An intelligent archive management system based on remote monitoring

Abstract

The present invention relates to the field of archive management technology, specifically to an intelligent archive management system based on remote monitoring, comprising 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. 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, obtains transmission optimization information based on an analysis of the data transmission process and the interference environment, ensures the real-time nature of data transmission, and improves the timeliness of monitoring; the present invention obtains label status information by analyzing label information data, and obtains label optimization instructions by analyzing the label status information, performs reading optimization adjustment on the archive label, and facilitates improving the accuracy of reading.

Description

Technical Field

[0001] The present invention relates to the technical field of file management, and in particular to an intelligent file 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 archive management system is a digital tool for archive management. It streamlines and standardizes the archive management process. 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 archive management, quickly complete the classification, retrieval and call of archives, and greatly reduce the time and energy spent on manual archive search.

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

[0005] The present invention provides an intelligent file 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, comprising 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 archival information data through detection sensors, and send the environmental detection data, signal transmission data and archival information data to the data processing library;

[0008] Environmental detection instruments and signal detection instruments are installed at multiple locations within the archive management room. The environmental detection instruments are used to collect data on the indoor signal environment within the archive management room, and signal detection is used to collect various data on signal transmission. Based on the storage location of the archives, a full range of sensors are deployed to sense 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] Signal transmission data is collected by a signal detection instrument, and the signal transmission data includes signal transmission rate, signal power data and signal characteristics;

[0011] The archive information data is collected through sensors, 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 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: Obtain signal strength values based on the signal quality data and obtain multiple pre-set signal quality intervals. 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 signal quality interval number and is a positive integer. Calculate the average value of the maximum signal value and the minimum signal value in 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 based on 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 in the archive management area is identified to obtain obstacles in each signal optimization block. The signal interference value corresponding to the obstacle is obtained, and a pre-set 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. The interference density is calculated by comparing the interference obstacle value with 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 status threshold, compare the signal status value of each signal optimization block with the signal status threshold, and generate corresponding signal impact information that the block interference intensity is high when the signal status value is less than the signal status threshold.

[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 multiple transmission segments based on the transmission segment distance, obtaining signal transmission data of each transmission segment, and obtaining signal transmission rate, signal power data and signal characteristics based on the signal transmission data;

[0022] The transmission rate of each transmission segment is compared with the pre-set rate standard value. When the transmission rate is less than the rate standard value, the difference between the transmission rate of each transmission segment and the rate standard value is calculated to obtain the rate quality fluctuation value, and the pre-set quality fluctuation threshold is obtained. The part of the rate quality fluctuation value that is 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 transmission end point of each transmission segment are obtained. The original signal characteristics corresponding to the starting transmission point and the final signal characteristics corresponding to the transmission end point are obtained based on the signal characteristics. The signal distortion is obtained by comparing the original signal characteristics corresponding to the transmission segment with the final signal characteristics. A signal distortion curve is constructed by combining the signal distortion of each transmission segment in order of distance between the transmission segments. A pre-set upper limit value for the distortion is obtained, and the signal distortion exceeding the upper limit value is marked as a distortion impact value.

[0025] Two squares are constructed with the values of the rate impact value and the attenuation impact value as the sides of the squares. A straight line perpendicular to the two squares is drawn with the center of gravity 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 impact 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 volume value is marked as the signal transmission status value. When the signal transmission status value is greater than the preset transmission status threshold, the corresponding signal transmission status is generated as a transmission segmentation status 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 to be optimized 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 file information data and identify the file information to obtain label information data, analyze the label information data to obtain label status information, analyze the label status information to obtain label optimization instructions, and send the label optimization instructions 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] According to the label information data, the label reading data and the file image data of each file are obtained; according to the label reading data, multiple recognition data of each file are obtained, 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 abnormality number, and the ratio of the recognition abnormality number to the total number of recognition data is calculated to obtain the recognition abnormality ratio value.

