Generation method and device of smart community digital twin interaction system

Abstract

The invention discloses a method and a device for generating a smart community digital twin interaction system. The method comprises the following steps: acquiring information data of each physical entity of a community; constructing a smart community three-dimensional model according to the information data; associating the physical entity with a virtual object corresponding to the physical entity in the three-dimensional model to enable the physical entity and the virtual object to form a mapping relation; designing an interaction logic and an interaction interface of the user and the three-dimensional model according to the mapping relation; according to the interaction logic and the interaction interface, generating an initial smart community digital twin interaction system; collecting feedback of the user in the initial intelligent community digital twin interaction system; and iteratively optimizing the interaction logic and the interaction interface according to the feedback, and generating the intelligent community digital twin interaction system. According to the intelligent community digital twin interaction system generated by the method, the community management efficiency can be remarkably improved, the life experience of residents is improved, and the sustainable development of the community is promoted.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and device for generating a digital twin interactive system for a smart community. Background Art

[0002] Within the framework of existing smart community interactive technologies, the single design of the user interface has become a bottleneck for improving user experience, limiting the depth and breadth of users' exploration of community information. The current system mainly relies on static text and basic graphics to convey information. This traditional display method not only reduces the efficiency of information transmission, but also makes it lengthy and inefficient for users to find key information in massive data, significantly increasing the cognitive burden of users. As a result, it is difficult for users to quickly grasp the real-time dynamics of the community, which seriously affects their ability to participate in the intelligent management of the community and enjoy personalized services. Summary of the invention

[0003] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies in the prior art and propose a method and device for generating a digital twin interactive system for a smart community. The method can generate a digital twin interactive system for a smart community so that community residents can participate in community intelligent management and enjoy personalized services.

[0004] In a first aspect, the present invention provides a method for generating a smart community digital twin interaction system, the method comprising the following steps:

[0005] Step S1: Obtain information data of each physical entity in the community;

[0006] Step S2: constructing a three-dimensional model of a smart community based on the information data;

[0007] Step S3: Associating the physical entity with a virtual object in the three-dimensional model corresponding to the physical entity, so that a mapping relationship is formed between the physical entity and the virtual object;

[0008] Step S4: designing the interaction logic and interaction interface between the user and the three-dimensional model according to the mapping relationship;

[0009] Step S5: generating an initial smart community digital twin interaction system according to the interaction logic and interaction interface;

[0010] Step S6: Collect user feedback in the initial smart community digital twin interaction system; and iteratively optimize the interaction logic and interaction interface based on the feedback to generate a smart community digital twin interaction system.

[0011] Furthermore, the step S1 specifically includes the following steps:

[0012] Step S11: Obtain a sample set;

[0013] Step S12: Based on the sample set, the BERT model or the GPT model is trained and tuned to obtain an acquisition model;

[0014] Step S13: Acquire information data of each physical entity in the community through the acquisition model.

[0015] Furthermore, the step S4 specifically includes the following steps:

[0016] According to the mapping relationship, design a user input type; and according to the mapping relationship, design a triggering of an alarm event;

[0017] Wherein, the user input type includes voice command, and / or click interaction, and / or touch interaction; the alarm event includes a flood alarm event and a fire alarm event;

[0018] Perform community scene status switching according to the user input type and the alarm event;

[0019] The community scene status is visualized to complete the design of the interaction logic and interaction interface between the user and the three-dimensional model.

[0020] Furthermore, the community scene status includes: surveillance camera focus status, surveillance camera multi-camera focus status, alarm focus status, alarm multi-camera focus status, smart lamp pole focus status;

[0021] Wherein, the multi-camera focusing state of the surveillance camera is achieved by multi-camera focusing;

[0022] The multi-camera focusing is realized, and the realization specifically includes the following steps:

[0023] Step B1: determining the geometric center coordinates of the target camera in a multi-camera focusing state; and determining the height h of the target camera;

[0024] The geometric center coordinates (x center , z center ) is calculated as follows:

[0025]

[0026] Among them, (x center , z center ) is the geometric center coordinate, (x, z) is the three-dimensional space X and Z axis coordinates of each camera position; m represents the number of cameras;

[0027] The calculation formula of the height h of the target camera is as follows:

[0028] h=d / (tan(w 1 +w 2 )-tan(w 1 ));

[0029] Where d is the distance between the geometric center and the z-axis of the target camera position;

[0030] w 1 W is the angle between the lower edge of the target camera FOV and the negative direction of the vertical y axis. 2 is the value of the upper and lower angles of the target camera FOV; tan() represents the tangent trigonometric function;

[0031] The value of d is obtained by the maximum distance between all the machine positions and the geometric center point, and its calculation formula is as follows:

[0032]

[0033] Among them, x 0 , x 1 , ..., x m etc. are the X-axis coordinates of each camera position, z 0 , z 1 , ..., z m etc. are the Z-axis coordinates of the positions of the camera positions; c , z c The value is the X and Z axis coordinates of the geometric center;

[0034] Step B2: According to the geometric center coordinates and the height h of the target camera, the distance between the geometric centers is adjusted to achieve multi-camera focusing.

[0035] Furthermore, the information data specifically includes:

[0036] Service facility POI information data, building information data, road information data, IoT device information data, and green belt information data;

[0037] The step S2 specifically includes:

[0038] Based on the service facility POI information data, build a three-dimensional model of service facilities in the smart community; and,

[0039] Build a 3D building model of the smart community based on building information data; and,

[0040] Build a 3D road model for smart communities based on road information data; and

[0041] Build a 3D model of IoT devices in a smart community based on IoT device information data; and,

[0042] Based on the green belt information data, a three-dimensional model of the green belt of the smart community is constructed.

[0043] Furthermore, the service facility POI information data includes:

[0044] Supermarket geographic information data, express station geographic information data, bank geographic information data, and bus station geographic information data;

[0045] The three-dimensional model of service facilities in the smart community is constructed based on the service facility POI information data, which specifically includes:

[0046] According to the supermarket geographic information data, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the supermarket virtual scene map; and,

[0047] According to the geographic information data of the express station, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the virtual scene map of the express station; and,

[0048] According to the bank's geographic information data, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the bank's virtual scene map; and,

[0049] According to the geographic information data of the bus station, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the virtual scene map of the bus station.

