Data information integrated management platform based on cloud storage

Abstract

The invention discloses a data information integrated management platform based on cloud storage, and relates to the technical field of data management, a condition monitoring unit monitors the environmental condition of the management platform, and generates an environmental condition coefficient; if the environment condition coefficient is higher than a preset condition threshold value, the environment temperature in the current monitoring period is increased, a hardware state data set is established according to the monitoring result, and a hardware condition coefficient is generated; the fault self-checking unit carries out self-checking on the management platform, and the data backup unit backs up data in the management platform to a pre-prepared memory; and establishing a running state prediction model of the management platform, outputting a predicted value of the hardware condition coefficient and the maximum maintenance time of the management platform, and backing up data stored in the management platform to a cloud storage. The operation state of the management platform is predicted, the operation risk of the management platform is sensed or predicted in advance, and when the operation risk possibly exists, the operation risk can be processed in advance.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a data information integrated management platform based on cloud storage. Background Art

[0002] The data information integrated management platform is a comprehensive system software for managing and processing various types of data information. It provides a set of tools and functions for collecting, storing, organizing, analyzing and processing data to support the decision-making and business operations of enterprises or organizations. Through the data information integrated management platform, enterprises or organizations can better manage and utilize data, obtain value and insights from it, and support decision-making and business innovation. It provides a one-stop solution to help users gain a competitive advantage in the data-driven era. The management platform also includes hardware in addition to software, and the normal operation of the software system is also based on the hardware system, such as the normal operation of computer hardware.

[0003] However, if the management platform operates in a relatively closed environment with a high temperature, its own operating status may be affected to a certain extent. It may even bring certain operational risks to the operation of the management platform due to difficulty in heat dissipation or low heat dissipation efficiency. When it is difficult for users to deal with it in a timely manner, the security of the data stored and managed by the management platform will be affected to a certain extent.

[0004] To this end, the present invention provides a data information comprehensive management platform based on cloud storage. Summary of the invention

[0005] 1. Technical issues to be resolved In view of the deficiencies of the prior art, the present invention provides a data information integrated management platform based on cloud storage, wherein the environmental conditions of the management platform are monitored by a condition monitoring unit to generate an environmental condition coefficient; if the environmental condition coefficient is higher than a preset condition threshold, the ambient temperature in the current monitoring cycle increases, a hardware status data set is established based on the monitoring results, and a hardware condition coefficient is generated; the fault self-checking unit performs a self-check on the management platform, and the data backup unit backs up the data in the management platform to a pre-prepared storage; a management platform operation status prediction model is established, the predicted value of the hardware condition coefficient and the maximum maintenance time of the management platform are output, and the data stored in the management platform is backed up to the cloud storage. The operation status of the management platform is predicted, and the operation risk of the management platform is perceived or predicted in advance. When there may be an operation risk, it can be processed in advance, thereby solving the problems raised in the background technology.

[0006] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: a data information integrated management platform based on cloud storage, comprising: a condition monitoring unit, an early warning unit, a processing unit, a fault self-checking unit, a data backup unit, an analysis and prediction unit, an evaluation unit and an alarm unit, wherein when the management platform is in a working state, the condition monitoring unit monitors the environmental conditions of the management platform, and generates an environmental condition coefficient Hpj from the monitoring results; if the environmental condition coefficient Hpj is higher than a preset condition threshold, the early warning unit sends an early warning message to the outside; if the ambient temperature Wt increases within the current monitoring period, the processing unit monitors the hardware operating environment of the management platform, establishes a hardware status data set from the monitoring results, and generates a hardware condition coefficient Ypj; If the hardware condition coefficient Ypj exceeds the preset hardware threshold, the alarm unit will send an alarm message to the outside; set a detection cycle, and the fault self-detection unit will perform self-detection on the management platform to detect whether there is an operation fault during the operation of the management platform, and determine whether the operation fault can be handled in time. If so, it will be handled in a targeted manner. If not, the data backup unit will back up the data in the management platform to a pre-prepared storage; the storage may be a solid-state hard disk; and the alarm unit will send an alarm to the outside; if the hardware condition coefficient Ypj does not exceed the hardware threshold, establish an operation status prediction model of the management platform; use the ambient temperature Wt and ambient humidity Hs as input, and use the analysis and prediction unit to use the operation status prediction model to output the predicted value of the hardware condition coefficient Ypj and the maximum maintenance time Ct of the management platform; enable the cloud backup unit to back up the data stored in the management platform to the cloud storage within the maintenance time Ct.

