Intelligent building management analysis system based on AI large model

Abstract

The invention discloses an intelligent building management analysis system based on an AI large model, and relates to the technical field of management analysis systems.The intelligent building management analysis system comprises a statistics module, an analysis module, a link module and a function module, the statistics module is used for collecting virtual information, space information and user information in an intelligent building; the link module is used for performing interface API adjustment and data transmission path regulation and control on the management analysis system of the intelligent building; the function module is used by a user for direct application of the intelligent equipment and overall management of the management analysis system; according to the intelligent building management analysis system, seamless mutual linkage and data transmission between the intelligent building management analysis system and other different AI large models can be achieved through the conversion interface, a user can select the needed AI model to operate and use all intelligent devices in the intelligent building where the user is located, and multiple requirements of modern city development are met.

Description

Technical Field

[0001] The present invention relates to the technical field of management and analysis systems, and in particular to an intelligent building management and analysis system based on an AI big model. Background Art

[0002] With the acceleration of urbanization, the construction industry is facing increasingly complex electromechanical systems and equipment installation needs, including building electromechanical, industrial installation, municipal electromechanical pipelines and equipment installation. The main equipment involved includes fans, pumps, electrical pipelines and intelligent equipment. The efficient operation of these systems is not only related to the energy efficiency and environmental comfort of the building, but also directly affects safety and sustainable development. The electromechanical installation engineering technology among the ten new technologies in the construction industry came into being, aiming to improve the installation and operation and maintenance efficiency of electromechanical equipment through advanced management methods and technologies. These new technologies emphasize the combination of informatization, intelligence and automation, and promote the transformation of traditional building management models. The rapid development of electromechanical installation technology has made energy management, environmental monitoring and control of buildings more efficient. However, traditional management models often rely on manual experience and paper records, resulting in problems such as delayed information transmission and untimely data processing. These problems not only increase management costs, but also affect the normal operation and maintenance efficiency of equipment. The demand for intelligent management in modern buildings is constantly increasing, which is mainly reflected in the ability of real-time monitoring and management, data analysis and decision support, system integration and interconnection. The application of AI big models in intelligent building management and analysis systems will bring new solutions to the management of mechanical and electrical equipment. Through deep learning and data mining technology, it can realize the functions of predictive maintenance, intelligent scheduling and environmental monitoring and optimization.

[0003] At present, in the Chinese invention patent with publication number CN116187701B, an intelligent building monitoring and management system based on multidimensional data and data analysis is disclosed. By performing data statistics and preprocessing from the basic aspects and operation aspects of the building itself, data support of different dimensions is provided for subsequent intelligent building monitoring and management, which effectively improves the diversity and comprehensiveness of the monitoring data. The fault conditions occurring on different floors of the building are analyzed and classified through fault factors, and the operation status of different floors of the building is obtained efficiently and comprehensively, realizing modular monitoring and analysis of the building, which can provide reliable data support for the dynamic management of different floors in the subsequent building. However, the existing technology cannot make the intelligent building management and analysis system seamlessly link and transmit data with other different AI models, and users cannot choose the AI ​​model they need to operate and use. It is impossible to significantly improve the energy efficiency and management level of the building by integrating data-driven decision-making mechanisms, and it cannot provide strong support for achieving the goal of sustainable development. Summary of the invention

[0004] The technical problem solved by the present invention is that the existing technology cannot enable the intelligent building management and analysis system to seamlessly link and transmit data with other different AI large models. Users cannot select the AI ​​model they need to operate and use all the intelligent devices in the intelligent building in their location. It is impossible to significantly improve the energy efficiency and management level of the building by integrating data-driven decision-making mechanisms, and cannot provide strong support for achieving the goal of sustainable development.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent building management and analysis system based on an AI big model, comprising a statistical module, a link module and a functional module:

[0006] The statistical module is used to collect virtual information, space information and user information inside the intelligent building;

[0007] The link module is used to adjust the interface API and regulate the data transmission path of the management and analysis system of the intelligent building;

[0008] The functional modules are used for the direct application of smart devices by users and the overall management of the management and analysis system.

