Smart city data intelligent fusion system

Abstract

The invention discloses a smart city data intelligent fusion system. The invention discloses a smart city data intelligent fusion system, and the system comprises a map information collection device which is used for obtaining the digital elevation model data of a target region, and constructing a three-dimensional scene basic model based on the digital elevation model data; according to the system, multi-source heterogeneous city management information formats are unified through the information standardization processing device, standardized information such as traffic, population, economy and energy is accurately rendered to corresponding preset data layers through the multi-dimensional scene rendering device, and finally the layers are overlaid on a unified three-dimensional scene basic model. The barrier of'data islands' among different departments is effectively broken, and deep integration and space coupling of cross-domain data are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of city management, in particular to a smart city data intelligent fusion system. BACKGROUND

[0002] In the construction of smart city, a large amount of multi-source and heterogeneous data (such as traffic flow video, energy consumption record, air quality monitoring value, etc.) is continuously generated in the fields of transportation, energy, environmental protection, population, economy, etc. However, these data are scattered in different departments and systems, and there are problems such as different formats, different interface standards, and different update frequencies, forming a serious "data island".

[0003] This "island" state makes it difficult to effectively coordinate and integrate cross-domain data. For example, the transportation department cannot conveniently use the real-time air quality data of the environmental protection department to analyze its impact on the traffic mode, and the data of different departments cannot be correlated and analyzed. This makes it difficult for city managers to obtain a comprehensive and multi-dimensional panoramic view of city operation, resulting in one-sided decision-making and low efficiency, which restricts the overall effectiveness of smart city management. SUMMARY

[0004] The summary part of the present application is used to introduce the concept in a simple form, which will be described in detail in the specific embodiment part. The summary part of the present application is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0005] As a first aspect of the present application, in order to solve the technical problems mentioned in the background part, some embodiments of the present application provide a smart city data intelligent fusion system, comprising:

[0006] A map information acquisition device is configured to acquire digital elevation model data of a target area and construct a three-dimensional scene base model based on the digital elevation model data;

[0007] A management information acquisition device is configured to acquire multi-source city management information, wherein the city management information includes traffic information representing traffic flow, population information representing resident population distribution, economic information representing economic activities, and energy information representing energy use;

[0008] An information standardization processing device is connected to the management information acquisition device and configured to perform standardization processing on the acquired city management information to generate standardized information with uniform format;

[0009] A multi-dimensional scene rendering device connected to the map information collection device and the information standardization processing device, the multi-dimensional scene rendering device being preconfigured with a plurality of data layers corresponding to the types of city management information, for rendering the standardized information into the corresponding data layers respectively, and superimposing each of the rendered layers on the three-dimensional scene base model to generate a three-dimensional scene model fused with multi-dimensional data;

[0010] A model interaction calling device connected to the multi-dimensional scene rendering device, for calling and generating corresponding visual model information from the three-dimensional scene model fused with multi-dimensional data in response to demand information input by an administrator.

[0011] The present application unifies the formats of multi-source heterogeneous city management information through the information standardization processing device, and accurately renders the standardized information of traffic, population, economy, energy, etc. to the corresponding preconfigured data layers using the multi-dimensional scene rendering device, and finally superimposes these layers on the unified three-dimensional scene base model, effectively breaking the "data island" barriers between different departments and realizing the deep integration and spatial coupling of cross-field data. The three-dimensional scene model fused with multi-dimensional data generated thereby provides a city manager with an intuitive, unified and spatio-temporal related panoramic view of city operation, enabling convenient correlation analysis of originally fragmented data (such as traffic patterns and air quality), significantly improving the comprehensiveness of decision-making basis and cross-field collaborative analysis capability, thereby overcoming the problems of one-sided decision-making and low efficiency caused by scattered data and different formats in the background technology, and enhancing the overall efficiency of smart city management.

[0012] Further, the map information collection device comprises:

[0013] The map information collection device comprises:

[0014] A data acquisition module for acquiring original digital elevation model data of a target area from an external data source;

[0015] A coordinate conversion module for performing spatial reference system unification processing on the original DME data acquired by the data acquisition module, and converting it to a preconfigured geographic coordinate system;

[0016] A three-dimensional modeling module for constructing a three-dimensional scene base model describing the continuous undulating topography of the target area based on the DME data in the unified coordinate system processed by the coordinate conversion module.