[0007] Furthermore, the environmental condition coefficient Hpj is generated as follows: the condition monitoring unit uses a fixed time interval as a monitoring period to continuously detect the temperature conditions in the environment where the management platform is located, obtains several groups of environmental temperatures Wt, and generates a temperature change rate Ws according to the change rate of the environmental temperature Wt, arranges the several groups of temperature change rates Ws along the time axis, obtains the variance of the several groups of temperature change rates Ws, uses the variance as the smoothness of temperature change, and generates the temperature smoothness Wp; obtains several groups of environmental humidity Hs and the variance of the several groups of environmental humidity Hs, uses the variance as the smoothness of humidity change, and generates the humidity smoothness Hp.

[0008] Furthermore, the environmental condition coefficient Hpj is obtained as follows: the temperature stability Wp and the humidity stability Hp are obtained, and after dimensionless processing, the environmental condition coefficient Hpj is generated according to the following formula: Where:

[0009] in, , ,and , is the weight, and its specific value is set by the user. is the correlation coefficient of the ambient temperature Wt and the ambient humidity Hs; if at least one of the current ambient temperature Wt and the ambient humidity Hs is higher than the corresponding threshold, and the environmental condition coefficient Hpj is higher than the preset condition threshold, the early warning unit will issue an early warning message to the outside.

[0010] Furthermore, the hardware status data set is established as follows: when the management platform is in operation, the processing unit monitors and collects its operation status data, as follows: the operating temperature Yt of the management platform is obtained. If the operating temperature Yt exceeds the corresponding temperature threshold, the operating time Yx of the management platform that has been continued in the current stage and the data processing speed of the management platform in the current stage are continued to be collected, and the data processing speed is used as the operating speed Ys of the management platform; the operating temperature Yt, operating time Yx and operating speed Ys are summarized to establish the hardware status data set.

[0011] Furthermore, the hardware condition coefficient Ypj is generated as follows: after dimensionless processing of the above data in the hardware status data set, the hardware condition coefficient Ypj is generated according to the following formula:

[0012] in, , ,and , is the weight, It is a constant correction coefficient, and its specific value is set by the user or generated by analytical function fitting.

[0013] Furthermore, a detection cycle is set, and the fault self-detection unit performs self-detection on the management platform to detect whether there is an operational fault during the operation of the management platform. If an operational fault occurs, the location of the fault and the corresponding fault characteristics are obtained; after building a three-dimensional model of the management platform, the operational fault and the corresponding location are marked on the three-dimensional model, and the maintenance plan for the management platform is obtained through retrieval and collection, and a maintenance plan library is established after summarizing.

[0014] Furthermore, it also includes a solution matching unit, which matches a corresponding maintenance solution from a maintenance solution library by combining the trained matching model with the fault characteristics of the operating fault, and executes the maintenance solution to maintain the management platform and eliminate the operating fault; if the solution matching unit fails to match a corresponding maintenance solution in the maintenance solution library, the data backup unit backs up the data in the management platform to a pre-prepared storage; the storage may be a solid-state hard disk; and the alarm unit sends an alarm to the outside.

[0015] Furthermore, if the hardware condition coefficient Ypj does not exceed the hardware threshold, the operating status data and specification performance data of the management platform are detected and obtained, and combined with the neural network model, after training and testing, an operating status prediction model of the management platform is established; several groups of ambient temperatures Wt are obtained along the time axis, and the ambient temperature Wt is predicted according to the smoothing exponential prediction model to obtain several prediction values. If the predicted value of the ambient temperature Wt is higher than the average of the previous several monitoring cycles, the adjustment value of the ambient temperature Wt is generated according to the predicted value of the ambient temperature Wt; and in the same way, the adjustment value of the ambient humidity Hs is obtained.

[0016] Furthermore, it also includes a data identification unit and a cloud backup unit. Before backing up the stored data of the management platform to the cloud storage, the trained classifier is used to divide the stored data into a number of backup areas according to the purpose of the stored data; the data identification unit identifies the data in each backup area, establishes a data quality data set, and generates a data quality coefficient Spx from the data quality data set; Sort each data quality coefficient Spx from high to low, and use the sorting result as the backup priority, so that the cloud backup unit backs up the data in each backup area to the cloud storage in turn according to the backup priority; while executing the backup task, adopt a cooling strategy to at least reduce the ambient temperature Wt in the area where the management platform is located. After completing the cloud backup of the management platform data, if the environmental condition coefficient Hpj has not increased within the maintenance time Ct, continue to use the management platform.

