Intelligent management system based on three-dimensional visualization

Abstract

The invention discloses an intelligent management system based on three-dimensional visualization, and relates to the field of intelligent management and control. Comprising a control terminal, and the control terminal is in communication connection with an information acquisition module, a data processing module, a data analysis module, a data visualization module and a data management module. The information acquisition module is used for acquiring city data in real time; the data processing module comprises a first processing unit and a second processing unit; respectively obtaining a subset database and urban pollution data, and further obtaining an urban pollution data index; the data analysis module is used for analyzing the urban pollution data and generating an abnormal pollution data curve coordinate graph according to an analysis result; the data visualization module is used for visualizing the subset database, generating a city data curve coordinate graph, analyzing city data and generating a city log; and the data management module is used for managing the city data according to the city log.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management and control, and specifically to a smart management system based on three-dimensional visualization. Background Art

[0002] With the development of science and technology, in the current photovoltaic power generation system, due to the multi-source heterogeneous and geographically dispersed characteristics of distributed photovoltaic power stations, information islands are easily formed. The existing photovoltaic power generation system lacks centralized and intuitive visual supervision and safety means, and cannot manage in a timely manner according to the production situation of distributed photovoltaic power generation equipment. Information cannot play its due value in industrial production, and there are several limitations in the statistical data sources of the existing photovoltaic power generation system, including: low update frequency, inconsistent statistical calibers, and statistical materials reported layer by layer from bottom to top, which are prone to cause inconsistent standard scales in each region (city); In the prior art, there are data latency and inaccuracy in the data management of urban management. The system security data operation needs to be monitored in real time, and each data online / offline needs to be managed flexibly to ensure the timeliness and accuracy of the data; Therefore, a visual smart management system based on three-dimensional numbers is provided. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention provides a smart management system based on three-dimensional visualization; The purpose of the present invention can be achieved through the following technical solutions: A smart management system based on three-dimensional visualization, including a control terminal, and the control terminal is communicatively connected to an information collection module, a data processing module, a data analysis module, a data visualization module, and a data management module; The information collection module is used to collect urban data in real time; The data processing module includes a first processing unit and a second processing unit; the first processing unit is used to process urban data to obtain a subset database; the second processing unit is used to process the urban pollution data obtained by the sensor nodes to obtain an urban pollution data index; The data analysis module is used to analyze the urban pollution data, and according to the analysis result, generate an abnormal pollution data curve coordinate diagram; The data visualization module is used to visualize the subset database to generate an urban data curve coordinate diagram, and then analyze the urban data to generate an urban log; The data management module is used to manage urban data according to the urban log.

[0004] Further, the process of the information collection module collecting urban data in real time includes: The urban data includes population data, economic data, infrastructure data, environmental data, land use data, traffic data, education data, medical data, social security data, and cultural data; The urban data is obtained through government department statistics, sensor networks, and various Internet platforms; The sensor network includes a number of sensor nodes, and the number of sensor nodes is formed into a distributed intelligent network system that can autonomously complete specified tasks according to the environment through a self-organizing method; and a number of sensor nodes are deployed inside the city, and the positions of the sensor nodes in the sensor network are obtained through GPS and marked as node positions; The sensor nodes are used to obtain urban pollution data corresponding to the node positions; the pollution data includes air pollution data, water pollution data, soil pollution data, and noise pollution data; A gateway is set up to wirelessly connect the sensor network and the data management module.

[0005] Further, the process by which the first processing unit obtains the subset database includes: Preprocess the urban data, and the preprocessing includes data cleaning and data reduction; The data cleaning is used to clean the format of the urban data, and the format cleaning is used to set a standard format for the urban data, and according to the standard format, the urban data different from the standard format is cleaned; Furthermore, the urban data after data cleaning is classified according to the types it contains to obtain corresponding data pools.

[0006] Further, the data in each data pool is rearranged according to the collection time, the urban data and the collection time are associated with each other to generate corresponding urban data sets; the average value, maximum value, minimum value, and variance of the data in the data pool are obtained; Obtain the expected value according to the average value and variance; Compare the expected value corresponding to each data pool with the data in the corresponding data pool. If the data corresponding to the data pool deviates from the corresponding expected value, the corresponding data is excluded; otherwise, the corresponding data is retained to generate a new data pool.

