CN115585783A

CN115585783A - Building settlement long-term monitoring system and method based on Internet of things

Info

Publication number: CN115585783A
Application number: CN202211220635.3A
Authority: CN
Inventors: 李琦
Original assignee: Chengdu Oujuanqiao Electronic Technology Co ltd
Current assignee: Chengdu Oujuanqiao Electronic Technology Co ltd
Priority date: 2022-10-07
Filing date: 2022-10-07
Publication date: 2023-01-10

Abstract

The invention discloses a long-term monitoring system and a long-term monitoring method for building settlement based on the Internet of things, belonging to the technical field of building monitoring; the method comprises the steps of monitoring the soil state of geography for a long time by integrating the data of the building and the geographic data of the building in a simultaneous manner, analyzing and evaluating the settlement of the building based on the change in the geographic aspect, and adaptively adjusting the duration of an evaluation time interval according to the analysis result to realize the intelligent operation of long-term monitoring of the settlement of the building; the invention is used for solving the technical problems that the building settlement monitoring process cannot be self-adaptively and dynamically adjusted in the existing scheme, and different monitoring results are integrated, so that the overall effect of long-term building settlement monitoring is poor.

Description

Building settlement long-term monitoring system and method based on Internet of things

Technical Field

The invention relates to the technical field of building monitoring, in particular to a long-term building settlement monitoring system and method based on the Internet of things.

Background

In order to master the settlement condition of the building and discover the unfavorable settlement phenomenon of the building in time so as to take measures to ensure the safe use of the building and provide data for reasonable design in the future, the settlement monitoring is required in the construction process of the building and after the building is put into operation.

The invention discloses a Chinese invention with the publication number of CN112683233B and the name of a building settlement detection method, which takes a building as a center, divides the width of the building according to a preset radius value to obtain a detection area, deeply divides the detection area by using the preset depth value to obtain the detection divided area, respectively obtains building information and soil information in the detection divided area, processes the building information to obtain building processing information, processes the soil information to obtain soil processing information, analyzes the settlement of the building by using the building processing information and the soil processing information to obtain settlement analysis information, generates early warning information by using the settlement analysis information, and prevents and processes the settlement of the building by using the early warning information; the invention can solve the problems that the prior proposal can not carry out comprehensive analysis and detection according to the change of buildings and the change of soil and the defect of poor detection accuracy caused by the failure of analysis according to the soil with different depths.

However, the implementation process of the building settlement detection scheme has certain defects, and dynamic tracking verification is not performed on abnormal conditions found during monitoring, so that the data integrity of abnormal monitoring analysis is poor, and if an all-weather real-time monitoring scheme is adopted, the utilization rate of data resources is low; in addition, the monitoring results of different periods are not integrated, so that the overall effect of building settlement detection is poor.

Disclosure of Invention

The invention aims to provide a building settlement long-term monitoring system and method based on the Internet of things, which are used for solving the technical problems that the building settlement monitoring process cannot be adaptively and dynamically adjusted and different monitoring results are integrated in the existing scheme, so that the overall effect of long-term monitoring of the building settlement is poor.

The purpose of the invention can be realized by the following technical scheme:

a building settlement long-term monitoring system based on the Internet of things comprises:

the system comprises a sample acquisition module, a monitoring module and a monitoring module, wherein the sample acquisition module is used for acquiring target information of a building to be monitored and geographic information of the building; the target information comprises building recessive data and building dominant data; the geographic information comprises attribute data;

the geographic evaluation module is used for extracting and marking the characteristics of the target information and the geographic information, and integrating and evaluating each preprocessed data in a preset reference evaluation time period to obtain the change degree of the building settlement;

the analysis prompt module is used for analyzing the change degree; the method comprises the following steps: if the change degree BH belongs to [ c1, c2], judging that the soil monitoring state of the monitored building is moderate abnormal, generating a second monitoring signal, shortening the duration of the reference evaluation period according to the second monitoring signal to obtain a first adjustment evaluation period, and tracking the abnormal state in the scene;

