when the used storage space of the storage module is greater than the space cleaning threshold; generates a cleaning signal according to the storage space and the storage time of each abnormal log data; cleans the abnormal log data according to the cleaning signal; and then stores the newly generated abnormal log data; otherwise, directly stores the newly generated abnormal log data; detects the network transmission quality in real time, and uploads the abnormal log data in time when the network transmission quality is good; generates an alarm signal and an abnormal data packet according to the error code in the abnormal log data; and sends the alarm signal and the abnormal data packet to the smart device of the business personnel; by timely cleaning the storage module and uploading the abnormal log data, the relevant business personnel or smart devices can handle the abnormal problems in time, so as to improve the efficiency of log management of smart devices and enhance the user experience of smart devices.

[0014] Preferably, the program processing exceptions include network exceptions and access service exceptions; the network exceptions include device networking exceptions, device reset exceptions, and device parsing instruction exceptions, etc.; the access service exceptions include device access interface exceptions, request failure exceptions, and request return data exceptions, etc.

[0015] In this application, each program processing exception has its own unique corresponding error code; for example, the error code for device networking exception is "101", the error code for device reset exception is "102", etc.; the error code for device access interface exception is "201", the error code for unable to request exception is "202", etc.

[0016] Preferably, generating the cleaning signal according to the storage space and the storage time of each abnormal log data includes the following steps:

[0017] Step 1: Get the storage time of each abnormal log data in the storage module.

[0018] Step 2: Determine whether there is abnormal log data whose storage time exceeds the storage time threshold; if yes, mark the abnormal log data as deletable data; then proceed to step 3; if no, mark the abnormal log data as storable data; then proceed to step 3;

[0019] Step 3, obtain the storage space occupied by the abnormal log data corresponding to all storable data; determine whether the occupied storage space is greater than the space cleaning threshold; if so, number the storable data from large to small according to the storage time, and proceed to step 4; if not, proceed to step 5;

[0020] Step 4: Mark the abnormal log data corresponding to the storable data with the largest number as deletable data; jump to step 3;

[0021] Step 5: Mark each deletable data as deleted data and generate a cleanup signal.

[0022] Preferably, the space cleaning threshold is set according to the abnormal log data stored in the storage module, including:

[0023] Get the average log data volume corresponding to the abnormal log data stored in the storage module and mark it as PSJ; calculate the space cleaning threshold KQ through the formula KQ = exp(-a×PSJ / ZSJ)×ZKQ; where ZSJ is the total storage data volume of the storage module; ZKQ is the maximum space cleaning threshold set; a is the proportional coefficient, and a>0.

[0024] The present application obtains the space cleaning threshold by calculating according to the above formula. When the remaining storage space of the storage module is the same, the larger the average log data volume of the recent abnormal log data, the smaller the number of abnormal logs stored in the remaining storage space; if multiple abnormal storage logs are generated continuously, it is not conducive to the storage of abnormal log data; therefore, the present application sets the space cleaning threshold to be smaller accordingly when the average log data volume is larger, so as to increase the number of abnormal logs stored in the remaining storage space after cleaning the data.

[0025] Preferably, the transmitting of abnormal storage data in the storage module to the cloud server according to the network transmission quality includes:

[0026] The network transmission quality is obtained. When the network transmission quality is greater than the transmission quality threshold, the abnormal log data stored in the storage module is obtained, the abnormal log data is encrypted, and the encrypted abnormal log data is uploaded to the cloud server.

[0027] Preferably, generating an alarm signal and an abnormal data packet according to the error code includes:

[0028] Get the error code, and query the corresponding processing solution and solution category in the exception problem processing library according to the error code; determine whether the solution category is automatic processing;

[0029] If yes, the program processing exception is processed according to the processing plan. When the processing result is successful, the processing result is sent to the business personnel's smart device; otherwise, the processing plan and the plan category are integrated into an exception data packet, and an automatic processing exception alarm signal is generated;

[0030] If not, the processing scheme and scheme category are generated into an abnormal data packet; and a program abnormality alarm signal is generated;

[0031] The alarm signals include automatic processing abnormality alarm signals and program abnormality alarm signals; the processing results include success and failure, and the solution categories include automatic processing and manual processing.

