Intelligent archive management system based on remote monitoring

Abstract

The invention relates to the technical field of archive management, in particular to an intelligent archive management system based on remote monitoring, which comprises a sensing layer module, a wireless signal optimization module, a label optimization module, an execution control module, an archive management monitoring module and a data processing library. According to the method, the signal influence information is obtained by analyzing the environment detection data, the signal transmission state is obtained by obtaining the signal transmission data and analyzing the signal transmission data, and the signal transmission optimization information is obtained by comprehensively analyzing the signal influence information and the signal transmission state. Transmission optimization information is obtained by analyzing a data transmission process and an interference environment, so that the real-time performance of data transmission is guaranteed, and the monitoring timeliness is improved; according to the method, the label state information is obtained by analyzing the label information data, the label optimization instruction is obtained by analyzing the label state information, reading optimization adjustment is performed on the archive label, and the reading accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of archive management, and in particular to an intelligent archive management system based on remote monitoring. Background Art

[0002] Archives management is the work of managing and maintaining archival entities and information. It is of far-reaching significance. It is an important carrier of historical and cultural heritage, recording the development process of society, organizations and individuals, and can help people trace the past and understand the origin and evolution of things. At the same time, archives management provides authoritative credentials for various affairs, and rich archival resources provide real materials to promote the advancement and innovation of knowledge.

[0003] The archives management system is a digital tool for archives management. It streamlines and standardizes the archives management workflow. By centrally storing archive information, it can effectively avoid the loss and damage of archives and ensure the integrity and security of archives. This system can improve the efficiency of archives management, quickly complete the classification, retrieval and call of archives, and greatly reduce the time and effort spent on manual archive search.

[0004] In the complex archive warehouse environment, the wireless signals of the existing intelligent archive management system are easily blocked or interfered by obstacles such as metal shelves and walls, resulting in interruption or delay of data transmission, affecting the real-time monitoring effect; at the same time, when the archives are densely stored or the labels are blocked, the label reader of the intelligent archive rack may have inaccurate recognition or missed readings, which in turn affects the accurate positioning and tracking of the archives. Summary of the invention

[0005] The present invention provides an intelligent archive management system based on remote monitoring, which is used to solve the above technical problems.

[0006] A first aspect of the present invention provides an intelligent archive management system based on remote monitoring, including a perception layer module, a wireless signal optimization module, a label optimization module, an execution control module, an archive management monitoring module and a data processing library.

[0007] The perception layer module is used to collect environmental detection data, signal transmission data and archive information data through detection sensors, and send the environmental detection data, signal transmission data and archive information data to the data processing library;

[0008] Environmental detection instruments and signal detection instruments are installed at multiple locations in the archive management room. The environmental detection instruments are used to collect data on the indoor signal environment in the archive management room, and various data on signal transmission are collected through signal detection. Based on the storage location of the archives, all-round sensor arrangements are carried out to sense the archive labels, archive environment, and operating data of the master control equipment.

[0009] Environmental monitoring data is collected through environmental monitoring instruments. The environmental monitoring data includes signal coverage data, obstacle data and signal quality data;

[0010] The signal transmission data is acquired by collecting the signal detection instrument, and the signal transmission data includes the signal transmission rate, signal power data and signal characteristics;

[0011] The archive information data is obtained through sensor collection, and the archive information data includes label information data, archive environment data, equipment operation status and user access data.

[0012] The wireless signal optimization module is used to obtain environmental detection data and analyze the environmental detection data to obtain signal impact information, obtain signal transmission data and analyze the signal transmission data to obtain signal transmission status, comprehensively analyze the signal impact information and the signal transmission status to obtain signal transmission optimization information, and send the signal transmission optimization information to the execution control module.

[0013] As a further improvement of the present invention, the environmental detection data is analyzed, and the specific analysis method is as follows:

[0014] A1: Obtain signal coverage data, obstacle data and signal quality data through environmental monitoring data;

[0015] A2: A signal strength value is obtained according to the signal quality data, and a plurality of pre-set signal quality intervals are obtained. Each signal quality interval corresponds to a maximum signal value and a minimum signal value. The maximum signal value and the minimum signal value are marked as iXm and iXn, respectively, that is, each signal quality interval corresponds to [iXn, iXm], where i represents the number of the signal quality interval and is a positive integer. The average value is calculated according to the maximum signal value and the minimum signal value of each signal quality interval to obtain the mean signal strength of each signal quality interval.

