Intelligent building management system and method based on digital twinning

Abstract

The invention discloses a smart building management system and method based on digital twinning, and relates to the technical field of smart building management. Comprising a cloud server, a data acquisition module used for acquiring park management data, and a data transmission module used for transmitting the park management data to an edge computing node for preprocessing and then uploading the data to the cloud server. The data analysis module is used for analyzing the preprocessed park management data; and the evaluation optimization module is used for generating a corresponding management scheme according to an analysis result of the data analysis module. According to the system, the data analysis module is arranged, so that the system can carry out optimization analysis on personnel distribution, equipment operation conditions, park energy consumption conditions and vehicle driving routes in the park, the energy utilization efficiency and economic benefits are improved, carbon emission is remarkably reduced, and the economic benefit is improved. And park management is promoted to develop towards the direction of intelligence and greenization.

Description

Technical Field

[0001] The present invention relates to the technical field of smart building management, and in particular to a smart building management system and method based on digital twins. Background Art

[0002] With the acceleration of urbanization and the development of technology, the traditional building management model can no longer meet the requirements of modern society for energy conservation, environmental protection, safety and comfort. As an emerging technical means, digital twins can simulate and predict actual operation in a virtual environment by creating digital copies of physical entities, providing new ideas and tools for building management. As an integration of a group of buildings, the park needs to be managed in all aspects. However, the management system currently on the market does not allocate resources within the park reasonably, resulting in low energy utilization efficiency and low intelligence within the park. Summary of the invention

[0003] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a smart building management system and method based on digital twins, aiming to solve the above-mentioned technical problems.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: In the first aspect, a smart building management system based on digital twins includes: Cloud servers; A data acquisition module, wherein the data acquisition module is used to acquire park management data; A data transmission module, which is used to transmit the park management data to the edge computing node for pre-processing and then upload it to the cloud server; A data analysis module, which is used to analyze the pre-processed park management data; An evaluation and optimization module is used to generate a corresponding management plan based on the analysis results of the data analysis module.

[0005] Preferably, the park management data includes personnel data, equipment data, vehicle data and energy data in the park, the personnel data is obtained through cameras and access control systems; the equipment data is obtained through Internet of Things sensors; the vehicle data is obtained through cameras, license plate recognition and parking management systems; the energy data is obtained from electricity meters and water meters in the park.

[0006] Preferably, the data transmission module is used to transmit the park management data to the edge computing node for preprocessing and then upload it to the cloud server. The specific process is as follows: Data packaging: The data transmission module reads the park management data from the local cache, packages it according to the set rules, and generates data packets that comply with the transmission protocol; Data encryption: SSL / TLS protocol is used to encrypt the park management data to ensure that the park management data will not be eavesdropped or tampered with during network transmission; Data transmission, data packets are sent to edge computing nodes through wireless communication technology; Data reception and preprocessing: After receiving the data, the edge computing node performs preliminary processing such as decryption, analysis, noise filtering, and data compression; Data upload, the preprocessed data is uploaded to the cloud server through a secure channel.

[0007] Preferably, the data analysis module includes an equipment analysis unit, an energy analysis unit, a personnel analysis unit and a vehicle analysis unit.

[0008] Preferably, the equipment analysis unit is used to analyze the operation status of equipment in the park, and the specific steps are as follows: Obtain the average temperature, maximum pressure, and vibration frequency characteristics of the device to build the health index of the device; Use the LSTM model to predict the temperature change trend in the next week and prepare countermeasures in advance; Apply the isolation forest algorithm to detect abnormal data points and promptly warn of potential failures; Display the real-time status and health score of the device through web and mobile applications; Generate equipment operation reports regularly to show the changing trends of key equipment indicators, abnormal event records, and maintenance recommendations; Collect feedback from frontline operation and maintenance personnel based on operation reports, and continuously optimize the calculation formula and prediction model of the health index; Adjust the operating parameters of the equipment according to the analysis results of the prediction model to achieve energy saving and consumption reduction.

[0009] Preferably, the energy analysis unit is used to analyze the energy consumption in the park, and the specific steps are as follows: Obtain the sub-item energy consumption data of each energy consumption, build a multivariate regression model, and analyze the impact of each factor on total energy consumption; Use the ARIMA model to predict the energy consumption trend in the next month and prepare countermeasures in advance; Apply K-means clustering algorithm to classify energy consumption characteristics of different buildings and floors and identify high energy consumption areas; The real-time energy consumption status and energy consumption percentage of each item in the park are displayed through web and mobile applications; Generate detailed energy consumption reports regularly to show the changing trends of key energy consumption indicators and abnormal event records; Collect feedback from park managers on energy consumption reports and continuously optimize energy consumption models; Adjust the operating parameters of energy-consuming equipment according to the analysis results of the energy consumption model to achieve energy saving and consumption reduction.

