Intelligent building and facility management system based on artificial intelligence

Abstract

The invention provides an intelligent building and facility management system based on artificial intelligence, and relates to the technical field of intelligent buildings, a receiving module obtains a management instruction, a determination module intelligently identifies a target facility according to an instruction parameter and a facility type, an execution module executes a management operation, and a recording module records an operation result and data. The system comprises a plurality of determining units, target facilities can be accurately positioned according to parameters such as time ranges, position areas, energy consumption indexes and fault keywords, efficient and intelligent facility management is achieved, the method is achieved through electronic equipment and a readable storage medium, the method is suitable for improving the management efficiency, energy consumption control and fault response capacity of building facilities, and the method is suitable for popularization and application. And a comprehensive intelligent management solution is provided for the intelligent building.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent buildings, and more specifically, to an intelligent building and facility management system based on artificial intelligence. Background Art

[0002] With the acceleration of the urbanization process and the continuous improvement of people's requirements for living and working environments, intelligent buildings have emerged. Intelligent buildings integrate a variety of advanced technologies and are designed to provide users with an efficient, comfortable, and safe space environment. In intelligent buildings, various facilities such as lighting systems, air-conditioning systems, and elevator systems work together, playing a key role in the normal operation of the building and the user experience. However, the existing building facility management methods have many limitations. On the one hand, the existing management relies on manual experience judgment and manual operation, which is not only inefficient but also prone to human errors. For example, when adjusting the lighting brightness or controlling the air-conditioning temperature, it is difficult to accurately operate according to the real-time needs of different areas. On the other hand, the existing management system lacks effective analysis and utilization of a large amount of facility operation data. With the expansion of the building scale and the increase in the number of facilities, a large amount of operation data such as energy consumption data and fault reports are only simply recorded, and valuable information cannot be mined from them for optimizing facility management strategies and preventing faults in advance. At the same time, the operation requirements of building facilities vary significantly in different time ranges and location areas, and the existing system is difficult to achieve targeted management. For example, the energy consumption requirements of lighting and air-conditioning are different during peak and off-peak hours in the office area; the operation requirements of facilities in different floors and functional areas also have their own characteristics. In addition, when a facility fails, it is difficult to quickly locate the key problem facility by the existing method, affecting the overall operation of the building.

[0003] Therefore, the existing system has low management efficiency, insufficient data utilization, lack of targeted management, and lagging fault handling. Summary of the Invention

[0004] In order to overcome the problems of low management efficiency, insufficient data utilization, lack of targeted management, and lagging fault handling of the existing system, the intelligent building and facility management system based on artificial intelligence designed by the present invention can effectively solve the above technical problems.

[0005] To solve the above technical problems, the technical solution of the present invention is as follows: An intelligent building and facility management system based on artificial intelligence, comprising: A receiving module, configured to receive a first operation instruction for building facility management, wherein the first operation instruction is a management instruction for a specific building facility; A determining module, configured to determine a target facility according to the parameters of the first operation instruction and the type of the building facility, wherein the target facility is a specific facility that needs to be managed; An execution module, configured to execute corresponding management operations according to the target facility and the first operation instruction; A recording module, configured to record the execution results and relevant data of the management operations; wherein, the execution results and relevant data are used for subsequent facility status evaluation and optimization decision-making.

[0006] Preferably, the determination module includes a first determination unit; The first determination unit is configured to, when the parameters of the first operation instruction at least include a time range, determine, as the target facility, a facility that runs within the time range and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

[0007] Preferably, the determination module includes a second determination unit; The second determination unit is configured to, when the parameters of the first operation instruction at least include a location area, determine, as the target facility, a facility that is located within the location area and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

[0008] Preferably, the determination module includes a third determination unit; The third determination unit is configured to, when the parameters of the first operation instruction at least include an energy consumption index, determine an energy consumption screening range based on the current facility energy consumption data according to the energy consumption index; determine, as the target facility, a facility whose energy consumption is within the screening range and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

[0009] Preferably, the determination module includes a fourth determination unit; The fourth determination unit is configured to, when the parameters of the first operation instruction at least include a fault keyword, perform semantic analysis on the fault reports and operation logs of the facilities, extract facility information related to the fault keyword; determine, as the target facility, a facility for which the information is extracted and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

[0010] Preferably, determining the facility for which the information is extracted as the target facility includes: if there are multiple facilities for which the information is extracted, sorting these facilities according to the fault severity and the impact degree on the building operation; determining the facility ranked first as the target facility.