[0016] A3: Divide the archive management area into multiple signal optimization blocks according to the signal coverage data, obtain the signal strength value of each signal optimization block, match the signal strength value of the signal optimization block with multiple signal quality intervals to obtain the signal quality interval corresponding to each signal optimization block, and obtain the mean signal strength corresponding to the signal quality interval.

[0017] A4: Obstacle data of the archive management area is identified to obtain obstacles of each signal optimization block, signal interference values ​​corresponding to the obstacles are obtained, and a preset signal interference threshold is obtained, obstacles with signal interference values ​​greater than the signal interference threshold are marked as interference obstacles, the number of interference obstacles is counted and recorded as the interference obstacle value, and the interference density is calculated by ratio of the interference obstacle value to the area of ​​each optimization block; interference obstacles include but are not limited to metal products, electrical equipment, walls, glass products and water bodies.

[0018] A5: Normalize the mean signal strength and interference density of each signal optimization block and take their values, using the formula The signal state value XH of each signal optimization block is calculated; where JQ and GR represent the mean signal strength and interference density, respectively. It is expressed as the mean signal reference intensity; f1 and f2 are both preset weight factors, with values ​​of 12.245 and 11.241 respectively.

[0019] A6: Obtain a preset signal state threshold, compare the signal state value of each signal optimization block with the signal state threshold, and when the signal state value is less than the signal state threshold, generate corresponding signal impact information that the block interference intensity is high.

[0020] As a further improvement of the present invention, the signal transmission data is analyzed, and the specific analysis method is as follows:

[0021] Obtaining a preset transmission segment distance, dividing the archive management area into a plurality of transmission segments based on the transmission segment distance, obtaining signal transmission data of each transmission segment, and obtaining a signal transmission rate, signal power data and signal characteristics according to the signal transmission data;

[0022] The transmission rate of each transmission segment is compared with the preset rate standard value. When the transmission rate is lower than the rate standard value, the transmission rate of each transmission segment is calculated by difference with the rate standard value to obtain the rate quality fluctuation value, and the preset quality fluctuation threshold is obtained. The part of the rate quality fluctuation value greater than the quality fluctuation threshold is marked as the rate impact value.

[0023] The signal power and noise power are obtained according to the signal power data of each transmission segment, the signal power and the noise power are ratio-calculated to obtain the signal-to-noise ratio, the difference between the signal-to-noise ratios corresponding to two adjacent transmission segments is calculated to obtain the signal attenuation value, the signal attenuation value is divided into multiple attenuation value intervals, each attenuation value interval corresponds to an attenuation impact value, and the signal attenuation values ​​corresponding to the current two adjacent transmission segments are matched with the multiple attenuation value intervals to obtain the corresponding attenuation impact values.

[0024] The starting transmission point and the transmission end point of each transmission segment are obtained, and the original signal characteristics corresponding to the starting transmission point and the final signal characteristics corresponding to the transmission end point are obtained according to the signal characteristics. The signal distortion degree is obtained by comparing the original signal characteristics corresponding to the transmission segment with the final signal characteristics. The signal distortion degree of each transmission segment is constructed into a signal distortion degree curve according to the distance order of the transmission segments, and a preset upper limit value of the distortion degree is obtained, and the signal distortion degree exceeding the upper limit value of the distortion degree is marked as a distortion impact value.

[0025] Two squares are constructed with the values ​​of the rate influence value and the attenuation influence value as the sides of the squares. A straight line perpendicular to the two squares is drawn with the centroids of the two squares as the starting point and the end point. The length of the straight line is equal to the value of the distortion influence value. The four vertices of the two squares are matched and connected to obtain a tetrahedron. The volume of the tetrahedron is calculated and the value of the volume is marked as the signal transmission state value. When the signal transmission state is greater than the preset transmission state threshold, the corresponding signal transmission state is generated as a transmission segment state abnormality.