[0007] Further, set the characteristic values corresponding to the new data pool, and obtain the characteristic subsets corresponding to the new data pool according to the characteristic values; extract the characteristic subsets obtained from the new data pool, set new characteristic values for the remaining data in the new data pool, and obtain new characteristic subsets according to the new characteristic values; loop in turn until all the data in the new data pool generates characteristic subsets; Store the several characteristic subsets according to the differences of the new data pools to obtain the corresponding subset database.

[0008] Further, the process by which the second processing unit obtains the urban pollution data index includes: Obtain the node location corresponding to the sensor node and the corresponding urban pollution data; further obtain the collection time corresponding to the urban pollution data, associate the data, and generate an urban data set; Obtain the maximum and minimum values of the urban pollution data in the urban data set and the real-time urban pollution data; Obtain the urban pollution data index based on the maximum and minimum values and the real-time urban pollution data.

[0009] Further, the process by which the data analysis module generates the abnormal pollution data curve coordinate diagram includes: Set the urban pollution data index threshold corresponding to the urban data set and compare it with the corresponding urban pollution data; if it is less than the urban pollution data index, mark the corresponding urban pollution data as abnormal urban pollution data, and then obtain the corresponding collection time and node location; otherwise, do nothing; Associate the abnormal urban pollution data with the corresponding collection time and node location to generate an abnormal urban pollution data set.

[0010] Generate an abnormal pollution data curve coordinate diagram with the abnormal pollution data and the collection time.

[0011] Further, the process by which the data visualization module generates the urban log includes: Generate subset curve coordinate diagrams for each subset database corresponding to the new data pool; associate the subset curve diagrams to generate an urban data curve coordinate diagram; Analyze the urban data based on the urban data curve coordinate diagram to obtain the urban log and send it to the data management module; The urban log includes the data situation today, data trend, and suggestions.

[0012] Further, the process by which the data management module manages the urban data according to the urban log includes: Set the allowed access accounts in the data management module; log in to the allowed access accounts to view the urban log and the abnormal pollution data curve coordinate diagram corresponding to the urban data.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention collects urban data in real time through an information collection module, sets a first processing unit and a second processing unit, processes the urban data through the first processing unit to obtain a subset database, processes the urban pollution data obtained by the sensor nodes through the second processing unit, and further obtains an urban pollution data index; and sends it to the data analysis module for analyzing the urban pollution data. According to the analysis results, an abnormal pollution data curve coordinate graph is generated; according to the data visualization module, the subset database is visualized to generate an urban data curve coordinate graph, and then the urban data is analyzed to generate an urban log; and then through the data management module, the urban data is managed according to the urban log; improving the need for real-time monitoring of urban data and flexible management of various online / offline data, ensuring the timeliness and accuracy of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0015] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0017] As Figure 1 shown, a smart management system based on three-dimensional visualization includes a control terminal, and the control terminal is communicatively connected to an information collection module, a data processing module, a data analysis module, a data visualization module, and a data management module; The information collection module is used to collect urban data in real time, and the specific process includes: The urban data includes population data, economic data, infrastructure data, environmental data, land use data, traffic data, education data, medical data, social security data, and cultural data; It should be further noted that in the specific implementation process, the economic data includes the GDP, employment rate, income level, and industrial structure of the city; the infrastructure data includes the road network, public transportation system, water supply and power supply system, and waste treatment system; the environmental data includes air quality, water quality, noise level, and greening coverage rate; the land use data includes land use, building type, and land use distribution; the traffic data includes road congestion, traffic flow, and public transportation operation; the education data includes the number of schools, education resource allocation, and education quality; the medical data includes the number of hospitals, medical resource allocation, and health indicators; the social security data includes the crime rate, number of fire accidents, and natural disaster risks; the cultural data includes cultural heritage, number of museums, and art performance venues; In one embodiment, urban data is of great significance to a city. Through urban data, the quality of life, management efficiency, economic development, and urban governance of a city can be understood; by visualizing urban data, the development of the city can be understood more clearly; Urban data is obtained through government department statistics, sensor networks, and various network platforms on the Internet; The sensor network includes a number of sensor nodes, and the number of sensor nodes is organized in a self-organizing manner to form a distributed intelligent network system that can autonomously complete specified tasks according to the environment; and a number of sensor nodes are deployed inside the city, and the positions of the sensor nodes in the sensor network are obtained through GPS and marked as node positions; The sensor nodes are used to obtain urban pollution data corresponding to the node positions; the pollution data includes air pollution data, water pollution data, soil pollution data, and noise pollution data; A gateway is set up to wirelessly connect the sensor network and the data management module; It should be further noted that in the specific implementation process, the various network platforms on the data Internet include Baidu, Douyin, and Xiaohongshu, etc.