[0050] Furthermore, the three-dimensional building model of the smart community is constructed based on the building information data, which specifically includes the following steps:

[0051] Obtain GIS data from building information data;

[0052] Determining the geographic coordinates of the building based on the GIS data;

[0053] According to the preset reference points, the building geographic coordinates are converted into three-dimensional building space coordinates;

[0054] The coordinate conversion formula is as follows:

[0055]

[0056] y=y 0

[0057]

[0058] in,

[0059] θ is the angle between the direction of the three-dimensional building space coordinate system and the direction of the building geographic coordinate system; sin() is the sine function; cos() is the cosine function;

[0060] (x, y, z) is the three-dimensional building space coordinate system;

[0061] (x 0 ,y 0 , z 0 ) is the building geographic coordinate system;

[0062] w is the width of the three-dimensional building space coordinates;

[0063] h is the height of the three-dimensional building space coordinates;

[0064] w 0 is the width of the building’s geographic coordinates;

[0065] h 0 is the height of the building's geographic coordinates;

[0066] n is the scale ratio between the building geographic coordinates and the three-dimensional building space coordinates, and the value range is n>=1;

[0067] According to the three-dimensional building space coordinates, a three-dimensional building model is generated at a corresponding position of the virtual scene, thereby constructing a three-dimensional building model of the smart community;

[0068] Among them, the building three-dimensional model includes the building three-dimensional model, the floor three-dimensional model and the room three-dimensional model.

[0069] Furthermore, based on the road information data, a three-dimensional road model of the smart community is constructed, which specifically includes the following steps:

[0070] Obtain road GIS data based on road information data;

[0071] According to the road GIS data, the coordinates of the road network points are obtained;

[0072] Convert the coordinates of road network points from geographic coordinates to three-dimensional scene space coordinates;

[0073] The three-dimensional scene space coordinates are connected through automated point connections to generate a road model to complete the construction of a three-dimensional road model for the smart community.

[0074] Furthermore, a three-dimensional model of IoT devices in a smart community is constructed based on IoT device information data;

[0075] The three-dimensional model of the IoT device of the smart community includes a three-dimensional model of a lamp pole of the smart community;

[0076] The construction of the three-dimensional model of the lamp pole of the smart community specifically includes the following steps: Step A1: starting the modeling software;

[0077] Step A2: creating a lamp pole model in the modeling software;

[0078] Step A3: marking a first marked measuring point corresponding to the actual PM2.5 measuring point in the lamp pole model; and marking a second marked measuring point corresponding to the actual temperature measuring point in the virtual lamp pole;

[0079] Step A4: obtaining a PM2.5 empirical value according to the PM2.5 value read at the first marked measuring point; and obtaining a temperature empirical value according to the temperature value read at the second marked measuring point;

[0080] PM2.5 experience valuef pm2.5 The expression is as follows:

[0081]

[0082] in,

[0083] V pm2.5 The PM2.5 value read at the first marked measuring point;

[0084] min() is the minimum function;

[0085] Temperature experience value f T The expression is as follows:

[0086]

[0087] Where T is the temperature value read at the second marked measuring point;

[0088] Step A5: Calculating a fire identification value based on the PM2.5 empirical value and the temperature empirical value;

[0089] The calculation formula of the fire identification value is as follows:

[0090] R=a*fp m2.5 +b*fT;

[0091] in,

[0092] R is the fire identification value;

[0093] a is the weighted value of PM2.5;

[0094] b is the temperature weighted value;

[0095] f T is the empirical value of temperature;

[0096] f pm2.5 It is the PM2.5 experience value;

[0097] Step A6: constructing a lamp pole identification according to the fire identification value;

[0098] Wherein, if the fire identification value exceeds the warning threshold, the lamp pole mark is a warning mark;

[0099] Step A7: Integrate the lamp pole logo into the lamp pole model for display, so as to complete the construction of the three-dimensional model of the lamp pole in the smart community.

[0100] In a second aspect, the present invention provides a device for generating a smart community digital twin interactive system, the device comprising:

[0101] An acquisition unit, used to acquire information data of various physical entities in the community;

[0102] A construction unit, connected to the acquisition unit, for constructing a three-dimensional model of a smart community according to the information data;

[0103] an associating unit, connected to the constructing unit, and configured to associate the physical entity with a corresponding virtual object in the three-dimensional model so that a mapping relationship is formed between the physical entity and the virtual object;

[0104] A design unit, connected to the association unit, for designing an interaction logic and an interaction interface between a user and a three-dimensional model according to the mapping relationship;

[0105] A generation unit, connected to the design unit, for generating an initial smart community digital twin interaction system according to the interaction logic and interaction interface;

[0106] A processing unit is connected to the generating unit and is used to collect user feedback in the initial smart community digital twin interactive system; and is used to iteratively optimize the interactive logic and interactive interface according to the feedback to generate a smart community digital twin interactive system.

[0107] Beneficial effects of the present invention:

[0108] 1. The smart community digital twin interactive system generated by the present invention can enable community residents to participate in community intelligent management and enjoy personalized services, thereby significantly improving the efficiency of community governance, improving residents' life experience, promoting the sustainable development of the community, and providing a solid basic platform for the construction of future smart cities.

[0109] 2. The present invention enables users to obtain the latest dynamic information in the community through real-time data collection and model updating, thereby ensuring the timeliness and accuracy of the information.

[0110] 3. The present invention provides an intuitive visual effect through a three-dimensional model, so that users can better understand the community layout and resource allocation, and enhance their sense of participation and experience.

[0111] 4. The present invention can perform personalized optimization according to user behavior, provide services that meet user needs, and improve user satisfaction.

[0112] 5. The present invention provides multiple interaction modes, and the designed interaction logic can allow users to interact with the three-dimensional model in multiple ways, thereby satisfying the usage habits and preferences of different users.

[0113] 6. The present invention supports managers in making scientific decisions and improves the level of intelligent community management through analysis and visualization of community data.

[0114] 7. The present invention can improve the participation of users in community management and activities, and enhance community cohesion and sense of belonging.