[0017] Further, the query times of each item data in the backup area are obtained respectively, and the query frequency Ck is generated after averaging; if some of the item data are encrypted, the proportion of the encrypted data volume to the total data volume is obtained to generate the encryption ratio Jm; The average space occupied by each entry data is obtained, and the data volume St is generated after averaging; the query frequency Ck, encryption ratio Jm and data volume St are summarized to establish a data quality data set; the data quality data set is sent to the evaluation unit, so that the evaluation unit generates a data quality coefficient Spx according to the data quality data set in each backup area. The specific method is as follows: after the query frequency Ck, encryption ratio Jm and data volume St are dimensionless, they are calculated according to the following formula:

[0018] in, It is a constant correction coefficient, and its specific value is set by the user or generated by analytical function fitting.

[0019] (III) Beneficial effects The present invention provides a data information comprehensive management platform based on cloud storage, which has the following beneficial effects: 1. Continuously monitor the operating environment of the management platform, obtain the ambient temperature Wt and ambient humidity Hs, generate the environmental condition coefficient Hpj, and evaluate the operating environment of the management platform. If the operation of the management platform may be affected, issue an early warning to the outside, adjust the environment in time, increase ventilation and heat dissipation in the area where the management platform is located, and ensure the normal operation of the management platform.

[0020] 2. Identify possible operational failures on the management platform. After establishing a maintenance solution library, quickly match maintenance solutions for the management platform to maintain the management platform and ensure its normal operation, thereby ensuring the security of data on the platform. When the current operational failure is difficult to handle in a timely manner, prioritize backing up the current data to the storage device to reduce the negative impact of sudden shutdown of the management platform and fully ensure data security.

[0021] 3. Predict the environmental data of the management platform. If the environmental conditions change, generate the ambient temperature Wt adjustment value and the ambient humidity Hs adjustment value as the basis for predicting the operating status of the management platform. The operating risks of the management platform can be perceived or predicted in advance, and when there may be operating risks, they can be handled in advance.

[0022] 4. Generate the predicted value of the hardware condition coefficient Ypj and the maintenance time Ct, transfer the data of the management platform to the cloud storage, and complete the data transfer and backup within the maintenance time Ct when determining the specific impact of environmental conditions on the operation of the management platform to fully ensure the security of the data. You can also adjust the environment of the management platform within the maintenance time Ct to improve the operating conditions of the management platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a schematic diagram of the first working process of the data information integrated management platform of the present invention; Figure 2 This is a schematic diagram of the second workflow of the data information integrated management platform of the present invention; In the figure: 10, condition monitoring unit; 20, early warning unit; 30, processing unit; 40, fault self-detection unit; 50, solution matching unit; 60, data backup unit; 70, analysis and prediction unit; 80, data identification unit; 90, evaluation unit; 100, cloud backup unit; 110, alarm unit. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1 and Figure 2 The present invention provides a data information integrated management platform based on cloud storage, including a condition monitoring unit 10, an early warning unit 20, a processing unit 30, a fault self-checking unit 40, a scheme matching unit 50, a data backup unit 60, an analysis and prediction unit 70, a data identification unit 80, an evaluation unit 90, a cloud backup unit 100 and an alarm unit 110, wherein: When a management platform for running and processing data, such as a server, workstation or large computer, is in a working state, the condition monitoring unit 10 monitors the environmental conditions of the management platform and generates an environmental condition coefficient Hpj based on the monitoring results; wherein the environmental condition coefficient Hpj is generated as follows: The condition monitoring unit 10 measures the ambient temperature of the management platform at a fixed time interval as a monitoring cycle, for example, once every three minutes, to obtain a plurality of sets of ambient temperatures Wt, and generates a temperature change rate Ws according to the change rate of the ambient temperature Wt, arranges the plurality of sets of temperature change rates Ws along the time axis, obtains the variance of the plurality of sets of temperature change rates Ws, and uses the variance as the temperature change stability to generate the temperature stability Wp; Based on the same method as above, several groups of environmental humidity Hs and the variance of the several groups of environmental humidity Hs are obtained, and the variance is used as the stability of humidity change to generate humidity stability Hp; The temperature stability Wp and humidity stability Hp are obtained, and after dimensionless processing, the environmental condition coefficient Hpj is generated according to the following formula:

