Data analysis method based on real-time intelligent monitoring of urban and rural building complexes

Abstract

The present invention discloses a data analysis method based on real-time intelligent monitoring of urban and rural building complexes, and relates to the technical field of digital data processing. The Internet of Things cloud platform obtains the additional layout parameters of the monitoring points of the urban and rural building complexes by analyzing the status data of the urban and rural building complexes, monitors the structural status monitoring data and communication data of the urban and rural building complexes, and the edge computing node pre-processes the monitoring data in real time, selects the communication method to upload to the cloud platform for in-depth analysis, realizes the real-time intelligent monitoring and maintenance early warning of the urban and rural building complexes, and improves the monitoring efficiency by optimizing the layout of the monitoring points; the data communication method selection of the edge computing node accelerates the response speed, ensures the stability and efficiency of data transmission, realizes the intelligent monitoring and analysis of the urban and rural building complexes, and effectively prevents safety hazards.

Description

Technical Field

[0001] The present invention relates to the technical field of digital data processing, and in particular to a data analysis method based on real-time intelligent monitoring of urban and rural building complexes. Background Art

[0002] Data analysis for real-time intelligent monitoring of urban and rural building complexes is crucial. It uses sensor technology for data collection, timely detects potential safety hazards and operational anomalies, determines whether the building needs maintenance, and provides targeted maintenance plans. The advantage of this process is that it can detect structural problems or equipment failures in a timely manner through real-time data, thereby avoiding potential safety risks and sudden failures, reducing unnecessary maintenance expenses, and improving maintenance efficiency, thereby extending the service life of the building and improving the overall operational effect.

[0003] For example, the invention patent with announcement number CN118133411B announces a method for monitoring the displacement of urban buildings, which belongs to the technical field of building displacement monitoring. It includes: S1. Obtaining building terrain data and building structure data, and obtaining a building information model with control point latitude, longitude and height information based on terrain data and building structure data; S2. Performing drone route modeling to update the real-time spatial position data of points of interest in the building; S3. Monitoring the vertical section offset and horizontal section offset of the building. The vertical section offset of the building includes the monitoring of the absolute value of settlement and the measurement of uneven settlement; the monitoring of the absolute value of settlement includes the settlement value of the building itself LSP I and the settlement value of the ground itself LSP II; the measurement of uneven settlement of the vertical section of the building includes uneven force on the horizontal section and uneven ground settlement. To solve the problem of being unable to effectively monitor building deformation, the building is analyzed from two aspects: horizontal deformation and vertical settlement. The analysis is more complete and close to the actual needs of building monitoring.

[0004] For example, the invention patent with announcement number CN114840390B announces a BIM-based building data monitoring system, including a building data acquisition terminal, a data preprocessing terminal, a central processing terminal, a display terminal, an alarm terminal, and a database. The building data acquisition terminal obtains the internal data of the building in real time through various sensors installed in the building, including smoke alarm data, water pipe and water pump data, wind pressure data, circuit data, temperature data, and humidity data; the main body of the data preprocessing terminal is a PCB board equipped with a computer chip, with a built-in wireless transceiver. The overall architecture is reasonable, the functional module design, connection method and working principle are in line with reality, the building data is monitored in real time, the BIM model status is continuously updated so that the staff in the building can understand the changing status of the building, and the alarm function is set to facilitate the evacuation of the crowd in abnormal situations, with good adaptability and easy promotion.

[0005] Based on the above findings, the existing technical solutions for monitoring buildings have the problems of single parameters, high cost, and difficult installation. It is difficult to obtain high-precision monitoring data and capture the comprehensive changes in the state of the building. As a result, the deformation of the building is difficult to predict, and key problems are not discovered in time, thereby increasing safety risks. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a data analysis method based on real-time intelligent monitoring of urban and rural building complexes, which solves the problems designed in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: based on a data analysis method for real-time intelligent monitoring of urban and rural building complexes, the Internet of Things cloud platform obtains and analyzes the status data of urban and rural building complexes to obtain the layout parameters of additional monitoring points of urban and rural building complexes.

[0008] The intelligent monitoring cloud platform arranges monitoring points for urban and rural building complexes according to the additional layout parameters of the monitoring points in the urban and rural building complexes, thereby monitoring the structural status of each building in the urban and rural building complexes, obtaining the structural status monitoring data of the urban and rural building complexes, and inputting it into the edge computing node.

[0009] The edge computing nodes receive the structural status monitoring data of urban and rural building complexes in real time for preprocessing, and analyze and obtain the maintenance demand representation value of urban and rural building complexes.

[0010] Based on the maintenance demand characterization value of urban and rural building complexes, the data communication transmission mode of the edge computing node is determined, the structural status monitoring data of urban and rural building complexes are counted and transmitted to the intelligent monitoring cloud platform for reprocessing, and maintenance warnings are issued for urban and rural building complexes based on the reprocessing.

[0011] Furthermore, the status data of urban and rural building complexes are extracted, and the status data of urban and rural building complexes include the historical monthly average inclination angle of the building complex, the historical monthly average settlement depth and the historical monthly cumulative number of cracks of the building complex. After processing, the monitoring demand characterization value of the urban and rural building complex in each month is obtained.

[0012] Furthermore, based on the monitoring demand characterization values ​​of urban and rural building complexes in each month, the monitoring point additional layout parameters corresponding to each interval of the monitoring demand characterization values ​​of urban and rural building complexes in each month in the database are compared to obtain the monitoring point additional layout parameters of urban and rural building complexes. The monitoring points of the urban and rural building complexes include tilt monitoring points, settlement monitoring points and crack monitoring points.

[0013] Furthermore, the intelligent monitoring cloud platform adds layout parameters according to the monitoring points of the urban and rural building complexes, arranges several monitoring cycles, and monitors the structural status of each building in the urban and rural building complexes in each monitoring cycle, thereby obtaining the structural status monitoring data of each building in the urban and rural building complexes in each monitoring cycle. The structural status monitoring data of each building in the urban and rural building complexes in each monitoring cycle include the average inclination angle of each building in the urban and rural building complex, the average settlement depth of each building in the urban and rural building complex, the cumulative number of cracks of each building in the urban and rural building complex, the average vibration frequency of each building in the urban and rural building complex, and the average horizontal displacement of each building in the urban and rural building complex.