[0018] The data processing module is used to process urban data to obtain a subset database and an urban pollution data index. The specific process includes: The data processing module includes a first processing unit and a second processing unit; the first processing unit is used to process urban data to obtain a subset database; the second processing unit is used to process the urban pollution data obtained by the sensor nodes to further obtain an urban pollution data index; The process of the first processing unit processing urban data includes: Preprocess the urban data, and the preprocessing includes data cleaning and data reduction; The data cleaning is used to clean the format of urban data. The format cleaning is used to set a standard format for urban data, and according to the standard format, the urban data different from the standard format is cleaned; Furthermore, the urban data after data cleaning is classified according to the types it contains to obtain corresponding data pools; the data pools include a population data pool, an economic data pool, an infrastructure data pool, an environmental data pool, a land use data pool, a traffic data pool, an education data pool, a medical data pool, a social security data pool, and a cultural data pool; Denoise each data pool; Obtain the expected values corresponding to each data pool; The process of obtaining the expected values includes: Rearrange the data in each data pool according to the collection time, associate the urban data with the collection time to generate corresponding urban data sets; obtain the average value, maximum value, minimum value, and variance of the data in the data pool; Obtain the expected values according to the average value and variance; Compare the expected values corresponding to each data pool with the data in the corresponding data pool. If the data in the data pool deviates from the corresponding expected value, the corresponding data is excluded; otherwise, the corresponding data is retained to generate a new data pool; The new data pool includes a new population data pool, a new economic data pool, a new infrastructure data pool, a new environmental data pool, a new land use data pool, a new traffic data pool, a new education data pool, a new medical data pool, a new social security data pool, and a new cultural data pool; Perform data reduction on the new data pool. The specific process includes: Set the characteristic values corresponding to the new data pool, and obtain the corresponding characteristic subsets according to the characteristic values; extract the characteristic subsets obtained from the new data pool, set new characteristic values for the remaining data in the new data pool, and obtain the corresponding characteristic subsets according to the new characteristic values; loop in turn until all the data in the new data pool generates characteristic subsets; Store several characteristic subsets according to the differences of the new data pool to obtain the corresponding subset database; It should be further noted that in the specific implementation process, using these data, the city can be analyzed and planned to improve the city's development and the quality of life of residents.

[0019] The process of the second processing unit for processing urban pollution data includes: Obtain the node positions corresponding to the sensor nodes and the corresponding urban pollution data; furthermore, obtain the collection time corresponding to the urban pollution data, associate the data to generate an urban data set; Obtain the maximum and minimum values of the urban pollution data corresponding to the urban data set and the real-time urban pollution data; Obtain the urban pollution data index based on the maximum and minimum values and the real-time urban pollution data; That is, the specific formula is:

[0020] Among them, t represents the collection time corresponding to the urban pollution data; r represents the node position; represents the maximum value in the urban pollution data; represents the minimum value in the urban pollution data; represents the real-time urban pollution data; It should be further noted that in the specific implementation process, among urban data, urban pollution data plays a crucial role in the development of the city. The reduction and treatment of urban pollution data have an impact on the urban environment.