[0009] Preferably, the statistical module includes a virtual unit, a space unit and a user unit:

[0010] The virtual unit is used for:

[0011] Collecting the working environment, operating status and performance data of the smart devices in the smart building in real time, wherein the smart devices include temperature control devices, lighting devices, security devices and household electrical appliances, the working environment includes environmental parameters of temperature, humidity and air quality, the operating status includes the operating time of the smart devices and the degree of equipment loss, the performance data includes energy consumption data and user satisfaction scores of the smart devices, the energy consumption data is the product of the power consumption value corresponding to a certain time of the smart device and the time difference, and the user satisfaction score is the average score of the users on each smart device in the user interface of the functional module;

[0012] The operating status and performance data are divided into a first recording area, a second recording area, ... and an nth recording area according to physical areas, and each recording area respectively counts the operating status and performance data of the smart devices in the recording area into a virtual database;

[0013] Record the data in the virtual database in a background storage hard disk, schedule the data in the background storage hard disk and delete unnecessary data according to a multi-level feedback queue scheduling algorithm, and input the scheduled data into the upgrade unit in the functional module in sequence to upgrade the management analysis system;

[0014] The data transmission modes in the background storage hard disk are recorded and classified.

[0015] Preferably, the space unit is used for:

[0016] Scan the entire intelligent building, obtain the internal space structure of the intelligent building and the network structure of the intelligent equipment, as well as the information of physical access lines and virtual access lines, and use sensors and monitoring systems to count the personnel usage of each space, and identify the peak usage period and off-peak usage period of each space. The personnel usage is the flow of people entering the space.

[0017] Preferably, the user unit is used for:

[0018] The user's activity data in the space is used to obtain the user's usage habits and preferences for smart devices, and the user's satisfaction evaluation of the smart building environment is collected through the feedback interface of the functional module.

[0019] Preferably, the link module includes an interface unit and a control unit:

[0020] The interface unit is used for:

[0021] A virtual abstract interface is defined at the interface of the information transmission channel of the management and analysis system. The abstract interface includes an adapter for collecting the implementation logic of each different AI model, encapsulating the adapter into a class module corresponding to each AI model, and setting a corresponding switch for each class module. When the management and analysis system needs to link any AI model, the switch corresponding to the AI ​​model is called to obtain the adapter corresponding to the switch, and the required AI model is linked using the adapter as the entry.

[0022] All switches are connected in parallel. When the management and analysis system needs to link multiple AI models at the same time, multiple switches corresponding to the AI ​​models are called, and the management and analysis system sequentially enters the AI ​​models that need to be linked according to the Peterson algorithm;

[0023] The interface of the information transmission channel of the management and analysis system is divided into multiple units including a virtual abstract interface, a data input unit, a data processing unit and a data output unit.

[0024] Preferably, the control unit is used for:

[0025] Identify the MAC address of information input from the interface of the information transmission channel of the management and analysis system, and identify the network format of the information included in the MAC address according to the MAC address, wherein the network format includes a data transmission format, a network protocol and a network layer format, wherein the data transmission format includes JSON, XML and HTML, the network protocol includes HTTP, HTTPS, FTP, TCP and IP, and the network layer format includes an IP address and a MAC address;

[0026] Secondarily encapsulating all the encapsulated information transmitted through the interface includes encapsulating data in a universal format, and performing frequency hopping to adjust the encapsulation signal during the encapsulation process, so as to encrypt all the information in the form of a secure password;

[0027] The interface calls are logged and recorded into a document by time, wherein the document includes the functions, request examples and response formats of all units of the interface.

[0028] Preferably, the control unit is also used for:

[0029] Calling the class module corresponding to the adapter as the underlying coding logic, performing binary conversion on the underlying coding logic, and identifying the underlying coding logic converted into binary according to the machine language recognition logic, counting the underlying logic types of the underlying coding logic, and dividing them into a first logic type type, a second logic type type, ... and an nth logic type type, where n is a constant;

[0030] The common underlying logic is summarized according to all the underlying logic types, and the logic code blocks are written according to the common underlying logic, the classes of the code blocks are adjusted according to the different logic types, and all the classes are encapsulated as code blocks.