[0010] Preferably, the personnel analysis unit is used to provide park personnel with the distribution of personnel at each intersection and area in the park, and the specific steps are as follows: Construct real-time personnel distribution heat maps at various intersections and areas in the park to intuitively display the density and flow direction of personnel in different time periods; Analyze the movement paths of personnel within the park and identify high-frequency routes and hot spots; Count the average length of stay of staff in different areas, evaluate the attractiveness and utilization efficiency of each area, and provide a reference for resource allocation in the park; Study the peak hours of daily, weekly and monthly personnel flows, and prepare emergency plans and resource allocation in advance to avoid congestion and safety hazards; Generate detailed personnel distribution reports regularly to show the changing trends of key indicators and records of abnormal events; Collect feedback from building managers and continuously optimize resource distribution within the park.

[0011] Preferably, the vehicle analysis unit is used to optimize the driving routes of vehicles in the park, and the specific steps are as follows: Use traffic simulation software to build a traffic model within the park, input real-time personnel distribution and vehicle traffic data, and simulate traffic flow changes under different driving routes; Apply Dijkstra algorithm and reinforcement learning method to dynamically calculate the optimal driving route; Display optimized driving routes and provide real-time navigation guidance through web and mobile applications; Collect feedback from drivers and pedestrians to continuously improve traffic route optimization plans.

[0012] Preferably, the evaluation and optimization module generates a corresponding management plan according to the analysis results of the data analysis module, and the specific process is as follows: Identify equipment health status, energy consumption distribution, personnel density and flow direction, and traffic flow changes; Define specific goals of management plans based on identifying equipment health status, energy consumption distribution, personnel density and flow direction, and traffic flow changes; Select and design corresponding management plans based on the identification of equipment health status, energy consumption distribution, personnel density and flow direction, traffic flow changes and specific goals; Predict the implementation effect of management plans and evaluate their feasibility through simulation and cost-benefit analysis; Implement the management plan that passes the evaluation and collect feedback on the management plan; Continuously optimize management solutions through user feedback.

[0013] In the second aspect, a smart building management method based on digital twins is applied to the above management system, comprising the following steps: Obtain the park management data of the park; The park management data is transmitted to the edge computing node for pre-processing before being uploaded to the cloud server; Analyze the pre-processed park management data through the data analysis module; The evaluation and optimization module generates corresponding management plans based on the analysis results of the data analysis module.

[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. By setting up a data analysis module, this system can optimize the analysis of personnel distribution, equipment operation, energy consumption and vehicle routes within the park, which not only improves energy efficiency and economic benefits, but also significantly reduces carbon emissions, and promotes the development of park management towards intelligence and greenness.

[0015] 2. By setting up an evaluation and optimization module, this system can generate a scientific and reasonable management plan based on the analysis results of the data analysis module to ensure the effectiveness and sustainability of park management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0017] Figure 1 A structural schematic diagram of a smart building management system based on digital twins is shown.

[0018] Figure 2 The flowchart of the equipment analysis unit analyzing the equipment operation status in the park is shown.

[0019] Figure 3 The flowchart of the energy analysis unit analyzing the energy consumption in the park is shown.

[0020] Figure 4The flowchart of the personnel analysis unit analyzing the distribution of personnel at various intersections and areas within the park is shown.

[0021] Figure 5 A flow chart showing the vehicle analysis unit analyzing and optimizing the driving routes of vehicles in the park.

[0022] Figure 6 A flow chart of a smart building management method based on digital twins is shown. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Reference Figures 1 to 5 An embodiment of a smart building management system based on digital twins of the present invention is further described.