[0026] As a further improvement of the present invention, the signal impact information and the signal transmission status are comprehensively analyzed, and the specific analysis method is as follows:

[0027] The signal impact information corresponding to each signal optimization block is identified. When the signal impact information indicates that the block interference intensity is high, the corresponding signal optimization block is marked as an interference block, the signal status value of the interference block is obtained, and the pre-set signal status upper limit value is obtained. When the signal status value is greater than the signal status upper limit value, transmission congestion information is generated. Conversely, when the signal status value is less than the signal status upper limit value, signal optimization information is generated.

[0028] Based on the transmission congestion information, the corresponding signal transmission optimization information is generated as a transmission switching instruction; based on the signal optimizability information, the signal transmission status of the transmission segment corresponding to the signal optimization block is obtained. When the signal transmission status corresponds to an abnormal transmission segment status, the corresponding signal transmission optimization information is generated as a transmission self-inspection and maintenance; conversely, when the signal transmission status corresponds to normal, the corresponding signal transmission optimization information is generated as a signal enhancement start instruction.

[0029] The label optimization module is used to obtain the archive information data and identify the archive information to obtain the label information data, analyze the label information data to obtain the label status information, analyze the label status information to obtain the label optimization instruction, and send the label optimization instruction to the execution control module.

[0030] As a further improvement of the present invention, the tag information data is analyzed, and the specific analysis method is as follows:

[0031] The label reading data and the file image data of each file are obtained according to the label information data; multiple recognition data of each file are obtained according to the label reading data, the recognition time corresponding to each recognition data is obtained, and the pre-set recognition upper limit time is obtained, and the recognition time corresponding to each recognition data is compared with the recognition upper limit time. When the recognition time exceeds the recognition upper limit time, the corresponding recognition data is marked as recognition abnormal data, the number of recognition abnormal data is counted and recorded as the recognition abnormal number, and the recognition abnormality ratio is calculated by calculating the ratio of the recognition abnormal number to the total number of recognition data.

[0032] Obtain reading results corresponding to multiple label reading data, obtain pre-stored archive images and actual archive images corresponding to the reading results according to the archive image data, overlap and compare the pre-stored archive images corresponding to each monthly result with the actual archive images, and when the pre-stored archive images are different from the actual archive images, mark the corresponding reading results as abnormal reading results, count the number of abnormal reading results to obtain the abnormal reading number, and calculate the ratio of the abnormal reading number to the total number of reading results to obtain the abnormal reading ratio.

[0033] A triangle is constructed with the value of the recognition abnormality ratio as the side length of the equilateral triangle, a circle is constructed with the midpoint of one side of the equilateral triangle as the center and the value of the abnormal reading ratio as the radius, and then a closed figure is constructed with the equilateral triangle and the circle. The area of ​​the closed figure is calculated and the value of the area is marked as the label status value, and the label status value is used as the corresponding label status information.

[0034] As a further improvement of the present invention, the tag status information is analyzed, and the specific analysis method is as follows:

[0035] The label status information is identified to obtain the label status value, and a preset label status threshold is obtained. When the label status value is greater than the label status threshold, the corresponding label status is marked as a label status abnormality. According to the label status abnormality information, the label status abnormality includes but is not limited to label detachment, label obstruction, and label damage. The recognition abnormality ratio value and the abnormal reading ratio value are identified to obtain specific label abnormality items, and corresponding label optimization instructions are obtained according to the specific label abnormality items. The label optimization instructions include but are not limited to identifying files through image recognition when the label is abnormal, generating label maintenance instructions, and controlling the angle and focal length of label reading.

[0036] The execution control module is used to receive control instructions from each module and execute corresponding instructions, which is specifically: receiving signal transmission optimization information and label optimization instructions, and performing corresponding signal transmission self-inspection and repair and transmission enhancement according to the signal transmission optimization information; and executing corresponding label reading optimization instructions according to the label optimization instructions.

[0037] The archive management monitoring module is used to monitor and analyze the archive information data of the archive warehouse to obtain supervision information, and send the supervision information to the management end for display. Specifically, the archive environment data, equipment operation status and user access data are obtained by identifying the archive information data, and the archive supervision analysis is performed based on the archive environment data, equipment operation status and user access data to obtain the archive warehouse status and archive status, and the archive warehouse status and archive status are sent to the management end for display, and early warning reminders are issued according to abnormal archive warehouse status and archive status.

