Personnel document file storage safety monitoring system based on big data analysis

Abstract

The invention relates to the field of safety monitoring, and discloses a personnel document file storage safety monitoring system based on big data analysis, which comprises a document information acquisition module, a storage environment acquisition module, a storage equipment acquisition module, a storage information acquisition module, a fire-fighting information acquisition module, a data processing module and an information sending module, the document information collection module is used for collecting document information, the document information comprises document material information and document existence duration information, and the document information is imported into the Internet to collect and retrieve standard storage environment information of the corresponding duration of the corresponding material; the standard storage environment information comprises standard temperature information, standard humidity information and standard dust concentration information, the storage environment acquisition module is used for acquiring real-time storage environment information, and the storage equipment acquisition module is used for acquiring storage equipment information; according to the invention, the personnel document file storage safety monitoring can be carried out more comprehensively, and the storage safety of the personnel document file is ensured.

Description

Technical Field

[0001] The present invention relates to the field of security monitoring, and in particular to a personnel document file storage security monitoring system based on big data analysis. Background Art

[0002] Personnel documents and archives serve as evidence of a person's identity, education, and qualifications. They are closely linked to a person's salary, social security, and organizational relationships, and are an important basis for recording one's life trajectory. Physical personnel documents and archives require standardized storage, and their security must be monitored during the storage process. A storage security monitoring system is used during this storage security monitoring process. However, the storage security monitoring system in the existing technology has poor security monitoring effect, which makes the stored physical personnel document files vulnerable to damage, and has a certain impact on the use of the storage security monitoring system. Therefore, a personnel document file storage security monitoring system based on big data analysis is proposed. Summary of the Invention

[0003] The purpose of the present invention is to provide a personnel document file storage security monitoring system based on big data analysis to solve the technical defects proposed by the background technology.

[0004] The present invention solves the above technical problems through the following technical solutions. The present invention includes a document information collection module, a storage environment collection module, a storage equipment collection module, a storage information collection module, a fire information collection module, a data processing module and an information sending module; The document information collection module is used to collect document information, including document material information and document storage time information, and import the document information into the Internet to collect and retrieve standard storage environment information of the corresponding material and corresponding time. The standard storage environment information includes standard temperature information, standard humidity information, and standard dust concentration information; The storage environment acquisition module is used to acquire real-time storage environment information, and the storage equipment acquisition module is used to acquire storage equipment information; The storage information collection module is used to collect storage area information, and the fire information collection module is used to collect fire information; The data processing module is used to process the standard storage environment information and the real-time storage environment information to obtain environmental warning information, the data processing module processes the storage equipment information to obtain equipment warning information, and the data processing module processes the storage area information and the fire information to generate fire warning information; The information sending module is used to send the environmental warning information, equipment warning information and fire warning information to a preset receiving terminal after the above information is generated.

[0005] Furthermore, the specific processing process of the standard storage environment information is as follows: extracting the collected standard storage environment information of the corresponding material and the corresponding duration, marking the number of the collected standard storage environment information as Q, and marking the standard storage environment information as G; When Q is greater than the preset value a1, at least Q / 2 is selected as the benchmark parameter, and the average is calculated after removing the maximum and minimum values ​​of Q / 2 Gs, thus obtaining the standard storage environment information; When Q is between the preset values ​​a1 and a2, at least 3 / 4Q Gs are selected as the benchmark parameter. After removing the maximum and minimum values ​​of the 3 / 4Q Gs, the average is calculated to obtain the standard storage environment information. When Q is less than the preset value a2, the maximum and minimum values ​​of Q Gs are removed and the average is calculated, thus obtaining the standard storage environment information; a1>a2.

[0006] Furthermore, the specific processing process of the environmental warning information is as follows: Step 1: Extract the collected standard storage environment information, and extract the standard temperature information, standard humidity information, and standard dust concentration information from the standard storage environment information; Step 2: extract the real-time environmental information, which includes real-time temperature information, real-time humidity information and real-time dust concentration information; Step 3: Mark the standard temperature information as E1, the standard humidity information as E2, and the standard dust concentration information as E3; Step 4: Mark the real-time temperature information as P1, the real-time humidity information as P2, and the real-time dust concentration information as P3; Step 5: Calculate the difference between the real-time temperature information P1 and the standard temperature information E1 to obtain the first evaluation parameter PE1; calculate the difference between the real-time humidity information P2 and the standard humidity information E2 to obtain the second evaluation parameter PE2; calculate the difference between the real-time dust concentration information mark P3 and the standard dust concentration information E3 to obtain the third evaluation parameter PE3; Step 6: When any one of the first evaluation parameter PE1 and the second evaluation parameter PE2 exceeds a preset range or the third evaluation parameter PE3 is greater than a preset value, an environmental warning message is generated.