[0014] The structural status monitoring data of each building in the urban and rural building complex in each monitoring period are averaged to obtain the structural status monitoring data of the urban and rural building complex in each monitoring period. The structural status monitoring data of the urban and rural building complex in each monitoring period include the average inclination angle of the urban and rural building complex, the average settlement depth of the urban and rural building complex, the cumulative number of cracks in the urban and rural building complex, the average vibration frequency of the urban and rural building complex and the average horizontal displacement of the urban and rural building complex.

[0015] Furthermore, the average inclination angle, average settlement depth, cumulative number of cracks, average vibration frequency and average horizontal displacement of urban and rural building complexes in each monitoring period are extracted, and processed to obtain maintenance demand characterization values ​​of urban and rural building complexes in each monitoring period. The maintenance demand characterization values ​​of urban and rural building complexes in each monitoring period are used to quantitatively evaluate the maintenance needs of urban and rural building complexes.

[0016] Furthermore, the edge computing node receives the structural status monitoring data of the urban and rural building complexes in real time for preprocessing, which also includes the edge computing node dynamically adjusting the data response receiving method during the receiving process.

[0017] Furthermore, the maintenance demand characterization value of the urban and rural building complexes in each monitoring period is compared with the data receiving frequency of the edge computing node receiving sensor corresponding to each interval of the maintenance demand characterization value of the urban and rural building complexes in the database, and the data receiving frequency of the edge computing node receiving sensor is obtained, and used as the data receiving frequency of the edge computing node receiving sensor in the monitoring period.

[0018] Furthermore, in each monitoring cycle, each communication mode of each sensor in the urban and rural building complex is monitored, wherein the communication mode of each sensor includes wired communication and wireless communication, and the maximum bandwidth utilization, maximum network delay, and maximum throughput of each communication mode of each sensor in each monitoring cycle are obtained.

[0019] According to the maximum bandwidth utilization, maximum network delay, and maximum data throughput of each communication mode of each sensor in each monitoring period, the average values ​​are calculated respectively to obtain the average maximum bandwidth utilization, average maximum network delay, and average maximum data throughput of each communication mode in each monitoring period. The quality characterization value of each communication mode in each monitoring period is obtained by processing. The quality characterization value of each communication mode in each monitoring period is used to reflect the data transmission quality of each communication mode.

[0020] Furthermore, the quality characterization values ​​of each communication mode in each monitoring cycle are extracted and sorted from large to small, and the communication mode corresponding to the first quality characterization value of each communication mode in each monitoring cycle is selected as the data communication transmission mode of the edge computing node.

[0021] The structural status monitoring data of urban and rural building complexes are transmitted to the intelligent monitoring cloud platform, and maintenance warnings are issued for urban and rural building complexes based on the maintenance demand representation values ​​of urban and rural building complexes in each monitoring period.

[0022] Furthermore, the maintenance demand representation value of urban and rural building complexes in each monitoring period, the specific analysis conditions are:

[0023] ;

[0024] In the formula, represents the maintenance demand representation value of urban and rural building complexes in the jth monitoring period, represents the average tilt angle of urban and rural buildings in the jth monitoring period, represents the average settlement depth of urban and rural buildings in the jth monitoring period, represents the cumulative number of cracks in urban and rural buildings in the jth monitoring period, represents the average vibration frequency of urban and rural buildings in the jth monitoring period, represents the average horizontal displacement of urban and rural building complexes in the jth monitoring period, represents the average tilt angle of urban and rural buildings in the mth month, represents the average settlement depth of urban and rural building complexes in the mth month, represents the cumulative number of cracks in urban and rural building complexes in the mth month, Indicates the horizontal displacement reference value of the set urban and rural building complex. Indicates the correction factor corresponding to the set inclination angle of the urban and rural building complex, Indicates the correction factor corresponding to the set settlement depth of urban and rural building complexes, Indicates the correction factor corresponding to the number of cracks in the set urban and rural building complex, It represents the correction factor of the vibration frequency of the set urban and rural building complex. It represents the correction factor of the horizontal displacement of the set urban and rural building complex. , n represents the total number of monitoring cycles, , r represents the total number of months.

[0025] The present invention has the following beneficial effects:

[0026] (1) The present invention discloses a data analysis method based on real-time intelligent monitoring of urban and rural building complexes. The Internet of Things cloud platform obtains the layout parameters of additional monitoring points of urban and rural building complexes by analyzing the status data of urban and rural building complexes, monitors the structural status monitoring data and communication data of urban and rural building complexes, and the edge computing node pre-processes the monitoring data in real time and selects the communication method to upload it to the cloud platform for in-depth analysis, thereby realizing real-time intelligent monitoring and maintenance warning of urban and rural building complexes. By optimizing the layout of monitoring points, the monitoring efficiency is improved. The data communication method selection of the edge computing node accelerates the response speed, ensures the stability and efficiency of data transmission, realizes the intelligent monitoring and analysis of urban and rural building complexes, and effectively prevents safety hazards.

[0027] (2) The present invention calculates the monitoring demand characterization values ​​for each month by extracting historical monthly data of urban and rural building complexes, including average tilt angle, average settlement depth and cumulative number of cracks. These characterization values ​​are compared with the monitoring demand characterization value intervals in the database to determine the monitoring points that need to be added, including tilt monitoring points, settlement monitoring points and crack monitoring points. The location of the monitoring points is determined based on actual data, which is conducive to improving the accuracy of the layout points, enabling timely detection of problems and preventing potential risks.

[0028] (3) The present invention extracts historical monthly data of urban and rural building complexes, including the average tilt angle, average settlement depth and cumulative number of cracks in each month, calculates monitoring demand characterization values, and compares these characterization values ​​with the monitoring demand characterization value intervals in the database to determine the tilt, settlement and crack monitoring points that need to be added. The intelligent monitoring cloud platform monitors the structural status of the building complex in real time based on these layout parameters, obtains structural status data including the average tilt angle, average settlement depth, cumulative number of cracks, average vibration frequency and horizontal horizontal displacement, arranges monitoring points according to actual needs, improves the accuracy and comprehensiveness of monitoring, and optimizes the configuration of monitoring resources.