[0011] An intelligent building and facility management method based on artificial intelligence, including the following steps: Receiving a first operation instruction for building facility management, where the first operation instruction is a management instruction for specific building facilities; Determine a target facility according to the parameters of the first operation instruction and the type of building facilities, where the target facility is a specific facility that needs to be managed and operated; Execute corresponding management operations according to the target facility and the first operation instruction; Record the execution results and relevant data of the management operation, where the execution results and relevant data are used for subsequent facility status evaluation and optimization decision-making.

[0012] Preferably, the parameters of the first operation instruction include at least one of the following: time range, location area, energy consumption index, and fault keyword; When the parameters of the first operation instruction include a time range, determine as the target facility the facilities that will run within the time range and whose facility type is the same as or the similarity exceeds a preset similarity threshold of the facility type targeted by the first operation instruction; When the parameters of the first operation instruction include a location area, determine as the target facility the facilities that are located within the location area and whose facility type is the same as or the similarity exceeds a preset similarity threshold of the facility type targeted by the first operation instruction; When the parameters of the first operation instruction include an energy consumption index, based on the current facility energy consumption data, determine an energy consumption screening range according to the energy consumption index, and determine as the target facility the facilities whose energy consumption is within the screening range and whose facility type is the same as or the similarity exceeds a preset similarity threshold of the facility type targeted by the first operation instruction; When the parameters of the first operation instruction include a fault keyword, perform semantic analysis on the fault reports and operation logs of the facilities, extract the facility information related to the fault keyword, and determine as the target facility the facilities from which the information is extracted and whose facility type is the same as or the similarity exceeds a preset similarity threshold of the facility type targeted by the first operation instruction; If there are multiple facilities from which information is extracted, sort these facilities according to the severity of the fault and the degree of impact on the building operation, and determine the facility ranked first as the target facility.

[0013] Preferably, an electronic device includes a processor and a memory, the memory stores a program or instruction that can run on the processor, and when the program or instruction is executed by the processor, it implements the steps of the above-mentioned intelligent building and facility management method based on artificial intelligence.

[0014] Preferably, a readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, it implements the steps of the above-mentioned intelligent building and facility management method based on artificial intelligence.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The system quickly obtains management instructions through the receiving module. The determination module accurately locates the target facilities based on the instruction parameters and facility types. The execution module immediately responds and executes operations, reducing the time for manual operations and judgments, automating and streamlining the management process, and changing the problem of low efficiency caused by traditional reliance on manual experience. The recording module details the execution results and relevant data of management operations. These data provide data support for subsequent facility status evaluation and optimization decisions, realizing the transformation from data to value and mining the potential value of data for optimizing management strategies. Different determination units of the determination module accurately screen out target facilities that meet the conditions according to parameters such as time range, location area, and energy consumption indicators, achieving targeted management of facilities with different time periods, regions, and energy consumption requirements, avoiding resource waste, and improving the rationality of management resource allocation. When the operation instruction contains a fault keyword, the fourth determination unit extracts relevant facility information through semantic analysis. If there are multiple relevant facilities, they are sorted according to the severity of the fault and the impact on building operation, and key facilities are given priority for processing to quickly locate and solve core faults, ensuring the normal operation of the building and enhancing the timeliness and accuracy of fault handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only exemplary, and for those of ordinary skill in the art, without creative efforts, other implementation drawings can be obtained based on the provided drawings.

[0017] Figure 1 FIG. [X] is a structural diagram of an intelligent building and facility management system based on artificial intelligence; Figure 2 FIG. [Y] is a flowchart of the method for intelligent building and facility management based on artificial intelligence. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The drawings are only for illustrative purposes and should not be construed as a limitation of this patent; To better illustrate this embodiment, some components in the drawings are omitted, enlarged, or reduced, and do not represent the actual size of the product; For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0019] The following will further illustrate the technical solutions of the present invention with reference to the drawings and embodiments.