[0038] The data processing library is used to store environmental detection data, signal transmission data and archival information data, and is also used to store signal transmission optimization information and label optimization instructions, and is also used to store regulatory information.

[0039] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0040] 1. The present invention obtains signal impact information by analyzing environmental detection data, acquires signal transmission data and analyzes the signal transmission data to obtain signal transmission status, comprehensively analyzes the signal impact information and the signal transmission status to obtain signal transmission optimization information, and obtains transmission optimization information based on the analysis of the data transmission process and the interference environment, thereby ensuring the real-time performance of data transmission and improving the timeliness of monitoring.

[0041] 2. The present invention obtains label information data by identifying archive information, obtains label status information by analyzing the label information data, obtains label optimization instructions by analyzing the label status information, and optimizes and adjusts the reading of archive labels to improve reading accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0043] Figure 1 It is a principle block diagram of the present invention;

[0044] Figure 2 It is a schematic diagram of the signal distortion curve of the present invention. DETAILED DESCRIPTION

[0045] 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.

[0046] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1-2 In an embodiment of the present invention, an embodiment of an intelligent archive management system based on remote monitoring includes: a perception layer module, a wireless signal optimization module, a label optimization module, an execution control module, an archive management monitoring module and a data processing library.

[0047] The perception layer module collects environmental detection data, signal transmission data and archive information data through detection sensors, and sends the environmental detection data, signal transmission data and archive information data to the data processing library;

[0048] Environmental detection instruments and signal detection instruments are installed at multiple locations in the archive management room. The environmental detection instruments are used to collect data on the indoor signal environment of the archive management room, and signal detection is used to collect various data on signal transmission. Based on the storage location of the archives, all-round sensor arrangements are carried out to sense the archive labels, archive environment and operating data of the master control equipment. Environmental detection data are collected by environmental detection instruments, and the environmental monitoring data include signal coverage data, obstacle data and signal quality data. Signal transmission data are collected by signal detection instruments, and the signal transmission data include signal transmission rate, signal power data and signal characteristics. Archive information data are collected by sensors, and the archive information data include label information data, archive environment data, equipment operating status and user access data.

[0049] The wireless signal optimization module obtains environmental detection data and analyzes the environmental detection data to obtain signal impact information, obtains signal transmission data and analyzes the signal transmission data to obtain signal transmission status, comprehensively analyzes the signal impact information and the signal transmission status to obtain signal transmission optimization information, and sends the signal transmission optimization information to the execution control module.

[0050] The environmental testing data is analyzed in the following specific ways:

[0051] A1: Obtain signal coverage data, obstacle data and signal quality data through environmental monitoring data;

[0052] A2: A signal strength value is obtained according to the signal quality data, and a plurality of pre-set signal quality intervals are obtained. Each signal quality interval corresponds to a maximum signal value and a minimum signal value. The maximum signal value and the minimum signal value are marked as iXm and iXn, respectively, that is, each signal quality interval corresponds to [iXn, iXm], where i represents the number of the signal quality interval and is a positive integer. The average value is calculated according to the maximum signal value and the minimum signal value of each signal quality interval to obtain the mean signal strength of each signal quality interval.

[0053] A3: Divide the archive management area into multiple signal optimization blocks according to the signal coverage data, obtain the signal strength value of each signal optimization block, match the signal strength value of the signal optimization block with multiple signal quality intervals to obtain the signal quality interval corresponding to each signal optimization block, and obtain the mean signal strength corresponding to the signal quality interval.

[0054] A4: Obstacle data of the archive management area is identified to obtain obstacles of each signal optimization block, signal interference values ​​corresponding to the obstacles are obtained, and a preset signal interference threshold is obtained, obstacles with signal interference values ​​greater than the signal interference threshold are marked as interference obstacles, the number of interference obstacles is counted and recorded as the interference obstacle value, and the interference density is calculated by ratio of the interference obstacle value to the area of ​​each optimization block; interference obstacles include but are not limited to metal products, electrical equipment, walls, glass products and water bodies.

[0055] A5: Normalize the mean signal strength and interference density of each signal optimization block and take their values, using the formula The signal state value XH of each signal optimization block is calculated; where JQ and GR represent the mean signal strength and interference density, respectively. It is expressed as the mean signal reference intensity; f1 and f2 are both preset weight factors, with values ​​of 12.245 and 11.241 respectively.