[0115] 8. The present invention can continuously collect and analyze user feedback content, can continuously adapt to user needs, optimize functions and interfaces, and ensure a positive interaction between technology and users. BRIEF DESCRIPTION OF THE DRAWINGS

[0116] Figure 1 Schematic diagram of a method for generating a digital twin interactive system for a smart community in an embodiment of the present invention;

[0117] Figure 2 It is a framework diagram of a method for generating a smart community digital twin interactive system in an embodiment of the present invention;

[0118] Figure 3 This is a flowchart for implementing the large model voice interaction module in an embodiment of the present invention;

[0119] Figure 4 A flowchart for implementing a three-dimensional scene interaction module in an embodiment of the present invention;

[0120] Figure 5 A schematic diagram of a directed graph structure of a three-dimensional scene switching process of a three-dimensional scene interaction module in an embodiment of the present invention;

[0121] Figure 6 Schematic diagram of camera positions in an embodiment of the present invention;

[0122] Figure 7 Schematic diagram of a generating device of a smart community digital twin interactive system in an embodiment of the present invention;

[0123] Among them, the figure numbers are: 10, acquisition unit, 20, construction unit, 30, association unit, 40, design unit, 50, generation unit, 60, processing unit. DETAILED DESCRIPTION

[0124] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0125] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0126] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0127] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0128] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0129] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0130] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0131] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0132] Embodiment 1:

[0133] like Figure 1 As shown, this embodiment provides a method for generating a smart community digital twin interaction system, and the method includes the following steps:

[0134] Step S1: Obtain information data of each physical entity in the community.

[0135] When obtaining information data on various physical entities in the community, it includes buildings (such as houses, shops and office buildings), infrastructure (such as roads and bridges), public facilities (such as schools, hospitals and parks), public service equipment (such as trash cans and seats), water supply, power supply and gas supply facilities, natural environment (such as rivers and green spaces), security monitoring facilities (such as cameras and alarms), and transportation tools (such as public transportation vehicles and shared bicycles).

[0136] Specifically, step S1 includes the following steps:

[0137] Step S11: Obtain a sample set;

[0138] Step S12: Based on the sample set, the BERT model or the GPT model is trained and tuned to obtain an acquisition model;

[0139] Step S13: Acquire information data of each physical entity in the community through the acquisition model.

[0140] Step S2: Construct a three-dimensional model of a smart community based on the information data.

[0141] Step S3: Associating the physical entity with a virtual object in the three-dimensional model corresponding to the physical entity, so that a mapping relationship is formed between the physical entity and the virtual object.

[0142] Step S4: Designing the interaction logic and interface between the user and the three-dimensional model according to the mapping relationship.

[0143] According to the mapping relationship, the interaction logic between the user and the 3D model includes that after the user enters the interface, the system automatically loads the initial 3D model, and the user can rotate, zoom, and translate by dragging the mouse or using touch gestures; when clicking a specific object, the system highlights the object and pops up an information window to display relevant parameters and status. Design the interaction interface between the user and the 3D model, where the interface design is divided into the main display area, information pane, and control panel. The control panel provides view switching, path navigation, and export sharing buttons to ensure that users can easily obtain information and operations, while providing real-time feedback and status indications throughout the interaction process to optimize the user experience.

[0144] Specifically, step S4 includes the following steps:

[0145] According to the mapping relationship, design a user input type; and according to the mapping relationship, design a triggering of an alarm event;

[0146] Wherein, the user input type includes voice command, and / or click interaction, and / or touch interaction; the alarm event includes a flood alarm event and a fire alarm event;

[0147] Perform community scene status switching according to the user input type and the alarm event;

[0148] The community scene status is visualized to complete the design of the interaction logic and interaction interface between the user and the three-dimensional model.

[0149] Furthermore, the community scene status includes: surveillance camera focus status, surveillance camera multi-camera focus status, alarm focus status, alarm multi-camera focus status, smart lamp pole focus status;

[0150] Wherein, the multi-camera focusing state of the surveillance camera is achieved by multi-camera focusing;

[0151] Implementing the multi-camera focusing method specifically includes the following steps:

[0152] Step B1: determining the geometric center coordinates of the target camera in a multi-camera focusing state; and determining the height h of the target camera;

[0153] The geometric center coordinates (x center , z center ) is calculated as follows:

[0154]

[0155] Among them, (x center , z center ) is the geometric center coordinate, (x, z) is the three-dimensional space X and Z axis coordinates of each camera position; m represents the number of cameras;

[0156] The calculation formula of the height h of the target camera is as follows:

[0157] h=d / (tan(w 1 +w 2 )-tan(w 1 ));

[0158] Where d is the distance between the geometric center and the z-axis of the target camera position;

[0159] w 1 W is the angle between the lower edge of the target camera FOV and the negative direction of the vertical y axis. 2 is the value of the upper and lower angles of the target camera FOV; tan() represents the tangent trigonometric function;

[0160] The value of d is obtained by the maximum distance between all the machine positions and the geometric center point, and its calculation formula is as follows:

[0161]

[0162] Among them, x 0 , x 1 , ..., x m etc. are the X-axis coordinates of each camera position, z 0 , z 1 , ..., z m etc. are the Z-axis coordinates of the positions of the camera positions; c , z c The value is the X and Z axis coordinates of the geometric center;

[0163] Step B2: According to the geometric center coordinates and the height h of the target camera, the distance between the geometric centers is adjusted to achieve multi-camera focusing.

[0164] The field of view (FOV) of a camera refers to the range of images that the camera can capture, usually expressed in degrees. The size of the field of view will directly affect the camera's field of view coverage area, which is divided into horizontal field of view, vertical field of view, and diagonal field of view.

[0165] Step S5: Generate an initial smart community digital twin interaction system based on the interaction logic and interaction interface.

[0166] According to the interactive logic and interactive interface, the initial smart community digital twin interactive system is designed to provide users with an intuitive and dynamic three-dimensional environment, where users can explore the community model through a smooth navigation experience and obtain detailed information on buildings and facilities in real time. The system interface includes a main display area for displaying three-dimensional models, an information pane for displaying relevant data of the selected object, and a control panel for view switching, path navigation, and export sharing functions. The entire system enhances user interaction through highlight effects and status indicators, allowing users to easily and efficiently manage and analyze various data of the smart community.

[0167] Step S6: Collect user feedback in the initial smart community digital twin interaction system; and iteratively optimize the interaction logic and interaction interface based on the feedback to generate a smart community digital twin interaction system.

[0168] As a specific implementation, the information data specifically includes:

[0169] Service facility POI information data, building information data, road information data, IoT device information data, and green belt information data;

[0170] The step S2 specifically includes:

[0171] Based on the service facility POI information data, build a three-dimensional model of service facilities in the smart community; and,

[0172] Build a 3D building model of the smart community based on building information data; and,

[0173] Build a 3D road model for smart communities based on road information data; and

[0174] Build a 3D model of IoT devices in a smart community based on IoT device information data; and,

[0175] Based on the green belt information data, a three-dimensional model of the green belt of the smart community is constructed.