[0017] Further, constructing the three-dimensional scene base model comprises the following steps:

[0018] Receiving the two-dimensional regular grid array in the unified geographic coordinate system processed by the coordinate conversion module;

[0019] For each grid point p in the input two-dimensional regular grid array, the planar coordinates (x, y) of the grid point p are calculated, and the elevation value z of the grid point p is read to generate the vertex coordinates (x, y, z) of the grid point p;

[0020] All the grid points p are connected to form a continuous triangular facet network covering the entire area:

[0021] For each triangular facet network, the normal vector of the plane on which the triangle is located is calculated according to the three-dimensional coordinates of its three vertices;

[0022] A vertex array, an index array and a normal array are constructed, wherein:

[0023] The vertex array is: storing the three-dimensional coordinates of all unique vertices;

[0024] The index array is: storing the indexes of the three vertices of each triangular facet network;

[0025] The normal array is: storing the normal vector of each vertex or each facet;

[0026] A three-dimensional scene base model is constructed according to the vertex array, the index array and the normal array.

[0027] Further, the management information collection device comprises:

[0028] A multi-source interface adaptation module configured with multiple standardized data interfaces, which calls the corresponding interface to access the raw data of various city management information according to the type and access requirements of the target data source;

[0029] A protocol analysis and conversion module for protocol analysis and preliminary format conversion of the accessed raw data to generate intermediate data;

[0030] A data extraction and encapsulation module: extracts the core information field related to city management from the intermediate data after protocol analysis, and encapsulates it into structured city management information.

[0031] Further, the information standardization processing device comprises:

[0032] A data cleaning and verification module for missing value processing, outlier detection and correction, and format consistency verification of the input city management information;

[0033] A space-time reference unification module for spatial position standardization and time reference alignment of city management information;

[0034] A numerical normalization and grading module for converting city management information of different sources and different dimensions into standardized numerical values that can be compared and directly mapped to visual attributes;

[0035] A visual coding mapping rule generation module defines the conversion of standardized numerical values and spatial position information into specific visualization instructions to generate standardized information.

[0036] Further, the geographic coordinates in the city management information are acquired, and the geographic coordinates are converted into three-dimensional scene base model coordinates.

[0037] The time stamps of the city management information are unified to the same time reference, and time granularity aggregation is performed.

[0038] Further, the multi-dimensional scene rendering device comprises:

[0039] A layer management module draws the received standardized information to the corresponding preset layer according to the information type thereof.

[0040] A rendering processing module performs spatial superposition and fusion of the three-dimensional scene base model and all rendered preset data layers to generate a final, unified three-dimensional scene model of the fused multi-dimensional data.

[0041] Further, the model interaction calling device comprises:

[0042] An interaction interface module is configured to input administrator demand information.

[0043] A model analysis and data extraction module receives the demand information, performs real-time analysis and intelligent data extraction on the three-dimensional scene model of the fused multi-dimensional data to generate a model subset.

[0044] A dynamic view generation module generates highly focused and easily understood visual model information based on the extracted model subset.

[0045] Further, the model analysis and data extraction module comprises:

[0046] A demand information receiving unit is configured to receive demand information.

[0047] A demand information processing unit is configured to generate a model subset.

[0048] A model subset encryption unit encrypts the geographic position coordinates in the model subset based on the identity information of the administrator to generate an encrypted model subset.

[0049] The application has the following beneficial effects:

[0050] (1) effectively breaking down the "data silos" and achieving deep fusion of multi-source heterogeneous data: through the information standardization processing device, the original city management information in multiple fields, formats and interfaces such as traffic, population, economy and energy is uniformly processed to generate standardized information with consistent format, fundamentally solving the problem of different data formats and inconsistent interface standards and laying a foundation for data fusion.

[0051] (2) The multi-dimensional scene rendering device is pre-configured with multiple data layers, which provide independent bearing space and a unified rendering framework for data in different fields (such as traffic layers, population layers, economic layers, and energy layers). The standardized information is accurately rendered to the corresponding layers and superimposed on the unified three-dimensional scene base model, realizing seamless integration and visual fusion of cross-department, cross-field, and heterogeneous data under the same space-time reference, and completely breaking the original "data island" state.

