Intelligent building condition monitoring management system based on cloud computing and multi-dimensional data

Abstract

The present invention discloses an intelligent building status monitoring and management system based on cloud computing and multi-dimensional data, which belongs to the technical field of intelligent building status monitoring and management, and comprises a monitoring module, a supporting evaluation module, an opinion feedback module and a personalized management module; the monitoring module is used for real-time monitoring of intelligent buildings, obtaining monitoring data corresponding to each monitoring item, and displaying the monitoring data in real time in a preset building monitoring model; the opinion feedback module receives feedback data uploaded by residents, and stores the feedback data in a corresponding storage node; and based on the feedback data stored in the storage node, generates a resident opinion portrait corresponding to the resident according to a preset portrait template; the supporting evaluation module evaluates each supporting equipment, divides the building monitoring model into regions, and forms a plurality of unit management regions; sets a target management standard corresponding to each unit management region; and the personalized management module is used for personalized management of each unit management region.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent building status monitoring and management, and in particular to an intelligent building status monitoring and management system based on cloud computing and multi-dimensional data. Background Art

[0002] With the demand for efficiency, safety and sustainability of buildings in modern society, as well as the acceleration of urbanization and population growth, the number and scale of buildings are increasing, which puts higher requirements on the management and maintenance of buildings. Traditional building management methods often rely on manual inspections and manual operations, which are inefficient and prone to omissions. The emergence of intelligent building status monitoring and management systems, using advanced technologies such as the Internet of Things, big data and artificial intelligence, can monitor the various states of buildings in real time, provide data analysis and intelligent control, thereby improving the operating efficiency, safety and sustainability of buildings. In addition, with the increasing prominence of energy crises and environmental issues, energy conservation and emission reduction have become the focus of global attention. Intelligent building status monitoring and management systems can provide energy-saving suggestions and control strategies through real-time monitoring and optimization of building energy consumption, help buildings achieve efficient use of energy and reduce the impact on the environment. Therefore, the emergence of intelligent building status monitoring and management systems meets the needs of modern society for building efficiency, safety and sustainability, improves the management level and operating efficiency of buildings, and provides users with a more comfortable, safe and energy-saving building environment.

[0003] However, the existing intelligent building status monitoring and management system still has the following problems:

[0004] 1. Lack of supporting evaluation. The intelligent building status monitoring and management system needs to be integrated with various devices and systems, including sensors, control equipment, security systems, etc. If the technical compatibility between these devices and systems is not good, the stability and reliability of the system may be affected; and many current intelligent building status monitoring and management systems ignore this problem. Even if some users have discovered this phenomenon, the general method is to manually check and verify by the corresponding technicians during the installation of the intelligent building status monitoring and management system, which is inefficient and prone to omissions.

[0005] 2. Lack of personalized management. With the improvement of people's living standards, people's requirements for quality of life are getting higher and higher. The current intelligent building status monitoring and management system's unified management of the building makes certain aspects of monitoring and management unable to meet the requirements of some residents, which does not conform to the concept of fully serving residents. It is difficult to carry out personalized management of each resident by relying solely on manual experience and a small amount of feedback from residents. In particular, many residents are unwilling to spend more time to provide feedback to management personnel. Summary of the invention

[0006] In order to solve the problems existing in the above solutions, the present invention provides an intelligent building status monitoring and management system based on cloud computing and multi-dimensional data.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] Intelligent building status monitoring and management system based on cloud computing and multi-dimensional data, including monitoring module, supporting evaluation module, feedback module and personalized management module;

[0009] The monitoring module is used to monitor the intelligent building in real time, obtain the monitoring data corresponding to each monitoring item, and display the obtained monitoring data in real time in a preset building monitoring model. The building monitoring model is provided with display nodes corresponding to each monitoring item, and the display nodes are used to display the collected data of the corresponding collection equipment.

[0010] The opinion feedback module is used by each resident in the intelligent building, and receives feedback data uploaded by the resident, and stores the obtained feedback data in the corresponding storage node; and based on the feedback data stored in the storage node, generates a resident opinion portrait corresponding to the resident according to a preset portrait template; obtains resident information, and stores the resident information and the resident opinion portrait in the storage node; processes the feedback data stored in the storage node, obtains corresponding verification and adjustment feedback data and manual feedback data, and sends the obtained manual feedback data to the corresponding management personnel.