[0176] As a specific implementation manner, the service facility POI information data includes:

[0177] Supermarket geographic information data, express station geographic information data, bank geographic information data, and bus station geographic information data;

[0178] The three-dimensional model of service facilities in the smart community is constructed based on the service facility POI information data, which specifically includes:

[0179] According to the supermarket geographic information data, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the supermarket virtual scene map; and,

[0180] According to the geographic information data of the express station, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the virtual scene map of the express station; and,

[0181] According to the bank's geographic information data, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the bank's virtual scene map; and,

[0182] According to the geographic information data of the bus station, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the virtual scene map of the bus station.

[0183] The EPSG-3857 coordinate system, or EPSG:3857, also known as "Web Mercator", is a widely used planar coordinate system, mainly used in online map services such as Google Maps and OpenStreetMap. This coordinate system converts the curved surface of the earth into a flat surface through the pseudo-Mercator projection, using meters as units, expressed in X (easting) and Y (northing) coordinates.

[0184] POI (Point of Interest) information refers to location data with specific functions or meanings at a specific geographical location, such as restaurants, shops, schools, hospitals, scenic spots, etc. POI information usually includes details such as the name, type, address, contact information, business hours, user reviews, etc. This information is widely used in map services, navigation applications and geographic information systems (GIS) to help users easily and quickly find and obtain services or facilities related to specific locations, thereby improving the convenience of travel and life.

[0185] As a specific implementation method, the three-dimensional building model of the smart community is constructed according to the building information data, which specifically includes the following steps:

[0186] Obtain GIS data from building information data;

[0187] Determining the geographic coordinates of the building based on the GIS data;

[0188] According to the preset reference points, the building geographic coordinates are converted into three-dimensional building space coordinates;

[0189] The coordinate conversion formula is as follows:

[0190]

[0191] y=y0

[0192]

[0193] in,

[0194] θ is the angle between the direction of the three-dimensional building space coordinate system and the direction of the building geographic coordinate system; sin() is the sine function; cos() is the cosine function;

[0195] (x, y, z) is the three-dimensional building space coordinate system;

[0196] (x 0 ,y 0 , z 0 ) is the building geographic coordinate system;

[0197] w is the width of the three-dimensional building space coordinates;

[0198] h is the height of the three-dimensional building space coordinates;

[0199] W 0 is the width of the building’s geographic coordinates;

[0200] h 0 is the height of the building's geographic coordinates;

[0201] n is the scale ratio between the building geographic coordinates and the three-dimensional building space coordinates, and the value range is n>=1;

[0202] According to the three-dimensional building space coordinates, a three-dimensional building model is generated at a corresponding position of the virtual scene, thereby constructing a three-dimensional building model of the smart community;

[0203] Among them, the building three-dimensional model includes the building three-dimensional model, the floor three-dimensional model and the room three-dimensional model.

[0204] As a specific implementation method, a three-dimensional road model of a smart community is constructed based on road information data, which specifically includes the following steps:

[0205] Obtain road GIS data based on road information data;

[0206] According to the road GIS data, the coordinates of the road network points are obtained;

[0207] Convert the coordinates of road network points from geographic coordinates to three-dimensional scene space coordinates;

[0208] The three-dimensional scene space coordinates are connected through automated point connections to generate a road model to complete the construction of a three-dimensional road model for the smart community.

[0209] GIS data (Geographic Information System data) refers to data used to describe and analyze geographic spatial characteristics and phenomena, including information such as topography, land use, transportation network, and population distribution.

[0210] As a specific implementation method, a three-dimensional model of IoT devices in a smart community is constructed based on IoT device information data;

[0211] The three-dimensional model of the IoT device of the smart community includes a three-dimensional model of a lamp pole of the smart community;

[0212] The construction of the three-dimensional model of the lamp pole of the smart community specifically includes the following steps: Step A1: starting the modeling software;

[0213] Step A2: creating a lamp pole model in the modeling software;

[0214] Step A3: marking a first marked measuring point corresponding to the actual PM2.5 measuring point in the lamp pole model; and marking a second marked measuring point corresponding to the actual temperature measuring point in the virtual lamp pole;

[0215] Step A4: obtaining a PM2.5 empirical value according to the PM2.5 value read at the first marked measuring point; and obtaining a temperature empirical value according to the temperature value read at the second marked measuring point;

[0216] PM2.5 experience valuef pm2.5 The expression is as follows:

[0217]

[0218] in,

[0219] V pm2.5 The PM2.5 value read at the first marked measuring point;

[0220] min() is the minimum function;

[0221] The expression of the temperature experience value fT is as follows:

[0222]

[0223] Where T is the temperature value read at the second marked measuring point;

[0224] Step A5: Calculating a fire identification value based on the PM2.5 empirical value and the temperature empirical value;

[0225] The calculation formula of the fire identification value is as follows:

[0226] R=a*fp m2.5 +b*fT;

[0227] in,

[0228] R is the fire identification value;

[0229] a is the weighted value of PM2.5;

[0230] b is the temperature weighted value;

[0231] f T is the empirical value of temperature;

[0232] f pm2.5 It is the PM2.5 experience value;

[0233] Step A6: constructing a lamp pole identification according to the fire identification value;

[0234] Wherein, if the fire identification value exceeds the warning threshold, the lamp pole mark is a warning mark;

[0235] Step A7: Integrate the lamp pole logo into the lamp pole model for display, so as to complete the construction of the three-dimensional model of the lamp pole in the smart community.

[0236] PM2.5 refers to particles with a diameter of 2.5 microns or less, which belong to suspended particulate matter (PM) in the air. Due to its tiny size, it can penetrate deep into the lungs and enter the blood, which may have serious effects on human health. PM2.5 usually comes from automobile exhaust, industrial emissions, construction, burning of fossil fuels, etc. Long-term exposure to PM2.5 environment may lead to respiratory diseases, cardiovascular problems and other health risks. Therefore, it has been widely concerned and monitored, becoming an important indicator for evaluating air quality.

[0237] The 3D model of IoT devices in the smart community includes the 3D model of the lamp poles in the smart community and other 3D models of IoT devices. The construction process of the other 3D models of IoT devices is basically the same as that of the 3D model of the lamp poles, as follows:

[0238] Step 1: Start the modeling software.