[0007] Furthermore, the specific processing process of the storage device warning information is as follows: extracting the collected storage device information, the storage device information including the standard life information of the equipment, the actual use time information of the equipment and the equipment maintenance information; Calculate the difference between the standard life information of the device and the actual usage time of the device to obtain the life difference. When the life difference is less than a preset value, generate a storage device warning message; The equipment maintenance information is the time point information of each maintenance. The maintenance time point information is processed to obtain the maintenance interval information, and the mean of the maintenance interval information is calculated, that is, the maintenance evaluation parameter is obtained. When the maintenance evaluation parameter is greater than the preset value, the storage equipment warning information is generated.

[0008] Furthermore, the specific processing process of the fire warning information is as follows: extracting the collected fire equipment information, the fire equipment information including the number of fire equipment and the fire coverage area information of each fire equipment; The fire assessment parameters are obtained by processing the fire equipment quantity information, the fire coverage area information of a single fire equipment and the stored area information, and the fire assessment parameters are processed to generate fire warning information.

[0009] Furthermore, the specific processing process of the fire assessment parameters is as follows: extracting the number of fire-fighting equipment and the fire coverage area information of a single fire-fighting equipment, setting an auxiliary correction parameter α, marking the number of fire-fighting equipment information as Z1, marking the fire coverage area information of a single fire-fighting equipment as Z2, and marking the stored area information as K; Through the formula Z1*Z2*α-K=Zk, the fire assessment parameter Zk is obtained, α≈0.98.

[0010] Furthermore, the specific process of processing the fire assessment parameters to generate fire warning information is as follows: the collected fire assessment parameters are extracted, and when the fire assessment parameters are less than a preset warning value, fire warning information is generated.

[0011] Compared with the prior art, the present invention has the following advantages: The present invention imports document information into the Internet to collect and retrieve the standard storage environment information of the corresponding material and the corresponding time length, which can obtain more accurate personnel document file storage standards to ensure the accuracy of subsequent environmental warning information generation, and conduct detailed monitoring of the real-time storage environment. When there are abnormalities in the environment, timely warnings are issued to avoid the storage environment abnormality causing damage to the stored personnel document files. At the same time, by monitoring the storage device, when there is an abnormality in the storage device, warning information is also generated in time to avoid the damage to the stored physical personnel document files due to the abnormality of the storage device. The fire protection coverage of the storage site is monitored, and warnings are issued when abnormalities are found to avoid the damage to the stored physical personnel document files due to insufficient fire protection capabilities and the inability to eliminate the accident in time when an accident occurs, making the system more worthy of promotion and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0013] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process. However, the protection scope of the present invention is not limited to the following embodiment.

[0014] like Figure 1 As shown, this embodiment provides a technical solution: a personnel document file storage security monitoring system based on big data analysis, including a document information collection module, a storage environment collection module, a storage equipment collection module, a storage information collection module, a fire information collection module, a data processing module and an information sending module; The document information collection module is used to collect document information, including document material information and document storage time information. The document information is imported into the Internet to collect and retrieve the standard storage environment information of the corresponding material and corresponding time. The standard storage environment information includes standard temperature information, standard humidity information and standard dust concentration information. The storage environment collection module is used to collect real-time storage environment information, and the storage equipment collection module is used to collect storage equipment information; The storage information collection module is used to collect storage area information, and the fire information collection module is used to collect fire information; The data processing module is used to process the standard storage environment information and the real-time storage environment information to obtain the environmental warning information, the data processing module processes the storage equipment information to obtain the equipment warning information, and the data processing module processes the storage area information and the fire information to generate the fire warning information; The information sending module is used to send the environmental warning information, equipment warning information and fire warning information to the preset receiving terminal after the above information is generated; The present invention imports document information into the Internet to collect and retrieve the standard storage environment information of the corresponding material and the corresponding time length, which can obtain more accurate personnel document file storage standards, thereby ensuring the accuracy of subsequent environmental warning information generation, and performing detailed monitoring of the real-time storage environment. When there are abnormalities in the environment, timely warnings are issued to avoid the storage environment abnormality causing damage to the stored personnel document files. At the same time, by monitoring the storage device, when there is an abnormality in the storage device, warning information is also generated in time to avoid the damage to the stored physical personnel document files due to the abnormality of the storage device. The fire protection coverage of the storage site is monitored, and warnings are issued when abnormalities are found to avoid the damage to the stored physical personnel document files due to insufficient fire protection capabilities and the inability to eliminate accidents in time.