[0029] (4) The present invention processes the structural status monitoring data of urban and rural building complexes with the status data of urban and rural building complexes to obtain maintenance demand representation values ​​of urban and rural building complexes. The edge node adjusts the data transmission frequency according to the maintenance demand representation value and issues maintenance warnings for the urban and rural building complexes, thereby improving building safety and optimizing the efficiency of monitoring and maintenance.

[0030] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention is a flow chart of a data analysis method based on real-time intelligent monitoring of urban and rural building complexes.

[0032] Figure 2 It is the monitoring demand characterization value curve of the urban and rural building complex of the present invention. DETAILED DESCRIPTION

[0033] 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.

[0034] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inside", "all around" and the like indicating orientation or positional relationship are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0035] See also Figure 1 The embodiment of the present invention provides a technical solution: a data analysis method based on real-time intelligent monitoring of urban and rural building complexes, including an Internet of Things cloud platform obtaining and analyzing the status data of urban and rural building complexes to obtain the layout parameters of additional monitoring points of urban and rural building complexes.

[0036] The intelligent monitoring cloud platform arranges monitoring points for urban and rural building complexes according to the additional layout parameters of the monitoring points in the urban and rural building complexes, thereby monitoring the structural status of each building in the urban and rural building complexes, obtaining the structural status monitoring data of the urban and rural building complexes, and inputting it into the edge computing node.

[0037] The edge computing nodes receive the structural status monitoring data of urban and rural building complexes in real time for preprocessing, and analyze and obtain the maintenance demand representation value of urban and rural building complexes.

[0038] Based on the maintenance demand characterization value of urban and rural building complexes, the data communication transmission mode of the edge computing node is determined, the structural status monitoring data of urban and rural building complexes are counted and transmitted to the intelligent monitoring cloud platform for reprocessing, and maintenance warnings are issued for urban and rural building complexes based on the reprocessing.

[0039] It should be noted that by analyzing the status data of urban and rural building complexes, the layout parameters of additional monitoring points are obtained. According to the structural status monitoring data and communication data of urban and rural building complexes obtained by monitoring, the data transmission mode of edge computing nodes is obtained, and the communication mode is intelligently selected and uploaded to the cloud platform for in-depth analysis, so as to realize real-time intelligent monitoring and maintenance warning of urban and rural building complexes. By optimizing the layout of monitoring points, the monitoring efficiency is improved, the data communication mode selection of edge computing nodes accelerates the response speed, ensures the stability and efficiency of data transmission, realizes the intelligent monitoring and analysis of urban and rural building complexes, and effectively prevents safety hazards.

[0040] It should be noted that the Internet of Things cloud platform is a service platform based on cloud computing technology, which can obtain building information, help the system access hardware equipment, configure various hardware equipment information, and connect hardware equipment with buildings and monitoring content.

[0041] It should be noted that the intelligent monitoring cloud platform is a comprehensive monitoring and management platform based on advanced technologies such as cloud computing, Internet of Things, big data, and artificial intelligence. It can analyze monitoring data, obtain data collection frequency, communication methods of edge nodes, and provide maintenance warnings for buildings. It aims to achieve real-time monitoring, data analysis, early warning and alarm functions.

[0042] It should be noted that edge computing nodes refer to devices or nodes that perform computing and storage at the edge of the network. The network edge refers to the part of a computer network or communication system that is closest to the user or data source. The construction of edge nodes includes selecting appropriate hardware and software, configuring network connections, deploying necessary applications and services, implementing security measures, and monitoring and maintenance to ensure that they process data efficiently and securely and interact smoothly with the core network and other nodes. Edge nodes can be used to process structural status monitoring data of urban and rural building complexes, thereby reducing data transmission delays and improving response speed.

[0043] Specifically, the status data of urban and rural building complexes are extracted, and the status data of urban and rural building complexes include the historical monthly average inclination angle of the building complex, the historical monthly average settlement depth and the historical monthly cumulative number of cracks of the building complex. After processing, the monitoring demand characterization value of the urban and rural building complex in each month is obtained.

[0044] It should be noted that the inclination angle of the building is measured and recorded by the tilt sensor, the settlement depth of the house is measured and recorded by the settlement sensor, the data monitored by each sensor are accumulated and averaged to obtain the average inclination angle and average settlement depth of the urban and rural building complexes, the crack monitoring sensor is used to monitor the changes in cracks, and the number of cracks is recorded, the number of cracks monitored by the crack sensor is accumulated to obtain the cumulative number of cracks in the urban and rural building complexes, all the inclination angles and settlement depths in each month are averaged, the number of cracks measured in each month is summed up and stored in the database.

[0045] It should be noted that the monitoring demand representation values ​​of urban and rural building complexes in each month are analyzed in the following specific process:

[0046] ;

[0047] In the formula, represents the monitoring demand representation value of urban and rural building complexes in the mth month, represents the average tilt angle of urban and rural buildings in the mth month, represents the average settlement depth of urban and rural building complexes in the mth month, represents the cumulative number of cracks in urban and rural building complexes in the mth month, represents the average tilt angle of urban and rural buildings in the m-1th month, represents the average settlement depth of urban and rural buildings in the m-1th month, represents the cumulative number of cracks in urban and rural buildings in the m-1th month, It represents the correction factor of the average tilt angle of the set urban and rural building complex, It represents the correction factor of the average settlement depth of the set urban and rural building complex, The correction factor representing the cumulative number of cracks in the set urban and rural building complex, , r represents the total number of months.

[0048] It should be noted that the average tilt angle of urban and rural building complexes, the average settlement depth of urban and rural building complexes, and the cumulative number of cracks in urban and rural building complexes are correlated. When the settlement depth of the building increases, the building may tilt due to uneven settlement, thereby increasing the tilt angle; the increase in the building tilt angle will cause changes in the internal force of the building structure, thereby causing cracks, so the number of cracks in the building will increase as the building tilt angle increases; the horizontal displacement of the building will usually cause or aggravate the tilt angle, and when the horizontal displacement is larger, the building's tilt angle will usually increase.