[0026] in, , ,and , is the weight, and its specific value is set by the user. is the correlation coefficient between ambient temperature Wt and ambient humidity Hs; Obtaining the environmental condition coefficient Hpj, if at least one of the current environmental temperature Wt and the environmental humidity Hs is higher than the corresponding threshold value, and the environmental condition coefficient Hpj is higher than the preset condition threshold value, the warning unit 20 sends a warning message to the outside; During use, when the management platform is in a state of continuous working, the operating environment of the management platform is continuously monitored, and the ambient temperature Wt and ambient humidity Hs are obtained to generate the environmental condition coefficient Hpj, so as to evaluate the operating environment of the management platform. If the environmental conditions are poor or there are signs of deterioration, the operation of the management platform may be affected. Therefore, if an external warning is issued when the environmental conditions are worse than expected, the environment can be adjusted in time, for example, ventilation and heat dissipation in the area where the management platform is located can be increased to ensure the normal operation of the management platform.

[0027] refer to Figure 1 and Figure 2 After receiving the warning information, if the ambient temperature Wt increases during the current monitoring period, the processing unit 30 monitors the hardware operating environment of the management platform, establishes a hardware status data set based on the monitoring results, and generates a hardware condition coefficient Ypj; The hardware status data set is established as follows: When the management platform is in operation, the processing unit 30 monitors and collects its operation status data, specifically as follows: obtaining the operation temperature Yt of the management platform, if the operation temperature Yt exceeds the corresponding temperature threshold, continuing to collect the operation time Yx that has been continued in the current stage of the management platform, and the data processing speed of the management platform in the current stage, and taking the data processing speed as the operation speed Ys of the management platform; Summarize the operating temperature Yt, operating time Yx and operating speed Ys to establish a hardware status data set; The hardware condition coefficient Ypj is generated as follows: After the above data in the hardware status data set is dimensionless, the hardware condition coefficient Ypj is generated according to the following formula:

[0028] in, , ,and , is the weight, It is a constant correction coefficient, and its specific value is set by the user or generated by analytical function fitting.

[0029] The hardware condition coefficient Ypj is obtained. If the hardware condition coefficient Ypj exceeds a preset hardware threshold, the alarm unit 110 sends an alarm message to the outside.

[0030] When in use, under the condition of receiving early warning information, the operating status of the management platform is monitored, a hardware status data set is established, and a hardware condition coefficient Ypj is generated. When the hardware condition coefficient Ypj is higher than the preset hardware threshold, it means that the current operating status of the management platform is poor and needs to be processed in time, otherwise the management platform may fail and there is an operational risk. At this time, the management platform needs to be maintained.

[0031] refer to Figure 1 and Figure 2 After receiving the alarm information, a detection cycle is set, for example, 10 minutes is used as a detection cycle, and the fault self-detection unit 40 performs a self-detection on the management platform to detect whether there is an operation fault during the operation of the management platform. If there is an operation fault, the location of the fault and the corresponding fault characteristics are obtained; After establishing a three-dimensional model of the construction management platform, the operation faults and corresponding locations are marked on the three-dimensional model; by searching and collecting, existing maintenance plans for the management platform are obtained, and a maintenance plan library is established after summarizing; The solution matching unit 50 matches a corresponding maintenance solution from a maintenance solution library by combining the trained matching model with the fault characteristics of the operation fault, and executes the maintenance solution to maintain the management platform and eliminate the operation fault; If the solution matching unit 50 fails to match a corresponding maintenance solution in the maintenance solution library, the data backup unit 60 backs up the data in the management platform to a pre-prepared storage device; the storage device may be a solid state drive; and the alarm unit 110 sends an alarm to the outside.

[0032] When in use, after receiving the alarm information, it means that the management platform may have certain operational risks. At this time, the possible operational failures of the management platform are identified, and after establishing a maintenance plan library, a maintenance plan for the management platform is quickly matched. After execution, the management platform is maintained to ensure the normal operation of the management platform, thereby ensuring the security of data in the platform. At the same time, when the current operational failure is difficult to handle or difficult to handle in time, the current data will be backed up to the storage device first to reduce the negative impact of the sudden shutdown of the management platform and ensure data security.