[0031] Preferably, the functional module includes a user interface, an upgrade unit and a feedback interface:

[0032] The user interface is used to:

[0033] A main webpage is used to set the smart devices of the smart building as list view marks for user interaction. When the user clicks the list view mark of the corresponding smart device, the user enters the hyperlink stored in the list view mark, and the hyperlink includes the working environment, operation status and performance data of the smart device, and performs command-type remote control on the smart device. The command-type remote control is completed according to the wireless information transmission between the smart device and the user, including:

[0034] The user clicks any command button to send a command signal to the corresponding smart device wirelessly, and the smart device converts the command signal into the corresponding machine language through the link module;

[0035] The main webpage also includes a system conversion button, which is used to use the link module to link the management and analysis system with other AI models.

[0036] Preferably, the upgrading unit is used for:

[0037] The data input into the upgrading unit are subjected to k-means clustering, and the data separated by k-means clustering are respectively stored in corresponding queues; when the queue length reaches a preset data queue length threshold, the data in the queue are sequentially input into a trained adaptive neural network model to obtain a prediction model with the highest user score mean; the prediction model outputs the queue data with the highest user score mean; the parameters of the management and analysis system are adjusted according to the queue data to obtain an upgraded management and analysis system, wherein the parameters include the current scores of the smart devices and the management and analysis system in the feedback interface.

[0038] Preferably, the feedback interface is used for:

[0039] The user scores the smart device and the management and analysis system respectively on the feedback interface, and the average of all scores is calculated to obtain the current scores of the smart device and the management and analysis system.

[0040] The beneficial effects of the present invention are as follows: the intelligent building management and analysis system can be seamlessly linked and data transmitted with other different AI large models through the conversion interface. Users can choose the AI ​​model they need to operate and use all the intelligent devices in the intelligent building where they are located, meeting the multiple needs of modern urban development. By integrating data-driven decision-making mechanisms, the energy efficiency and management level of buildings can be significantly improved, providing strong support for achieving the goal of sustainable development. Through deep learning and data mining technology, the functions of predictive maintenance, intelligent scheduling and user rating optimization can be realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of the basic process of an intelligent building management and analysis system based on an AI big model provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0043] Reference Figure 1, is an embodiment of the present invention, and provides an intelligent building management and analysis system based on an AI big model, including a statistical module, an analysis module, a link module and a functional module:

[0044] The statistical module is used to collect virtual information, space information and user information inside the intelligent building;

[0045] The link module is used to adjust the interface API and data transmission path of the management and analysis system of the intelligent building, so that the management and analysis system can be compatible with all other systems and devices;

[0046] The functional modules are used for the direct application of smart devices by users and the overall management of the management and analysis system.

[0047] The statistical module includes a virtual unit, a space unit and a user unit:

[0048] The virtual unit is used for:

[0049] Collecting the working environment, operating status and performance data of the smart devices in the smart building in real time, wherein the smart devices include temperature control devices, lighting devices, security devices and household electrical appliances, the working environment includes environmental parameters of temperature, humidity and air quality, the operating status includes the operating time of the smart devices and the degree of equipment loss, the performance data includes energy consumption data and user satisfaction scores of the smart devices, the energy consumption data is the product of the power consumption value corresponding to a certain time of the smart device and the time difference, and the user satisfaction score is the average score of the users on each smart device in the user interface of the functional module;

[0050] The operating status and performance data are divided into a first recording area, a second recording area, ... and an nth recording area according to physical areas, and each recording area respectively counts the operating status and performance data of the smart devices in the recording area into a virtual database;

[0051] Record the data in the virtual database in a background storage hard disk, schedule the data in the background storage hard disk and delete unnecessary data according to a multi-level feedback queue scheduling algorithm, and input the scheduled data into the upgrade unit in the functional module in sequence to upgrade the management analysis system;

[0052] The data transmission modes in the background storage hard disk are recorded and classified.

[0053] The space unit is used for:

[0054] Scan the entire intelligent building, obtain the internal space structure of the intelligent building and the network structure of the intelligent equipment, as well as the information of physical access lines and virtual access lines, and use sensors and monitoring systems to count the personnel usage of each space, and identify the peak usage period and off-peak usage period of each space. The personnel usage is the flow of people entering the space.