[0239] Step 2: Create a corresponding 3D model based on the device type.

[0240] Step 3: Mark the corresponding sensor measurement points.

[0241] Step 4: Read sensor data and calculate experience value.

[0242] Step 5: Calculate the identification value (such as fire, smoke, etc.) based on the empirical value.

[0243] Step 6: Construct an identification and make a status judgment (such as warning or normal).

[0244] Step 7: Integrate the logo into the corresponding device model for display.

[0245] like Figure 2 As shown in the figure, based on the voice interaction of the large model, the visual large screen display and the three-dimensional scene interaction system provide functions such as real-time monitoring, community surrounding query, alarm prompts and lamp pole equipment status monitoring. Through the visual large screen, users can view the real-time video stream, environmental data and surrounding facility information in the community, and conduct interactive queries conveniently; in the three-dimensional scene, users can intuitively browse the community model and obtain detailed information on various facilities, including the status of smart lamp poles and real-time data of the surrounding environment. The system also supports voice commands, allowing users to easily obtain the required information through natural interaction, improving the intelligent level of community management and the sense of participation of residents.

[0246] The following is a clear and complete description of the technical solution in this embodiment, and the specific steps are as follows:

[0247] Step 1: Carefully collect at least 100 question and answer samples about smart communities, such as the sample question "How many buildings does XXX community contain?" to ensure that the sample is representative. The expected return structure of each sample strictly follows the format of "answer text_visual data identifier: specific data_scene status instruction", for example: "XXX community has XX buildings_data display: community basic details_community panoramic view activated".

[0248] Step 2: Based on the above sample set, the large model is trained and tuned to ensure that the responses it generates can accurately conform to the preset format. Then, based on the clear system architecture requirements, a large model voice interaction module is established to support complex language understanding and command execution.

[0249] like Figure 3 As shown in the figure, this embodiment forms a complete interactive chain by inputting "question and answer samples + visualization data + interaction instructions" into the large model reasoning and combining speech recognition and speech synthesis. This process can not only improve the efficiency of information transmission, but also improve the user experience, making it easier for users to obtain the required information in the environment of the smart community and achieve more efficient interaction and services. The implementation process is as follows:

[0250] (1) Input data preparation

[0251] (1.1) Sample Questions and Answers

[0252] Definition: Question-answer samples are pre-collected and structured question-answer pairs, containing questions that users may ask and their corresponding answers.

[0253] Format: Each sample needs to follow a fixed format, including:

[0254] Answer text: Directly answer the user's question.

[0255] Visual data: Visual information related to the answer, such as charts, pictures, or references to data dashboards.

[0256] Interaction instructions: used to guide users' interactive behaviors on the interface.

[0257] For example:

[0258] “XXX community has 50 buildings_Visual data: Community building distribution map_Interactive command: View building details.”

[0259] (1.2) Visualize data

[0260] Definition: Visual data refers to information presented through charts, images, or other visual methods, which can help users better understand and analyze data.

[0261] Implementation: Visual data is usually generated on the backend or frontend, and corresponding graphics (such as bar charts, pie charts, heat maps, etc.) are drawn based on the specific attributes of the data.

[0262] (1.3) Interactive instructions

[0263] Definition: Interaction instructions are guidance provided by the system to users to help them perform specific operations.

[0264] Examples: Include commands such as "tap to see details" or "swipe to see more data."

[0265] (2) Voice input and recognition

[0266] (2.1) Speech Recognition

[0267] Process: The user inputs the question via voice, and the audio input is converted into text through the speech recognition module.

[0268] Tools: Use readily available speech recognition APIs (e.g. Google Speech-to-Text, Microsoft AzureSpeech, etc.) to convert speech to text in real time.

[0269] (2.2) Text consultation

[0270] Converted text: The speech recognition module converts the user's questions into text form for subsequent processing.

[0271] (3) Large model reasoning and dialogue

[0272] (3.1) Input to the large model

[0273] Data integration: Input the text of user consultation into the big model, combined with previously prepared question and answer samples, visualization data, and interaction instructions.

[0274] Reasoning processing: Large models (such as BERT, GPT series, etc.) reason about the input to generate relevant answer text, extract visual data and corresponding interactive instructions.

[0275] (3.2) Large Model Dialogue

[0276] Return content:

[0277] Answer text: The generated answer responds to the user's question and context.

[0278] Visual data: Provide visual content related to the answer, such as a recommended chart or infographic.

[0279] Interaction instructions: Give follow-up operation suggestions and prompt users on how to interact further.

[0280] (4) Output and user interaction

[0281] (4.1) User interface display

[0282] Information display: Based on the output of the large model, the answer text, visual data, and interactive instructions are displayed on the user interface. For example:

[0283] Display the generated answer in the chat window;

[0284] Insert relevant visual charts on the page;

[0285] Display interactive command buttons for users to select subsequent operations.

[0286] (4.2) Speech Synthesis

[0287] Convert the answer text into speech: Through speech synthesis technology, the generated answer text is converted into speech for further interaction with the user. Commonly used speech synthesis tools (such as Google Text-to-Speech, IBM Watson Text to Speech, etc.) can achieve this function.

[0288] Output Audio: The synthesized speech is played through speakers or headphones so that the user can hear the response.

[0289] (4.3) User Interaction

[0290] Continue interaction: Users can perform follow-up actions based on the visualized data and interactive instructions, such as asking new questions, viewing specific data, or providing feedback.

[0291] Closed-loop feedback: The system can continue to learn from users’ interactive behaviors and optimize future question-answering processes and results.

[0292] Step 3: Use manual or automated technology to carefully construct a 3D virtual model of the community, covering elements such as buildings, roads, green belts, monitoring systems, and smart lighting, and accurately map them to the actual geographic location to achieve consistency between virtual and reality. The scene is subdivided into multiple levels such as panorama, floor, and single room to facilitate multi-level interactive operations.