[0033] refer to Figure 1 and Figure 2 If the hardware condition coefficient Ypj does not exceed the hardware threshold, it means that the management platform may not have any operating failures at present, and the operating status is temporarily good, but there may still be certain operating risks. At this time, it is necessary to predict the operating status of the management platform to determine whether the management platform will have operating failures when the external conditions, that is, when the ambient temperature Wt and the ambient humidity Hs change; At this time, the operating status data of the management platform is detected and obtained, such as the operating temperature Yt, the operating time Yx and the operating speed Ys, and the specification performance data of the management platform is obtained, such as the heat dissipation efficiency, the power and the heat generated during operation; after the above data are summarized, combined with the neural network model, after training and testing, an operating status prediction model of the management platform is established; several groups of ambient temperatures Wt are obtained along the time axis, and the changes of the ambient temperature Wt are predicted according to the smoothing exponential prediction model to obtain several prediction values. If the predicted value of the ambient temperature Wt is higher than the average of the previous several monitoring cycles, such as the previous ten monitoring cycles, the adjustment value of the ambient temperature Wt is generated according to the predicted value of the ambient temperature Wt; The adjustment value of the ambient temperature Wt is obtained from 120% to 140% of the predicted value of the ambient temperature Wt; and the adjustment value of the ambient humidity Hs is obtained in the same manner.

[0034] When in use, when the management platform currently has no operation risk, an operation status prediction model of the management platform is established based on the operation data of the management platform; at the same time, the environmental data of the management platform is predicted. If the environmental conditions change, the ambient temperature Wt adjustment value and the ambient humidity Hs adjustment value are generated. Therefore, when the environmental conditions change, it serves as the basis for predicting the operation status of the management platform, and the operation risk of the management platform can be perceived or predicted in advance, so that when there may be operation risks, it can be handled in advance.

[0035] refer to Figure 1 and Figure 2 , respectively taking the adjusted ambient temperature Wt and ambient humidity Hs as input, the analysis and prediction unit 70 uses the operation state prediction model of the management platform to analyze and predict the operation state of the management platform and obtain the prediction result; the prediction value of the hardware condition coefficient Ypj is generated from the prediction result, and under the environmental condition, if the management platform can maintain operation, the maximum maintenance time Ct of the management platform is analyzed and obtained; If the predicted value of the hardware condition coefficient Ypj is higher than the current value and exceeds the hardware threshold, it means that when the operating environment of the management platform gradually changes, its operating risk is also gradually increasing; at this time, if the environmental condition coefficient Hpj increases, the early warning unit 20 will issue an early warning; and the cloud backup unit 100 will back up the data stored in the management platform to the cloud storage within the maintenance time Ct.

[0036] When in use, after obtaining the operation status prediction model, the operation of the management platform is predicted and analyzed under preset conditions to generate the predicted value of the hardware condition coefficient Ypj and the maintenance time Ct, which indicates that the operation risk of the management platform has increased. The early warning unit 20 issues an early warning and transfers the data of the management platform to the cloud storage. At this time, when determining the specific impact of environmental conditions on the operation of the management platform, the data transfer and backup are completed within the maintenance time Ct to fully ensure the security of the data. At the same time, the environment in which the management platform is located can be adjusted within the maintenance time Ct to improve the operating conditions of the management platform.

[0037] refer to Figure 2 , before backing up the stored data (e.g., data currently being processed) of the management platform to the cloud storage, using the trained classifier to divide the stored data into a number of backup areas according to the purpose of the stored data; The data identification unit 80 identifies the data in each backup area, obtains the query times of each item data in the backup area, and generates the query frequency Ck after averaging; if some of the item data are encrypted, obtains the proportion of the encrypted data volume to the total data volume, and generates the encryption ratio Jm; obtains the average space occupied by each item data, and generates the data volume St after averaging; summarizes the query frequency Ck, encryption ratio Jm and data volume St, and establishes a data quality data set; The data quality data set is sent to the evaluation unit 90, so that the evaluation unit 90 generates a data quality coefficient Spx according to the data quality data set in each backup area. The specific method is as follows: after the query frequency Ck, the encryption ratio Jm and the data volume St are dimensionlessly processed, according to the following formula:

[0038] in, It is a constant correction coefficient, and its specific value is set by the user or generated by analytical function fitting.