[0011] Furthermore, the method for processing the feedback data stored in the storage node includes:

[0012] Preset each feedback type, identify the feedback data stored in the storage node according to each feedback type, and obtain feedback type data corresponding to each feedback type; integrate each feedback type data to form verification and adjustment feedback data; integrate each feedback data that does not belong to each feedback type into manual feedback data.

[0013] The supporting evaluation module is used to evaluate each supporting device, and the evaluation process is as follows:

[0014] Identify the building monitoring model, divide the area according to the building monitoring model, and form a plurality of unit management areas; mark each of the obtained unit management areas in the building monitoring model accordingly;

[0015] Set the assessment adjustment standards corresponding to each unit management area, obtain the historical monitoring data corresponding to each unit management area, analyze whether the historical monitoring data can meet the corresponding assessment adjustment standards, and identify the corresponding adjustment items; send the obtained adjustment items to the corresponding management personnel, and the management personnel make corresponding supporting adjustment decisions, and adjust the assessment adjustment standards accordingly according to the adjustment decisions, so as to obtain the target management standards corresponding to each unit management area.

[0016] Furthermore, the method for dividing the area according to the building monitoring model includes:

[0017] Step SA1: identifying each unit area in the building monitoring model, and marking each unit area accordingly in the building monitoring model;

[0018] Identify each supporting device according to the preset list table, and obtain the functional range corresponding to each supporting device; mark each supporting device and the corresponding functional range in the building monitoring model accordingly;

[0019] Step SA2: identifying each supporting device whose functional range is not smaller than the unit area and marking them as reference devices; marking the functional range corresponding to the reference device as the reference range;

[0020] Step SA3: marking a reference unit in the unit area, and identifying each reference device whose reference range includes the reference unit;

[0021] When there is no reference device including the reference unit, proceed to step SA5;

[0022] When there is a reference device including the reference unit, the reference device is marked as a standard device, and the reference unit is merged with the next-level unit area to form a new reference unit; go to step SA4; if there is no next-level unit area, go to step SA5;

[0023] Step SA4: Identify whether the reference range of each target device includes the reference unit;

[0024] When the reference unit is not included, proceed to step SA5;

[0025] When the reference unit is included, the reference unit is merged with the next-level unit area to form a new reference unit. If there is no next-level unit area, step SA5 is entered; step SA4 is looped until each of the target devices does not include the reference unit;

[0026] Step SA5: treat the reference unit as a unit management area;

[0027] Step SA6: Return to step SA3 until there is no cell area.

[0028] Further, the method for setting the assessment adjustment standard of the unit management area includes:

[0029] Identify the residents corresponding to each of the unit management areas, connect to the corresponding storage node according to the identified resident information, and identify the corresponding verification and adjustment feedback data in the storage node; analyze the obtained verification and adjustment feedback data to obtain the evaluation and adjustment standards corresponding to each of the unit management areas.

[0030] Furthermore, the method for analyzing the obtained calibration adjustment feedback data includes:

[0031] Identify feedback classification data corresponding to each household in the unit management area according to the verified and adjusted feedback data, identify feedback needs of the household according to the feedback classification data, screen the feedback needs, and obtain corresponding target needs;

[0032] The target demand is divided into similar demand and individual demand, households corresponding to the similar demand are identified and marked as target households, and the target households are marked as i, i=1, 2, ..., n, and n is the number of target households; the demand value corresponding to the similar demand is marked as TSi;

[0033] Obtaining household opinion portraits of the target households, identifying the number of historical feedbacks and the demand proportion corresponding to the same type of demand of each target household according to the household opinion portraits, and marking the number of historical feedbacks and the demand proportion as Ci·freq and Xi·weight, respectively;

[0034] According to the standard adjustment formula Calculate the standard demand value corresponding to the same type of demand, where: T par is the standard demand value; Y par is the original standard demand value;

[0035] Identify the demand value corresponding to each individual demand, marked as TS, then the standard demand value T·par=Y·par+TS;

[0036] The obtained standard requirement values ​​are sorted out to form evaluation and adjustment standards.