[0021] The data analysis module is used to analyze the urban pollution data. According to the analysis results, visual data is generated. The specific process includes: Set the threshold of the urban pollution data index corresponding to the urban data set and compare it with the corresponding urban pollution data; if it is less than the urban pollution data index, mark the corresponding urban pollution data as abnormal urban pollution data, and then obtain the corresponding collection time and node position; otherwise, no processing is performed; Associate the abnormal urban pollution data with the corresponding collection time and node position to generate an abnormal urban pollution data set; Generate an abnormal pollution data curve coordinate graph with the abnormal pollution data and the collection time; the abnormal pollution data curve coordinate graph includes an x-axis and a y-axis; the collection time is used to represent the x-axis of the abnormal pollution data curve coordinate graph; the abnormal pollution data is used to represent the y-axis of the abnormal pollution data curve coordinate graph; And send the abnormal pollution data curve coordinate graph to the data management module.

[0022] The data visualization module is used to visualize the subset database, generate an urban data curve coordinate graph, and then analyze the urban data to generate an urban log. The specific process includes: Generate subset curve coordinate graphs for each subset database corresponding to the new data pool; associate the subset curve graphs to generate an urban data curve coordinate graph; It should be further noted that in the specific implementation process, the urban data curve coordinate map includes a population data curve coordinate map, an economic data curve coordinate map, an infrastructure data pool curve coordinate map, an environmental data curve coordinate map, a land use data curve coordinate map, a traffic data curve coordinate map, an education data curve coordinate map, a medical data curve coordinate map, a social security data curve coordinate map, and a cultural data curve coordinate map; Analyze the urban data according to the urban data curve coordinate map to obtain urban logs and send them to the data management module; The urban logs include the data situation today, data trends, and suggestions.

[0023] The data management module is used to manage urban logs and abnormal pollution data curve coordinate maps. The specific process includes: Set an allowed access account in the data management module; log in to the allowed access account to view the urban logs and abnormal pollution data curve coordinate maps corresponding to the urban data.

[0024] Working principle: The present invention collects urban data in real time through an information collection module, sets a first processing unit and a second processing unit. The first processing unit processes the urban data to obtain a subset database, and the second processing unit processes the urban pollution data obtained by the sensor nodes to obtain an urban pollution data index; and sends it to the data analysis module for analyzing the urban pollution data. According to the analysis results, an abnormal pollution data curve coordinate map is generated; the subset database is visualized according to the data visualization module to generate an urban data curve coordinate map, and then the urban data is analyzed to generate urban logs; and then the data management module manages the urban data according to the urban logs; improving the need for real-time monitoring of urban data and flexible management of various online / offline data to ensure the timeliness and accuracy of the data.

[0025] The features and exemplary embodiments of various aspects of the present application will be described in detail above. For the purpose, technical solutions and advantages of the present application to be more clearly understood, the present application will be further described in detail below in combination with the accompanying drawings and specific embodiments; it should be understood that the specific embodiments described herein are only intended to explain the present application, rather than limiting the present application; for those skilled in the art, the present application can be implemented without some of these specific details. The above description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0026] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A smart management system based on three-dimensional visualization, including a control terminal, characterized in that, The control terminal is communicatively connected to an information acquisition module, a data processing module, a data analysis module, a data visualization module, and a data management module; The information acquisition module is used to collect urban data in real time; The data processing module includes a first processing unit and a second processing unit; the first processing unit is used to process urban data to obtain a subset database; the second processing unit is used to process the urban pollution data obtained by the sensor nodes, and then obtain the urban pollution data index; The data analysis module is used to analyze the urban pollution data, and generate an abnormal pollution data curve coordinate diagram according to the analysis results; The data visualization module is used to visualize the subset database, generate an urban data curve coordinate diagram, and then analyze the urban data to generate an urban log; The data management module is used to manage the urban data according to the urban log.