[0056] A6: Obtain a preset signal state threshold, compare the signal state value of each signal optimization block with the signal state threshold, and when the signal state value is less than the signal state threshold, generate corresponding signal impact information that the block interference intensity is high.

[0057] The signal transmission data is analyzed in the following specific ways:

[0058] Obtaining a preset transmission segment distance, dividing the archive management area into a plurality of transmission segments based on the transmission segment distance, obtaining signal transmission data of each transmission segment, and obtaining a signal transmission rate, signal power data and signal characteristics according to the signal transmission data;

[0059] The transmission rate of each transmission segment is compared with the preset rate standard value. When the transmission rate is lower than the rate standard value, the transmission rate of each transmission segment is calculated by difference with the rate standard value to obtain the rate quality fluctuation value, and the preset quality fluctuation threshold is obtained. The part of the rate quality fluctuation value greater than the quality fluctuation threshold is marked as the rate impact value.

[0060] The signal power and noise power are obtained according to the signal power data of each transmission segment, the signal power and the noise power are ratio-calculated to obtain the signal-to-noise ratio, the difference between the signal-to-noise ratios corresponding to two adjacent transmission segments is calculated to obtain the signal attenuation value, the signal attenuation value is divided into multiple attenuation value intervals, each attenuation value interval corresponds to an attenuation impact value, and the signal attenuation values ​​corresponding to the current two adjacent transmission segments are matched with the multiple attenuation value intervals to obtain the corresponding attenuation impact values.

[0061] The starting transmission point and the transmission end point of each transmission segment are obtained, and the original signal characteristics corresponding to the starting transmission point and the final signal characteristics corresponding to the transmission end point are obtained according to the signal characteristics. The signal distortion degree is obtained by comparing the original signal characteristics corresponding to the transmission segment with the final signal characteristics. The signal distortion degree of each transmission segment is constructed into a signal distortion degree curve according to the distance order of the transmission segments, and a preset upper limit value of the distortion degree is obtained, and the signal distortion degree exceeding the upper limit value of the distortion degree is marked as a distortion impact value.

[0062] Two squares are constructed with the values ​​of the rate influence value and the attenuation influence value as the sides of the squares. A straight line perpendicular to the two squares is drawn with the centroids of the two squares as the starting point and the end point. The length of the straight line is equal to the value of the distortion influence value. The four vertices of the two squares are matched and connected to obtain a tetrahedron. The volume of the tetrahedron is calculated and the value of the volume is marked as the signal transmission state value. When the signal transmission state is greater than the preset transmission state threshold, the corresponding signal transmission state is generated as a transmission segment state abnormality.

[0063] The signal impact information and signal transmission status are comprehensively analyzed. The specific analysis method is as follows:

[0064] The signal impact information corresponding to each signal optimization block is identified. When the signal impact information indicates that the block interference intensity is high, the corresponding signal optimization block is marked as an interference block, the signal status value of the interference block is obtained, and the pre-set signal status upper limit value is obtained. When the signal status value is greater than the signal status upper limit value, transmission congestion information is generated. Conversely, when the signal status value is less than the signal status upper limit value, signal optimization information is generated.

[0065] Based on the transmission congestion information, the corresponding signal transmission optimization information is generated as a transmission switching instruction; based on the signal optimizability information, the signal transmission status of the transmission segment corresponding to the signal optimization block is obtained. When the signal transmission status corresponds to an abnormal transmission segment status, the corresponding signal transmission optimization information is generated as a transmission self-inspection and maintenance; conversely, when the signal transmission status corresponds to normal, the corresponding signal transmission optimization information is generated as a signal enhancement start instruction.

[0066] The label optimization module acquires the archive information data and identifies the archive information to obtain the label information data, analyzes the label information data to obtain the label status information, analyzes the label status information to obtain the label optimization instruction, and sends the label optimization instruction to the execution control module.

[0067] The tag information data is analyzed in the following specific way:

[0068] The label reading data and the file image data of each file are obtained according to the label information data; multiple recognition data of each file are obtained according to the label reading data, the recognition time corresponding to each recognition data is obtained, and the pre-set recognition upper limit time is obtained, and the recognition time corresponding to each recognition data is compared with the recognition upper limit time. When the recognition time exceeds the recognition upper limit time, the corresponding recognition data is marked as recognition abnormal data, the number of recognition abnormal data is counted and recorded as the recognition abnormal number, and the recognition abnormality ratio is calculated by calculating the ratio of the recognition abnormal number to the total number of recognition data.