[0052] (3) The three-dimensional scene model generated by the system visually and stereoscopically presents geographic spatial information (terrain, buildings) and dynamic urban management information (people flow, vehicle flow, economic activity, energy consumption) in three-dimensional space. Managers can simultaneously observe and analyze multi-dimensional information such as traffic congestion, surrounding population density distribution, regional economic activity, and energy use intensity and their mutual relationships on a unified, geospatially accurate platform, obtaining an unprecedented panoramic view of city operation.

[0053] (4) The fusion and superposition of data in the unified three-dimensional scene makes the potential correlation between originally scattered data visually apparent (for example, the spatio-temporal correlation between traffic flow changes and surrounding commercial activities, energy consumption peaks, or population density in specific areas). Managers can easily discover cross-field influencing factors and linkage effects (such as analyzing the impact of environmental protection data on traffic patterns), providing strong data support and visual analysis tools for developing comprehensive and collaborative urban management strategies (such as traffic relief and commercial activity guidance linkage, energy allocation and population flow prediction combination).

[0054] (5) The model interaction calling device allows administrators to accurately and quickly retrieve the required data dimensions and spatial range from the vast fusion model according to specific decision-making or analysis needs (demand information). The system can dynamically generate visual model information for specific problems (such as the traffic-population-energy comprehensive situation in a certain area during peak hours, or the impact of a major project on the surrounding environment and economy), greatly improving information acquisition efficiency and relevance, and meeting the decision support needs in different scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0055] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application and are incorporated in and constitute a part of this application. The drawings illustrate embodiments of the present application and, together with their description, serve to explain the application. It is expressly understood that the drawings are included solely for purposes of illustrating the present application and are not to be construed as being limiting in any way.

[0056] In addition, throughout the drawings, same or similar reference numerals are used to represent same or similar elements. It should be understood that the drawings are schematic, and elements and elements are not necessarily drawn to scale.

[0057] In the drawings:

[0058] Figure 1 Fig. 1 is a structural schematic diagram of a smart city data intelligent fusion system. DETAILED DESCRIPTION

[0059] Embodiments of the present application will be described in more detail with reference to the drawings. Although certain embodiments of the present application are shown in the drawings, it should be understood that the present application can be embodied in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present application can be more thoroughly and completely understood. It should be understood that the drawings and embodiments of the present application are only for illustrative purposes and are not intended to limit the scope of protection of the present application.

[0060] In addition, it should be further noted that only parts related to the present application are shown in the drawings for ease of description. The embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0061] The present application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0062] Reference Figure 1 The smart city data intelligent fusion system comprises a map information acquisition device, a management information acquisition device, an information standardization processing device, a multi-dimensional scene rendering device, and a model interactive calling device. The map information acquisition device is configured to obtain digital elevation model data of a target region and construct a three-dimensional scene base model based on the digital elevation model data. The management information acquisition device is configured to acquire multi-source city management information, which includes traffic information representing traffic flow, population information representing resident population distribution, economic information representing economic activities, and energy information representing energy use. The information standardization processing device is connected to the management information acquisition device and configured to perform standardization processing on the acquired city management information to generate standardized information in a unified format.

[0063] The multi-dimensional scene rendering device is connected to the map information acquisition device and the information standardization processing device. The multi-dimensional scene rendering device is preconfigured with a plurality of data layers corresponding to the types of city management information. The multi-dimensional scene rendering device is configured to render the standardized information into the corresponding data layers and superimpose the rendered layers on the three-dimensional scene base model to generate a three-dimensional scene model fused with multi-dimensional data.

[0064] The model interactive calling device is connected to the multi-dimensional scene rendering device and configured to respond to demand information input by an administrator, retrieve and generate corresponding visual model information from the three-dimensional scene model fused with multi-dimensional data based on the demand information.

[0065] Further, the map information collection device comprises a data acquisition module, a coordinate conversion module and a three-dimensional modeling module.

[0066] The external data source is a basic geographic information database established by a country or a region.

[0067] The coordinate conversion module is configured to perform spatial reference system unification processing on the original DME data acquired by the data acquisition module and convert the original DME data to a preset geographic coordinate system.

[0068] The processing process of the coordinate conversion module is to convert the original DME data from its inherent coordinate system to a unified geographic coordinate system, such as the WGS-84 coordinate system, so as to accurately process all geographic position information in the target area.