2. The intelligent management system based on three-dimensional visualization according to claim 1, characterized in that The process of the information acquisition module collecting urban data in real time includes: The urban data includes population data, economic data, infrastructure data, environmental data, land use data, traffic data, education data, medical data, social security data, and cultural data; Obtain urban data through government department statistics, sensor networks, and various Internet platforms; The sensor network includes a number of sensor nodes, and the number of sensor nodes is organized in a self-organizing manner to form a distributed intelligent network system that can autonomously complete specified tasks according to the environment; and a number of sensor nodes are deployed inside the city, and the positions of the sensor nodes in the sensor network are obtained through GPS and marked as node positions; The sensor nodes are used to obtain the urban pollution data corresponding to the node positions; the pollution data includes air pollution data, water pollution data, soil pollution data, and noise pollution data; Set up a gateway, which is wirelessly communicatively connected to the sensor network and the data management module.

3. The intelligent management system based on three-dimensional visualization according to claim 2, characterized in that, The process of the first processing unit obtaining the subset database includes: Preprocess the urban data, and the preprocessing includes data cleaning and data reduction; The data cleaning is used to clean the format of the urban data, and the format cleaning is used to set a standard format for the urban data, and according to the standard format, clean the urban data that is different from the standard format; Furthermore, classify the urban data after data cleaning according to the types it contains to obtain corresponding data pools.

4. A smart management system based on 3D visualization according to claim 3, characterized in that, Rearrange the data in each data pool according to the collection time, associate the urban data with the collection time to generate a corresponding urban data set; obtain the average value, maximum value, minimum value, and variance of the data in the data pool; Obtain the expected value according to the average value and variance; Compare the expected value corresponding to each data pool with the data in the corresponding data pool. If the data corresponding to the data pool deviates from the corresponding expected value, the corresponding data is excluded; otherwise, the corresponding data is retained to generate a new data pool.

5. The intelligent management system based on three-dimensional visualization according to claim 4, characterized in that, Set the characteristic value corresponding to the new data pool, and obtain the characteristic subset corresponding to the new data pool according to the characteristic value; extract the characteristic subset obtained from the new data pool, set a new characteristic value for the remaining data in the new data pool, and obtain the new characteristic subset according to the new characteristic value; Loop sequentially until all the data in the new data pool are generated into feature subsets; Store several feature subsets according to the differences in the new data pool to obtain the corresponding subset databases.

6. The intelligent management system based on three-dimensional visualization according to claim 5, wherein, The process by which the second processing unit obtains the urban pollution data index includes: Obtain the node location corresponding to the sensor node and the corresponding urban pollution data; further obtain the collection time corresponding to the urban pollution data, and perform data association on the data to generate an urban data set; Obtain the maximum value, minimum value, and real-time urban pollution data in the urban pollution data corresponding to the urban data set; Obtain the urban pollution data index according to the maximum value, minimum value, and real-time urban pollution data.

7. A smart management system based on three-dimensional visualization according to claim 6, characterized in that, The process by which the data analysis module generates the abnormal pollution data curve coordinate diagram includes: Set the threshold of the urban pollution data index corresponding to the urban data set and compare it with the corresponding urban pollution data; if it is less than the urban pollution data index, mark the corresponding urban pollution data as abnormal urban pollution data, and further obtain the corresponding collection time and node location; otherwise, do nothing; Perform data association on the abnormal urban pollution data and the corresponding collection time and node location to generate an abnormal urban pollution data set; Generate an abnormal pollution data curve coordinate diagram with the abnormal pollution data and the collection time.

8. A smart management system based on 3D visualization according to claim 7, characterized in that The process by which the data visualization module generates the urban log includes: Generate subset curve coordinate diagrams for each subset database corresponding to the new data pool; associate the subset curve diagrams to generate an urban data curve coordinate diagram; Analyze the urban data according to the urban data curve coordinate diagram to obtain the urban log and send it to the data management module; The urban log includes the data situation today, data trend, and suggestions.

9. A smart management system based on 3D visualization according to claim 8, characterized in that The process by which the data management module manages the urban data according to the urban log includes: Set the allowed access accounts in the data management module; log in to the allowed access accounts to view the urban log and the abnormal pollution data curve coordinate diagram corresponding to the urban data.

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