if the change degree BH is more than c2, judging that the soil monitoring state of the monitored building is highly abnormal, generating a third monitoring signal, shortening the duration of the reference evaluation period according to the second monitoring signal to obtain a second adjustment evaluation period, and tracking the abnormal state in the scene;

setting the starting time point as a first time stamp in the tracking process, setting the corresponding time point as a second time stamp until the tracked change degree BH < c1, and recovering the adjusted evaluation time period to the reference evaluation time period;

acquiring tracking time differences according to the first time stamp and the second time stamp, and respectively setting the tracking time differences corresponding to the second monitoring signal and the third monitoring signal as a first time difference and a second time difference;

the second monitoring signal and the third monitoring signal as well as the first time difference and the second time difference form an analysis result;

and different tracking schemes are implemented according to the preset reference evaluation time period of the self-adaptive adjustment of the analysis results, and the early warning prompt is carried out on the settlement condition of the building by combining different analysis results.

Preferably, the feature extraction and labeling of the target information and the geographic information includes:

acquiring building recessive data and building dominant data in the target information and attribute data in the geographic information;

matching the building type in the building recessive data with a pre-constructed building type-weight table to obtain a corresponding building weight and marking the building weight as J1; marking the building quality in the building implicit data as J2; acquiring the building volume according to the length, the width and the height of the building in the building dominant data and marking the building volume as J3; and arranging and combining the marked data to obtain first marked data.

Preferably, the total number of different types of soil is marked as S0; matching the soil type in the attribute data with a pre-constructed soil type-weight table to obtain a corresponding soil weight and marking the soil weight as S1; marking the humidity and the partial depth of each type of soil in the attribute data as S2 and S3 respectively; and arranging and combining the marked data to obtain second marked data.

Preferably, calculating and obtaining the change degree BH of the building settlement through a formula; the formula is:

in the formula, j1 and j2 are different preset proportionality coefficients, and j1 is more than 0 and less than j2; TRX is the soil coefficient.

Preferably, the soil coefficient is calculated by the formula:

in the formula, s1 and s2 are different preset proportionality coefficients, and s2 is more than 0 and less than s1.

Preferably, different analysis results are combined to give an early warning prompt to the settlement condition of the building, and the method comprises the following steps:

acquiring the total occurrence times of the second monitoring signal and the third monitoring signal and respectively marking as C1 and C2; the first time difference and the second time difference are marked as C3 and C4 respectively; extracting the numerical values of all marked data and obtaining the threat degree WX in a simultaneous manner;

matching the threat degree WX with a pre-constructed threat table to obtain a corresponding threat label, carrying out self-adaptive early warning prompt according to the obtained threat label, and carrying out processing by dynamic regulation and control personnel.

Preferably, the threat degree WX is obtained through formula calculation; the formula is:

in the formula, w1 and w2 are different preset proportionality coefficients, and w1 is more than 0 and less than w2; q1 is a monitoring weight corresponding to the preset second monitoring signal, and Q2 is a monitoring weight corresponding to the preset third monitoring signal.

Preferably, monitoring statistics is respectively carried out on the geographic information of the building and the surroundings based on the equipment of the Internet of things; counting the building type and the building quality of a building to be monitored to obtain building implicit data;

expanding the length and the width of the building to obtain an expanded length and an expanded width; and setting the expansion length and the expansion width as monitoring areas with the areas between the buildings, wherein the monitoring areas and the heights of the buildings form building dominant data.

Preferably, the total depth of the monitored soil of a plurality of monitoring points preset in the monitoring area is counted, and attribute data of different soils are obtained from top to bottom according to the total depth of the monitored soil, wherein the attribute data comprise the type, the humidity and the sub-depth of the soil.