[0055] The user unit is used for:

[0056] By utilizing the user's activity data in the space, the user's usage habits and preferences for smart devices are obtained to provide a basis for customized services for the intelligent control system. The user's satisfaction evaluation of the smart building environment is collected through the feedback interface of the functional module to provide suggestions for subsequent improvements.

[0057] These functions of the statistical module can provide comprehensive data support for smart building management, help managers make scientific decisions, and improve building operational efficiency and user experience. At the same time, these data also lay the foundation for subsequent machine learning and data analysis applications, and promote the sustainable development of smart buildings.

[0058] The link module includes an interface unit and a control unit:

[0059] The interface unit is used for:

[0060] A virtual abstract interface is defined at the interface of the information transmission channel of the management and analysis system. The abstract interface includes an adapter for collecting the implementation logic of each different AI model, encapsulating the adapter into a class module corresponding to each AI model, and setting a corresponding switch for each class module. When the management and analysis system needs to link any AI model, the switch corresponding to the AI ​​model is called to obtain the adapter corresponding to the switch, and the required AI model is linked using the adapter as the entry.

[0061] The AI ​​models include GPT, BERT, Vision Transformers, YOLO, CLIP, DALL-E, Wav2Vec, Tacotron, StyleGAN and OpenAI.

[0062] All switches are connected in parallel. When the management and analysis system needs to link multiple AI models at the same time, multiple switches corresponding to the AI ​​models are called. The management and analysis system sequentially enters the AI ​​models that need to be linked according to the Peterson algorithm to achieve the effect of no information collision. Because of the parallel processing of information, users can submit multiple requests and obtain results without information congestion.

[0063] Dividing the interface of the information transmission channel of the management and analysis system into multiple units including a virtual abstract interface, a data input unit, a data processing unit and a data output unit can make the management and analysis system easy to expand and maintain.

[0064] The interface is a declarative API, which submits the desired state to the system. The system will continuously adjust the actual state until it is consistent with the desired state. Compared with the imperative API, the declarative API makes the distributed system more robust, especially when the distributed system fails and the component needs to be restored. At this time, in the system designed according to the declarative style, the component only needs to check the current state of the system to determine the operation it needs to perform, so that the component can quickly recover to a normal state. When using the imperative API, it is more difficult to handle and the user needs to tell the system how to operate. For the declarative API, the user needs to write a YAML file in a specific format to tell the system the topology and desired state of the required service, and then the system will complete the user's goal according to the content of the YAML file.

[0065] The control unit is used for:

[0066] Identify the MAC address of information input from the interface of the information transmission channel of the management and analysis system, and identify the network format of the information included in the MAC address according to the MAC address, wherein the network format includes a data transmission format, a network protocol and a network layer format, wherein the data transmission format includes JSON, XML and HTML, the network protocol includes HTTP, HTTPS, FTP, TCP and IP, and the network layer format includes an IP address and a MAC address;

[0067] Secondary encapsulation of all encapsulated information transmitted through the interface includes encapsulating data in a universal format, which should ensure that different systems can understand and process the received information, and performing frequency hopping to adjust the encapsulation signal during the encapsulation process, so as to encrypt all information in the form of a secure password, ensure the security of the interface, encrypt data transmission, and ensure that sensitive data is not stolen;

[0068] The interface calls are logged and recorded into a document by time. The document includes the functions, request examples and response formats of all units of the interface, so that developers can get started quickly and facilitate debugging and performance analysis.

[0069] Through the above steps, an efficient, flexible and compatible virtual interface can be developed to promote the collaboration and integration among various artificial intelligence systems.

[0070] The control unit is also used for:

[0071] Calling the class module corresponding to the adapter as the underlying coding logic, performing binary conversion on the underlying coding logic, and identifying the underlying coding logic converted into binary according to the machine language recognition logic, counting the underlying logic types of the underlying coding logic, and dividing them into a first logic type type, a second logic type type, ... and an nth logic type type, where n is a constant;

[0072] Summarize the common underlying logic according to all underlying logic types, write logic code blocks according to the common underlying logic, adjust the classes of code blocks according to different logic types, and encapsulate all classes into code blocks. The interface can directly call the code blocks, and the code blocks can encapsulate all data transmitted by the interface into data encoding that can be transmitted by all transmission types.