[0020] Embodiment 1

[0021] An embodiment provides an intelligent building and facility management method based on artificial intelligence, which is based on facility management within a time range. Refer to Figure 1-2 , including: Receiving a first operation instruction: The receiving module of the intelligent building management system receives a first operation instruction for building facility management. This instruction is input by the management personnel through the system operation interface, and the content of the instruction is to turn off all public area lighting facilities during non-business hours (0:00 - 6:00) on weekdays. At this time, the first operation instruction is a management instruction for public area lighting facilities, and the parameters of the operation instruction include the time range, that is, 0:00 - 6:00 on weekdays.

[0022] Determining target facilities according to instruction parameters: The first determination unit in the determination module starts to work. First, the system obtains the operation time data and facility type information of all lighting facilities from the facility database. After judgment, the operation time data of the lighting facilities on weekdays shows that the public area lighting facilities are in a state that can be turned off (no lighting is required during non-business hours) from 0:00 - 6:00, and the facility type is the same as that of the public area lighting facilities targeted by the first operation instruction. The preset similarity threshold is set at 90% here (because they are all lighting facilities and the type similarity is high). The type similarity of the public area lighting facilities far exceeds this threshold, so the system determines the public area lighting facilities operating from 0:00 - 6:00 on weekdays as the target facilities.

[0023] Executing management operations: The execution module executes corresponding management operations based on the target facilities and the first operation instruction. Through the communication interface with the lighting facility control system, it sends a turn-off instruction to the determined target facilities (public area lighting facilities). After receiving the instruction, the lighting facility control system controls the relevant lighting equipment to cut off the power and turn off, realizing the turn-off operation of the public area lighting facilities.

[0024] Recording the execution results and relevant data: The recording module starts to work and records the execution results and relevant data of this management operation. The execution results show that the public area lighting facilities are successfully turned off. The relevant data includes the operation time (such as the specific time point when the turn-off operation is executed), the operation object (information such as the location and model of the specific public area lighting facilities to be turned off), the energy consumption data before the facility is turned off (for subsequent energy consumption comparison and analysis), etc. These execution results and relevant data are stored in the system database for subsequent status evaluation of the public area lighting facilities, such as judging whether the facilities are normally turned off and whether the energy consumption is reasonable, and also providing a decision-making basis for optimizing the operation strategy of the lighting system, such as adjusting the turn-off time of lighting facilities in different areas according to the energy consumption data.

[0025] In this embodiment, by receiving an operation instruction containing a time range parameter, determining the target facility and performing management operations, and recording relevant results and data, the effective management of building facilities within a specific time range is achieved, improving energy utilization efficiency. At the same time, it provides data support for subsequent facility management optimization, enhancing the intelligence and refinement level of intelligent building facility management.

[0026] Embodiment 2

[0027] This embodiment provides an intelligent building and facility management method based on artificial intelligence, for facility management based on fault keywords, refer to Figure 1-2 , including: Receiving the first operation instruction: The receiving module of the intelligent building management system receives the first operation instruction for building facility management, which is input by the system monitor. The instruction content is to troubleshoot all elevators with the problem of "abnormal vibration". At this time, the first operation instruction is a management instruction for elevator facilities, and the parameters of the operation instruction include the fault keyword, that is, "abnormal vibration".

[0028] Determining the target facility according to the instruction parameters: The fourth determination unit in the determination module is activated. The system first performs semantic analysis on the fault reports and operation logs of the elevators. Through natural language processing technology, facility information related to "abnormal vibration" is extracted from the fault reports and operation logs. During the analysis process, it is found that multiple elevators have recorded different degrees of vibration in the recent operation logs. The preset similarity threshold is set to 80% (the similarity of elevator facility types is relatively high). After judgment, the facility types of these elevators are all more similar to the elevator facility type targeted by the first operation instruction than this threshold. Then the system sorts these elevators with the extracted information according to the severity of the fault and the degree of impact on building operation. The severity of the fault is evaluated based on indicators such as vibration amplitude and frequency, and the degree of impact on building operation considers factors such as the floor where the elevator is located and the number of served people. Finally, the elevator ranked first is determined as the target facility.

[0029] Performing management operations: The execution module performs corresponding management operations according to the target facility and the first operation instruction. The system sends a repair work order containing detailed information of the target elevator (such as elevator number, location, fault description, etc.) to the elevator maintenance personnel. After receiving the work order, the maintenance personnel go to the location of the target elevator and conduct a comprehensive inspection and repair of the elevator, such as checking key components such as the elevator guide rails, car suspension system, and drive device, finding the cause of the abnormal vibration and repairing it.