In order to solve the problem, the invention also provides a building settlement long-term monitoring method based on the Internet of things, which comprises the following steps:

collecting target information of a building to be monitored and geographic information of the building;

extracting and marking the characteristics of the target information and the geographic information, and integrating and evaluating each preprocessed data in a preset reference evaluation time period to obtain the change degree of the building settlement;

analyzing the degree of change, implementing different tracking schemes according to the analysis result, adaptively adjusting the preset reference evaluation time period, and performing simultaneous acquisition on different analysis results to obtain the threat degree;

and early warning and prompting are carried out on the settlement condition of the building based on the threat degree and the corresponding threat label.

Compared with the prior art, the invention has the following beneficial effects:

the invention carries out long-term monitoring on the geographical soil state by simultaneously integrating the data of the building and the geographical data, analyzes and evaluates the settlement of the building based on the change in the geographical aspect, and can self-adaptively adjust the duration of the evaluation time period according to the analysis result, thereby realizing the intelligent operation of long-term monitoring of the settlement of the building; in addition, the influence of the building settlement is evaluated by combining the number of times of occurrence of different abnormal states and corresponding duration obtained by monitoring with corresponding weights, and the overall effect of long-term monitoring of the building settlement can be effectively improved by integrating various data in different aspects.

Drawings

The invention will be further described with reference to the accompanying drawings.

Fig. 1 is a block diagram of a long-term monitoring system for building settlement based on the internet of things.

Fig. 2 is a schematic flow diagram of the long-term monitoring method for building settlement based on the internet of things.

Fig. 3 is a schematic structural diagram of a computer device implementing an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example one

As shown in fig. 1, the invention relates to a long-term monitoring system for building settlement based on the internet of things, which comprises a table construction module, a sample collection module, a geographical evaluation module and an analysis prompt module;

the table building module is used for building a building type-weight table and a soil type-weight table in advance; the building type-weight table is composed of a plurality of different building types and corresponding building weights thereof, and the different building types are preset with one corresponding building weight; the construction mode of the soil type-weight table is the same as that of the building type-weight table; the purpose of setting the weight is to enable different types of text data to be represented in a digital and differential mode, so that more comprehensive monitoring can be conducted;

the system comprises a sample acquisition module, a monitoring module and a monitoring module, wherein the sample acquisition module is used for acquiring target information of a building to be monitored and geographic information of the building; the target information comprises building recessive data and building dominant data; the geographic information comprises attribute data; the method comprises the following specific steps:

monitoring and counting the geographic information of the building and the surroundings respectively based on the equipment of the Internet of things;

counting the building type and the building quality of a building to be monitored to obtain building implicit data; building types include, but are not limited to, civilian types, commercial types, and scientific types; building quality can be obtained based on the quality of all building materials during construction;

counting the length, width and height of a building to be monitored, and expanding the length and width of the building according to a preset expansion distance to obtain an expanded length and an expanded width; the measurement can be carried out by a theodolite; the preset expansion distance can be set according to specific scenes and building types;

setting the expansion length, the expansion width and the area between the buildings as monitoring areas, wherein the monitoring areas and the height form building dominant data;

counting the total depth of monitored soil of a plurality of monitoring points preset in a monitoring area, and acquiring attribute data of different soils from top to bottom according to the total depth of the monitored soil, wherein the attribute data comprises the type, humidity and sub-depth of the soil; the partial depth refers to the depth corresponding to each type of soil.

In the embodiment of the invention, information monitoring is carried out on the building to be monitored and the geography of the building based on the equipment of the Internet of things, and reliable data support can be provided for long-term monitoring, early warning and regulation and control of building settlement by integrating and connecting information in different aspects.

The geographic evaluation module is used for extracting and marking the characteristics of the target information and the geographic information, and integrating and evaluating various preprocessed data in a preset reference evaluation time period to obtain the degree of change of the building settlement;

the method for extracting and marking the characteristics of the target information and the geographic information comprises the following steps:

matching the building type in the building recessive data with a pre-constructed building type-weight table to obtain a corresponding building weight and marking the building weight as J1; marking the building quality in the building implicit data as J2;

obtaining the building volume according to the length, the width and the building height in the building dominant data and marking the building volume as J3; arranging and combining various marked data to obtain first marked data;

marking the total number of different types of soil as S0; matching the soil type in the attribute data with a pre-constructed soil type-weight table to obtain a corresponding soil weight and marking the soil weight as S1; marking the humidity and the partial depth of each type of soil in the attribute data as S2 and S3 respectively; and arranging and combining the marked data to obtain second marked data.