[0069] In this way, all spatial data (including subsequent city management information) can be superimposed and fused under the same accurate geographic space framework, ensuring the consistency and accuracy of the spatial position.

[0070] The three-dimensional modeling module is configured to construct a three-dimensional scene basic model describing the continuous undulating form of the ground surface of the target area based on the DME data in the unified coordinate system processed by the coordinate conversion module.

[0071] Further, the construction of the three-dimensional scene basic model comprises the following steps:

[0072] S1: receiving a two-dimensional regular grid array in the unified geographic coordinate system processed by the coordinate conversion module;

[0073] For each grid point p in the input two-dimensional regular grid array, the plane coordinates (x, y) of the grid point p are calculated, and the elevation value z of the grid point p is read to generate the vertex coordinates (x, y, z) of the grid point p.

[0074] The regular grid elevation data is raster data arranged at a fixed interval, and each raster unit (grid point) stores an elevation value (z).

[0075] S2: connecting all grid points p to form a continuous triangular facet network covering the entire area.

[0076] Specifically: each grid cell is directly regarded as a mesh point, the spatial position (x, y) of which is determined by the row and column numbers and the resolution, and the elevation value (z) is directly taken from the grid data. Adjacent mesh points are connected to form regularly arranged triangular or quadrilateral patches. Then, within the regular grid cell, a linear interpolation or bilinear interpolation algorithm is applied to calculate and fill the elevation values of any points within the triangle / mesh according to the elevation values of the vertices / mesh points, thereby generating a continuous and seamless three-dimensional terrain surface.

[0077] For four adjacent vertices in a two-dimensional regular grid array (for example, the points located at (i, j), (i, j+1), (i+1, j), and (i+1, j+1)), they are divided into two triangular patches as follows:

[0078] Triangle 1: vertex (i, j) -> (i, j+1) -> (i+1, j); Triangle 2: vertex (i, j+1) -> (i+1, j+1) -> (i+1, j).

[0079] S3: For each triangular patch network, the normal vector of the plane on which the triangle is located is calculated according to the three-dimensional coordinates of its three vertices.

[0080] Construct a vertex array, an index array, and a normal array, wherein:

[0081] The vertex array stores the three-dimensional coordinates of all unique vertices.

[0082] The index array stores the indices of the three vertices of each triangular patch network. By reusing the vertices through indexing, repeated storage is avoided, saving memory and improving rendering efficiency.

[0083] The normal array stores the normal vector of each vertex or each patch. Storing the normal vector of each vertex or each patch, the normal vector is used to determine how light shines on the surface during rendering, enhancing the three-dimensionality of the terrain, and the normal vector is calculated according to the three-dimensional coordinates of its three vertices.

[0084] S4: Construct a three-dimensional scene base model according to the vertex array, the index array, and the normal array.

[0085] Define the constructed vertex array, index array, and normal array as a three-dimensional scene base model and output it, explicitly as a spatial substrate carrying multi-dimensional data.

[0086] Further, the management information collection device comprises a multi-source interface adaptation module, a protocol analysis and conversion module, and a data extraction and packaging module.

[0087] The multi-source interface adaptation module is configured with multiple standardized data interfaces, and according to the type and access requirements of the target data source, the corresponding interface is called to access the original data of various city management information.

[0088] Standardized data interfaces include: API interfaces, database connection interfaces, message queue interfaces, file transfer interfaces, Internet of Things sensor protocol interfaces.

[0089] For example:

[0090] Obtain real-time traffic information such as traffic flow, speed, congestion index, etc. through the traffic management platform API.

[0091] Obtain population information such as the number of permanent residents, density, age structure, etc. at the community / grid level through the population database connection.

[0092] Obtain economic information such as enterprise registration, tax, commercial district consumer heat, etc. through the e-government data exchange platform or commercial institution data interface.

[0093] Obtain energy information such as regional / building-level energy consumption data through the smart meter / water meter / gas meter data collection platform or energy management system (EMS) interface.

[0094] Protocol parsing and conversion module: protocol parsing and preliminary format conversion of the accessed raw data to generate intermediate data.

[0095] The processing process of the protocol parsing and conversion module is:

[0096] Parse the native data protocol (such as HTTP / JSON) from different interfaces. Extract and convert the parsed data content into an internal unified intermediate representation format.