[0069] Obtain reading results corresponding to multiple label reading data, obtain pre-stored archive images and actual archive images corresponding to the reading results according to the archive image data, overlap and compare the pre-stored archive images corresponding to each monthly result with the actual archive images, and when the pre-stored archive images are different from the actual archive images, mark the corresponding reading results as abnormal reading results, count the number of abnormal reading results to obtain the abnormal reading number, and calculate the ratio of the abnormal reading number to the total number of reading results to obtain the abnormal reading ratio.

[0070] A triangle is constructed with the value of the recognition abnormality ratio as the side length of the equilateral triangle, a circle is constructed with the midpoint of one side of the equilateral triangle as the center and the value of the abnormal reading ratio as the radius, and then a closed figure is constructed with the equilateral triangle and the circle. The area of ​​the closed figure is calculated and the value of the area is marked as the label status value, and the label status value is used as the corresponding label status information.

[0071] The tag status information is analyzed in the following specific ways:

[0072] The label status information is identified to obtain the label status value, and a preset label status threshold is obtained. When the label status value is greater than the label status threshold, the corresponding label status is marked as a label status abnormality. According to the label status abnormality information, the label status abnormality includes but is not limited to label detachment, label obstruction, and label damage. The recognition abnormality ratio value and the abnormal reading ratio value are identified to obtain specific label abnormality items, and corresponding label optimization instructions are obtained according to the specific label abnormality items. The label optimization instructions include but are not limited to identifying files through image recognition when the label is abnormal, generating label maintenance instructions, and controlling the angle and focal length of label reading.

[0073] The execution control module receives the signal transmission optimization information and the label optimization instruction, and performs corresponding signal transmission self-check repair and transmission enhancement according to the signal transmission optimization information; and executes corresponding label reading optimization instructions according to the label optimization instruction.

[0074] The archive management monitoring module obtains archive environment data, equipment operation status and user access data by identifying archive information data, and performs archive supervision and analysis based on the archive environment data, equipment operation status and user access data to obtain the archive warehouse status and archive status, and sends the archive warehouse status and archive status to the management end for display, and issues early warning reminders based on abnormal archive warehouse status and archive status.

[0075] The data processing library stores environmental detection data, signal transmission data and archival information data, and is used to store signal transmission optimization information and label optimization instructions, and is also used to store regulatory information.

[0076] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent archive management system based on remote monitoring, including a perception layer module and a data processing library, characterized in that: Also includes: A wireless signal optimization module, used to obtain environmental detection data and analyze the environmental detection data to obtain signal impact information, obtain signal transmission data and analyze the signal transmission data to obtain signal transmission status, comprehensively analyze the signal impact information and the signal transmission status to obtain signal transmission optimization information, and send the signal transmission optimization information to the execution control module; The label optimization module is used to obtain the archive information data and identify the archive information to obtain the label information data, analyze the label information data to obtain the label status information, analyze the label status information to obtain the label optimization instruction, and send the label optimization instruction to the execution control module; An execution control module is used to receive control instructions from each module and execute corresponding instructions; The archive management monitoring module is used to monitor and analyze the archive information data in the archive warehouse to obtain supervision information, and send the supervision information to the management end for display.

2. According to claim 1, the intelligent archive management system based on remote monitoring is characterized in that: The perception layer module is used to collect environmental detection data, signal transmission data and archive information data through detection sensors, and send the environmental detection data, signal transmission data and archive information data to the data processing library; Environmental detection data is collected through environmental detection instruments, and the environmental monitoring data includes signal coverage data, obstacle data and signal quality data; signal transmission data is collected through signal detection instruments, and the signal transmission data includes signal transmission rate, signal power data and signal characteristics; archival information data is collected through sensors, and the archival information data includes label information data, archival environment data, equipment operation status and user access data.