[0073] The functional modules include a user interface, an upgrade unit and a feedback interface:

[0074] The user interface is used to:

[0075] A main webpage is used to set the smart devices of the smart building as list view marks for user interaction. When the user clicks the list view mark of the corresponding smart device, the user enters the hyperlink stored in the list view mark. The hyperlink includes the working environment, operating status and performance data of the smart device. The user can view the detailed information of the smart device in real time and perform command-type remote control on the smart device. The command-type remote control is completed according to the wireless information transmission between the smart device and the user, including:

[0076] The user clicks any command button to send a command signal to the corresponding smart device wirelessly, and the smart device converts the command signal into a corresponding machine language through the link module, and the machine language can be directly understood and executed by the smart device;

[0077] The main webpage also includes a system conversion button, which is used to use the link module to link the management and analysis system with other AI models, so that users can select AI models for use.

[0078] The upgrade unit is used for:

[0079] The data input into the upgrading unit are subjected to k-means clustering, and the data separated by k-means clustering are respectively stored in corresponding queues; when the queue length reaches a preset data queue length threshold, the data in the queue are sequentially input into a trained adaptive neural network model to obtain a prediction model with the highest user score mean; the prediction model outputs the queue data with the highest user score mean; the parameters of the management and analysis system are adjusted according to the queue data to obtain an upgraded management and analysis system, wherein the parameters include the current scores of the smart devices and the management and analysis system in the feedback interface.

[0080] The feedback interface is used to:

[0081] The user scores the smart device and the management and analysis system respectively on the feedback interface, and the average of all scores is calculated to obtain the current scores of the smart device and the management and analysis system.

[0082] The present invention enables the intelligent building management and analysis system to seamlessly link and transmit data with other different AI large models through a conversion interface. Users can choose the AI ​​model they need to operate and use all the intelligent devices in the intelligent building in their location, thereby meeting the multiple needs of modern urban development.

[0083] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0084] It should be noted that the above embodiments are only used to illustrate the technical solutions 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. Intelligent building management and analysis system based on AI big model, characterized by: Including statistical module, analysis module, link module and functional module: The statistical module is used to collect virtual information, space information and user information inside the intelligent building; The link module is used to adjust the interface API and regulate the data transmission path of the management and analysis system of the intelligent building; The functional modules are used for the direct application of smart devices by users and the overall management of the management and analysis system.

2. The intelligent building management and analysis system based on AI big model as claimed in claim 1 is characterized in that: The statistical module includes a virtual unit, a space unit and a user unit: The virtual unit is used for: Collecting the working environment, operating status and performance data of the smart devices in the smart building in real time, wherein the smart devices include temperature control devices, lighting devices, security devices and household electrical appliances, the working environment includes environmental parameters of temperature, humidity and air quality, the operating status includes the operating time of the smart devices and the degree of equipment loss, the performance data includes energy consumption data and user satisfaction scores of the smart devices, the energy consumption data is the product of the power consumption value corresponding to a certain time of the smart device and the time difference, and the user satisfaction score is the average score of the users on each smart device in the user interface of the functional module; The operating status and performance data are divided into a first recording area, a second recording area, ... and an nth recording area according to physical areas, and each recording area respectively counts the operating status and performance data of the smart devices in the recording area into a virtual database; Record the data in the virtual database in a background storage hard disk, schedule the data in the background storage hard disk and delete unnecessary data according to a multi-level feedback queue scheduling algorithm, and input the scheduled data into the upgrade unit in the functional module in sequence to upgrade the management analysis system; The data transmission modes in the background storage hard disk are recorded and classified.

3. The intelligent building management and analysis system based on AI big model as claimed in claim 2, characterized in that: The space unit is used for: Scan the entire intelligent building, obtain the internal space structure of the intelligent building and the network structure of the intelligent equipment, as well as the information of physical access lines and virtual access lines, and use sensors and monitoring systems to count the personnel usage of each space, and identify the peak usage period and off-peak usage period of each space. The personnel usage is the flow of people entering the space.

4. The intelligent building management and analysis system based on AI big model as claimed in claim 2, characterized in that: The user unit is used for: The user's activity data in the space is used to obtain the user's usage habits and preferences for smart devices, and the user's satisfaction evaluation of the smart building environment is collected through the feedback interface of the functional module.