[0293] This embodiment provides a specific operation:

[0294] To obtain information, first collect the GIS geographic information data of the corresponding community, community building schematics and road schematics, building cross-section photos, lamp pole perspective photos and other relevant information;

[0295] Manual modeling of general objects, where humans use modeling software to manually complete the 3D models of standard buildings in the community, 3D models of IoT devices, 3D models of roads, 3D models of light poles, 3D models of standard rooms, etc. according to schematic diagrams, photos, etc.;

[0296] Building automation generation uses the geographic coordinates of the polygonal building outline in the GIS data to sum up the geographic coordinates of the center point of the outline. The geographic coordinates are converted into three-dimensional scene space coordinates, and a three-dimensional model of a standard building is generated at the corresponding position. The three-dimensional model orientation of the building needs to be adjusted according to the community schematic diagram. The default three-dimensional scene is that the buildings are at the same height within the community scene range. Then, when the geographic information coordinates are converted into three-dimensional scene space coordinates, the formula is as follows:

[0297]

[0298] y=y 0

[0299]

[0300] Where θ is the angle between the three-dimensional space coordinate system and the geographic coordinate system. In general, θ is 0. (x, y, z) is the three-dimensional scene space coordinate of the target object. 0 ,y 0 , z 0 ) is the 3D scene space coordinate of the reference object. (w,h) is the geographic information coordinate of the target object, (w 0 ,h 0 ) is the geographic information coordinate of the reference object, n is the scale ratio of the real world and 3D time, and the value range is n>=1. When using the formula for calculation, it is necessary to find the same reference point in the 3D scene coordinate system and the geographic information coordinate system for calculation. Generally, the gate of the community is selected as the reference object;

[0301] Automatic road generation uses the road network point data in GIS data to convert the point coordinates from geographic coordinates to three-dimensional scene space coordinates. Use automatic point connection to generate a road model to complete the automatic connection generation of roads inside and around the community. It should be noted that the data generally does not contain road width information, and the width of the road needs to be adjusted manually;

[0302] IoT device generation: Based on the obtained IoT device distribution map, if the distribution map contains precise location information such as longitude and latitude, it can be automatically generated on the scene after conversion through coordinate formulas. Otherwise, it needs to be placed manually according to the schematic diagram.

[0303] The green environment of the community is automatically generated, and bushes, grass, trees and other three-dimensional objects are randomly generated on the blank ground. The green environment of the community is automatically generated.

[0304] For the construction of floors inside a building, if the order of rooms inside the floors is complex, it is necessary to manually arrange the rooms inside the floors according to the floor plan inside the building. If the arrangement of rooms on the floors is relatively simple, they can be arranged and generated in a distribution method similar to the real situation, such as side by side or single column.

[0305] Step 4: In the three-dimensional scene, realize the precise binding of physical entities and virtual objects, such as buildings, floors, rooms, alarms, lamp poles, etc., to ensure the dynamic synchronization of data and models, and create an accurate digital twin image. The three-dimensional interactive model needs to be configured with corresponding tag attributes, and bound through the tag attributes and the tag attributes of the Internet of Things in the database, so that the virtual objects in the scene and the objects in reality are bound. Among them, the camera in the Internet of Things device reads the rotation angle in the camera measurement point data and synchronously updates the rotation angle of the virtual camera in the scene to achieve the effect of virtual-real synchronization of the camera device. The smart lamp pole can achieve the effect of virtual-real synchronization of the lamp pole by reading the power-on status of the lamp pole in the smart lamp pole measurement point data, the value of the brightness of the lamp pole bulb, and modifying the power-on status of the lamp pole and the brightness of the lamp pole bulb model in the virtual scene.

[0306] Step 5: Use visual effects to enhance the presentation of scene status, such as building highlighting and camera focus tracking. Multi-camera focus is achieved by calculating the average spatial coordinates of all cameras to ensure full coverage of the viewing angle. The optimal height and position of the camera are calculated through mathematical formulas to ensure that all objects of interest are clearly visible. The multi-camera focus state is achieved by summing up the corresponding coordinates of the X-axis and Z-axis of each camera in the three-dimensional space, obtaining its geometric center coordinates, and moving the camera focus point to the geometric coordinates. Specific formula: Where (x center , z center ) is the geometric center coordinate, (x, z) is the three-dimensional space X, Z axis coordinate of each virtual object. At the same time, the distance of the camera to the focus point needs to be adjusted to ensure that the viewing angle includes all virtual objects in the camera position. The specific implementation method is based on the degree of the camera field of view (FOV), such as Figure 6 As shown, the height value of the camera is obtained.

[0307] h is the height of the camera, d is the distance between the geometric center and the z-axis of the closest position to the camera, w 1 is the angle between the lower edge of the camera FOV and the negative direction of the vertical y axis, w 2 is the value of the upper and lower angles of FOV. According to the formula:

[0308] h=d / (tan(W i +w 2 )-tan(W 1 ))

[0309] The value of the camera height can be obtained. 2 The value of can be obtained by obtaining the upper and lower FOV values ​​of the camera, that is, w 2 =FOV / 2. Where w 1 +w 2 The value of can be obtained by the angle between the camera's facing direction and the vertical direction. The value of d is obtained based on the farthest distance between all camera positions and the geometric center point. The specific formula is as follows:

[0310]

[0311] x 0 , x 1 , x 2 etc. are the X-axis coordinates of each machine position, z 0 , z 1 , z 2 etc. are the Z-axis coordinates of each machine position. c , z c The values ​​are the X and Z coordinates of the geometric center. When entering the multi-camera focus state, without changing the camera rotation angle, adjust the scene camera's gaze point to the geometric center, and move the camera to a height of h, and a distance from the geometric center of h*tan(w 1 +w 2 ). To achieve the highlight effect of camera focus. Community scene status includes: surveillance camera focus status, surveillance camera multi-camera focus status, alarm focus status, alarm multi-camera focus status, smart lamp pole focus status.

[0312] Step 6: Design a scene switching logic diagram based on the attached figure, and use the Dijkstra algorithm to find the path to ensure smooth animation switching. For example, from the room state to the floor, the panoramic view, and finally to the focus state of a specific device, to achieve seamless connection across scenes.

[0313] As a specific implementation scheme, Figure 4 and Figure 5 As shown in the figure, the user's current scene state is the house state. After observing the apartment introduction and related visualization information, the user requests to view the lamp pole equipment near a residential building through the community large model dialogue. Then, the large model returns the corresponding interaction instructions, and the scene state switching path is: house state → floor state → community panoramic display state → lamp pole equipment multi-camera focus state. When the target scene state is finally reached, the relevant visualization module will be activated.

[0314] Step 7: Construct visualization modules in each scene state, and give different content display to different scene states. During the scene state switching process, an activation request is received to display the data of the visualization module. In this way, the visualization module and each functional module cooperate and interact with each other.