[0097] Data extraction and packaging module: extract and package the core information fields related to city management from the intermediate data parsed according to the predefined information schema (Schema).

[0098] The processing process of the data extraction and packaging module is:

[0099] According to the predefined information schema (Schema), identify and extract key data items. For example:

[0100] Extract timestamp, location (road segment / intersection ID or coordinates), traffic volume, average speed from traffic data.

[0101] Extract statistical time, geographic area code, population, population density from population data.

[0102] Extract enterprise registration location, turnover, industry classification, commercial district foot traffic from economic data.

[0103] Extract metering point location, timestamp, electricity / water / gas consumption, peak load from energy data.

[0104] Further, the information standardization processing device comprises: a data cleaning and checking module, a space-time reference unification module, a numerical normalization and grading module, and a visual coding mapping rule generation module.

[0105] The data cleaning and checking module performs missing value processing, format consistency checking, outlier detection and correction, and visual coding mapping rule generation on the input urban management information.

[0106] Missing value processing: identify and fill in missing values (e.g., use adjacent value interpolation, average value filling, or mark as a specific value) in key fields (such as location, timestamp, core indicator value).

[0107] Outlier detection and correction: detect and correct or exclude obviously abnormal data points based on statistical rules or business rules (such as population density cannot be negative, traffic flow has a reasonable upper limit).

[0108] Format consistency checking: ensure uniformity of timestamp format (such as uniformity of UTC timestamp), uniformity of geographic location identifier format (such as uniformity of latitude and longitude coordinates or standard regional code), and uniformity of numerical unit (such as uniformity of energy consumption in kilowatt-hours).

[0109] Logical consistency checking: check the logical relationship between data (such as the population of a certain area should be consistent with the sum of the population of its subordinate communities).

[0110] The space-time reference unification module standardizes the spatial position and aligns the time reference of the urban management information.

[0111] The alignment method is as follows:

[0112] Obtain the geographic coordinates in the urban management information, convert the geographic coordinates to three-dimensional scene base model coordinates; unify the timestamps of the urban management information to the same time reference, and perform time granularity aggregation.

[0113] Specifically:

[0114] If the collected urban management information contains geographic coordinates (latitude and longitude), verify whether the coordinate system is consistent with the three-dimensional scene base model (such as both being WGS-84), and if not, perform coordinate system conversion.

[0115] If the urban management information contains a region identifier (such as an administrative division code), it is associated with the pre-defined spatial boundary data corresponding to the three-dimensional scene base model, and converted to a center point coordinate, a barycenter coordinate, or a geometric face covering the region as its spatial anchor point in the three-dimensional scene.

[0116] Alignment time: all the time stamps of the city management information are unified to the same time reference (e.g. UTC), and time granularity aggregation (e.g. aggregating second-level data into minute-level or hour-level average) can be performed as needed to match the rendering requirements and analysis targets.

[0117] Value normalization and classification module: different sources and different dimensions of city management information are converted into standardized values that can be compared and directly mapped to visual attributes.

[0118] Mapping raw value indicators (e.g. population, traffic volume, energy consumption, turnover) to a pre-set, unified value range [0~255].

[0119] Visual encoding mapping rule generation module: defines the conversion of standardized values and spatial location information into specific visualization instructions, generating standardized information.

[0120] Standardized information includes the following generation steps:

[0121] Z1: Pre-set visual encoding scheme:

[0122] Predefine the visualization form (i.e. which layer to render to and how to render) for each type of city management information (traffic, population, economy, energy).

[0123] The form includes color mapping, height / size mapping, and icon / symbol mapping.

[0124] Color mapping: population density: map normalized value 0 (low) to blue, 0.5 (medium) to yellow, and 1 (high) to red; or interpolate on a continuous color band (e.g. blue -> yellow -> red gradient). Air quality: map pollutant concentration classification to different colors.

[0125] Height / size mapping: regional economic activity: map normalized turnover to the height of the corresponding region's 3D column chart. Traffic volume: map normalized traffic volume to the density or speed of particles flowing on the road model.

[0126] Icon / symbol mapping: energy facility location: render a specific 3D icon (e.g. power plant, transformer station icon) at the corresponding coordinate point.

[0127] Z2: Generate rendering instruction metadata:

[0128] For each processed city management information, combine spatial location information with standardized values.