[0039] The data quality coefficients Spx are sorted from high to low, and the sorting result is used as the backup priority, so that the cloud backup unit 100 backs up the data in each backup area to the cloud storage in turn according to the backup priority to complete the cloud backup; while executing the backup task, a cooling strategy is adopted to at least reduce the ambient temperature Wt in the area where the management platform is located. After completing the cloud backup of the management platform data, if the environmental condition coefficient Hpj has not increased within the maintenance time Ct, the management platform continues to be used.

[0040] When in use, if it is difficult to complete the transfer of all data within the maintenance time Ct, the data quality coefficient Spx is generated, and the backup priority is generated accordingly. After the existing data is divided, the backup priority of the data in each area is determined, and each data is backed up in sequence according to the backup priority. When time is limited, important data is backed up first. When the management platform is about to face operational risks, the security of important data is prioritized.

[0041] Based on the above, when the environmental conditions of the management platform change, the environmental conditions are adjusted to improve the operating status of the management platform. On this basis, the management platform is self-checked and maintained to enable it to operate normally. If the management platform is difficult to maintain, the data is backed up to the cloud storage in advance to ensure data security.

[0042] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0043] 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 on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0044] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A data information integrated management platform based on cloud storage, characterized by: include: A condition monitoring unit (10), an early warning unit (20), a processing unit (30), a fault self-checking unit (40), a data backup unit (60), an analysis and prediction unit (70), a cloud backup unit (100) and an alarm unit (110), wherein: When the management platform is in a working state, the condition monitoring unit (10) monitors the environmental conditions of the management platform and generates an environmental condition coefficient Hpj based on the monitoring result; if the environmental condition coefficient Hpj is higher than a preset condition threshold, the early warning unit (20) sends an early warning message to the outside; If the ambient temperature Wt increases during the current monitoring period, the processing unit (30) monitors the hardware operating environment of the management platform, establishes a hardware status data set based on the monitoring results, and generates a hardware condition coefficient Ypj; if the hardware condition coefficient Ypj exceeds a preset hardware threshold, the alarm unit (110) sends an alarm message to the outside; A detection cycle is set, and the fault self-detection unit (40) performs a self-detection on the management platform to detect whether there is an operation fault in the operation of the management platform, and judge whether the operation fault can be handled in time. If so, it is handled in a targeted manner; if not, the data backup unit (60) backs up the data in the management platform to a pre-prepared storage, and the alarm unit (110) issues an alarm to the outside; If the hardware condition coefficient Ypj does not exceed the hardware threshold, an operation status prediction model of the management platform is established; the analysis and prediction unit (70) uses the operation status prediction model to output the predicted value of the hardware condition coefficient Ypj and the maximum maintenance time Ct of the management platform, so that the cloud backup unit (100) backs up the data stored in the management platform to the cloud storage within the maintenance time Ct.

2. The cloud storage-based data information integrated management platform according to claim 1, characterized in that: The environmental condition coefficient Hpj is generated as follows: the condition monitoring unit (10) continuously detects the temperature conditions in the environment where the management platform is located at a fixed time interval as a monitoring cycle, obtains a plurality of sets of environmental temperatures Wt, and generates a temperature change rate Ws according to the change rate of the environmental temperature Wt, and arranges the plurality of sets of temperature change rates Ws along the time axis; Obtain the variance of the temperature change rate Ws of the several groups, use the variance as the temperature change smoothness, and generate the temperature smoothness Wp; obtain the several groups of ambient humidity Hs and the variance of the several groups of ambient humidity Hs, use the variance as the humidity change smoothness, and generate the humidity smoothness Hp.

3. The cloud storage-based data information integrated management platform according to claim 2, characterized in that: The environmental condition coefficient Hpj is obtained as follows: obtain the temperature stability Wp and humidity stability Hp, and after dimensionless processing, generate the environmental condition coefficient Hpj according to the following formula: Where: in, , ,and , is the weight, and its specific value is set by the user. is the correlation coefficient between ambient temperature Wt and ambient humidity Hs; If at least one of the current ambient temperature Wt and the ambient humidity Hs is higher than the corresponding threshold value, and the ambient condition coefficient Hpj is higher than the preset condition threshold value, the early warning unit (20) sends an early warning message to the outside.