[0015] The specific processing process of the standard storage environment information is as follows: extract the collected standard storage environment information of the corresponding material and the corresponding duration, mark the number of the collected standard storage environment information as Q, and mark the standard storage environment information as G; When Q is greater than the preset value a1, at least Q / 2 is selected as the benchmark parameter, and the average is calculated after removing the maximum and minimum values ​​of Q / 2 Gs, thus obtaining the standard storage environment information; When Q is between the preset values ​​a1 and a2, at least 3 / 4Q Gs are selected as the benchmark parameter. After removing the maximum and minimum values ​​of the 3 / 4Q Gs, the average is calculated to obtain the standard storage environment information. When Q is less than the preset value a2, the maximum and minimum values ​​of Q Gs are removed and the average is calculated, thus obtaining the standard storage environment information; a1>a2; Through the above process, more accurate standard storage environment information can be obtained, and the basic data for calculating the standard storage environment information can be selected based on the actual amount of data collected. This not only ensures the accuracy of the obtained standard storage environment information, but also speeds up data processing.

[0016] The specific processing process of environmental warning information is as follows: Step 1: Extract the collected standard storage environment information, and extract the standard temperature information, standard humidity information, and standard dust concentration information from the standard storage environment information; Step 2: extract the real-time environmental information, which includes real-time temperature information, real-time humidity information and real-time dust concentration information; Step 3: Mark the standard temperature information as E1, the standard humidity information as E2, and the standard dust concentration information as E3; Step 4: Mark the real-time temperature information as P1, the real-time humidity information as P2, and the real-time dust concentration information as P3; Step 5: Calculate the difference between the real-time temperature information P1 and the standard temperature information E1 to obtain the first evaluation parameter PE1; calculate the difference between the real-time humidity information P2 and the standard humidity information E2 to obtain the second evaluation parameter PE2; calculate the difference between the real-time dust concentration information mark P3 and the standard dust concentration information E3 to obtain the third evaluation parameter PE3; Step 6: When any one of the first evaluation parameter PE1 and the second evaluation parameter PE2 exceeds a preset range or the third evaluation parameter PE3 is greater than a preset value, an environmental warning message is generated; Through the above process, environmental warning information can be generated in a timely manner to avoid the damage of stored physical personnel document files due to environmental problems.

[0017] The specific processing process of storage equipment warning information is as follows: extracting the collected storage equipment information, which includes equipment standard life information, equipment actual use time information and equipment maintenance information; Calculate the difference between the standard life information of the device and the actual usage time of the device to obtain the life difference. When the life difference is less than a preset value, generate a storage device warning message; The equipment maintenance information is the time point information of each maintenance. The maintenance time point information is processed to obtain the maintenance interval information, and the mean of the maintenance interval information is calculated to obtain the maintenance evaluation parameter. When the maintenance evaluation parameter is greater than the preset value, a storage equipment warning information is generated; Through the above process, the status information of the equipment storing the entity's personnel document files can be understood, and warning information can be generated in time to avoid the damage of the entity's personnel document files due to abnormalities in the storage equipment.

[0018] The specific processing process of fire warning information is as follows: extract the collected fire equipment information, which includes the number of fire equipment and the fire coverage area information of each fire equipment; The fire assessment parameters are obtained by processing the fire equipment quantity information, the fire coverage area information of a single fire equipment and the storage area information; The fire assessment parameters are processed to generate fire warning information. The specific processing process of the fire assessment parameters is as follows: the number of fire equipment information and the fire coverage area information of each fire equipment are extracted, and the auxiliary correction parameter α is set. The number of fire equipment information is marked as Z1, the fire coverage area information of each fire equipment is marked as Z2, and the stored area information is marked as K; The fire assessment parameter Zk is obtained through the formula Z1*Z2*α-K=Zk, where α≈0.98; Through the above process, the status of the fire-fighting equipment at the storage site can be evaluated, the actual fire-fighting coverage status of the fire-fighting equipment can be understood, and timely warnings can be issued when abnormalities are found.

[0019] The specific process of processing the fire assessment parameters to generate fire warning information is as follows: the collected fire assessment parameters are extracted, and when the fire assessment parameters are less than the preset warning value, the fire warning information is generated.