[0049] It is the correction factor of the average tilt angle of the urban and rural building complex preset in the database, which represents the degree of correction of the average tilt angle of the urban and rural building complex to the monitoring demand characterization value of the urban and rural building complex. When used, the correction factor of the average tilt angle of the urban and rural building complex can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the average tilt angle of the urban and rural building complex and the correction factor of the average tilt angle of the urban and rural building complex preset in the database form a mapping set, and the real-time average tilt angle of the urban and rural building complex is input into the mapping set to obtain the correction factor of the average tilt angle of the urban and rural building complex, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0050] It is the correction factor of the average settlement depth of urban and rural building complexes preset in the database, which represents the degree of correction of the average settlement depth of urban and rural building complexes to the monitoring demand characterization value of urban and rural building complexes. When used, the correction factor of the average settlement depth of urban and rural building complexes can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the average settlement depth of urban and rural building complexes and the correction factor of the average settlement depth of urban and rural building complexes preset in the database form a mapping set, and the real-time average settlement depth of urban and rural building complexes is input into the mapping set to obtain the correction factor of the average settlement depth of urban and rural building complexes. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0051] It is the correction factor of the cumulative number of cracks of urban and rural building complexes preset in the database, which represents the correction degree of the cumulative number of cracks of urban and rural building complexes to the monitoring demand characterization value of urban and rural building complexes. When used, the correction factor of the cumulative number of cracks of urban and rural building complexes can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the cumulative number of cracks of urban and rural building complexes and the correction factor of the cumulative number of cracks of urban and rural building complexes preset in the database form a mapping set, and the real-time cumulative number of cracks of urban and rural building complexes is input into the mapping set to obtain the correction factor of the cumulative number of cracks of urban and rural building complexes, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0052] like Figure 2 As shown, Figure 2 The monitoring demand characterization value curve of urban and rural building complexes, where the x-axis represents the average settlement depth of urban and rural building complexes in the mth month, in millimeters , the y-axis represents the monitoring demand characterization value of the urban and rural building complex in the mth month. Three different sets of example parameters are defined in the figure, corresponding to different situations of the three curves, represented by solid lines, dashed lines and dotted lines respectively, and the corresponding curve labels are a, b, and c respectively. When the average inclination angle of the urban and rural building complex in the mth month is 0.02, the schematic diagram of the monitoring demand characterization value of the urban and rural building complex in the mth month is shown in curve a, when the average inclination angle of the urban and rural building complex in the mth month is 0.04, the schematic diagram of the monitoring demand characterization value of the urban and rural building complex in the mth month is shown in curve b, when the average inclination angle of the urban and rural building complex in the mth month is 0.08, the schematic diagram of the monitoring demand characterization value of the urban and rural building complex in the mth month is shown in curve c, when the average settlement depth of the urban and rural building complex in the mth month is greater than the average inclination angle of the urban and rural building complex in the m-1th month, the greater the monitoring demand characterization value of the urban and rural building complex in the mth month, which reflects the influence of the average settlement depth rate of the urban and rural building complex on the monitoring demand characterization value of the urban and rural building complex.

[0053] As shown in Table 1, Table 1 is sample data of monitoring demand characterization values ​​of urban and rural building complexes, which lists the monitoring demand characterization values ​​of urban and rural building complexes and the average settlement depth of urban and rural building complexes.

[0054] Table 1 Example data of monitoring demand representation values ​​for urban and rural building complexes

[0055]

[0056] As shown in Table 1, in a specific embodiment, assuming that the cumulative number of cracks in the urban and rural building complex in the mth month is = 1 (unit), the average tilt angle of urban and rural buildings in the m-1th month (degrees), average settlement depth of urban and rural buildings in the m-1th month 30 (mm), cumulative number of cracks in urban and rural buildings in month m-1 (), correction factor for the average tilt angle of urban and rural building complexes , set the correction factor for the average settlement depth of urban and rural building complexes , the correction factor for the cumulative number of cracks in urban and rural building complexes The monitoring demand characterization value of urban and rural building complexes is determined by the average inclination angle of urban and rural building complexes, the average settlement depth of urban and rural building complexes and the cumulative number of cracks in urban and rural building complexes.

[0057] Specifically, according to the monitoring demand characterization values ​​of urban and rural building complexes in each month, the monitoring point additional layout parameters corresponding to each interval of the monitoring demand characterization values ​​of urban and rural building complexes in each month in the database are compared to obtain the monitoring point additional layout parameters of urban and rural building complexes. The monitoring points of the urban and rural building complexes include tilt monitoring points, settlement monitoring points and crack monitoring points.

[0058] It should be noted that, according to the monitoring demand characterization values ​​of urban and rural building complexes, these values ​​are compared with the monitoring point layout parameters corresponding to each interval in the database to determine the monitoring points that need to be added. The monitoring point addition layout parameters are preset in the database. When used, the monitoring point addition layout parameters can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the monitoring demand characterization values ​​of urban and rural building complexes and the monitoring point addition layout parameters preset in the database form a mapping set, and the real-time monitoring demand characterization values ​​of each urban and rural building complex are input into the mapping set to obtain the monitoring point addition layout parameters. The mapping relationship can be a one-to-one relationship to obtain the monitoring point addition layout parameters, including tilt monitoring points, settlement monitoring points and crack monitoring points, to ensure that the monitoring system can fully cover the status of the building complex, and by reasonably adding monitoring points, the monitoring coverage is improved to ensure that key areas and structures are fully monitored.

[0059] Specifically, the intelligent monitoring cloud platform adds layout parameters according to the monitoring points of the urban and rural building complexes, arranges several monitoring cycles, and monitors the structural status of each building in the urban and rural building complexes in each monitoring cycle, thereby obtaining the structural status monitoring data of each building in the urban and rural building complexes in each monitoring cycle. The structural status monitoring data of each building in the urban and rural building complexes in each monitoring cycle include the average inclination angle of each building in the urban and rural building complex, the average settlement depth of each building in the urban and rural building complex, the cumulative number of cracks of each building in the urban and rural building complex, the average vibration frequency of each building in the urban and rural building complex, and the average horizontal displacement of each building in the urban and rural building complex.

[0060] The structural status monitoring data of each building in the urban and rural building complex in each monitoring period are averaged to obtain the structural status monitoring data of the urban and rural building complex in each monitoring period. The structural status monitoring data of the urban and rural building complex in each monitoring period include the average inclination angle of the urban and rural building complex, the average settlement depth of the urban and rural building complex, the cumulative number of cracks in the urban and rural building complex, the average vibration frequency of the urban and rural building complex and the average horizontal displacement of the urban and rural building complex.