[0129] For example, generate a standardized rendering instruction containing rendering location, visual attribute value (e.g. color RGB value, height scaling factor, icon type) based on traffic. These instructions themselves or their collection are the standardized information.

[0130] The standardized information is intermediate data decoupled from rendering logic and unified in format, the core of which contains:

[0131] Where in the three-dimensional scene, what information the intensity / category of the information is (Value-standardized value / hierarchy), and how it should be visually presented (How-point to a preset visual encoding scheme or include specific rendering parameters).

[0132] Further, the multi-dimensional scene rendering device comprises a layer management module and a rendering processing module. The layer management module draws the received standardized information to the corresponding preset layer according to the information type thereof.

[0133] The data layer setting mode comprises the following steps:

[0134] Step 1: In the system initialization or configuration phase, an independent data layer corresponding to each city management information type (traffic, population, economy, energy) is created in advance. For example, a traffic information layer is used to render road traffic and congestion status. A population information layer is used to render population density distribution and heat map. An economic information layer is used to render regional economic activity and commercial hotspots. An energy information layer is used to render energy consumption intensity and facility location.

[0135] Step 2: Each layer is associated with its corresponding information type identifier and exclusive rendering strategy (such as color mapping rules, height mapping rules, particle effect rules, etc.).

[0136] The rendering process of the preset layer comprises the following steps:

[0137] Step 1: Receive the standardized information. According to the information type identifier carried by each piece of standardized information, it is sent to the corresponding preset data layer (such as population density information -> population information layer).

[0138] Step 2: Based on the accurate spatial position information (coordinate point, associated geometric region) contained in the standardized information: for point information (such as specific sensor location, facility point): perform rendering operation at the corresponding coordinate point. For area / region information (such as administrative district population density, grid energy consumption): perform rendering operation within the corresponding geographical boundary (polygon) range. The boundary needs to be accurately matched with the three-dimensional scene base model.

[0139] Step 3: Perform rendering operation along the corresponding linear geometry (road centerline). For each preset layer, all rendering instructions contained therein are independently executed to generate the corresponding two-dimensional / three-dimensional graphical elements of the layer. These graphical elements only contain their exclusive city management information visualization content, and their spatial positions have been accurately registered.

[0140] a rendering processing module, which performs spatial superposition and fusion of the three-dimensional scene base model and all rendered preset data layers to generate a final and unified three-dimensional scene model of fused multi-dimensional data.

[0141] The fusion process includes the following steps:

[0142] S1: receiving and loading a three-dimensional scene base model (a three-dimensional terrain mesh) generated by a map information collection device.

[0143] S2: superimposing preset layers as independent rendering layers on the corresponding geographical positions of the three-dimensional scene base model according to a preset rendering order and a transparency setting.

[0144] S3: using a unified geographical coordinate system and the accurate spatial positioning completed during layer rendering, ensuring that the visual elements on all layers are perfectly aligned with the actual positions on the terrain model.

[0145] S4: integrating the three-dimensional scene base model superimposed with all preset layers into a single, coherent and interactive three-dimensional scene object, i.e., a three-dimensional scene model of fused multi-dimensional data. The model retains all geometric and visual features of the base terrain and superimposes and displays the visualized urban management information (traffic, population, economy, energy) carried by each preset layer at the corresponding geographical positions. The model supports three-dimensional operations such as overall rotation, zooming, panning, etc.

[0146] Further, the model interaction calling device includes an interaction interface module, a model analysis and data extraction module, and a dynamic view generation module.

[0147] The interaction interface module is configured to input the demand information of an administrator.

[0148] The demand information includes the administrator's identity, the layer information of the demand, and the corresponding position information. For example, administrator A needs the population density information of the entire region, and administrator B needs the energy information of the entire region.

[0149] The model analysis and data extraction module receives the demand information, performs real-time analysis and intelligent data extraction on the three-dimensional scene model of fused multi-dimensional data to generate a model subset.

[0150] The processing process includes the following steps:

[0151] Step 1: based on the target spatial range in the query, quickly clipping the model to only retain the base terrain and superimposed layer visual elements within the geographical region.

[0152] Step 2: according to the type of information to be focused on, only activating and extracting the relevant preset data layers (such as only activating the traffic and population layers and hiding the economy and energy layers).