4. The cloud storage-based data information integrated management platform according to claim 3, characterized in that: The hardware status data set is established as follows: when the management platform is in operation, the processing unit (30) monitors and collects its operation status data, as follows: Get the operating temperature Yt of the management platform. If the operating temperature Yt exceeds the corresponding temperature threshold, continue to collect the operating time Yx that has been continued in the current stage of the management platform, and the data processing speed of the management platform in the current stage, and use the data processing speed as the operating speed Ys of the management platform; summarize the operating temperature Yt, operating time Yx and operating speed Ys, and establish a hardware status data set.

5. The cloud storage-based data information integrated management platform according to claim 4, characterized in that: The hardware condition coefficient Ypj is generated as follows: After the above data in the hardware status data set is dimensionless, the hardware condition coefficient Ypj is generated according to the following formula: in, , ,and , is the weight, It is a constant correction coefficient, and its specific value is set by the user or generated by analytical function fitting.

6. The cloud storage-based data information integrated management platform according to claim 5, characterized in that: Setting a detection cycle, wherein the fault self-detection unit (40) performs a self-detection on the management platform to detect whether there is an operation fault during operation of the management platform, and if there is an operation fault, obtaining the location where the fault occurs and the corresponding fault characteristics; After building a three-dimensional model of the construction management platform, the operating faults and their corresponding locations are marked on the three-dimensional model. Through retrieval and collection, maintenance plans for the management platform are obtained, and a maintenance plan library is established after summarizing.

7. The data information integrated management platform based on cloud storage according to claim 6, characterized in that: It also includes a solution matching unit (50), which matches a corresponding maintenance solution from a maintenance solution library by combining the trained matching model with the fault characteristics of the operation fault, and executes the maintenance solution to maintain the management platform and eliminate the operation fault; If the solution matching unit (50) fails to match a corresponding maintenance solution in the maintenance solution library, the data backup unit (60) backs up the data in the management platform to a pre-prepared storage device, and the alarm unit (110) issues an alarm.

8. The cloud storage-based data information integrated management platform according to claim 7, characterized in that: If the hardware condition coefficient Ypj does not exceed the hardware threshold, detect and obtain the operation status data and specification performance data of the management platform, and establish an operation status prediction model of the management platform after training and testing in combination with the neural network model; Several groups of ambient temperatures Wt are obtained along the time axis, and the ambient temperature Wt is predicted based on the smoothing exponential prediction model to obtain several prediction values. If the predicted value of the ambient temperature Wt is higher than the average of the previous several monitoring cycles, the adjustment value of the ambient temperature Wt is generated based on the predicted value of the ambient temperature Wt, and then the adjustment value of the ambient humidity Hs is obtained.

9. The cloud storage-based data information integrated management platform according to claim 8, characterized in that: It also includes a data identification unit (80) and a cloud backup unit (100), Before backing up the data stored in the management platform to the cloud storage, the trained classifier is used to divide the stored data into several backup areas according to the purpose of the stored data; The data identification unit (80) identifies the data in each backup area, establishes a data quality data set, and generates a data quality coefficient Spx from the data quality data set; sorting the data quality coefficients Spx from high to low, using the sorting result as the backup priority, so that the cloud backup unit (100) backs up the data in each backup area to the cloud storage in sequence according to the backup priority; While executing the backup task, a cooling strategy is adopted to at least reduce the ambient temperature Wt in the area where the management platform is located. After completing the cloud backup of the management platform data, if the environmental condition coefficient Hpj does not increase within the maintenance time Ct, the management platform continues to be used.

10. The cloud storage-based data information integrated management platform according to claim 9, characterized in that: The query times of each item data in the backup area are obtained respectively, and the query frequency Ck is generated after averaging; if some of the item data are encrypted, the proportion of the encrypted data volume to the total data volume is obtained to generate the encryption ratio Jm; the average space occupied by each item data is obtained, and the data volume St is generated after averaging; Summarize the query frequency Ck, encryption ratio Jm and data volume St to establish a data quality data set; The data quality data set is sent to the evaluation unit (90), so that the evaluation unit (90) generates a data quality coefficient Spx according to the data quality data set in each backup area. The specific method is as follows: after the query frequency Ck, the encryption ratio Jm and the data volume St are dimensionlessly processed, the following formula is used: in, It is a constant correction coefficient, and its specific value is set by the user or generated by analytical function fitting.

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