[0061] It should be noted that the additional layout parameters of the monitoring points in urban and rural building complexes include the spacing, number, location, number and type of sensors to be arranged for various monitoring points (tilt monitoring points, settlement monitoring points and crack monitoring points), and sensors are arranged at the tilt monitoring points, settlement monitoring points and crack monitoring points as well as in each monitoring point. For example: high-precision inclination sensors are installed at the four corners and the center of the building to monitor the tilt; static levels are set up approximately every 15 meters around the building and under the load-bearing walls, with a total of 12 points arranged to accurately monitor ground settlement; at the same time, for the 5 cracks that have been discovered, crack meters are attached to both ends and the middle of each crack, totaling 15, to monitor changes in the cracks.

[0062] It should be noted that the vibration frequency of the building can provide accurate building vibration frequency data through vibration sensors, and the horizontal displacement of the building can be collected in real time through horizontal displacement sensors. The vibration frequency and horizontal translation of each building in the urban and rural building complex are monitored and averaged within a monitoring period to obtain the average vibration frequency and horizontal horizontal displacement of the urban and rural building complex in each monitoring period.

[0063] Specifically, the average inclination angle, average settlement depth, cumulative number of cracks, average vibration frequency and average horizontal displacement of urban and rural building complexes in each monitoring period are extracted, and processed to obtain the maintenance demand characterization value of urban and rural building complexes in each monitoring period. The maintenance demand characterization value of urban and rural building complexes in each monitoring period is used to quantitatively evaluate the maintenance demand of urban and rural building complexes.

[0064] It should be noted that by extracting data such as the average inclination angle, average settlement depth, cumulative number of cracks, average vibration frequency and horizontal displacement of urban and rural building complexes, the maintenance demand characterization value calculated can be used to quantitatively evaluate the maintenance needs of the building complex. By analyzing the structural status monitoring data of urban and rural building complexes, it is helpful to accurately evaluate the maintenance needs of buildings and discover and deal with potential building problems as early as possible.

[0065] Specifically, the edge computing node receives the structural status monitoring data of urban and rural building complexes in real time for preprocessing, which also includes the edge computing node dynamically adjusting the data response receiving method during the receiving process.

[0066] It should be noted that the preprocessing includes missing value filling, outlier processing, duplicate value removal and noise data smoothing. Missing value filling means filling the missing values ​​in the structural status monitoring dataset of urban and rural building complexes with the median. Outlier processing means replacing the outliers in the structural status monitoring dataset of urban and rural building complexes with the mean. Duplicate value removal means removing duplicate data in the structural status monitoring dataset of urban and rural building complexes. Noise data smoothing means using a filter to smooth the noise in the data.

[0067] It should be noted that the edge computing node dynamically adjusts the receiving method according to the data transmission situation to optimize the data processing efficiency and accuracy, which helps to quickly process and respond to monitoring data and ensure timely detection of building problems.

[0068] It should be noted that sensors may send data to edge computing nodes through wired (such as optical fiber, Ethernet) or wireless (such as LoRa, ZigBee, Wi-Fi, 4G / 5G) communication methods. Edge computing nodes can dynamically select different communication methods based on real-time network conditions (such as signal strength, bandwidth, latency, etc.).

[0069] Specifically, the maintenance demand characterization value of the urban and rural building complexes in each monitoring period is compared with the data receiving frequency of the edge computing node receiving sensor corresponding to each interval of the maintenance demand characterization value of the urban and rural building complexes in the database, and the data receiving frequency of the edge computing node receiving sensor is obtained, and used as the data receiving frequency of the edge computing node receiving sensor in the monitoring period.

[0070] It should be noted that by comparing the maintenance demand representation value with the data receiving frequency in the database, the data receiving frequency of the edge computing node is determined and adjusted to meet the current monitoring requirements. The data receiving frequency is preset in the database, and the data receiving frequency can be directly obtained from the database when in use. The corresponding relationship can be a pre-set mapping relationship. For example, the maintenance demand representation value of the urban and rural building complex and the data receiving frequency preset in the database form a mapping set, and the real-time maintenance demand representation value of the urban and rural building complex is input into the mapping set to obtain the data receiving frequency. The mapping relationship can be a one-to-one relationship. Dynamic adjustment of the receiving frequency helps to improve the system's response speed to important data, thereby improving the efficiency of the overall monitoring system.

[0071] Specifically, in each monitoring cycle, each communication mode of each sensor in the urban and rural building complex is monitored, wherein the communication mode of each sensor includes wired communication and wireless communication, and the maximum bandwidth utilization, maximum network delay, and maximum throughput of each communication mode of each sensor in each monitoring cycle are obtained.

[0072] According to the maximum bandwidth utilization, maximum network delay, and maximum data throughput of each communication mode of each sensor in each monitoring period, the average values ​​are calculated respectively to obtain the average maximum bandwidth utilization, average maximum network delay, and average maximum data throughput of each communication mode in each monitoring period. The quality characterization value of each communication mode in each monitoring period is obtained by processing. The quality characterization value of each communication mode in each monitoring period is used to reflect the data transmission quality of each communication mode.

[0073] It should be noted that network monitoring tools (such as Wireshark, PRTG, SolarWinds) are used to measure the network delay of each communication mode of each sensor in each monitoring period, and the maximum network delay is obtained and averaged to obtain the average maximum network delay of each communication mode in each monitoring period; operating system tools (such as nload, Task Manager / Resource Monitor) are used to monitor the data throughput of each communication mode of each sensor in real time in each monitoring period, and the maximum value is taken and averaged to obtain the average maximum data throughput of each communication mode in each monitoring period; bandwidth analyzers (such as SolarWinds Bandwidth Analyzer Pack, PRTG Network Monitor) are used to perform real-time analysis on the bandwidth utilization of each communication mode of each sensor in each monitoring period, and the maximum bandwidth utilization of each sensor is taken and averaged to obtain the average maximum bandwidth utilization of each communication mode in each monitoring period.