[0315] Step 8: Build a real-time monitoring module, access the monitoring system through the network interface, and bind different camera streaming links to the corresponding virtual monitoring camera positions. At the same time, the acquired streaming media needs to be recognized in real time by various image algorithms in the system. This includes human posture recognition to identify whether a person has fallen, and electric vehicle target detection algorithms to identify electric vehicles. Among them, electric vehicle target detection mainly identifies cameras in the corridors of floors to prevent electric vehicles from going upstairs.

[0316] Step 9: Collect geographic information data of various supermarkets, express delivery stations, banks, and bus stations within 500 meters around the community, adapt the virtual scene map through the EPSG-3857 coordinate system, convert according to the reference object coordinates and the virtual scene coordinate system, and complete the placement and configuration of each point.

[0317] Step 10: Build an alarm prompt module, access the alarm device IoT system through the network interface, and obtain the alarm device information in real time through real-time network link requests. Monitor the values ​​in real time, and when they exceed the standard value, issue an alarm reminder in the visualization module. When the user clicks or voice requests to view, the interactive command and specific device number will be sent to the 3D scene module and visualization module, which will display the location of the alarm device and the current device measurement point value of the alarm device respectively.

[0318] Step 11: Build the smart light pole module, access the smart light pole IoT system through the network interface, and obtain the smart light pole measurement point information in real time through real-time network link requests. Perform algorithm calculations on the measurement point information, and use the PM2.5 readings and temperature readings to implement the weighted algorithm.

[0319]

[0320]

[0321] R=a*f pm2.5 +b*f T

[0322] Where R refers to the fire identification value, a is the weighted value of PM2.5, and V pm2.5 is the PM2.5 value, f pm2.5 is the empirical formula for calculating PM2.5 values, b is the weighted value of temperature detection data, y is the temperature detection value, and f TThis is an empirical formula for calculating temperature values. The weighted values ​​of a and b in this algorithm are empirical parameter values, usually a=0.5 and b=0.5. The normal value of PM2.5 is 0-50, and it is above 500 when a fire occurs. The normal outdoor temperature is 40 degrees, and it is above 100 degrees when a fire occurs. The warning threshold of this formula is 50: it can meet the situation that under the percentage system, the value of R is less than 10 under normal circumstances, and when there is a risk of fire, the value of R will be greater than 50. Therefore, through the real-time calculation of R, the temperature measurement point information and PM2.5 measurement point information of each lamp pole can be obtained. When the real-time calculation value of R exceeds the predicted value, an alarm reminder is issued in the visualization module. When the user clicks or voice requests to view, the interactive command and specific device number will be sent to the three-dimensional scene module and the visualization module, respectively displaying the position of the lamp pole and the current device measurement point value.

[0323] The above steps demonstrate the entire process from data preparation, model training to system integration, reflecting the systematicness and innovation of this embodiment, and providing a comprehensive and efficient technical solution for the construction of digital twin interactive systems in smart communities.

[0324] Embodiment 2:

[0325] like Figure 7 As shown, this embodiment provides a device for generating a smart community digital twin interaction system, the device comprising:

[0326] An acquisition unit 10 is used to acquire information data of various physical entities in the community;

[0327] A construction unit 20, connected to the acquisition unit 10, is used to construct a three-dimensional model of a smart community according to the information data;

[0328] an associating unit 30, connected to the constructing unit 20, and configured to associate the physical entity with a corresponding virtual object in the three-dimensional model so that a mapping relationship is formed between the physical entity and the virtual object;

[0329] A design unit 40, connected to the association unit 30, for designing the interaction logic and interaction interface between the user and the three-dimensional model according to the mapping relationship;

[0330] A generation unit 50, connected to the design unit 40, is used to generate an initial smart community digital twin interaction system according to the interaction logic and interaction interface;

[0331] The processing unit 60 is connected to the generating unit 50, and is used to collect user feedback in the initial smart community digital twin interactive system; and is used to iteratively optimize the interactive logic and interactive interface according to the feedback to generate a smart community digital twin interactive system.

[0332] The device in this embodiment can execute the method in embodiment 1.

[0333] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for generating a digital twin interactive system for a smart community, characterized in that: The method comprises the following steps: Step S1: Obtain information data of each physical entity in the community; Step S2: constructing a three-dimensional model of a smart community based on the information data; Step S3: Associating the physical entity with a virtual object in the three-dimensional model corresponding to the physical entity, so that a mapping relationship is formed between the physical entity and the virtual object; Step S4: designing the interaction logic and interaction interface between the user and the three-dimensional model according to the mapping relationship; Step S5: Generate an initial smart community digital twin interaction system according to the interaction logic and interaction interface; Step S6: Collect user feedback in the initial smart community digital twin interaction system; And, the interaction logic and interaction interface are iteratively optimized according to the feedback to generate a smart community digital twin interaction system.

2. The method for generating a smart community digital twin interactive system according to claim 1, characterized in that: The step S1 specifically includes the following steps: Step S11: Obtain a sample set; Step S12: Based on the sample set, the BERT model or the GPT model is trained and tuned to obtain an acquisition model; Step S13: Acquire information data of each physical entity in the community through the acquisition model.

3. The method for generating a smart community digital twin interactive system according to claim 1, characterized in that: The step S4 specifically comprises the following steps: According to the mapping relationship, design a user input type; and according to the mapping relationship, design a triggering of an alarm event; Wherein, the user input type includes voice command, and / or click interaction, and / or touch interaction; the alarm event includes a flood alarm event and a fire alarm event; Switching the community scene state according to the user input type and the alarm event; The community scene status is visualized to complete the design of the interaction logic and interaction interface between the user and the three-dimensional model.