[0025] A smart building management system based on digital twins, comprising: Cloud servers; A data acquisition module, wherein the data acquisition module is used to acquire park management data; The park management data includes personnel data, equipment data, vehicle data and energy data in the park. The personnel data is obtained through cameras, such as installing high-definition cameras at key locations such as the park entrance, office area, public facilities, etc., combined with face recognition technology to automatically identify and record the identity information of people entering and leaving, and access control systems, such as using electronic access control cards or biometrics (such as fingerprints, irises) to manage and record the entry and exit of personnel, ensuring safety while collecting personnel flow data; the equipment data is obtained through Internet of Things sensors, such as temperature, humidity, light, vibration and other sensors deployed inside and outside the building to monitor environmental parameters in real time to ensure that the equipment operating environment is good, and pressure, flow, and liquid level sensors to monitor the operating status of water supply, power supply, gas supply and other systems, and promptly discover abnormal situations or upload the working status of the equipment, fault alarm and other information in real time through the intelligent equipment management system, and through remote operation and maintenance, reduce the frequency of on-site inspections and improve operation and maintenance efficiency; the vehicle data is obtained through cameras at intersections, license plate recognition and parking management systems; the energy data is obtained from electricity meters and water meters in the park.

[0026] A data transmission module, which is used to transmit the park management data to the edge computing node for pre-processing and then upload it to the cloud server; The data transmission module is used to transmit the park management data to the edge computing node for pre-processing and then upload it to the cloud server. The specific process is as follows: Data packaging, the data transmission module reads the park management data from the local cache, packages it according to the set rules, and generates data packets that comply with the transmission protocol. For example, the data from multiple sensors can be combined into one data packet to reduce the number of transmissions.

[0027] Data encryption: SSL / TLS protocol is used to encrypt the park management data to ensure that the park management data will not be eavesdropped or tampered with during network transmission; Data transmission,data packets are sent to edge computing nodes through wireless communication technology.,It should be noted that different transmission paths and methods can be selected,based on network conditions and data priorities to ensure the timeliness and,reliability of data; Data reception and preprocessing: After receiving the data, the edge computing node performs preliminary processing such as decryption, analysis, noise filtering, and data compression; Data upload, the preprocessed data is uploaded to the cloud server through a secure channel.

[0028] A data analysis module, wherein the data analysis module is used to analyze the pre-processed park management data, and the data analysis module includes an equipment analysis unit, an energy analysis unit, a personnel analysis unit and a vehicle analysis unit.

[0029] The equipment analysis unit is used to analyze the operation status of equipment in the park. The specific steps are as follows: Obtain the average temperature, maximum pressure, and vibration frequency characteristics of the device to build the health index of the device; Use the LSTM model to predict the temperature change trend in the next week and prepare countermeasures in advance; Apply the isolation forest algorithm to detect abnormal data points and promptly warn of potential failures; Display the real-time status and health score of the device through web and mobile applications; Generate equipment operation reports regularly to show the changing trends of key equipment indicators, abnormal event records, and maintenance recommendations; Collect feedback from frontline operation and maintenance personnel based on operation reports, and continuously optimize the calculation formula and prediction model of the health index; Adjust the operating parameters of the equipment according to the analysis results of the prediction model to achieve energy saving and consumption reduction.

[0030] This system is equipped with an equipment analysis unit so that it can comprehensively and accurately analyze the operation status of equipment in the park, discover potential problems in a timely manner, and provide a scientific basis for the optimized management and maintenance of park equipment, which not only improves the operating efficiency and safety of the equipment, but also significantly reduces operating costs.

[0031] The energy analysis unit is used to analyze the energy consumption in the park. The specific steps are as follows: Obtain the sub-item energy consumption data of each energy consumption, build a multivariate regression model, and analyze the impact of each factor on total energy consumption; Use the ARIMA model to predict the energy consumption trend in the next month and prepare countermeasures in advance; Apply K-means clustering algorithm to classify energy consumption characteristics of different buildings and floors and identify high energy consumption areas; The real-time energy consumption status and energy consumption percentage of each item in the park are displayed through web and mobile applications; Generate detailed energy consumption reports regularly to show the changing trends of key energy consumption indicators and abnormal event records; Collect feedback from park managers on energy consumption reports and continuously optimize energy consumption models; Adjust the operating parameters of energy-consuming equipment according to the analysis results of the energy consumption model to achieve energy saving and consumption reduction.

[0032] By setting up an energy analysis unit, this system can comprehensively and accurately analyze the energy consumption in the park, discover potential problems in a timely manner, and provide a scientific basis for energy-saving optimization. It not only improves energy utilization efficiency and economic benefits, but also significantly reduces carbon emissions, and promotes the development of park management towards intelligence and greenness.