3. The intelligent archive management system based on remote monitoring according to claim 1 is characterized in that: The environmental detection data is analyzed in the following specific manner: A1: Obtain signal coverage data, obstacle data and signal quality data through environmental monitoring data; A2: A signal strength value is obtained according to the signal quality data, and a plurality of pre-set signal quality intervals are obtained, each of which corresponds to a maximum signal value and a minimum signal value, and the maximum signal value and the minimum signal value are marked as iXm and iXn, respectively, that is, each signal quality interval corresponds to [iXn, iXm], where i represents the number of the signal quality interval, and its value is a positive integer; the average value is calculated according to the maximum signal value and the minimum signal value of each signal quality interval to obtain the mean signal strength of each signal quality interval; A3: Divide the archive management area into multiple signal optimization blocks according to the signal coverage data, obtain the signal strength value of each signal optimization block, match the signal strength value of the signal optimization block with multiple signal quality intervals to obtain the signal quality interval corresponding to each signal optimization block, and obtain the mean signal strength corresponding to the signal quality interval; A4: Obstacle data of the archive management area is identified to obtain obstacles of each signal optimization block, and the signal interference value corresponding to the obstacle is obtained, and the preset signal interference threshold is obtained, and obstacles with signal interference values ​​greater than the signal interference threshold are marked as interference obstacles, and the number of interference obstacles is counted and recorded as the interference obstacle value, and the interference density is calculated by ratio of the interference obstacle value to the area of ​​each optimization block; A5: The mean signal strength and interference density of each signal optimization block are comprehensively calculated to obtain the signal state value of each signal optimization block; A6: Obtain a preset signal state threshold, compare the signal state value of each signal optimization block with the signal state threshold, and when the signal state value is less than the signal state threshold, generate corresponding signal impact information that the block interference intensity is high.

4. The intelligent archive management system based on remote monitoring according to claim 3 is characterized in that: The mean signal strength and interference density of each signal optimization block are comprehensively calculated, and the specific calculation method is as follows: The mean signal strength and interference density of each signal optimization block are normalized and their values ​​are taken. The formula is used The signal state value XH of each signal optimization block is calculated; where JQ and GR represent the mean signal strength and interference density, respectively. It is expressed as the mean signal reference intensity; f1 and f2 are both preset weight factors.

5. The intelligent archive management system based on remote monitoring according to claim 3 is characterized in that: The signal transmission data is analyzed, and the specific analysis method is as follows: Obtaining a preset transmission segment distance, dividing the archive management area into a plurality of transmission segments based on the transmission segment distance, obtaining signal transmission data of each transmission segment, and obtaining a signal transmission rate, signal power data and signal characteristics according to the signal transmission data; The transmission rate of each transmission segment is compared with a preset rate standard value. When the transmission rate is less than the rate standard value, the transmission rate of each transmission segment and the rate standard value are calculated to obtain a rate quality fluctuation value, a preset quality fluctuation threshold is obtained, and the portion of the rate quality fluctuation value greater than the quality fluctuation threshold is marked as a rate impact value; The signal power and the noise power are obtained according to the signal power data of each transmission segment, the signal power and the noise power are calculated as a ratio to obtain the signal-to-noise ratio, the difference between the signal-to-noise ratios corresponding to two adjacent transmission segments is calculated as a difference to obtain the signal attenuation value, the signal attenuation value is divided into a plurality of attenuation value intervals, each attenuation value interval corresponds to an attenuation impact value, and the signal attenuation values ​​corresponding to the current two adjacent transmission segments are matched with the plurality of attenuation value intervals to obtain the corresponding attenuation impact value; Obtaining the starting transmission point and the transmission end point of each transmission segment, obtaining the original signal feature corresponding to the starting transmission point and the final signal feature corresponding to the transmission end point according to the signal feature, obtaining the signal distortion by comparing the original signal feature corresponding to the transmission segment with the final signal feature, constructing a signal distortion curve based on the signal distortion of each transmission segment in the order of the distance of the transmission segments, obtaining a preset upper limit value of the distortion, and marking the signal distortion exceeding the upper limit value of the distortion as a distortion impact value; Two squares are constructed with the values ​​of the rate influence value and the attenuation influence value as the sides of the squares. A straight line perpendicular to the two squares is drawn with the centroids of the two squares as the starting point and the end point. The length of the straight line is equal to the value of the distortion influence value. The four vertices of the two squares are matched and connected to obtain a tetrahedron. The volume of the tetrahedron is calculated and the value of the volume is marked as the signal transmission state value. When the signal transmission state is greater than the preset transmission state threshold, the corresponding signal transmission state is generated as a transmission segment state abnormality.