[0030] Record the execution results and relevant data: The recording module records the execution results and relevant data of this management operation. The execution results record the handling situation of the maintenance work order, such as the arrival time of the maintenance personnel, the start time of the maintenance, the end time of the maintenance, the maintenance measures, and the operating status of the elevator after maintenance. The relevant data also includes the time when the elevator failure occurred, the frequency of the failure, the operating parameters of the elevator when the failure occurred, etc. These execution results and relevant data are stored in the system database for subsequent status evaluation of the elevator facilities, to judge whether the operating stability of the elevator has been improved after maintenance, whether there are still potential failure risks, etc., and at the same time provide a decision-making basis for optimizing the elevator maintenance plan and strategy. For example, adjust the maintenance cycle according to the failure frequency and formulate more effective preventive measures for frequently occurring failure problems.

[0031] In this embodiment, by receiving an operation instruction containing a failure keyword, determining the target facility using semantic analysis, performing a maintenance operation, and recording relevant information, it realizes the rapid positioning and effective handling of building facilities with specific failures, ensures the safe and stable operation of building facilities, and at the same time improves the preventive and reliability of intelligent building facility management through the analysis of the recorded data.

[0032] Embodiment 3

[0033] This embodiment provides an intelligent building and facility management method based on artificial intelligence, for facility management based on location area, refer to Figure 1-2 , including: Receive the first operation instruction: The receiving module of the intelligent building and facility management system receives the first operation instruction for building facility management. The instruction is issued by the office building management personnel and input through the system terminal. The instruction content is to perform filter cleaning and maintenance on all air conditioning equipment in the office area on the third floor of the office building. At this time, the first operation instruction targets the air conditioning equipment in the office area on the third floor, and the instruction parameters include the location area, that is, the office area on the third floor of the office building.

[0034] Determine the target facility according to the instruction parameters: The second determination unit in the determination module starts to work. The system obtains the location information and facility type information of all air conditioning equipment from the building facility database. After screening, the air conditioning equipment located in the office area on the third floor of the office building is identified, and the facility types of these air conditioning equipment are the same as the type of air conditioning equipment targeted by the first operation instruction. The preset similarity threshold is set to 95% (because they are all air conditioning equipment and the type similarity is extremely high). The type similarity of these air conditioning equipment all exceeds this threshold. Therefore, the system determines all the air conditioning equipment located in the office area on the third floor of the office building as the target facility.

[0035] Execute management operations: The execution module performs corresponding management operations based on the target facility and the first operation instruction. The system generates a maintenance work order and sends the work order to the staff responsible for air conditioning maintenance. Based on the work order information, the staff goes to the office area on the third floor of the office building to perform filter cleaning and maintenance operations on the identified target facility (air conditioning equipment).

[0036] Record execution results and related data: The recording module records the execution results and related data of this management operation. The execution results record the completion status of the filter cleaning and maintenance work, such as the maintenance start time, end time, maintenance personnel information, etc. The related data includes the location and model of the air-conditioning equipment, the length of time the filter was used before cleaning, the degree of dirtiness of the filter, and other information. These execution results and related data are stored in the system database for subsequent status evaluation of the air-conditioning equipment, such as determining whether the filter cleaning and maintenance is effective, whether the operating performance of the air-conditioning equipment is improved, etc. At the same time, it provides a decision-making basis for optimizing the maintenance plan of the air-conditioning equipment, such as adjusting the maintenance cycle according to the degree of dirtiness of the filter.

[0037] This embodiment receives operation instructions containing location area parameters, determines the target facilities and performs management operations, and records relevant results and data, thereby achieving precise management of building facilities within a specific location area, ensuring the normal operation of the facilities, and providing support for subsequent facility management optimization, thereby improving the pertinence and effectiveness of intelligent building facility management.

[0038] Example 4

[0039] This embodiment provides an intelligent building and facility management method based on artificial intelligence, facility management based on energy consumption indicators, see Figure 1-2 ,include: Receiving the first operation instruction: The receiving module of the intelligent building and facility management system receives the first operation instruction for building facility management. The instruction is input by the park energy management department through the system platform. The instruction content is to carry out energy-saving transformation of lighting facilities in the park whose energy consumption exceeds a certain standard. The first operation instruction is for lighting facilities, and the instruction parameters include energy consumption indicators, that is, higher than a specific energy consumption standard.