[0033] The personnel analysis unit is used to provide park personnel with the distribution of personnel at each intersection and area in the park. The specific steps are as follows: Construct real-time personnel distribution heat maps at various intersections and areas in the park to intuitively display the density and flow direction of personnel in different time periods; Analyze the movement paths of personnel within the park, identify high-frequency routes and hot spots, and thus optimize traffic planning and facility layout; Statistics on the average stay time of staff in different areas, evaluate the attractiveness and utilization efficiency of each area, provide reference for the resource allocation of the park, make the various resources of the park more reasonably distributed, and improve the utilization efficiency of park resources to a certain extent; Study the peak hours of daily, weekly and monthly personnel flows, and prepare emergency plans and resource allocation in advance to avoid congestion and safety hazards; Generate detailed personnel distribution reports regularly to show the changing trends of key indicators and records of abnormal events; Collect feedback from building managers and continuously optimize resource distribution within the park.

[0034] This system is equipped with a personnel analysis unit, so that the park can optimize the layout of facilities and the distribution of various resources within the park according to personnel hot spots, thereby improving the utilization efficiency of park resources to a certain extent.

[0035] The vehicle analysis unit is used to optimize the driving routes of vehicles in the park, and the specific steps are as follows: Use traffic simulation software to build a traffic model within the park, input real-time personnel distribution and vehicle traffic data, and simulate traffic flow changes under different driving routes; Apply Dijkstra algorithm and reinforcement learning method to dynamically calculate the optimal driving route; Display optimized driving routes and provide real-time navigation guidance through web and mobile applications; Collect feedback from drivers and pedestrians to continuously improve traffic route optimization plans.

[0036] This system is equipped with a vehicle analysis unit, which can optimize driving routes according to the distribution of people at intersections within the park, ensuring smooth, safe and efficient traffic. It not only improves the management level and safety of the park, but also significantly improves user experience and service quality, and promotes the development of park management towards intelligence and refinement.

[0037] The evaluation and optimization module is used to generate a corresponding management plan according to the analysis results of the data analysis module. The evaluation and optimization module generates a corresponding management plan according to the analysis results of the data analysis module. The specific process is as follows: Identify equipment health status, energy consumption distribution, personnel density and flow direction, and traffic flow changes; Define specific goals of management plans based on identifying equipment health status, energy consumption distribution, personnel density and flow direction, and traffic flow changes; Select and design corresponding management plans based on the identification of equipment health status, energy consumption distribution, personnel density and flow direction, traffic flow changes and specific goals; Predict the implementation effect of management plans and evaluate their feasibility through simulation and cost-benefit analysis; Implement the management plan that passes the evaluation and collect feedback on the management plan; Continuously optimize management solutions through user feedback.

[0038] By setting up an evaluation and optimization module, this system can generate scientific and reasonable management plans based on the analysis results of the data analysis module to ensure the effectiveness and sustainability of park management.

[0039] Second, refer to Figure 6 , a smart building management method based on digital twins, applied to the above management system, comprises the following steps: Obtain the park management data of the park; The park management data is transmitted to the edge computing node for pre-processing before being uploaded to the cloud server; Analyze the pre-processed park management data through the data analysis module; The evaluation and optimization module generates corresponding management plans based on the analysis results of the data analysis module.

[0040] The above description of the embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A smart building management system based on digital twins, characterized in that: include: Cloud servers; A data acquisition module, wherein the data acquisition module is used to acquire park management data; A data transmission module, which is used to transmit the park management data to the edge computing node for pre-processing and then upload it to the cloud server; A data analysis module, which is used to analyze the pre-processed park management data; An evaluation and optimization module is used to generate a corresponding management plan based on the analysis results of the data analysis module.

2. According to claim 1, a smart building management system based on digital twins is characterized in that: The park management data includes personnel data, equipment data, vehicle data and energy data in the park. The personnel data is obtained through cameras and access control systems; the equipment data is obtained through Internet of Things sensors; the vehicle data is obtained through cameras, license plate recognition and parking management systems; and the energy data is obtained from electricity meters and water meters in the park.

3. According to claim 1, a smart building management system based on digital twins is characterized in that: The data transmission module is used to transmit the park management data to the edge computing node for pre-processing and then upload it to the cloud server. The specific process is as follows: Data packaging: The data transmission module reads the park management data from the local cache, packages it according to the set rules, and generates data packets that comply with the transmission protocol; Data encryption: SSL / TLS protocol is used to encrypt the park management data to ensure that the park management data will not be eavesdropped or tampered with during network transmission; Data transmission, data packets are sent to edge computing nodes through wireless communication technology; Data reception and preprocessing: After receiving the data, the edge computing node performs preliminary processing such as decryption, analysis, noise filtering, and data compression; Data upload, the preprocessed data is uploaded to the cloud server through a secure channel.