[0153] The dynamic view generation module generates highly focused and easily understandable visual model information based on the extracted model subset.

[0154] The main function of the dynamic view generation module is to focus on some key information by changing the color depth, increasing the brightness, etc., so as to facilitate the understanding of the administrator.

[0155] The model analysis and data extraction module includes:

[0156] The demand information receiving unit is used to receive demand information.

[0157] The demand information processing unit is used to generate a model subset.

[0158] The model subset encryption unit encrypts the geographic location coordinates in the model subset based on the identity information of the administrator to generate an encrypted model subset.

[0159] In this scheme, the model analysis and data extraction module further includes an encryption unit. The encryption unit can determine whether to encrypt the geographic location information according to the identity information, so as to reduce the risk of city management information leakage. Generally, the obtained geographic information is distorted geographic information, and this is especially true for some key energy facilities. Therefore, in order to avoid the leakage of key geographic location information, the model subset needs to be encrypted and distorted to reduce the risk of geographic information leakage.

[0160] The encryption process is as follows:

[0161] Z1: The model subset encryption unit obtains the administrator identity information in the demand information, and obtains the administrator permission level according to the administrator identity information;

[0162] Z2: The model subset encryption unit pre-configures a secret key k according to the administrator permission level;

[0163] The secret key k is generated by PBKDF2-HMAC-SHA256 according to the user identity information S and the random number r,

[0164] The user identity information S is saved by the user himself, and the random number r is a random number generated according to the time stamp and the random function.

[0165] The generation process of the random number r is as follows:

[0166] Define a random function f(t) for each time period, and the random function is an inverse proportional function f(t) = a / (t+1);

[0167] Wherein, t is the sum of all numbers in the timestamp, for example, t = 2 + 0 + 2 + 4 + 0 + 2 + 0 + 1 + 2 + 3 + 6 + 0 of 2024-01-02.01.23.60s. a is a random number, different for each time period.

[0168] Thus, for the key k, the model subset encryption unit can obtain the current corresponding random function according to the identity information of the user and the generation time of the demand information, and directly calculate it out.

[0169] The interaction interface module can also obtain the current corresponding random function according to the identity information of the user and the generation time of the demand information, and directly calculate it out. Therefore, for the users in the same system, it is impossible to obtain the secret keys of other users without knowing the identity information of the remaining users. And for some illegal attackers, when they illegally obtain the identity information of the user and some specific model subsets, they cannot obtain the secret key k because they do not have the generation time of the demand information corresponding to the model subset, so they cannot obtain the real geographic coordinates.

[0170] Z3: The model subset encryption unit distorts and encrypts the coordinate information in the model subset according to k.

[0171] Z3 includes the following steps:

[0172] Z31: Obtain the original geographic coordinates P = {p i i , y i | i = 1, 2, …, N} in the model subset; i represents the index of the coordinate point, and N represents the total number of coordinate points;

[0173] Z32: Initialize a pseudo-random number generator using the hash value of the key k, and the pseudo-random number generator generates M parameters, each group of parameters including: amplitude a j , b j , frequency and phase

[0174] Z33: Construct a perturbation function for each point p i i i

[0175]

[0176] Z34: Encrypt p i i i

[0177]

[0178] ​​​​​​​In the case of a known encryption process, the interaction interface module can directly perform decryption, the decryption process being omitted.

[0179] The above description is merely some of the preferred embodiments of the application, and the technical principles used. Those skilled in the art should understand that the scope of the application involved in the embodiments of the present application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or equivalent features without departing from the above inventive concept. For example, the above features are replaced with each other to form technical solutions with similar functions disclosed in the embodiments of the present application (but not limited to).