[0032] Obtain reading results corresponding to multiple tag reading data, obtain pre-stored archival images and actual archival images corresponding to the reading results based on the archival image data, overlap and compare the pre-stored archival images corresponding to each monthly result with the actual archival images, and when the pre-stored archival images are different from the actual archival 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. A closed figure is then constructed using the equilateral triangle and the circle. The area of the closed figure is calculated and the area value is marked as the label status value. 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 pre-set 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 shedding, 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 the 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 specifically includes: 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, it is used to obtain archive environment data, equipment operation status and user access data by identifying the archive information data, and to perform archive supervision analysis based on the archive environment data, equipment operation status and user access data to obtain the archive warehouse status and archive status, and send the archive warehouse status and archive status to the management end for display, and issue early warning reminders based on 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 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 file information, analyzes the label information data to obtain label status information, and analyzes the label status information to obtain label optimization instructions, and performs reading optimization and adjustment on the file label 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 is a brief introduction to the drawings required for 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 Schematic diagram of the signal distortion curve of the present invention. DETAILED DESCRIPTION

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall 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 archival information data through detection sensors, and sends the environmental detection data, signal transmission data and archival 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 in 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 is collected by environmental detection instruments, and the environmental monitoring data includes signal coverage data, obstacle data and signal quality data. Signal transmission data is collected by signal detection instruments, and the signal transmission data includes signal transmission rate, signal power data and signal characteristics. Archive information data is collected by sensors, and the archive information data includes 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: Obtain signal strength values based on the signal quality data and obtain multiple pre-set signal quality intervals. 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 signal quality interval number and is a positive integer. Calculate the average value of the maximum signal value and the minimum signal value in 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 based on 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 in the archive management area is identified to obtain obstacles in each signal optimization block. The signal interference value corresponding to the obstacle is obtained, and a pre-set 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. The interference density is calculated by comparing the interference obstacle value with 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 status threshold, compare the signal status value of each signal optimization block with the signal status threshold, and generate corresponding signal impact information that the block interference intensity is high when the signal status value is less than the signal status threshold.

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

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

[0059] The transmission rate of each transmission segment is compared with the pre-set rate standard value. When the transmission rate is less than the rate standard value, the difference between the transmission rate of each transmission segment and the rate standard value is calculated to obtain the rate quality fluctuation value, and the pre-set quality fluctuation threshold is obtained. The part of the rate quality fluctuation value that is 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 transmission end point of each transmission segment are obtained. The original signal characteristics corresponding to the starting transmission point and the final signal characteristics corresponding to the transmission end point are obtained based on the signal characteristics. The signal distortion is obtained by comparing the original signal characteristics corresponding to the transmission segment with the final signal characteristics. A signal distortion curve is constructed by combining the signal distortion of each transmission segment in order of distance between the transmission segments. A pre-set upper limit value for the distortion is obtained, and the signal distortion exceeding the upper limit value is marked as a distortion impact value.

[0062] Two squares are constructed with the values of the rate impact value and the attenuation impact value as the sides of the squares. A straight line perpendicular to the two squares is drawn with the center of gravity 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 impact 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 volume value is marked as the signal transmission status value. When the signal transmission status value is greater than the preset transmission status threshold, the corresponding signal transmission status is generated as a transmission segmentation status 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 to be optimized 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 obtains 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 ways:

[0068] According to the label information data, the label reading data and the file image data of each file are obtained; according to the label reading data, multiple recognition data of each file are obtained, 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 abnormality number, and the ratio of the recognition abnormality number to the total number of recognition data is calculated to obtain the recognition abnormality ratio value.

[0069] Obtain reading results corresponding to multiple tag reading data, obtain pre-stored archival images and actual archival images corresponding to the reading results based on the archival image data, overlap and compare the pre-stored archival images corresponding to each monthly result with the actual archival images, and when the pre-stored archival images are different from the actual archival 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. A closed figure is then constructed using the equilateral triangle and the circle. The area of the closed figure is calculated and the area value is marked as the label status value. The label status value is used as the corresponding label status information.

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

[0072] The label status information is identified to obtain the label status value, and a pre-set 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 shedding, 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 the 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 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 above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can 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, configured 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 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 status value of the interference block and the preset signal status upper limit. When the signal status value is greater than the signal status upper limit, generate transmission congestion information. Conversely, when the signal status value is less than the signal status upper limit, 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 to be optimized 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; a label optimization module, configured to obtain archive information data and identify the archive information to obtain label information data, analyze the label information data to obtain label status information, analyze the label status information to obtain label optimization instructions, and send the label optimization instructions to the execution control module; Execution control module, 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; The perception layer module is used to collect environmental detection data, signal transmission data and archival information data through detection sensors, and send the environmental detection data, signal transmission data and archival information data to the data processing library; collect environmental detection data through environmental detection instruments, and the environmental monitoring data includes signal coverage data, obstacle data and signal quality data; collect signal transmission data through signal detection instruments, and the signal transmission data includes signal transmission rate, signal power data and signal characteristics; collect archival information data through sensors, and the archival information data includes label information data, archival environment data, equipment operation status and user access data.