[0074] It should be noted that the quality characterization value of each communication mode in each monitoring cycle. The specific analysis process is:

[0075] ;

[0076] In the formula, represents the quality characterization value of the i-th communication mode in the j-th monitoring period, It represents the average maximum network delay of the ith communication mode in the jth monitoring period. represents the average maximum data throughput of the i-th communication mode in the j-th monitoring period, It represents the average maximum bandwidth utilization of the i-th communication mode in the j-th monitoring period. Indicates the reference value of the set network delay. Indicates the reference value of the set data throughput. Indicates the reference value of the set bandwidth utilization. Indicates the correction factor corresponding to the set network delay. Indicates the correction factor corresponding to the set data throughput, Indicates the correction factor corresponding to the set bandwidth utilization. , n represents the total number of monitoring cycles, , q represents the total number of communication modes.

[0077] It should be noted that there is a correlation between the network delay, data throughput and bandwidth utilization of the communication method. When the bandwidth increases, more data can be transmitted in a shorter time, so the network delay will be reduced. Increasing the bandwidth means a higher data transmission rate, which may increase the risk of bit error rate, so the bit error rate will increase. When the bit error rate increases, it will lead to an increase in errors in data transmission, and retransmission or error correction must be performed, which will occupy additional bandwidth resources and reduce bandwidth utilization. Therefore, an increase in the bit error rate will lead to a decrease in bandwidth utilization.

[0078] It is a correction factor of network delay preset in the database, which indicates the degree of correction of the communication mode quality characterization value by network delay. When used, the correction factor of network delay can be directly obtained from the database, and its corresponding relationship can be a preset mapping relationship. For example, the network delay and the correction factor of network delay preset in the database form a mapping set, and the real-time network delay is input into the mapping set to obtain the correction factor of network delay, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0079] It is a correction factor of data throughput preset in the database, which indicates the degree of correction of data throughput to the communication mode quality characterization value. When used, the correction factor of data throughput can be directly obtained from the database, and its corresponding relationship can be a preset mapping relationship. For example, the data throughput and the correction factor of data throughput preset in the database form a mapping set, and the real-time data throughput is input into the mapping set to obtain the correction factor of data throughput, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0080] It is a correction factor of bandwidth utilization preset in the database, which indicates the degree of correction of bandwidth utilization to the communication mode quality characterization value. When used, the correction factor of bandwidth utilization can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the bandwidth utilization and the correction factor of bandwidth utilization preset in the database form a mapping set, and the real-time bandwidth utilization is input into the mapping set to obtain the correction factor of bandwidth utilization, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0081] Specifically, the quality characterization values ​​of each communication mode in each monitoring cycle are extracted and sorted from large to small, and the communication mode corresponding to the first quality characterization value of each communication mode in each monitoring cycle is selected as the data communication transmission mode of the edge computing node.

[0082] The structural status monitoring data of urban and rural building complexes are transmitted to the intelligent monitoring cloud platform, and maintenance warnings are issued for urban and rural building complexes based on the maintenance demand representation values ​​of urban and rural building complexes in each monitoring period.

[0083] It should be noted that the characteristic values ​​of each communication mode are sorted from high to low, and the communication mode corresponding to the characteristic value of the communication mode ranked first is selected as the data transmission mode of the edge computing node, ensuring that the sensor data is transmitted to the edge computing node quickly and accurately, which is conducive to improving the real-time and accuracy of data processing.

[0084] It should be noted that the maintenance demand representation value of the urban and rural building complex is matched with the building safety status of each interval of the maintenance demand representation value of the urban and rural building complex in the database. The building safety status is preset in the database, and the building safety status can be directly obtained from the database when used. The corresponding relationship can be a pre-set mapping relationship. For example, the maintenance demand representation value of the urban and rural building complex and the building safety status preset in the database form a mapping set, and the real-time maintenance demand representation value of the urban and rural building complex is input into the mapping set to obtain the building safety status, and the mapping relationship can be a one-to-one relationship. The building safety status includes a normal safety status, which means that the building structure is intact and no significant safety hazards are found; a hidden danger status, which means that the building may have minor safety hazards or structural problems, such as minor cracks and local settlement; a dangerous state, which means that the building may have serious safety hazards, serious cracks, large-scale settlement and other problems. When the building safety status is in a normal safety state, no warning is required and the building can continue to be used normally. The intelligent monitoring cloud platform generates an inspection cycle and dispatches maintenance staff to regularly maintain and inspect the building. When the building safety status is a hidden danger state, a text message warning is issued through the cloud platform to increase the maintenance and inspection frequency of the building. When the building safety status is a dangerous state, an alarm is issued through the cloud platform and a text message warning is issued simultaneously, prohibiting the building from continuing to use, generating a building maintenance plan, and dispatching maintenance personnel to conduct inspections and repairs.

[0085] Specifically, the maintenance demand representation value of urban and rural building complexes in each monitoring period, the specific analysis conditions are:

[0086]

[0087] In the formula, represents the maintenance demand representation value of urban and rural building complexes in the jth monitoring period, represents the average tilt angle of urban and rural buildings in the jth monitoring period, represents the average settlement depth of urban and rural buildings in the jth monitoring period, represents the cumulative number of cracks in urban and rural buildings in the jth monitoring period, represents the average vibration frequency of urban and rural buildings in the jth monitoring period, represents the average horizontal displacement of urban and rural building complexes in the jth monitoring period, represents the average tilt angle of urban and rural buildings in the mth month, represents the average settlement depth of urban and rural building complexes in the mth month, represents the cumulative number of cracks in urban and rural building complexes in the mth month, Indicates the horizontal displacement reference value of the set urban and rural building complex. Indicates the correction factor corresponding to the set inclination angle of the urban and rural building complex, Indicates the correction factor corresponding to the set settlement depth of urban and rural building complexes, Indicates the correction factor corresponding to the number of cracks in the set urban and rural building complex, It represents the correction factor of the vibration frequency of the set urban and rural building complex. It represents the correction factor of the horizontal displacement of the set urban and rural building complex. , n represents the total number of monitoring cycles, , r represents the total number of months.