[0037] Furthermore, methods for screening feedback requirements include:

[0038] Summarize the feedback needs of each household, simulate various feedback needs, form simulated needs, and establish a corresponding judgment model based on the simulated needs. The expression of the judgment model is: Where x represents the corresponding feedback demand, and A represents the abnormal demand; the input of the judgment model is the feedback demand, and the output is the judgment result y, y=G(x); each feedback demand is analyzed by the judgment model to obtain the judgment result corresponding to each feedback demand, and the feedback demand with the judgment result y=0 is marked as the target demand.

[0039] The personalized management module is used to perform personalized management on each of the unit management areas, connect to the building monitoring model, and identify the monitoring data of each of the unit management areas in the building monitoring model in real time; obtain the target management standard of each of the unit management areas, and dynamically manage the corresponding equipment of the unit management area according to the target management standard and the monitoring data.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] Through the cooperation among the monitoring module, supporting evaluation module, feedback module and personalized management module, the intelligent management of intelligent buildings is realized, and personalized services are provided to each resident in the intelligent building to improve the management quality. By setting up the feedback module, it is convenient for each householder to upload relevant opinions and suggestions at any time, avoiding the unwillingness of each resident to give feedback due to the need to spend a lot of time, resulting in the lack of sufficient feedback data and the inability to better serve each resident, and providing data support for the subsequent supporting evaluation module and personalized management module. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0044] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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.

[0045] like Figure 1 As shown, the intelligent building status monitoring and management system based on cloud computing and multi-dimensional data includes a monitoring module, a supporting evaluation module, an opinion feedback module and a personality management module;

[0046] The monitoring module is used to utilize the various functions in the existing intelligent building status monitoring and management system for monitoring, such as temperature, humidity, various energy consumption, light, etc., and utilize the original sensor collection equipment for monitoring to achieve real-time acquisition of monitoring data corresponding to each monitoring item; establish a three-dimensional building model corresponding to the intelligent building according to existing drawings such as the architectural drawing and construction drawing of the intelligent building, and set corresponding display nodes at corresponding positions in the three-dimensional building model according to the collection equipment positions and data display requirements corresponding to each monitoring item, display the collection data of each sensor through each display node, and mark the current three-dimensional building model as a building monitoring model; the monitoring data corresponding to a monitoring item includes the collection data of each collection equipment corresponding to the monitoring item.

[0047] The feedback module is used by each resident in the intelligent building. Through the feedback module, the resident can upload his opinions and suggestions on his location in the intelligent building at any time to form the feedback data of the resident, and store it in the storage node corresponding to the resident. Each storage node stores the resident information corresponding to the resident and the resident opinion portrait; the resident information includes data such as household number and address; the resident opinion portrait is a resident portrait generated according to the feedback data of the resident in the storage node, which can be set using the existing portrait generation technology to quickly count the feedback type, proportion, feedback time distribution and other related data of the resident. The corresponding portrait template can be preset to generate the resident opinion portrait according to the corresponding data.

[0048] Preset various feedback types. Feedback types refer to types that can be used for subsequent verification and adjustment, such as feedback on incomplete monitoring data, temperature adjustment feedback, humidity adjustment feedback and other feedback types. The specific feedback types need to be set according to actual monitoring needs; identify the feedback data stored in the storage node according to each feedback type, and obtain the feedback type data corresponding to each feedback type; integrate the data of each feedback type to form the verification and adjustment feedback data of the resident; integrate the feedback data that does not belong to each feedback type into manual feedback data, that is, the residents upload other feedback opinions, which are not within the scope of analysis and need to be manually processed by the staff; send the obtained manual feedback data to the corresponding management personnel.

[0049] By setting up an opinion feedback module, each householder can upload relevant opinions and suggestions at any time, avoiding the residents' reluctance to provide feedback due to the need to spend a lot of time, resulting in a lack of sufficient feedback data and the inability to provide better services to the residents, and providing data support for subsequent supporting evaluation modules and personalized management modules.