In the embodiment of the invention, various data are standardized for calculation by carrying out digital processing and marking on different types of data, so that the accuracy of data calculation and analysis can be improved.

In addition, the step of acquiring the degree of change of the building settlement comprises the steps of:

respectively extracting various marked data in the first marked data and the second marked data, performing simultaneous operation, and calculating the change degree BH of the building settlement through a formula; the formula is:

in the formula, j1 and j2 are different preset proportionality coefficients, j1 is more than 0 and less than j2, j1 can be 1.367, and j2 can be 2.685; TRX is the soil coefficient;

wherein, the soil coefficient is calculated by a formula, and the formula is as follows:

in the formula, s1 and s2 are preset different proportionality coefficients, s2 is more than 0 and less than s1, s1 can be 2.767, and s2 can be 1.233; the soil coefficient is a numerical value used for integrally evaluating the bearing capacity of the soil by simultaneously integrating data of all aspects of the soil; under the same other conditions, the smaller the soil humidity is, the larger the obtained soil coefficient is, and the smaller the corresponding change degree is; different types of soil, depth and humidity of the soil are related to bearing capacity of the soil, generally speaking, the larger the water content of the soil is, the softer the soil quality is, the lower the foundation bearing capacity of the soil is, if the water content of the soil is small, the harder the soil quality is, the larger the foundation bearing capacity of the soil is, and the different physical characteristics of the soil directly affect the foundation bearing capacity of the soil;

in the embodiment of the invention, the change degree is a numerical value used for integrally evaluating the soil monitoring state of the building, the soil state of the geography is monitored for a long time by simultaneously integrating the data of the building and the geographic data, and the settlement of the building is analyzed and evaluated based on the change in the geography;

in addition, various preprocessed data are integrated and evaluated in a preset reference evaluation time interval, the unit of the reference evaluation time interval can be second, specifically 60 seconds, namely data processing and calculation analysis are carried out every 60 seconds, the time length of the evaluation time interval can be adjusted in a self-adaptive mode according to the analysis result, and intelligent operation of long-term monitoring of building settlement is achieved;

the analysis prompting module is used for analyzing the change degree, implementing different tracking schemes according to the analysis result, adaptively adjusting the preset reference evaluation time period, and performing early warning prompting on the settlement condition of the building by combining different analysis results;

when the change degree is analyzed, if the change degree BH is less than c1, judging that the soil monitoring state of the monitored building is normal and generating a first monitoring signal;

if the change degree BH belongs to [ c1, c2], judging that the soil monitoring state of the monitored building is moderate abnormal, generating a second monitoring signal, shortening the duration of the reference evaluation period according to the second monitoring signal to obtain a first adjustment evaluation period, and tracking the abnormal state in the scene;

if the change degree BH is more than c2, judging that the soil monitoring state of the monitored building is highly abnormal, generating a third monitoring signal, shortening the duration of the reference evaluation period according to the second monitoring signal to obtain a second adjustment evaluation period, and tracking the abnormal state in the scene; the duration of the second adjusted evaluation period is less than the duration of the first adjusted evaluation period, the duration of the first adjusted evaluation period may be 40 seconds, and the duration of the second adjusted evaluation period may be 20 seconds;

setting a starting time point as a first time stamp in the tracking process, setting a corresponding time point as a second time stamp until the tracked change degree BH < c1, and recovering the adjusted evaluation time period to a reference evaluation time period;

acquiring tracking time difference according to the first time stamp and the second time stamp, and respectively setting the tracking time difference corresponding to the second monitoring signal and the third monitoring signal as a first time difference and a second time difference; the units of the time difference are minutes;

the first monitoring signal, the second monitoring signal, the third monitoring signal, the first time difference and the second time difference form an analysis result.