[0088] It should be noted that the average tilt angle of urban and rural building complexes, the average settlement depth of urban and rural building complexes, the cumulative number of cracks in urban and rural building complexes, the vibration frequency of buildings in urban and rural building complexes, and the horizontal displacement of buildings in urban and rural building complexes are correlated. When the settlement depth of the building increases, the building may tilt due to uneven settlement, thereby increasing the tilt angle; the increase in the building tilt angle will cause changes in the internal force of the building structure, thereby causing cracks, so the number of cracks in the building will increase as the building tilt angle increases; when the vibration frequency of the building increases, it means that the rigidity of the building is low and the horizontal displacement will increase; the horizontal displacement of the building usually causes or aggravates the tilt angle. When the horizontal displacement is larger, the building's tilt angle will usually increase.

[0089] It is the correction factor of the tilt angle of the urban and rural building complex preset in the database, which represents the degree of correction of the tilt angle of the urban and rural building complex to the maintenance demand characterization value of the urban and rural building complex. When used, the correction factor of the tilt angle of the urban and rural building complex can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the tilt angle of the urban and rural building complex and the correction factor of the tilt angle of the urban and rural building complex preset in the database form a mapping set, and the real-time tilt angle of the urban and rural building complex is input into the mapping set to obtain the correction factor of the tilt angle of the urban and rural building complex, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0090] It is the correction factor of the settlement depth of the urban and rural building complex preset in the database, which represents the degree of correction of the settlement depth of the urban and rural building complex to the maintenance demand characterization value of the urban and rural building complex. When used, the correction factor of the settlement depth of the urban and rural building complex can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the settlement depth of the urban and rural building complex and the correction factor of the settlement depth of the urban and rural building complex preset in the database form a mapping set, and the real-time settlement depth of the urban and rural building complex is input into the mapping set to obtain the correction factor of the settlement depth of the urban and rural building complex, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0091] It is the correction factor of the cumulative number of cracks of urban and rural building complexes preset in the database, which represents the degree of correction of the cumulative number of cracks of urban and rural building complexes to the maintenance demand characterization value of urban and rural building complexes. When used, the correction factor of the cumulative number of cracks of urban and rural building complexes can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the cumulative number of cracks of urban and rural building complexes and the correction factor of the cumulative number of cracks of urban and rural building complexes preset in the database form a mapping set, and the real-time cumulative number of cracks of urban and rural building complexes is input into the mapping set to obtain the correction factor of the cumulative number of cracks of urban and rural building complexes, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0092] It is the correction factor of the vibration frequency of the urban and rural building complex buildings preset in the database, which represents the degree of correction of the vibration frequency of the urban and rural building complex buildings to the maintenance demand representation value of the urban and rural building complex. When used, the correction factor of the vibration frequency of the urban and rural building complex buildings can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the vibration frequency of the urban and rural building complex buildings and the correction factor of the vibration frequency of the urban and rural building complex buildings preset in the database form a mapping set, and the real-time vibration frequency of the urban and rural building complex buildings is input into the mapping set to obtain the correction factor of the vibration frequency of the urban and rural building complex buildings. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0093] It is the correction factor of the horizontal displacement of the urban and rural building complex buildings preset in the database, which represents the degree of correction of the horizontal displacement of the urban and rural building complex buildings to the maintenance demand representation value of the urban and rural building complex. When used, the correction factor of the horizontal displacement of the urban and rural building complex buildings can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the horizontal displacement of the urban and rural building complex buildings and the correction factor of the horizontal displacement of the urban and rural building complex buildings preset in the database form a mapping set, and the real-time horizontal displacement of the urban and rural building complex buildings is input into the mapping set to obtain the correction factor of the horizontal displacement of the urban and rural building complex buildings, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1].

[0094] It should be noted that the data analysis method based on real-time intelligent monitoring of urban and rural building complexes also includes a database, which is an important tool for storing and managing data related to the structural status monitoring data of urban and rural building complexes. In this embodiment, the database is used to store the historical monthly average inclination angle of the building complex, the historical monthly average settlement depth, the historical monthly cumulative number of cracks of the building complex, the average vibration frequency reference value of the urban and rural building complex, the horizontal displacement reference value of the urban and rural building complex, the correction factor corresponding to the inclination angle of the urban and rural building complex, the correction factor corresponding to the settlement depth of the urban and rural building complex, the correction factor corresponding to the cumulative number of cracks in the urban and rural building complex, the correction factor of the vibration frequency of buildings in the urban and rural building complex, the correction factor of the horizontal displacement of buildings in the urban and rural building complex, the correction factor of the average inclination angle of the urban and rural building complex, the correction factor of the average settlement depth of the urban and rural building complex, the correction factor of the cumulative number of cracks in the urban and rural building complex, the reference value of network delay, the reference value of data throughput, the reference value of bandwidth utilization, the correction factor corresponding to network delay, the correction factor corresponding to data throughput, and the correction factor corresponding to bandwidth utilization.