[0050] The supporting evaluation module is used to evaluate each supporting device, and the evaluation process is as follows:

[0051] Identify the building monitoring model, obtain the location of each resident in the building monitoring model, the location of each supporting equipment, and the processing range to divide the area to form several unit management areas; mark the obtained unit management areas accordingly in the building monitoring model;

[0052] Identify the residents corresponding to each unit management area, connect to the corresponding storage node according to the identified resident information, and identify the corresponding verification and adjustment feedback data in the storage node; analyze the obtained verification and adjustment feedback data to obtain the evaluation and adjustment standards corresponding to each unit management area;

[0053] Obtain the historical monitoring data corresponding to each unit management area, analyze whether the historical monitoring data can meet the corresponding assessment adjustment standards, and identify the corresponding adjustment items, such as missing items, items that cannot be adjusted, etc.; send the obtained adjustment items to the corresponding management personnel, and the management personnel will make corresponding supporting adjustment decisions, such as deciding whether to adjust the adjustment item, how to adjust it, and other related decisions;

[0054] And based on the adjustment decision, the evaluation adjustment standards will be adjusted accordingly to obtain the target management standards corresponding to each unit management area; if the adjustment items have not been adjusted, they will still be managed according to the original management standards, and if the adjustment items are adjusted, the original management standards will be adjusted according to their evaluation adjustment standards. After all are completed, the target management standards for the unit management area will be formed.

[0055] Methods for analyzing the obtained calibration adjustment feedback data include:

[0056] According to the feedback data of the verification adjustment unit, the feedback classification data corresponding to each household in the management area is identified, and the feedback needs of the residents are identified according to the feedback classification data, such as temperature needs, humidity needs, lighting needs, monitoring type adjustment needs, etc.; the existing data recognition and analysis technology is used to perform recognition and analysis to determine the feedback needs corresponding to each feedback classification data;

[0057] Summarize the feedback needs of each household, simulate various possible feedback needs, form simulated needs, and establish a corresponding judgment model based on the simulated needs. The expression of the judgment model is:

[0058] Where x represents the corresponding feedback demand, A represents the abnormal demand, that is, the feedback demand does not meet the requirements. It is trained and established using a large number of simulated demands. The input of the judgment model is the feedback demand, and the output is the judgment result y, y=G(x). Each feedback demand is analyzed through the judgment model to obtain the judgment result corresponding to each feedback demand, and the feedback demand with the judgment result y=0 is marked as the target demand.

[0059] The target demands are divided into similar demands and individual demands. Similar demands are the target demands of different households corresponding to the same feedback type, and individual demands are the target demands proposed by only one household.

[0060] Identify the households corresponding to the same type of needs and mark them as target households. The target households are marked as i, where i=1, 2, ..., n, and n is the number of target households. The demand values ​​corresponding to the same type of needs are marked as TSi, such as the temperature adjustment change, humidity adjustment change, and light intensity adjustment change (such as adjusting by 10%). Each type of feedback is set with a corresponding numerical method. Most of the needs are direct numerical values ​​and can be directly applied. For some needs that cannot obtain numerical values, the corresponding conversion relationship can be preset for conversion, such as conversion according to different adjustment degrees, the percentage of decrease or increase.

[0061] Obtain the household opinion portrait of each target household, identify the number of historical feedbacks corresponding to the same type of demand and the proportion of historical feedbacks of each target household in all types of historical feedbacks according to the household opinion portrait, mark them as demand proportion, and mark the obtained historical feedback number and demand proportion as Ci·freq and Xi·weight respectively;

[0062] According to the standard adjustment formula Calculate the standard demand value corresponding to the same type of demand, where: T par is the standard demand value; Y par is the original standard demand value;

[0063] Identify the demand value corresponding to each individual demand, marked as TS, then the standard demand value T·par=Y·par+TS;

[0064] The obtained standard demand values ​​are sorted out and combined with the standard demand values ​​that have no corresponding requirements to form the evaluation adjustment standards.

[0065] Among them, the method of dividing the area according to the building monitoring model includes:

[0066] Step SA1: Identify each unit area in the building monitoring model. The unit area is determined according to the hierarchical layout of the smart building. For example, if the smart building consists of 2 units, each unit is not connected, and each unit has one elevator and two households. Then each unit on each floor has a unit area, that is, the area corresponding to one elevator and two households is a unit area. The first floor of the smart building has 2 unit areas; if there is one unit, and the residents on the first floor can be connected through the public area, then the first floor is a unit area; the above two situations or similar situations are generally common. Corresponding unit area identification rules are formulated, and identification is performed according to the unit area identification rules to determine the unit areas.