In the embodiment of the invention, the abnormal states with different degrees are tracked through different adjusted evaluation periods, so that the whole-process monitoring statistics of different abnormal states is realized.

Carry out the antithetical couplet with different analysis results and carry out early warning suggestion to the settlement condition of building, include:

acquiring the total occurrence times of the second monitoring signal and the third monitoring signal and respectively marking as C1 and C2;

the first time difference and the second time difference are marked as C3 and C4, respectively; extracting numerical values of all marked data, combining the numerical values, and calculating by a formula to obtain the threat degree WX; the formula is:

in the formula, w1 and w2 are different preset proportionality coefficients, w1 is more than 0 and less than w2, w1 can be 1.231, and w2 can be 2.468; q1 is a monitoring weight corresponding to a preset second monitoring signal, and Q2 is a monitoring weight corresponding to a preset third monitoring signal; the monitoring weights corresponding to Q1 and Q2 can be set based on the existing building monitoring big data;

matching the threat degree WX with a pre-constructed threat table to obtain a corresponding threat tag, and carrying out self-adaptive early warning prompt according to the obtained threat tag and carrying out processing by dynamic regulation and control personnel;

the threat tag may include a plurality of different levels, where the levels include, but are not limited to, normal, mild anomaly, moderate anomaly, and high anomaly, and the levels correspond to different levels of early warning prompts respectively.

In the embodiment of the invention, the influence of the building settlement is evaluated by combining the occurrence frequency and the corresponding duration of different abnormal states with the corresponding weight, and various data in different aspects are integrated, so that the overall effect of long-term monitoring of the building settlement can be effectively improved, and the defects of a single monitoring scheme and single monitoring data prompt are overcome;

in addition, the formulas involved in the above are all numerical calculations by removing dimensions, and are one formula which is closest to the real situation and obtained by collecting a large amount of data and performing software simulation.

Example two

As shown in fig. 2, a long-term monitoring method for building settlement based on the internet of things includes:

EXAMPLE III

Fig. 3 is a schematic structural diagram of a computer device for implementing a long-term monitoring system for building settlement based on the internet of things according to an embodiment of the present invention.

The computer device may include a processor, a memory, and a bus, and may further include a computer program stored in the memory and executable on the processor, such as an internet of things-based building settlement long-term monitoring program.

The memory includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, and the like. The memory may in some embodiments be an internal storage unit of the computer device, for example a removable hard disk of the computer device. The memory may also be an external storage device of the computer device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer device. Further, the memory may also include both internal storage units and external storage devices of the computer device. The memory can be used for storing application software installed on the computer equipment and various data, such as codes of a building settlement long-term monitoring program based on the internet of things, and the like, and can also be used for temporarily storing data which is output or is to be output.

A processor may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor is a Control Unjt of the computer device, connects various components of the whole computer device by using various interfaces and lines, executes or executes a program or a module (such as a building settlement long-term monitoring program based on the internet of things, and the like) stored in the memory, and calls data stored in the memory to execute various functions of the computer device and process the data.

The bus may be a peripheral component interconnect (PCj) bus, an extended industry standard architecture (EjSA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connected communication between the memory and the at least one processor or the like.

Fig. 3 shows only a computer device having components, and those skilled in the art will appreciate that the configuration shown in fig. 3 does not constitute a limitation of the computer device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.

For example, although not shown, the computer device may further include a power supply (such as a battery) for supplying power to the various components, and preferably, the power supply may be logically connected to the at least one processor through a power management device, so that functions such as charge management, discharge management, and power consumption management are implemented through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The computer device may further include various sensors, a bluetooth module, a Wi-Fi module, etc., which are not described herein again.