5. The intelligent building management and analysis system based on AI big model as claimed in claim 1, characterized in that: The link module includes an interface unit and a control unit: The interface unit is used for: A virtual abstract interface is defined at the interface of the information transmission channel of the management and analysis system. The abstract interface includes an adapter for collecting the implementation logic of each different AI model, encapsulating the adapter into a class module corresponding to each AI model, and setting a corresponding switch for each class module. When the management and analysis system needs to link any AI model, the switch corresponding to the AI ​​model is called to obtain the adapter corresponding to the switch, and the required AI model is linked using the adapter as the entry. All switches are connected in parallel. When the management and analysis system needs to link multiple AI models at the same time, multiple switches corresponding to the AI ​​models are called, and the management and analysis system sequentially enters the AI ​​models that need to be linked according to the Peterson algorithm; The interface of the information transmission channel of the management and analysis system is divided into multiple units including a virtual abstract interface, a data input unit, a data processing unit and a data output unit.

6. The intelligent building management and analysis system based on the AI ​​big model as claimed in claim 5, characterized in that: The control unit is used for: Identify the MAC address of information input from the interface of the information transmission channel of the management and analysis system, and identify the network format of the information included in the MAC address according to the MAC address, wherein the network format includes a data transmission format, a network protocol and a network layer format, wherein the data transmission format includes JSON, XML and HTML, the network protocol includes HTTP, HTTPS, FTP, TCP and IP, and the network layer format includes an IP address and a MAC address; Secondarily encapsulating all the encapsulated information transmitted through the interface includes encapsulating data in a universal format, and performing frequency hopping to adjust the encapsulation signal during the encapsulation process, so as to encrypt all the information in the form of a secure password; The interface calls are logged and recorded into a document by time, wherein the document includes the functions, request examples and response formats of all units of the interface.

7. The intelligent building management and analysis system based on the AI ​​big model as claimed in claim 6, characterized in that: The control unit is also used for: Calling the class module corresponding to the adapter as the underlying coding logic, performing binary conversion on the underlying coding logic, and identifying the underlying coding logic converted into binary according to the machine language recognition logic, counting the underlying logic types of the underlying coding logic, and dividing them into a first logic type type, a second logic type type, ... and an nth logic type type, where n is a constant; The common underlying logic is summarized according to all the underlying logic types, and the logic code blocks are written according to the common underlying logic, the classes of the code blocks are adjusted according to the different logic types, and all the classes are encapsulated as code blocks.

8. The intelligent building management and analysis system based on AI big model as claimed in claim 2, characterized in that: The functional modules include a user interface, an upgrade unit and a feedback interface: The user interface is used to: A main webpage is used to set the smart devices of the smart building as list view marks for user interaction. When the user clicks the list view mark of the corresponding smart device, the user enters the hyperlink stored in the list view mark, and the hyperlink includes the working environment, operation status and performance data of the smart device, and performs command-type remote control on the smart device. The command-type remote control is completed according to the wireless information transmission between the smart device and the user, including: The user clicks any command button to send a command signal to the corresponding smart device wirelessly, and the smart device converts the command signal into the corresponding machine language through the link module; The main webpage also includes a system conversion button, which is used to use the link module to link the management and analysis system with other AI models.

9. The intelligent building management and analysis system based on AI big model as claimed in claim 8, characterized in that: The upgrade unit is used for: The data input into the upgrading unit are subjected to k-means clustering, and the data separated by k-means clustering are respectively stored in corresponding queues; when the queue length reaches a preset data queue length threshold, the data in the queue are sequentially input into a trained adaptive neural network model to obtain a prediction model with the highest user score mean; the prediction model outputs the queue data with the highest user score mean; the parameters of the management and analysis system are adjusted according to the queue data to obtain an upgraded management and analysis system, wherein the parameters include the current scores of the smart devices and the management and analysis system in the feedback interface.

10. The intelligent building management and analysis system based on AI big model as claimed in claim 8, characterized in that: The feedback interface is used to: The user scores the smart device and the management and analysis system respectively on the feedback interface, and the average of all scores is calculated to obtain the current scores of the smart device and the management and analysis system.

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