4. According to claim 1, a smart building management system based on digital twins is characterized in that: The data analysis module includes an equipment analysis unit, an energy analysis unit, a personnel analysis unit and a vehicle analysis unit.

5. The digital twin-based smart building management system according to claim 4 is characterized in that: The equipment analysis unit is used to analyze the operation status of equipment in the park. The specific steps are as follows: Obtain the average temperature, maximum pressure, and vibration frequency characteristics of the device to build the health index of the device; Use the LSTM model to predict the temperature change trend in the next week and prepare countermeasures in advance; Apply the isolation forest algorithm to detect abnormal data points and promptly warn of potential failures; Display the real-time status and health score of the device through web and mobile applications; Generate equipment operation reports regularly to show the changing trends of key equipment indicators, abnormal event records, and maintenance recommendations; Collect feedback from frontline operation and maintenance personnel based on operation reports, and continuously optimize the calculation formula and prediction model of the health index; Adjust the operating parameters of the equipment according to the analysis results of the prediction model to achieve energy saving and consumption reduction.

6. The digital twin-based smart building management system according to claim 4 is characterized in that: The energy analysis unit is used to analyze the energy consumption in the park. The specific steps are as follows: Obtain the sub-item energy consumption data of each energy consumption, build a multivariate regression model, and analyze the impact of each factor on total energy consumption; Use the ARIMA model to predict the energy consumption trend in the next month and prepare countermeasures in advance; Apply K-means clustering algorithm to classify energy consumption characteristics of different buildings and floors and identify high energy consumption areas; The real-time energy consumption status and energy consumption percentage of each item in the park are displayed through web and mobile applications; Generate detailed energy consumption reports regularly to show the changing trends of key energy consumption indicators and abnormal event records; Collect feedback from park managers on energy consumption reports and continuously optimize energy consumption models; Adjust the operating parameters of energy-consuming equipment according to the analysis results of the energy consumption model to achieve energy saving and consumption reduction.

7. The digital twin-based smart building management system according to claim 4 is characterized in that: The personnel analysis unit is used to provide park personnel with the distribution of personnel at each intersection and area in the park. The specific steps are as follows: Construct real-time personnel distribution heat maps at various intersections and areas in the park to intuitively display the density and flow direction of personnel in different time periods; Analyze the movement paths of personnel within the park and identify high-frequency routes and hot spots; Count the average length of stay of staff in different areas, evaluate the attractiveness and utilization efficiency of each area, and provide a reference for resource allocation in the park; Study the peak hours of daily, weekly and monthly personnel flows, and prepare emergency plans and resource allocation in advance to avoid congestion and safety hazards; Generate detailed personnel distribution reports regularly to show the changing trends of key indicators and records of abnormal events; Collect feedback from building managers and continuously optimize resource distribution within the park.

8. The digital twin-based smart building management system according to claim 7 is characterized in that: The vehicle analysis unit is used to optimize the driving routes of vehicles in the park, and the specific steps are as follows: Use traffic simulation software to build a traffic model within the park, input real-time personnel distribution and vehicle traffic data, and simulate traffic flow changes under different driving routes; Apply Dijkstra algorithm and reinforcement learning method to dynamically calculate the optimal driving route; Display optimized driving routes and provide real-time navigation guidance through web and mobile applications; Collect feedback from drivers and pedestrians to continuously improve traffic route optimization plans.

9. The digital twin-based smart building management system according to claim 8, characterized in that: The evaluation and optimization module generates a corresponding management plan based on the analysis results of the data analysis module. The specific process is as follows: Identify equipment health status, energy consumption distribution, personnel density and flow direction, and traffic flow changes; Define specific goals of management plans based on identifying equipment health status, energy consumption distribution, personnel density and flow direction, and traffic flow changes; Select and design corresponding management plans based on the identification of equipment health status, energy consumption distribution, personnel density and flow direction, traffic flow changes and specific goals; Predict the implementation effect of management plans and evaluate their feasibility through simulation and cost-benefit analysis; Implement the management plan that passes the evaluation and collect feedback on the management plan; Continuously optimize management solutions through user feedback.

10. A smart building management method based on digital twins, characterized in that: The management system according to any one of claims 1 to 9 comprises the following steps: Obtain the park management data of the park; The park management data is transmitted to the edge computing node for pre-processing before being uploaded to the cloud server; Analyze the pre-processed park management data through the data analysis module; The evaluation and optimization module generates corresponding management plans based on the analysis results of the data analysis module.

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