The computer device may also include a network interface, which may optionally include a wired interface and/or a wireless interface (e.g., a Wi-Fi interface, a bluetooth interface, etc.), typically used to establish a communication connection between the computer device and other computer devices.

The computer device may further comprise a user interface, which may be a display (djsplash), an input unit, such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the computer device and for displaying a visualized user interface.

It is to be understood that the embodiments are illustrative only and that the scope of the appended claims is not limited to the details of construction set forth herein.

An internet of things based building settlement long-term monitoring program stored in memory in a computer device is a combination of instructions.

The specific implementation method of the instruction by the processor may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 to fig. 2, which is not described herein again.

The computer device integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or nonvolatile. For example, the computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM).

The invention also provides a computer-readable storage medium having stored thereon a computer program for execution by a processor of a computer device.

In the several embodiments provided in the present invention, it should be understood that the disclosed method or system may be implemented in other manners. For example, the above-described embodiments of the invention are merely illustrative, and for example, a module may be divided into only one logic function, and another division may be implemented in practice.

Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.

Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A long-term monitoring system for building settlement based on the Internet of things is characterized by comprising:

the analysis prompt module is used for analyzing the change degree; the method comprises the following steps: if the change degree BH belongs to [ c1, c2], judging that the soil monitoring state of the monitored building is moderate and abnormal, generating a second monitoring signal, shortening the time length of the reference evaluation time period according to the second monitoring signal to obtain a first adjustment evaluation time period, and tracking the abnormal state in the scene;

if the change degree BH is larger than c2, judging that the soil monitoring state of the monitored building is highly abnormal, generating a third monitoring signal, shortening the duration of the reference evaluation period according to the second monitoring signal to obtain a second adjustment evaluation period, and tracking the abnormal state in the scene;

2. The internet of things-based long-term building settlement monitoring system as claimed in claim 1, wherein the feature extraction and labeling of target information and geographic information comprises:

3. The internet of things-based building settlement long-term monitoring system as claimed in claim 2, wherein the total number of different types of soil is marked as S0; matching the soil type in the attribute data with a pre-constructed soil type-weight table to obtain a corresponding soil weight, and marking the soil weight as S1; marking the humidity and the component depth of each type of soil in the attribute data as S2 and S3 respectively; and arranging and combining the marked data to obtain second marked data.

4. The building settlement long-term monitoring system based on the Internet of things of claim 1, wherein the degree of change BH of the building settlement is obtained through formula calculation; the formula is:

5. The Internet of things-based building settlement long-term monitoring system as claimed in claim 4, wherein the soil coefficient is calculated by a formula:

6. The long-term monitoring system for building settlement based on the internet of things as claimed in claim 1, wherein the early warning prompt for the settlement condition of the building by associating different analysis results comprises:

acquiring the total occurrence times of the second monitoring signal and the third monitoring signal and respectively marking as C1 and C2; the first time difference and the second time difference are marked as C3 and C4, respectively; extracting the numerical values of all marked data and obtaining the threat degree WX in a simultaneous manner;

7. The long-term monitoring system for building settlement based on the internet of things as claimed in claim 1, wherein the threat degree WX is obtained by formula calculation; the formula is:

8. The long-term monitoring system for building settlement based on the internet of things as claimed in claim 1, wherein the monitoring statistics are performed on the geographical information of the building and the surrounding based on the internet of things equipment; counting the building type and the building quality of a building to be monitored to obtain building recessive data;

9. The building settlement long-term monitoring system based on the internet of things as claimed in claim 8, wherein the total depth of monitored soil of a plurality of monitoring points preset in a monitoring area is counted, and attribute data of different soils are obtained from top to bottom according to the total depth of the monitored soil, wherein the attribute data comprise the type, humidity and sub-depth of the soil.

10. A building settlement long-term monitoring method based on the Internet of things is characterized by comprising the following steps:

analyzing the degree of change, carrying out different tracking schemes according to the analysis result, adaptively adjusting the preset reference evaluation time period, and carrying out simultaneous operation on different analysis results to obtain the threat degree;