[0032] Preferably, the abnormal problem handling library is established by program processing abnormalities and their corresponding processing solutions, including:

[0033] Get program processing exceptions, as well as the corresponding error codes and processing solutions;

[0034] Determine whether the processing scheme requires manual operation, if yes, mark the scheme category corresponding to the processing scheme as manual processing, if no, mark the scheme category corresponding to the processing scheme as automatic processing;

[0035] Establish a mapping relationship between error codes and their corresponding processing solutions and solution categories;

[0036] And build an exception problem handling library based on error codes, handling solutions and solution categories, as well as their corresponding mapping relationships.

[0037] On the other hand, a method for automatically tracking network configuration logs of smart devices is provided, comprising the following steps:

[0038] Step 1: When a program processing exception occurs in the smart device, a log record of the smart device is obtained and recorded as abnormal log data;

[0039] Step 2: Obtain the used storage space of the storage module and determine whether the used storage space is greater than the space clearing threshold; if yes, proceed to step 3; if no, proceed to step 4;

[0040] Step 3: Obtain the storage time of each abnormal log data stored in the storage module; generate a cleaning signal according to the storage space and the storage time of each abnormal log data; clean up the abnormal log data according to the cleaning signal;

[0041] Step 4: Obtain abnormal log data and store the abnormal log data in a storage module;

[0042] Step 5: Obtain network transmission quality; upload abnormal storage data in the storage module according to the network transmission quality;

[0043] Step 6: Extract the error code from the abnormal log data, generate an alarm signal and an abnormal data packet according to the error code; and send the alarm signal and the abnormal data packet to the business personnel's smart device.

[0044] Compared with the prior art, the beneficial effects of this application are:

[0045] 1. The present application obtains the log records of the smart device and records them as abnormal log data when a program processing exception occurs in the smart device; when the used storage space of the storage module is greater than the space cleaning threshold; generates a cleaning signal according to the storage space and the storage time of each abnormal log data; cleans the abnormal log data according to the cleaning signal; and then stores the newly generated abnormal log data; otherwise, directly stores the newly generated abnormal log data; detects the network transmission quality in real time, and uploads the abnormal log data in time when the network transmission quality is good; generates an alarm signal and an abnormal data packet according to the error code in the abnormal log data; and sends the alarm signal and the abnormal data packet to the smart device of the business personnel; by timely cleaning the storage module and uploading the abnormal log data, the relevant business personnel or smart devices can handle the abnormal problems in time, so as to improve the efficiency of log management of smart devices and enhance the user experience of smart devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 This is a schematic diagram of the principle of the system for automatically tracking the network configuration log of smart devices in this application;

[0048] Figure 2 A schematic diagram of the cleaning signal generation process in this application;

[0049] Figure 3 This is a flowchart of the steps of the method for automatically tracking the network configuration log of smart devices in this application. DETAILED DESCRIPTION

[0050] The technical solution of the present application will be described clearly and completely below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0051] See also Figure 1 , a first aspect of the present application provides a system for automatically tracking network configuration logs of intelligent devices, including: a data acquisition module, a data processing module, a cloud server, a network module, an internal storage module and an alarm module;

[0052] Data collection module: When a program processing exception occurs in a smart device, such as an air conditioner, washing machine, and refrigerator, etc., the log records of the smart device are obtained and recorded as abnormal log data; the abnormal log data includes program processing exception, time, abnormal module, error code, device program version, etc.;

[0053] Data processing module: obtain the used storage space of the storage module, and when the used storage space is greater than the space cleaning threshold, obtain the storage time of each abnormal log data stored in the storage module; generate a cleaning signal according to the storage space and the storage time of each abnormal log data; the cleaning signal includes the abnormal log data to be cleaned; is used to clean the abnormal log data in the storage module; and obtain the abnormal log data through the data acquisition module connected thereto; store the abnormal log data in the storage module;