6. The intelligent archive management system based on remote monitoring according to claim 5 is characterized in that: The signal impact information and signal transmission status are comprehensively analyzed, and the specific analysis method is as follows: Identify the signal impact information corresponding to each signal optimization block. When the signal impact information indicates that the block interference intensity is high, mark the corresponding signal optimization block as an interference block, obtain the signal state value of the interference block, and obtain a preset signal state upper limit value. When the signal state value is greater than the signal state upper limit value, generate transmission congestion information. On the contrary, when the signal state value is less than the signal state upper limit value, generate signal optimization information. Generate corresponding signal transmission optimization information as a transmission switching instruction based on the transmission congestion information; Based on the signal optimizability information, the signal transmission status of the transmission segment corresponding to the signal optimization block is obtained. When the signal transmission status corresponds to an abnormal transmission segment status, the corresponding signal transmission optimization information is generated as a transmission self-inspection and maintenance; conversely, when the signal transmission status corresponds to normal, the corresponding signal transmission optimization information is generated as a signal enhancement start instruction.

7. The intelligent archive management system based on remote monitoring according to claim 1 is characterized in that: The specific analysis method of the tag information data is as follows: Obtain label reading data and file image data of each file according to the label information data; obtain multiple recognition data of each file according to the label reading data, obtain the recognition time corresponding to each recognition data, and obtain the pre-set recognition upper limit time, compare the recognition time corresponding to each recognition data with the recognition upper limit time, when the recognition time exceeds the recognition upper limit time, mark the corresponding recognition data as recognition abnormal data, count the number of recognition abnormal data and record it as the recognition abnormal number, and calculate the ratio of the recognition abnormal number to the total number of recognition data to obtain the recognition abnormality ratio value; Obtain reading results corresponding to multiple tag reading data, obtain pre-stored archive images and actual archive images corresponding to the reading results according to the archive image data, overlap and compare the pre-stored archive images corresponding to each monthly result with the actual archive images, and when the pre-stored archive images are different from the actual archive images, mark the corresponding reading results as abnormal reading results, count the number of abnormal reading results to obtain the abnormal reading number, and calculate the ratio of the abnormal reading number to the total number of reading results to obtain the abnormal reading ratio; A triangle is constructed with the value of the recognition abnormality ratio as the side length of the equilateral triangle, a circle is constructed with the midpoint of one side of the equilateral triangle as the center and the value of the abnormal reading ratio as the radius, and then a closed figure is constructed with the equilateral triangle and the circle. The area of ​​the closed figure is calculated and the value of the area is marked as the label status value, and the label status value is used as the corresponding label status information.

8. The intelligent archive management system based on remote monitoring according to claim 1 is characterized in that: The tag status information is analyzed in the following specific manner: The tag status information is identified to obtain the tag status value, and a preset tag status threshold is obtained. When the tag status value is greater than the tag status threshold, the corresponding tag status is marked as a tag status abnormality. According to the tag status abnormality information, the recognition abnormality ratio and the abnormal reading ratio are identified to obtain the specific tag abnormality items, and the corresponding tag optimization instructions are obtained according to the specific tag abnormality items.

9. The intelligent archive management system based on remote monitoring according to claim 1 is characterized in that: The method for receiving control instructions of each module and executing corresponding instructions is specifically: receiving signal transmission optimization information and label optimization instructions, and performing corresponding signal transmission self-check repair and transmission enhancement according to the signal transmission optimization information; and executing corresponding label reading optimization instructions according to the label optimization instructions.

10. The intelligent archive management system based on remote monitoring according to claim 1, characterized in that: The archive management monitoring module specifically analyzes in the following manner: by identifying the archive information data, the archive environment data, the equipment operation status and the user access data are obtained; based on the archive environment data, the equipment operation status and the user access data, the archive supervision analysis is performed to obtain the archive warehouse status and the archive status; the archive warehouse status and the archive status are sent to the management end for display; and early warning reminders are issued according to abnormal archive warehouse status and archive status.

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