4. The method for generating a smart community digital twin interactive system according to claim 3 is characterized in that: The community scene status includes: surveillance camera focus status, surveillance camera multi-camera focus status, alarm focus status, alarm multi-camera focus status, smart lamp pole focus status; Wherein, the multi-camera focusing state of the surveillance camera is achieved by multi-camera focusing; The multi-position focusing of the camera is realized, and specifically comprises the following steps: Step B1: determining the geometric center coordinates of the target camera in a multi-camera focusing state; and determining the height h of the target camera; The geometric center coordinates (x center , z center ) is calculated as follows: Among them, (x center , z center ) is the geometric center coordinate, (x, z) is the three-dimensional space X and Z axis coordinates of each camera position; m represents the number of cameras; The calculation formula of the height h of the target camera is as follows: h = d / (tan (w1 + w2) - tan (w1)); Where d is the distance between the geometric center and the z-axis of the target camera position; w1 is the angle between the lower edge of the target camera FOV and the negative direction of the vertical y axis, w2 is the value of the upper and lower angles of the target camera FOV; tan() represents the tangent trigonometric function; The value of d is obtained by the maximum distance between all the machine positions and the geometric center point, and its calculation formula is as follows: where x0, x1, ..., x m etc. are the X-axis coordinates of each camera position, z0, z1, ..., z m etc. are the Z-axis coordinates of the positions of the camera positions; c , z c The value is the X and Z axis coordinates of the geometric center; Step B2: According to the geometric center coordinates and the height h of the target camera, the distance between the geometric centers is adjusted to achieve multi-camera focusing.

5. The method for generating a smart community digital twin interactive system according to any one of claims 1 to 4, characterized in that: The information data specifically includes: Service facility POI information data, building information data, road information data, IoT device information data, and green belt information data; The step S2 specifically includes: Construct a 3D model of service facilities in a smart community based on the POI information data of service facilities; and Build a 3D building model of the smart community based on building information data; and, Build a 3D road model for smart communities based on road information data; and Build a 3D model of IoT devices in a smart community based on IoT device information data; and, Based on the green belt information data, a three-dimensional model of the green belt of the smart community is constructed.

6. The method for generating a smart community digital twin interactive system according to claim 5, characterized in that: The service facility POI information data includes: Supermarket geographic information data, express station geographic information data, bank geographic information data, and bus station geographic information data; The three-dimensional model of service facilities in the smart community is constructed based on the service facility POI information data, which specifically includes: According to the supermarket geographic information data, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the supermarket virtual scene map; and, According to the geographic information data of the express station, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the virtual scene map of the express station; and, According to the bank's geographic information data, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the bank's virtual scene map; and, According to the geographic information data of the bus station, the reference object coordinates and the virtual scene coordinates are converted through the EPSG-3857 coordinate system to obtain the virtual scene map of the bus station.

7. The method for generating a smart community digital twin interactive system according to claim 5, characterized in that: The step of constructing a three-dimensional building model of a smart community based on building information data specifically includes the following steps: Obtain GIS data from building information data; Determining the geographic coordinates of the building based on the GIS data; According to the preset reference points, the building geographic coordinates are converted into three-dimensional building space coordinates; The coordinate conversion formula is as follows: y=y0 in, θ is the angle between the direction of the three-dimensional building space coordinate system and the direction of the building geographic coordinate system; sin() is the sine function; cos() is the cosine function; (x, y, z) is the three-dimensional building space coordinate system; (x0, y0, z0) is the building geographic coordinate system; w is the width of the three-dimensional building space coordinates; h is the height of the three-dimensional building space coordinates; w0 is the width of the building’s geographic coordinates; h0 is the height of the building’s geographical coordinates; n is the scale ratio between the building geographic coordinates and the three-dimensional building space coordinates, and the value range is n>=1; According to the three-dimensional building space coordinates, a three-dimensional building model is generated at a corresponding position of the virtual scene, thereby constructing a three-dimensional building model of the smart community; Among them, the building three-dimensional model includes the building three-dimensional model, the floor three-dimensional model and the room three-dimensional model.

8. The method for generating a smart community digital twin interactive system according to claim 5, characterized in that: Based on the road information data, a three-dimensional road model of the smart community is constructed, which specifically includes the following steps: Obtain road GIS data based on road information data; According to the road GIS data, the coordinates of the road network points are obtained; Convert the coordinates of road network points from geographic coordinates to three-dimensional scene space coordinates; The three-dimensional scene space coordinates are connected through automated point connections to generate a road model to complete the construction of a three-dimensional road model for the smart community.

9. The method for generating a smart community digital twin interactive system according to claim 5, characterized in that: Build a three-dimensional model of IoT devices in a smart community based on IoT device information data; The three-dimensional model of the IoT device of the smart community includes a three-dimensional model of a lamp pole of the smart community; The construction of the three-dimensional model of the lamp poles in the smart community specifically includes the following steps: Step A1: Start the modeling software; Step A2: creating a lamp pole model in the modeling software; Step A3: marking a first marked measuring point corresponding to the actual PM2.5 measuring point in the lamp pole model; and marking a second marked measuring point corresponding to the actual temperature measuring point in the virtual lamp pole; Step A4: obtaining a PM2.5 empirical value according to the PM2.5 value read at the first marked measuring point; and obtaining a temperature empirical value according to the temperature value read at the second marked measuring point; PM2.5 experience valuef pm2.5 The expression is as follows: in, V pm2.5 The PM2.5 value read at the first marked measuring point; min() is the minimum function; Temperature experience value f T The expression is as follows: Where T is the temperature value read at the second marked measuring point; Step A5: Calculating a fire identification value based on the PM2.5 empirical value and the temperature empirical value; The calculation formula of the fire identification value is as follows: R=a*f pm2.5 +b*f T ; in, R is the fire identification value; a is the weighted value of PM2.5; b is the temperature weighted value; fT is the empirical value of temperature; f pm2.5 It is the PM2.5 experience value; Step A6: constructing a lamp pole identification according to the fire identification value; Wherein, if the fire identification value exceeds the warning threshold, the lamp pole mark is a warning mark; Step A7: Integrate the lamp pole logo into the lamp pole model for display, so as to complete the construction of the three-dimensional model of the lamp pole in the smart community.

10. A device for generating a digital twin interactive system for a smart community, characterized in that: The device comprises: An acquisition unit, used to acquire information data of various physical entities in the community; A construction unit, connected to the acquisition unit, for constructing a three-dimensional model of a smart community according to the information data; an associating unit, connected to the constructing unit, and configured to associate the physical entity with a corresponding virtual object in the three-dimensional model so that a mapping relationship is formed between the physical entity and the virtual object; A design unit, connected to the association unit, for designing an interaction logic and an interaction interface between a user and a three-dimensional model according to the mapping relationship; A generation unit, connected to the design unit, for generating an initial smart community digital twin interaction system according to the interaction logic and interaction interface; A processing unit is connected to the generating unit and is used to collect user feedback in the initial smart community digital twin interactive system; and is used to iteratively optimize the interactive logic and interactive interface according to the feedback to generate a smart community digital twin interactive system.

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