[0054] Network module: obtains network transmission quality; transmits abnormal storage data in the storage module to the cloud server according to the network transmission quality;

[0055] Storage module: obtains a cleaning signal and cleans up the stored abnormal log data; and obtains the abnormal log data and stores it;

[0056] Cloud server: extracts error codes from abnormal log data and generates abnormal data packets and alarm signals based on the error codes;

[0057] Alarm module: obtains alarm signals and abnormal data packets, and sends alarm signals and abnormal data packets to business personnel's smart computers, smart phones, smart tablets, etc.

[0058] In this embodiment, when a program processing exception occurs in the smart device, the log record of the smart device is obtained and recorded as abnormal log data; when the used storage space of the storage module is greater than the space cleaning threshold; a cleaning signal is generated according to the storage space and the storage time of each abnormal log data; the abnormal log data is cleaned according to the cleaning signal; and the newly generated abnormal log data is stored; otherwise, the newly generated abnormal log data is directly stored; the network transmission quality is detected in real time, and when the network transmission quality is good, the abnormal log data is uploaded in time; an alarm signal and an abnormal data packet are generated according to the error code in the abnormal log data; and the alarm signal and the abnormal data packet are sent to the smart device of the business personnel; by timely cleaning the storage module and uploading the abnormal log data, the relevant business personnel or smart devices can handle the abnormal problems in time, so as to improve the efficiency of log management of smart devices and enhance the user experience of smart devices.

[0059] Program processing exceptions include network exceptions and access service exceptions; the network exceptions include device networking exceptions, device reset exceptions, and device parsing instruction exceptions, etc.; the access service exceptions include device access interface exceptions, request failure exceptions, and request return data exceptions, etc.

[0060] In this embodiment, each program processing exception has its own unique corresponding error code; for example, the error code for device networking exception is "101", the error code for device reset exception is "102", etc.; the error code for device access interface exception is "201", the error code for unable to request exception is "202", etc.

[0061] See also Figure 2 , generating a cleanup signal according to the storage space and the storage time of each abnormal log data, including the following steps:

[0062] Step 1: Obtain the storage time of each abnormal log data in the storage module, where the storage time is the time when the abnormal log data is stored in the storage module;

[0063] Step 2: Determine whether there is abnormal log data whose storage time exceeds the storage time threshold; if yes, mark the abnormal log data as deletable data; proceed to step 3; if no, mark the abnormal log data as storable data; proceed to step 3; the storage time threshold is a time threshold set according to experience, such as one month and 15 days;

[0064] Step 3, obtain the occupied storage space of the abnormal log data corresponding to all storable data; the occupied storage space is the storage space occupied by all storable data; determine whether the occupied storage space is greater than the space cleaning threshold; if yes, number the storable data from large to small according to the storage time, and enter step 4; if no, enter step 5; the space cleaning threshold is the cleaning threshold of the storage module, such as the used storage space of the storage module has reached 85%, and the set space cleaning threshold is 80%, then the storage module needs to be cleaned up at this time;

[0065] Step 4: Mark the abnormal log data corresponding to the storable data with the largest number as deletable data; jump to step 3;

[0066] Step 5: Mark each deletable data as deleted data and generate a cleanup signal.

[0067] It is understandable that under normal circumstances, that is, when the storage module has not reached the storage threshold, the stored abnormal log data will not be deleted; this ensures that within a certain time limit, when errors occur in the abnormal log data in the cloud server, verified abnormal log data can be provided.

[0068] The space cleanup threshold is set based on the abnormal log data stored in the storage module, including:

[0069] Get the average log data volume corresponding to the abnormal log data stored in the storage module and mark it as PSJ; calculate the space cleaning threshold KQ through the formula KQ = exp(-a×PSJ / ZSJ)×ZKQ; where ZSJ is the total storage data volume of the storage module; ZKQ is the maximum space cleaning threshold set; a is the proportional coefficient, and a>0.