[0067] Mark the unit area in the building monitoring model accordingly, identify the supporting equipment, such as various acquisition equipment, control equipment, etc., and identify them according to the preset list. Some equipment that does not need to be analyzed or does not participate in the analysis are not included in the list. The main focus is on the equipment that adjusts and monitors each floor, such as the air conditioning control equipment on each floor, and the alarm equipment on several floors.

[0068] Obtain the responsible scope of each supporting equipment, that is, the collection scope of the collection equipment and the control scope of the control equipment, such as which floors the air conditioner is used to control the temperature; mark the functional scope of the obtained responsible scope; mark each supporting equipment and the corresponding functional scope in the building monitoring model;

[0069] Step SA2: Identify each supporting device whose functional range is not smaller than the unit area and mark it as a reference device; mark the functional range corresponding to the reference device as the reference range;

[0070] Mark the base unit in the unit area. The base unit is generally the unit area corresponding to the bottom floor of the smart building. You can also select the unit area corresponding to the top floor as the base unit.

[0071] Step SA3: Identify each reference device whose reference range includes the reference unit; this means that the reference range completely covers the reference unit, and if it is a merged and updated reference unit, the new reference unit is covered;

[0072] When there is no reference device including the reference unit, proceed to step SA5;

[0073] When there is a reference device including a reference unit, the corresponding reference device is marked as a standard device, and the reference unit is merged with the next-level unit area to form a new reference unit; enter step SA4; the next-level unit area is performed according to the floor, such as a building unit is sorted from bottom to top, the initial reference unit is the unit area of ​​the bottom floor, then the next-level unit area of ​​the reference unit is the unit area of ​​the upper floor (second floor) of the building unit; when marking the unit area and the reference unit, the corresponding unit area sequence table can be set synchronously;

[0074] Step SA4: Identify whether the reference range of each target device includes the reference unit;

[0075] When the reference cell is not included, proceed to step SA5;

[0076] When the reference unit is included, the reference unit is merged with the next level unit area to form a new reference unit; and the reference range of each target device is continuously determined to determine whether it includes the reference unit until each target device does not include the reference unit.

[0077] Step SA5: Treat the reference cell as a cell management area.

[0078] Step SA6: Return to step SA3 until there is no cell area.

[0079] If there is no next-level unit area, go directly to step SA5.

[0080] The personalized management module is used to perform personalized management of each unit management area, connect to the building monitoring model, and identify the monitoring data of each unit management area in the building monitoring model in real time; obtain the target management standards of each unit management area, and dynamically manage the corresponding equipment of the unit management area according to the obtained target management standards and corresponding monitoring data.

[0081] Through the mutual cooperation among the monitoring module, supporting evaluation module, feedback module and personalized management module, intelligent management of smart buildings can be realized, and personalized services can be provided to each resident in the smart building to improve the management quality.