[0040] Determine the target facilities according to the instruction parameters: the third determination unit in the determination module starts working, and the system first obtains the energy consumption data of all current lighting facilities. These data are obtained in real time from the park energy consumption monitoring system, and based on the current facility energy consumption data, the energy consumption screening range is determined according to the energy consumption indicators in the instruction. Assuming that the energy consumption screening range is set to lighting facilities with an electricity consumption of more than 5 degrees per hour, the system then screens out lighting facilities with energy consumption within the screening range, and further determines that the types of these facilities are the same as the types of lighting facilities targeted by the first operation instruction. The preset similarity threshold is set to 90%, and the similarity of the screened lighting facility types exceeds the threshold, so the system determines the lighting facilities with energy consumption higher than 5 degrees per hour and the types that meet the requirements as target facilities.

[0041] Execute management operations: The execution module performs corresponding management operations based on the target facilities and the first operation instructions. The system formulates energy-saving transformation plans, such as replacing energy-saving lamps for target lighting facilities, adjusting lighting brightness, etc., and then arranges professional and technical personnel to implement energy-saving transformation operations on the determined target facilities (lighting facilities).

[0042] Record execution results and related data: The recording module records the execution results and related data of this management operation. The execution results record the completion status of the energy-saving transformation work, such as whether the energy consumption of the lighting facilities after the transformation is reduced to the expected standard. The relevant data include the energy consumption data of the lighting facilities before the transformation, the transformation measures, the energy consumption data after the transformation, the location and model of the lighting facilities, etc. These execution results and related data are stored in the system database for subsequent status evaluation of the lighting facilities, such as judging whether the effect of the energy-saving transformation is significant and whether further optimization is needed. At the same time, it provides a decision-making basis for optimizing the energy management strategy of the park, such as adjusting the management methods of lighting facilities in other areas according to the energy consumption data after the transformation.

[0043] This embodiment receives operation instructions containing energy consumption index parameters, determines the target facilities and performs management operations, and records relevant results and data, thereby achieving effective management of high-energy-consuming building facilities and reducing energy consumption. At the same time, it provides data support for subsequent energy management optimization and improves the scientificity and rationality of intelligent building facility management in energy management.

[0044] Example 5

[0045] An embodiment of an electronic device for implementing an artificial intelligence-based intelligent building and facility management system: The device includes a processor and a memory. The memory may be a random access memory (RAM), a read-only memory (ROM), a flash memory or any other suitable storage medium.

[0046] Store a program in a memory, the program including an instruction set of the following steps: Receiving module: Receive a first operation instruction input by a user through a user interface, the instruction being directed to a specific building facility, such as a smart lighting system.

[0047] Determining module: Determine a target facility according to the parameters of the first operation instruction (for example, time range, location area, energy consumption index or fault keyword) and the facility type. For example, if the operation instruction is about energy saving, the determining module will screen out lighting devices with energy consumption exceeding a threshold.

[0048] Executing module: Execute corresponding management operations according to the determined target facility and the operation instruction, such as adjusting the lighting brightness or switch state.

[0049] Recording module: Record the operation results and related data of the executing module, such as energy saving effect, device response time, etc.

[0050] When a user inputs an operation instruction through the user interface, the processor executes the program stored in the memory and operates according to the above steps.

[0051] A readable storage medium is used to store a program for implementing an artificial intelligence-based intelligent building and facility management method: Provide a readable storage medium, such as a USB flash drive, an optical disc or a solid-state drive. Store a program on the readable storage medium, the program including the steps of the above method. Connect the readable storage medium to an electronic device having a processor. The processor loads the program from the readable storage medium and executes the instructions in the program to implement the intelligent building and facility management method.

[0052] The same or similar reference numerals correspond to the same or similar components; The terms describing the positional relationship in the drawings are only for illustrative purposes and should not be construed as a limitation of this patent; Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention and are not limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. An intelligent building and facility management system based on artificial intelligence, characterized in that, Comprising: A receiving module, configured to receive a first operation instruction for building facility management, wherein the first operation instruction is a management instruction for a specific building facility; A determining module, configured to determine a target facility according to the parameters of the first operation instruction and the type of the building facility, wherein the target facility is a specific facility that needs to perform a management operation; An executing module, configured to perform corresponding management operations according to the target facility and the first operation instruction; A recording module, configured to record the execution result of the management operation and related data; wherein the execution result and related data are used for subsequent facility status evaluation and optimization decision-making.