[0020] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0021] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0022] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A personnel document file storage security monitoring system based on big data analysis, characterized in that: It includes document information collection module, storage environment collection module, storage equipment collection module, storage information collection module, fire information collection module, data processing module and information sending module; The document information collection module is used to collect document information, including document material information and document storage time information, and import the document information into the Internet to collect and retrieve standard storage environment information of the corresponding material and corresponding time. The standard storage environment information includes standard temperature information, standard humidity information, and standard dust concentration information; The storage environment acquisition module is used to acquire real-time storage environment information, and the storage equipment acquisition module is used to acquire storage equipment information; The storage information collection module is used to collect storage area information, and the fire information collection module is used to collect fire information; The data processing module is used to process the standard storage environment information and the real-time storage environment information to obtain environmental warning information, the data processing module processes the storage equipment information to obtain equipment warning information, and the data processing module processes the storage area information and the fire information to generate fire warning information; The information sending module is used to send the environmental warning information, equipment warning information and fire warning information to a preset receiving terminal after the above information is generated.

2. The personnel document file storage security monitoring system based on big data analysis according to claim 1 is characterized by: The specific processing process of the standard storage environment information is as follows: extracting the collected standard storage environment information of the corresponding material and the corresponding duration, marking the number of the collected standard storage environment information as Q, and marking the standard storage environment information as G; When Q is greater than the preset value a1, at least Q / 2 is selected as the benchmark parameter, and the average is calculated after removing the maximum and minimum values ​​of Q / 2 Gs, thus obtaining the standard storage environment information; When Q is between the preset values ​​a1 and a2, at least 3 / 4Q Gs are selected as the benchmark parameter. After removing the maximum and minimum values ​​of the 3 / 4Q Gs, the average is calculated to obtain the standard storage environment information. When Q is less than the preset value a2, the maximum and minimum values ​​of Q Gs are removed and the average is calculated, thus obtaining the standard storage environment information; a1>a2.

3. The personnel document file storage security monitoring system based on big data analysis according to claim 1 is characterized by: The specific processing process of the environmental warning information is as follows: Step 1: Extract the collected standard storage environment information, and extract the standard temperature information, standard humidity information, and standard dust concentration information from the standard storage environment information; Step 2: extract the real-time environmental information, which includes real-time temperature information, real-time humidity information and real-time dust concentration information; Step 3: Mark the standard temperature information as E1, the standard humidity information as E2, and the standard dust concentration information as E3; Step 4: Mark the real-time temperature information as P1, the real-time humidity information as P2, and the real-time dust concentration information as P3; Step 5: Calculate the difference between the real-time temperature information P1 and the standard temperature information E1 to obtain the first evaluation parameter PE1; calculate the difference between the real-time humidity information P2 and the standard humidity information E2 to obtain the second evaluation parameter PE2; calculate the difference between the real-time dust concentration information mark P3 and the standard dust concentration information E3 to obtain the third evaluation parameter PE3; Step 6: When any one of the first evaluation parameter PE1 and the second evaluation parameter PE2 exceeds a preset range or the third evaluation parameter PE3 is greater than a preset value, an environmental warning message is generated.

4. The personnel document file storage security monitoring system based on big data analysis according to claim 1 is characterized by: The specific processing process of the storage device warning information is as follows: extracting the collected storage device information, the storage device information includes the equipment standard life information, the equipment actual use time information and the equipment maintenance information; Calculate the difference between the standard life information of the device and the actual usage time of the device to obtain the life difference. When the life difference is less than a preset value, generate a storage device warning message; The equipment maintenance information is the time point information of each maintenance. The maintenance time point information is processed to obtain the maintenance interval information, and the mean of the maintenance interval information is calculated, that is, the maintenance evaluation parameter is obtained. When the maintenance evaluation parameter is greater than the preset value, the storage equipment warning information is generated.

5. The personnel document file storage security monitoring system based on big data analysis according to claim 1 is characterized by: The specific processing process of the fire warning information is as follows: extracting the collected fire equipment information, which includes the number of fire equipment and the fire coverage area information of each fire equipment; The fire assessment parameters are obtained by processing the fire equipment quantity information, the fire coverage area information of a single fire equipment and the stored area information, and the fire assessment parameters are processed to generate fire warning information.

6. The personnel document file storage security monitoring system based on big data analysis according to claim 5 is characterized by: The specific processing process of the fire assessment parameters is as follows: extracting the number of fire-fighting equipment and the fire coverage area information of a single fire-fighting equipment, setting an auxiliary correction parameter α, marking the number of fire-fighting equipment information as Z1, marking the fire coverage area information of a single fire-fighting equipment as Z2, and marking the stored area information as K; Through the formula Z1*Z2*α-K=Zk, the fire assessment parameter Zk is obtained, α≈0.

98.

7. The personnel document file storage security monitoring system based on big data analysis according to claim 5 is characterized by: The specific process of processing the fire assessment parameters to generate fire warning information is as follows: extracting the collected fire assessment parameters, and when the fire assessment parameters are less than a preset warning value, generating fire warning information.

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