[0082] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0083] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Intelligent building status monitoring and management system based on cloud computing and multi-dimensional data, characterized by: It includes monitoring module, supporting evaluation module, feedback module and personality management module; The monitoring module is used to monitor the intelligent building in real time, obtain monitoring data corresponding to each monitoring item, and display the monitoring data in real time in a preset building monitoring model; The feedback module is used by each resident in the smart building, receives feedback data uploaded by the resident, and stores the feedback data in a corresponding storage node; and based on the feedback data stored in the storage node, generates a resident opinion portrait corresponding to the resident according to a preset portrait template; Acquire resident information, and store the resident information and the resident opinion portrait in the storage node; Processing the feedback data stored in the storage node to obtain corresponding verification and adjustment feedback data and manual feedback data, and sending the manual feedback data to corresponding management personnel; The supporting evaluation module is used to evaluate each supporting equipment, identify the building monitoring model, divide the area according to the building monitoring model, and form a number of unit management areas; each of the obtained unit management areas is marked accordingly in the building monitoring model; Set the evaluation adjustment standard corresponding to each unit management area, obtain the historical monitoring data corresponding to each unit management area, analyze whether the historical monitoring data can meet the corresponding evaluation adjustment standard, and identify the corresponding adjustment items; send the obtained adjustment items to the corresponding management personnel, and the management personnel make corresponding matching adjustment decisions, and adjust the evaluation adjustment standard accordingly according to the adjustment decision, so as to obtain the target management standard corresponding to each unit management area; The personalized management module is used to perform personalized management on each of the unit management areas, connect to the building monitoring model, and identify the monitoring data of each of the unit management areas in the building monitoring model in real time; obtain the target management standard of each of the unit management areas, and dynamically manage the corresponding equipment of the unit management area according to the target management standard and the monitoring data; The method for processing the feedback data stored in the storage node in the feedback module includes: Preset various feedback types, identify the feedback data stored in the storage node according to the various feedback types, and obtain feedback type data corresponding to the various feedback types; integrate the various feedback type data to form verification and adjustment feedback data; integrate the various feedback data that do not belong to the various feedback types into manual feedback data; The methods for regional division based on the building monitoring model in the supporting assessment module include: Step SA1: identifying each unit area in the building monitoring model, and marking each unit area accordingly in the building monitoring model; Identify each supporting device according to the preset list table, and obtain the functional range corresponding to each supporting device; mark each supporting device and the corresponding functional range in the building monitoring model accordingly; Step SA2: identifying each supporting device whose functional range is not smaller than the unit area and marking them as reference devices; marking the functional range corresponding to the reference device as the reference range; Step SA3: marking a reference unit in the unit area, and identifying each reference device whose reference range includes the reference unit; When there is no reference device including the reference unit, proceed to step SA5; When there is a reference device including the reference unit, the reference device is marked as a standard device, and the reference unit is merged with the next-level unit area to form a new reference unit; go to step SA4; if there is no next-level unit area, go to step SA5; Step SA4: Identify whether the reference range of each target device includes the reference unit; When the reference unit is not included, proceed to step SA5; When the reference unit is included, the reference unit is merged with the next-level unit area to form a new reference unit. If there is no next-level unit area, step SA5 is entered; step SA4 is looped until each of the target devices does not include the reference unit; Step SA5: treat the reference unit as a unit management area; Step SA6: Return to step SA3 until there is no cell area; Methods for setting assessment adjustment criteria for unit management areas include: Identify the residents corresponding to each of the unit management areas, connect to the corresponding storage node according to the identified resident information, and identify the corresponding verification adjustment feedback data in the storage node; analyze the obtained verification adjustment feedback data to obtain the evaluation adjustment standard corresponding to each of the unit management areas; Methods for analyzing the obtained calibration adjustment feedback data include: Identify feedback classification data corresponding to each household in the unit management area according to the verified and adjusted feedback data, identify feedback needs of the household according to the feedback classification data, screen the feedback needs, and obtain corresponding target needs; The target demand is divided into similar demand and individual demand, households corresponding to the similar demand are identified and marked as target households, and the target households are marked as i, i=1, 2, ..., n, and n is the number of target households; the demand value corresponding to the similar demand is marked as TSi; Obtaining household opinion portraits of the target households, identifying the number of historical feedbacks and the demand proportion corresponding to the same type of demand of each target household according to the household opinion portraits, and marking the number of historical feedbacks and the demand proportion as Ci·freq and Xi·weight, respectively; According to the standard adjustment formula Calculate the standard demand value corresponding to the same type of demand, where: T par is the standard demand value; Y par is the original standard demand value; Identify the demand value corresponding to each individual demand, marked as TS, then the standard demand value T·par=Y·par+TS; Arrange the obtained standard requirement values ​​to form evaluation and adjustment standards; Methods for screening feedback needs include: Summarize the feedback needs of each household, simulate various feedback needs, form simulated needs, and establish a corresponding judgment model based on the simulated needs. The expression of the judgment model is: , where x represents the corresponding feedback demand, and A represents the abnormal demand; the input of the judgment model is the feedback demand, and the output is the judgment result y, y=G(x); the judgment model is used to analyze each feedback demand, obtain the judgment result corresponding to each feedback demand, and mark the feedback demand with the judgment result y=0 as the target demand; The building monitoring model is provided with display nodes corresponding to the monitoring items, and the display nodes are used to display the collected data of the corresponding collection equipment; The preset directory table summarizes various supporting equipment information that needs to be analyzed.

Images