[0070] This embodiment obtains the space cleaning threshold by calculating according to the above formula. When the remaining storage space of the storage module is the same, the larger the average log data volume of the recent abnormal log data, the smaller the number of abnormal logs stored in the remaining storage space; if multiple abnormal storage logs are generated continuously, it is not conducive to the storage of abnormal log data; therefore, this application sets the space cleaning threshold to be smaller accordingly when the average log data volume is larger, so as to increase the number of abnormal logs stored in the remaining storage space after cleaning the data.

[0071] It is understandable that, since a storage time threshold is set in the storage module and the storage time threshold is set relatively small, such as 1 month and 15 days, the abnormal log data stored in the storage module can represent recent abnormal log data.

[0072] Transmit abnormal storage data in the storage module to the cloud server based on the network transmission quality, including:

[0073] Obtain the network transmission quality. When the network transmission quality is greater than the transmission quality threshold, obtain the abnormal log data stored in the storage module, encrypt the abnormal log data, and upload the encrypted abnormal log data to the cloud server. It can be understood that in the case of good network, the abnormal log data closer to the current record is preferentially uploaded, and then other data is uploaded.

[0074] It should be noted that the transmission quality threshold can be a fixed threshold set according to experience, or a variable threshold set according to the data volume of the current abnormal log data; mark the data volume of the current abnormal log data as SL; calculate the transmission quality threshold CY through the formula CY = (1 + k × arctan(SL / BL - 1)) × BCZ; where BL is the set standard data volume, BCZ is the optimal network transmission quality considering transmission timeliness and transmission efficiency set by experts according to experience; k is a proportionality coefficient, and 0 < k < 1 / π; since it is not recommended to perform transmission in the case of poor network transmission quality, k is set to be less than 1 / π; that is, the minimum transmission quality threshold is 0.5 times the optimal network transmission quality.

[0075] The transmission quality threshold calculated by the above formula in this embodiment; when the data volume of the abnormal log data to be uploaded is large, the required network transmission quality is higher, so that the probability of problems in the process of uploading the abnormal log data is smaller. Therefore, this embodiment sets the transmission quality threshold according to the data volume of the abnormal log data to be uploaded. When the data volume is larger, the corresponding transmission quality threshold is higher.

[0076] The network transmission quality is a comprehensive value that can average the network quality obtained by experts considering current network bandwidth, packet loss rate, transmission delay and other data.

[0077] In another embodiment, when the abnormal log data is uploaded to the cloud server, verify whether the abnormal log data in the cloud server is the same as the corresponding abnormal log data in the storage module. If they are the same, clear the corresponding abnormal log data in the storage module; if they are different, re-upload the corresponding abnormal log data.

[0078] Generate an alarm signal and an abnormal data packet according to the error code, including: obtain the error code, query its corresponding processing solution and solution category in the abnormal problem processing library according to the error code; judge whether the solution category is automatic processing;

[0079] If yes, process the program exception according to the processing solution. When the processing result is successful, send the processing result to the intelligent device of the business personnel; otherwise, integrate the processing solution and the solution category into an abnormal data packet, and generate an automatic processing exception alarm signal.

[0080] If not, the processing scheme and scheme category are generated into an abnormal data packet; and a program abnormality alarm signal is generated;

[0081] The alarm signals include automatic processing exception alarm signals and program exception alarm signals; the processing results include success and failure, and the solution categories include automatic processing and manual processing; automatic processing refers to exceptions that can be handled by automatically modifying the program, and manual processing refers to exceptions that require manual assistance or manual processing.

[0082] The exception problem handling library is established through program handling exceptions and their corresponding handling solutions, including: obtaining program handling exceptions, and their corresponding error codes and handling solutions;

[0083] Determine whether the processing scheme requires manual operation, if yes, mark the scheme category corresponding to the processing scheme as manual processing, if no, mark the scheme category corresponding to the processing scheme as automatic processing;

[0084] Establish a mapping relationship between error codes and their corresponding processing solutions and solution categories;

[0085] And build an exception problem handling library based on error codes, handling solutions and solution categories, as well as their corresponding mapping relationships.