2. The intelligent building and facility management system based on artificial intelligence according to claim 1, characterized in that, The determining module includes a first determining unit; The first determining unit is configured to, when the parameters of the first operation instruction at least include a time range, determine, as the target facility, a facility that operates within the time range and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

3. The intelligent building and facility management system based on artificial intelligence according to claim 1, characterized in that, The determining module includes a second determining unit; The second determining unit is configured to, when the parameters of the first operation instruction at least include a location area, determine, as the target facility, a facility that is located within the location area and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

4. The intelligent building and facility management system based on artificial intelligence according to claim 1, characterized in that, The determining module includes a third determining unit; The third determining unit is configured to, when the parameters of the first operation instruction at least include an energy consumption index, determine an energy consumption screening range based on the current facility energy consumption data according to the energy consumption index; determine, as the target facility, a facility whose energy consumption is within the screening range and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

5. The intelligent building and facility management system based on artificial intelligence according to claim 1, characterized in that, The determining module includes a fourth determining unit; The fourth determining unit is configured to, when the parameters of the first operation instruction at least include a fault keyword, perform semantic analysis on the fault reports and operation logs of the facilities, extract facility information related to the fault keyword; determine, as the target facility, a facility from which the information is extracted and whose facility type is the same as or the similarity to the facility type targeted by the first operation instruction exceeds a preset similarity threshold.

6. The intelligent building and facility management system based on artificial intelligence according to claim 5, characterized in that, Determining the facility from which the information is extracted as the target facility includes: if there are multiple facilities from which the information is extracted, sorting these facilities according to the fault severity and the impact degree on the building operation; determining the facility ranked first as the target facility.

7. An intelligent building and facility management method based on artificial intelligence, characterized in that, Including the following steps: Receiving a first operation instruction for building facility management, wherein the first operation instruction is a management instruction for a specific building facility; Determining a target facility according to the parameters of the first operation instruction and the type of the building facility, wherein the target facility is a specific facility that needs to perform a management operation; Performing corresponding management operations according to the target facility and the first operation instruction; Recording the execution result of the management operation and related data, wherein the execution result and related data are used for subsequent facility status evaluation and optimization decision-making.

8. The method for intelligent building and facility management based on artificial intelligence according to claim 7, characterized in that, The parameters of the first operation instruction include at least one of the following: time range, location area, energy consumption index, and fault keyword; When the parameters of the first operation instruction include a time range, facilities that will run within the time range and whose facility types are the same as or have a similarity exceeding a preset similarity threshold to the facility type targeted by the first operation instruction are determined as target facilities; When the parameters of the first operation instruction include a location area, facilities that are located within the location area and whose facility types are the same as or have a similarity exceeding a preset similarity threshold to the facility type targeted by the first operation instruction are determined as target facilities; When the parameters of the first operation instruction include an energy consumption index, based on the current facility energy consumption data, an energy consumption screening range is determined according to the energy consumption index, and facilities whose energy consumption is within the screening range and whose facility types are the same as or have a similarity exceeding a preset similarity threshold to the facility type targeted by the first operation instruction are determined as target facilities; When the parameters of the first operation instruction include a fault keyword, semantic analysis is performed on the fault reports and operation logs of the facilities to extract facility information related to the fault keyword, and facilities from which information is extracted and whose facility types are the same as or have a similarity exceeding a preset similarity threshold to the facility type targeted by the first operation instruction are determined as target facilities; If multiple facilities have information extracted, these facilities are sorted according to the severity of the fault and the degree of impact on the building operation, and the facility ranked first is determined as the target facility.

9. An electronic device, characterized in that, It includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the artificial intelligence-based intelligent building and facility management method described in any one of claims 7-8 are implemented.

10. A readable storage medium, characterized in that, A program or instruction is stored on the readable storage medium. When the program or instruction is executed by the processor, the steps of the artificial intelligence-based intelligent building and facility management method described in any one of claims 7-8 are implemented.

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