2. The intelligent file 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: Obtain signal strength values based on the signal quality data and obtain multiple pre-set signal quality intervals. 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. Calculate the average value of the maximum signal value and the minimum signal value in 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 based on 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 average signal strength corresponding to the signal quality interval; A4: Obstacle data in the archive management area is identified to obtain obstacles in each signal optimization block. The signal interference value corresponding to the obstacle is obtained, and a pre-set 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. The interference density is calculated by comparing the interference obstacle value with the area of each optimization block. A5: The average signal strength and interference density of each signal optimization block are comprehensively calculated to obtain the signal status value of each signal optimization block; A6: Obtain a preset signal status threshold, compare the signal status value of each signal optimization block with the signal status threshold, and generate corresponding signal impact information that the block interference intensity is high when the signal status value is less than the signal status threshold.

3. The intelligent file management system based on remote monitoring according to claim 2 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: Normalize the mean signal strength and interference density of each signal optimization block and take its value, and use 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.

4. The intelligent file management system based on remote monitoring according to claim 2 is characterized in that: The signal transmission data is analyzed in the following manner: Obtaining a preset transmission segment distance, dividing the archive management area into multiple transmission segments based on the transmission segment distance, obtaining signal transmission data of each transmission segment, and obtaining signal transmission rate, signal power data and signal characteristics based on the signal transmission data; Compare the transmission rate of each transmission segment with a preset rate standard value. When the transmission rate is lower than the rate standard value, calculate the difference between the transmission rate of each transmission segment and the rate standard value to obtain a rate quality fluctuation value, obtain a preset quality fluctuation threshold, and mark the portion of the rate quality fluctuation value that is higher than the quality fluctuation threshold as a rate impact value. The signal power and noise power are obtained based on the signal power data of each transmission segment, and the signal power and noise power are calculated as a ratio to obtain a signal-to-noise ratio. The signal-to-noise ratios corresponding to two adjacent transmission segments are calculated as a difference to obtain a 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. Obtaining the starting transmission point and transmission end point of each transmission segment, obtaining the original signal characteristics corresponding to the starting transmission point and the final signal characteristics corresponding to the transmission end point based on the signal characteristics, obtaining the signal distortion by comparing the original signal characteristics corresponding to the transmission segment with the final signal characteristics, constructing a signal distortion curve based on the signal distortion of each transmission segment in order of distance between the transmission segments, obtaining a pre-set distortion upper limit value, and marking the signal distortion that exceeds the distortion upper limit value as a distortion impact value; Two squares are constructed with the values of the rate impact value and the attenuation impact value as the sides of the squares. A straight line perpendicular to the two squares is drawn with the center of gravity 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 impact 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 volume value is marked as the signal transmission status value. When the signal transmission status value is greater than the preset transmission status threshold, the corresponding signal transmission status is generated as a transmission segmentation status abnormality.

5. The intelligent file management system based on remote monitoring according to claim 1 is characterized in that: The tag information data is analyzed in the following specific manner: Obtain label reading data and file image data of each file based on the label information data; obtain multiple recognition data of each file based on the label reading data, obtain the recognition time corresponding to each recognition data, and obtain a 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 abnormality number, and calculate the ratio of the recognition abnormality 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 archival images and actual archival images corresponding to the reading results based on the archival image data, overlap and compare the pre-stored archival images corresponding to each monthly result with the actual archival images, and when the pre-stored archival images are different from the actual archival images, mark the corresponding reading results as abnormal reading results, count the number of abnormal reading results to obtain the abnormal reading count, and calculate the ratio of the abnormal reading count 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. A closed figure is then constructed using the equilateral triangle and the circle. The area of the closed figure is calculated and the area value is marked as the label status value. The label status value is used as the corresponding label status information.

6. The intelligent file management system based on remote monitoring according to claim 1 is characterized in that: The tag status information is analyzed in the following manner: Identify the tag status information to obtain the tag status value, obtain the pre-set tag status threshold, and when the tag status value is greater than the tag status threshold, mark the corresponding tag status as a tag status abnormality. According to the tag status abnormality information, identify the recognition abnormality ratio and the abnormal reading ratio to obtain the specific tag abnormality item, and obtain the corresponding tag optimization instruction according to the specific tag abnormality item.

7. The intelligent file 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-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.

8. The intelligent file management system based on remote monitoring according to claim 1 is 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; and the archive warehouse status and the archive status are sent to the management end for display, and an early warning reminder is issued based on the abnormal archive warehouse status and the archive status.

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