[0086] See also Figure 3 On the other hand, a method for automatically tracking network configuration logs of smart devices is provided, comprising the following steps:

[0087] Step 1: When a program processing exception occurs on the smart device, the log record of the smart device is obtained and recorded as abnormal log data;

[0088] Step 2: Obtain the used storage space of the storage module and determine whether the used storage space is greater than the space clearing threshold; if yes, proceed to step 3; if no, proceed to step 4;

[0089] Step 3: Obtain the storage time of each abnormal log data stored in the storage module; generate a cleaning signal according to the storage space and the storage time of each abnormal log data; clean up the abnormal log data according to the cleaning signal;

[0090] Step 4: Obtain abnormal log data and store the abnormal log data in a storage module;

[0091] Step 5: Obtain network transmission quality; upload abnormal storage data in the storage module according to the network transmission quality;

[0092] Step 6: Extract the error code from the abnormal log data, generate an alarm signal and an abnormal data packet according to the error code; and send the alarm signal and the abnormal data packet to the business personnel's smart device.

[0093] This embodiment automatically tracks the network configuration log of smart devices, breaking the existing problem of being unable to timely troubleshoot abnormal device usage in user homes, and providing a fast and effective way for business personnel to obtain remote smart device network configuration log data, thereby better meeting the needs of business personnel and improving user experience. It brings convenience to users' daily use of smart devices and enhances their experience of using smart devices.

[0094] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0095] How this application works:

[0096] The present application obtains the log records of the smart device and records them as abnormal log data when a program processing exception occurs in the smart device; when the used storage space of the storage module is greater than the space cleaning threshold; generates a cleaning signal according to the storage space and the storage time of each abnormal log data; cleans the abnormal log data according to the cleaning signal; and then stores the newly generated abnormal log data; otherwise, directly stores the newly generated abnormal log data; detects the network transmission quality in real time, and uploads the abnormal log data in time when the network transmission quality is good; generates an alarm signal and an abnormal data packet according to the error code in the abnormal log data; and sends the alarm signal and the abnormal data packet to the smart device of the business personnel; by timely cleaning the storage module and uploading the abnormal log data, the relevant business personnel or smart devices can handle the abnormal problems in time, so as to improve the efficiency of log management of smart devices and enhance the user experience of smart devices.

[0097] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical method of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. A system for automatically tracking network configuration logs of smart devices, comprising: Data acquisition module, data processing module, cloud server, network module, internal storage module and alarm module; characterized in that, The data acquisition module: when a program processing exception occurs in the smart device, obtains the log record of the smart device and records it as abnormal log data; The data processing module: obtains the used storage space of the storage module, and when the used storage space is greater than the space cleaning threshold, obtains the storage time of each abnormal log data stored in the storage module; generates a cleaning signal according to the storage space and the storage time of each abnormal log data; and obtains the abnormal log data through the data acquisition module connected thereto; and stores the abnormal log data in the storage module; The network module: obtains the network transmission quality; transmits the abnormal storage data in the storage module to the cloud server according to the network transmission quality; The storage module: obtains a cleaning signal and cleans up the stored abnormal log data; and obtains the abnormal log data and stores it; The cloud server extracts error codes from abnormal log data and generates abnormal data packets and alarm signals according to the error codes; The alarm module is configured to obtain an alarm signal and an abnormal data packet, and send the alarm signal and the abnormal data packet to the smart device of the business personnel.

2. According to claim 1, a system for automatically tracking network configuration logs of intelligent devices is characterized in that: The program processing exceptions include network exceptions and access service exceptions; the network exceptions include device networking exceptions, device reset exceptions and device parsing instruction exceptions; the access service exceptions include device access interface exceptions, request failure exceptions and request return data exceptions.