[0095] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0096] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data analysis method based on real-time intelligent monitoring of urban and rural building complexes, characterized in that: include: The IoT cloud platform obtains and analyzes the status data of urban and rural building complexes to obtain the additional layout parameters of monitoring points in urban and rural building complexes; The intelligent monitoring cloud platform arranges monitoring points for urban and rural building complexes according to the additional arrangement parameters of monitoring points for urban and rural building complexes, thereby monitoring the structural status of each building in the urban and rural building complexes, obtaining the structural status monitoring data of the urban and rural building complexes, and inputting it into the edge computing node; The edge computing nodes receive the structural status monitoring data of urban and rural building complexes in real time for preprocessing and analyze to obtain the maintenance demand representation value of urban and rural building complexes; Based on the maintenance demand representation value of urban and rural building complexes, determine the data communication transmission mode of edge computing nodes, collect statistics on the structural status monitoring data of urban and rural building complexes and transmit them to the intelligent monitoring cloud platform for reprocessing, and issue maintenance warnings for urban and rural building complexes based on the reprocessing; The structural status of each building in the urban and rural building complex is monitored to obtain the structural status monitoring data of the urban and rural building complex. The specific process is as follows: The intelligent monitoring cloud platform adds layout parameters according to the monitoring points of the urban and rural building complex, arranges several monitoring cycles, monitors the structural status of each building in the urban and rural building complex in each monitoring cycle, thereby obtaining the structural status monitoring data of each building in the urban and rural building complex in each monitoring cycle, wherein the structural status monitoring data of each building in the urban and rural building complex in each monitoring cycle includes the average inclination angle of each building in the urban and rural building complex, the average settlement depth of each building in the urban and rural building complex, the cumulative number of cracks of each building in the urban and rural building complex, the average vibration frequency of each building in the urban and rural building complex, and the average horizontal displacement of each building in the urban and rural building complex; The structural status monitoring data of each building in the urban and rural building complex in each monitoring period are averaged to obtain the structural status monitoring data of the urban and rural building complex in each monitoring period, wherein the structural status monitoring data of the urban and rural building complex in each monitoring period include the average inclination angle of the urban and rural building complex, the average settlement depth of the urban and rural building complex, the cumulative number of cracks in the urban and rural building complex, the average vibration frequency of the urban and rural building complex, and the average horizontal displacement of the urban and rural building complex; The statistical data of the structural status monitoring of urban and rural building complexes is transmitted to the intelligent monitoring cloud platform for reprocessing. The specific process is as follows: In each monitoring cycle, each communication mode of each sensor of the urban and rural building complex is monitored, wherein each communication mode of each sensor includes wired communication and wireless communication, and the maximum bandwidth utilization, maximum network delay, and maximum throughput of each communication mode of each sensor in each monitoring cycle are obtained; According to the maximum bandwidth utilization, maximum network delay, and maximum data throughput of each communication mode of each sensor in each monitoring period, the average values ​​are calculated respectively to obtain the average maximum bandwidth utilization, average maximum network delay, and average maximum data throughput of each communication mode in each monitoring period, and the quality characterization value of each communication mode in each monitoring period is obtained by processing, and the quality characterization value of each communication mode in each monitoring period is used to reflect the data transmission quality of each communication mode; The data communication transmission mode of the edge computing node is determined, and the maintenance warning of the urban and rural building complex is analyzed based on the reprocessing: Extract the quality characterization values ​​of each communication mode in each monitoring cycle and sort them from large to small, and select the communication mode corresponding to the first quality characterization value of each communication mode in each monitoring cycle as the data communication transmission mode of the edge computing node; The structural status monitoring data of urban and rural building complexes are transmitted to the intelligent monitoring cloud platform, and maintenance warnings are issued for urban and rural building complexes based on the maintenance demand representation values ​​of urban and rural building complexes in each monitoring period.

2. The data analysis method based on real-time intelligent monitoring of urban and rural building complexes according to claim 1 is characterized by: The IoT cloud platform obtains and analyzes the status data of urban and rural building complexes. The specific analysis process is as follows: The status data of urban and rural building complexes are extracted, and the status data of urban and rural building complexes include the historical monthly average inclination angle of urban and rural building complexes, the historical monthly average settlement depth and the historical monthly cumulative number of cracks of the building complexes, and the monitoring demand characterization value of the urban and rural building complexes in each month is obtained after processing.

3. The data analysis method based on real-time intelligent monitoring of urban and rural building complexes according to claim 2 is characterized in that: The specific process of obtaining the additional arrangement parameters of monitoring points for urban and rural building complexes is as follows: According to the monitoring demand characterization values ​​of urban and rural building complexes in each month, the monitoring point additional layout parameters corresponding to each interval of the monitoring demand characterization values ​​of urban and rural building complexes in each month in the database are compared to obtain the monitoring point additional layout parameters of urban and rural building complexes. The monitoring points of the urban and rural building complexes include tilt monitoring points, settlement monitoring points and crack monitoring points.

4. The data analysis method based on real-time intelligent monitoring of urban and rural building complexes according to claim 1 is characterized in that: The edge computing node receives the structural status monitoring data of urban and rural building complexes in real time for preprocessing. The specific analysis process is as follows: The average inclination angle, average settlement depth, cumulative number of cracks, average vibration frequency and average horizontal displacement of urban and rural building complexes in each monitoring period are extracted, and processed to obtain maintenance demand characterization values ​​of urban and rural building complexes in each monitoring period. The maintenance demand characterization values ​​of urban and rural building complexes in each monitoring period are used to quantitatively evaluate the maintenance needs of urban and rural building complexes.

5. The data analysis method based on real-time intelligent monitoring of urban and rural building complexes according to claim 1 is characterized in that: The edge computing node receives the structural status monitoring data of urban and rural building complexes in real time for preprocessing, which also includes the edge computing node dynamically adjusting the data response receiving method during the receiving process.

6. The data analysis method based on real-time intelligent monitoring of urban and rural building complexes according to claim 5 is characterized by: The edge computing node dynamically adjusts the data response receiving mode during the receiving process. The specific process is as follows: The maintenance demand characterization value of the urban and rural building complexes in each monitoring period is compared with the data receiving frequency of the edge computing node receiving sensor corresponding to each interval of the maintenance demand characterization value of the urban and rural building complexes in the database, and the data receiving frequency of the edge computing node receiving sensor is obtained, and used as the data receiving frequency of the edge computing node receiving sensor in the monitoring period.

7. The data analysis method based on real-time intelligent monitoring of urban and rural building complexes according to claim 4 is characterized by: The maintenance demand representation value of the urban and rural building complex in each monitoring period, the specific analysis conditions are: ； In the formula, represents the maintenance demand representation value of urban and rural building complexes in the jth monitoring period, represents the average tilt angle of urban and rural buildings in the jth monitoring period, represents the average settlement depth of urban and rural buildings in the jth monitoring period, represents the cumulative number of cracks in urban and rural buildings in the jth monitoring period, represents the average vibration frequency of urban and rural buildings in the jth monitoring period, represents the average horizontal displacement of urban and rural building complexes in the jth monitoring period, represents the average tilt angle of urban and rural buildings in the mth month, represents the average settlement depth of urban and rural building complexes in the mth month, represents the cumulative number of cracks in urban and rural building complexes in the mth month, Indicates the horizontal displacement reference value of the set urban and rural building complex. Indicates the correction factor corresponding to the set inclination angle of the urban and rural building complex, Indicates the correction factor corresponding to the set settlement depth of urban and rural building complexes, Indicates the correction factor corresponding to the number of cracks in the set urban and rural building complex, It represents the correction factor of the vibration frequency of the set urban and rural building complex. It represents the correction factor of the horizontal displacement of the set urban and rural building complex. , n represents the total number of monitoring cycles, , r represents the total number of months.

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