Claims

1. A smart city data intelligent fusion system, characterized in that, The application relates to a city management information fusion system, which comprises the following parts: a map information acquisition device for acquiring digital elevation model data of a target area and constructing a three-dimensional scene basic model based on the digital elevation model data; a management information acquisition device for acquiring multi-source city management information, wherein the city management information comprises traffic information representing traffic flow, population information representing resident population distribution, economic information representing economic activities and energy information representing energy use; an information standardization processing device connected to the management information acquisition device and used for performing standardization processing on the acquired city management information to generate standardized information with unified formats; a multi-dimensional scene rendering device connected to the map information acquisition device and the information standardization processing device, wherein the multi-dimensional scene rendering device is preconfigured with a plurality of data layers corresponding to the types of the city management information, is used for rendering the standardized information into the corresponding data layers respectively, and is used for superimposing the rendered layers on the three-dimensional scene basic model to generate a three-dimensional scene model fused with multi-dimensional data; a model interactive calling device connected to the multi-dimensional scene rendering device and used for calling and generating corresponding visual model information from the three-dimensional scene model fused with multi-dimensional data in response to demand information input by an administrator. 2.The smart city data intelligent fusion system of claim 1, wherein: The map information acquisition device comprises: The map information acquisition device comprises: a data acquisition module for acquiring original digital elevation model data of a target area from an external data source; a coordinate conversion module for performing spatial reference system unification processing on the original DME data acquired by the data acquisition module and converting the original DME data into a preset geographic coordinate system; a three-dimensional modeling module for constructing a three-dimensional scene basic model describing the continuous undulating form of the ground surface of the target area based on the DME data in the unified coordinate system processed by the coordinate conversion module. 3.The smart city data intelligent fusion system of claim 2, wherein: The three-dimensional scene basic model is constructed by the following steps: receiving the two-dimensional regular grid array in the unified geographic coordinate system processed by the coordinate conversion module; calculating the plane coordinates (x, y) of each grid point p in the input two-dimensional regular grid array and reading the elevation value z of the grid point p to generate the vertex coordinates (x, y, z) of the grid point p; connecting all the grid points p to form a continuous triangular facet network covering the whole area: calculating the normal vector of the plane where each triangular facet network is located according to the three-dimensional coordinates of the three vertices of the triangular facet network; constructing a vertex array, an index array and a normal array, wherein: the vertex array is used for storing the three-dimensional coordinates of all unique vertices; the index array is used for storing the indexes of the three vertices of each triangular facet network; the normal array is used for storing the normal vector of each vertex or each facet; constructing the three-dimensional scene basic model according to the vertex array, the index array and the normal array. 4.The smart city data intelligent fusion system of claim 1, wherein: The management information acquisition device comprises: a multi-source interface adaptation module configured with a plurality of standardized data interfaces, which is used for calling corresponding interfaces to access the original data of various city management information according to the types and access requirements of target data sources; The protocol analysis and conversion module performs protocol analysis and preliminary format conversion on the accessed original data to generate intermediate data; The data extraction and packaging module extracts the core information field related to city management from the intermediate data after protocol analysis and packages it into structured city management information. 5.The smart city data intelligent fusion system according to claim 4, characterized in that: The information standardization processing device comprises: The data cleaning and checking module performs missing value processing, abnormal value detection and correction, and format consistency checking on the input city management information; The space-time reference unification module performs spatial position standardization and time reference alignment on the city management information; The numerical normalization and grading module converts city management information of different sources and different dimensions into standardized numerical values that can be compared and directly mapped to visual attributes; The visual coding mapping rule generation module defines the conversion of standardized numerical values and spatial position information into specific visual instructions to generate standardized information. 6.The smart city data intelligent fusion system according to claim 5, characterized in that: The geographic coordinates in the city management information are obtained and converted into three-dimensional scene base model coordinates; The timestamps of the city management information are unified to the same time reference and aggregated in time granularity. 7.The smart city data intelligent fusion system of claim 1, wherein: The multi-dimensional scene rendering device comprises: The layer management module draws the received standardized information to the corresponding preset layer according to its information type; The rendering processing module performs spatial superposition and fusion of the three-dimensional scene base model and all rendered preset data layers to generate the final unified three-dimensional scene model of the fused multi-dimensional data. 8.The smart city data intelligent fusion system of claim 1, wherein: The model interaction calling device comprises: The interactive interface module is used for inputting administrator demand information; The model analysis and data extraction module receives the demand information, performs real-time analysis and intelligent data extraction on the three-dimensional scene model of the fused multi-dimensional data to generate a model subset; The dynamic view generation module generates highly focused and easily understood visual model information based on the extracted model subset. 9.The smart city data intelligent fusion system of claim 1, wherein: The model analysis and data extraction module comprises: The demand information receiving unit is used for receiving demand information; The demand information processing unit is used for generating a model subset; The model subset encryption unit encrypts the geographic position coordinates in the model subset based on the identity information of the administrator to generate an encrypted model subset.

Images