3. The automatic tracking intelligent device network configuration log system according to claim 1 is characterized in that: Generating the cleaning signal according to the storage space and the storage time of each abnormal log data includes the following steps: Step 1: Get the storage time of each abnormal log data in the storage module. Step 2: Determine whether there is abnormal log data whose storage time exceeds the storage time threshold; if yes, mark the abnormal log data as deletable data; then proceed to step 3; if no, mark the abnormal log data as storable data; then proceed to step 3; Step 3, obtain the storage space occupied by the abnormal log data corresponding to all storable data; determine whether the occupied storage space is greater than the space cleaning threshold; if so, number the storable data from large to small according to the storage time, and proceed to step 4; if not, proceed to step 5; Step 4: Mark the abnormal log data corresponding to the storable data with the largest number as deletable data; jump to step 3; Step 5: Mark each deletable data as deleted data and generate a cleanup signal.

4. The automatic tracking intelligent device network configuration log system according to claim 2 is characterized in that: The space cleaning threshold is set according to the abnormal log data stored in the storage module, including: Get the average log data volume corresponding to the abnormal log data stored in the storage module and mark it as PSJ; calculate the space cleaning threshold KQ through the formula KQ = exp(-a×PSJ / ZSJ)×ZKQ; where ZSJ is the total storage data volume of the storage module; ZKQ is the maximum space cleaning threshold set; a is the proportional coefficient, and a>0.

5. The automatic tracking intelligent device network configuration log system according to claim 1 is characterized in that: The abnormal storage data in the storage module is transmitted to the cloud server according to the network transmission quality, including: obtaining the network transmission quality, when the network transmission quality is greater than the transmission quality threshold, obtaining the abnormal log data stored in the storage module, and encrypting the abnormal log data, and uploading the encrypted abnormal log data to the cloud server.

6. The automatic tracking intelligent device network configuration log system according to claim 1 is characterized in that: The generating of the alarm signal and the abnormal data packet according to the error code comprises: Get the error code, and query the corresponding processing solution and solution category in the exception problem processing library according to the error code; determine whether the solution category is automatic processing; If yes, the program processing exception is processed according to the processing plan. When the processing result is successful, the processing result is sent to the business personnel's smart device; otherwise, the processing plan and the plan category are integrated into an exception data packet, and an automatic processing exception alarm signal is generated; If not, the processing scheme and scheme category are generated into an abnormal data packet; and a program abnormality alarm signal is generated; The alarm signals include automatic processing abnormality alarm signals and program abnormality alarm signals; the processing results include success and failure, and the solution categories include automatic processing and manual processing.

7. The automatic tracking intelligent device network configuration log system according to claim 6 is characterized in that: The exception problem handling library is established by program processing exceptions and their corresponding processing solutions, including: Get program processing exceptions, as well as the corresponding error codes and processing solutions; Determine whether the processing scheme requires manual operation, if yes, mark the scheme category corresponding to the processing scheme as manual processing, if no, mark the scheme category corresponding to the processing scheme as automatic processing; Establish a mapping relationship between error codes and their corresponding processing solutions and solution categories; And build an exception problem handling library based on error codes, handling solutions and solution categories, as well as their corresponding mapping relationships.

8. A method for automatically tracking smart device network configuration logs, based on the operation of a system for automatically tracking smart device network configuration logs as claimed in any one of claims 1 to 7, characterized in that: The following steps are involved: Step 1: When a program processing exception occurs in the smart device, a log record of the smart device is obtained and recorded as abnormal log data; Step 2: Obtain the used storage space of the storage module and determine whether the used storage space is greater than the space clearing threshold; if yes, proceed to step 3; if no, proceed to step 4; Step 3: Obtain the storage time of each abnormal log data stored in the storage module; Generate a cleanup signal according to the storage space and the storage time of each abnormal log data; clean up the abnormal log data according to the cleanup signal; Step 4: Obtain abnormal log data and store the abnormal log data in a storage module; Step 5: Obtain network transmission quality; upload abnormal storage data in the storage module according to the network transmission quality; Step 6: Extract the error code in the abnormal log data, generate an alarm signal and an abnormal data packet according to the error code; and send the alarm signal and the abnormal data packet to the business personnel's smart device.

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