Data element management system applied to smart city

Abstract

The invention, which relates to the technical field of urban governance, discloses a data element governance system applied to a smart city, comprising a cloud platform, a data acquisition module, a data processing module, a data analysis module and an urban governance module. The data acquisition module acquires governance related data of a plurality of city districts of the smart city and binds the governance related data with district information of respective city districts to serve as a governance data set of the current smart city, the data processing module performs data cleaning, feature element mining, feature element matching and feature weight assignment on the governance data set, and the data processing module performs data processing on the governance data set. The data analysis module is used for integrating the governance feature elements of the city districts with the same feature weight assignment to generate a plurality of groups of city district sets and obtaining respective governance measures after data analysis, and the city governance module is used for dividing the governance priority of the city district corresponding to each city district set. And executing corresponding treatment measures according to the treatment priority.

Description

Technical Field

[0001] The present invention relates to the field of urban governance technology, and specifically to an application in smart city data element governance systems. Background Art

[0002] In the process of building smart cities, the issue of how to manage and utilize data elements has become increasingly prominent. In existing technologies, data governance systems often have the following shortcomings: uneven data quality, which makes it difficult to meet the application needs of smart cities, insufficient analysis of the governance needs of each urban area under smart cities, and inability to make decisions on corresponding governance measures, resulting in the failure to promptly handle and resolve events that need to be resolved in urban areas. These are the issues that urgently need to be resolved in current urban governance. Summary of the invention

[0003] In order to solve the above problems, the purpose of the present invention is to provide a data element governance system for smart cities.

[0004] The object of the present invention can be achieved by the following technical solution: applied to a smart city data element governance system, including a cloud platform, wherein the cloud platform is communicatively connected with a data acquisition module, a data processing module, a data analysis module and a city governance module;

[0005] The data collection module arranges corresponding data collection equipment in several urban areas of the smart city, collects governance-related data of each urban area through the data collection equipment, and binds the governance-related data with the area information of each urban area, and then integrates them as the governance data set of the current smart city;

[0006] The data processing module is used to perform data cleaning, feature element mining, feature element matching and feature weight assignment on the current smart city governance data set, thereby generating governance feature elements corresponding to each urban area in the smart city;

[0007] The data analysis module is used to integrate the governance characteristic elements of urban areas with the same characteristic weight assignment, thereby generating several groups of urban area sets, performing data analysis on each group of urban area sets, and then obtaining governance measures for each urban area set;

[0008] The urban governance module is used to divide the governance priorities of urban areas corresponding to several groups of urban area sets, and execute governance measures for each urban area set according to the governance priorities.

[0009] Furthermore, corresponding data collection equipment is arranged in several urban areas of the smart city. The process of collecting governance-related data of each urban area through the data collection equipment includes:

[0010] The smart city is divided into several urban areas and numbered, and the number is recorded as i, i = 1, 2, 3, ..., n, where n is a natural number greater than 0. Starting from number i = 1, corresponding data collection equipment is arranged in each urban area in turn. The data collection equipment includes a panoramic camera, a face recognition device, a sensor module, and a data control terminal;

[0011] The panoramic camera is used to monitor the urban area in real time, and then collect video images of each urban area. The face recognition equipment is arranged at the entrances and exits of the residential areas, communities and other public places in each urban area, and is used to enter the facial information of each person passing through the entrances and exits. The sensor modules are arranged at a number of accident-prone points corresponding to each urban area, and then the environmental monitoring data of all accident-prone points in each urban area are obtained, and the environmental monitoring data of all accident-prone points in the same urban area are integrated and used as the area environmental monitoring data of each urban area. The video images, facial information and area environmental monitoring data of each urban area are integrated, and then the corresponding governance-related data for each urban area are constructed.

[0012] Furthermore, the process of binding the governance-related data with the district information of each city district and then integrating it as the governance data set of the current smart city includes:

[0013] Get several area information, each area information is associated with the corresponding area frame boundary, record the governance-related data of the urban area numbered i as ZL-Data[i], get the actual area boundary of the urban area corresponding to each governance-related data, compare the current actual area boundary with several area frame boundaries, and then get the comparison overlap rate, record the comparison overlap rate as Ch, set the overlap rate threshold, and record it as Ch 阈值 ;

[0014] Ch ≥ Ch 阈值 The area information of the urban area corresponding to the boundaries of all areas is marked as the information to be bound corresponding to the current governance-related data, and the one with the highest Ch value in the information to be bound is selected to bind with the current governance-related data, and then a binding relationship is established. The area information bound to the governance-related data of the urban area numbered i is recorded as PQ-Info[i], and the binding relationship between the governance-related data of the urban area numbered i and its corresponding area information is recorded as BD[i], then BD[i] = {ZL-Data[i], PQ-Info[i]};

[0015] Ch<Ch 阈值The area information of the urban area corresponding to the area frame boundary is marked as unmatched information, and no operation is performed. After the governance-related data of each urban area is bound to the area information corresponding to the urban area, the governance-related data corresponding to all urban areas are integrated and used as the governance data set of the current smart city.

[0016] Furthermore, the process of data cleaning and feature element mining for the current smart city governance data set includes:

[0017] The data cleaning of the smart city governance data set includes data review, missing value processing, duplicate value processing, outlier correction and data format correction. Data review is performed to locate the missing data, duplicate data and abnormal data in the governance data set, and missing value processing is performed on the missing data to convert the missing data into complete data. Duplicate data is removed through duplicate value processing, and outlier correction is performed on abnormal data to convert abnormal data into normal data.

[0018] Correct the data format of the governance data set after converting missing data into complete data, removing duplicate data, and converting abnormal data into normal data, and then uniformly convert the data parts in the governance data set that do not meet the preset standard data format into the standard data format;

[0019] Through data cleaning, the current smart city governance data set is transformed into a corresponding standard data set, and feature element mining is performed on the standard data set to generate a number of preliminary feature elements. The preliminary feature elements include preliminary image feature elements corresponding to the video images of each urban area, preliminary identity credential feature elements corresponding to facial information, and preliminary environmental feature elements corresponding to the area environmental monitoring data.

[0020] Furthermore, the process of matching characteristic elements and assigning characteristic weights to generate corresponding governance characteristic elements for each urban area in the smart city includes:

[0021] An element library is set to store a plurality of supplementary feature elements corresponding to the preliminary image feature elements, preliminary identity credential feature elements, and preliminary environment feature elements, and the elements are respectively identified as supplementary feature element 1, supplementary feature element 2, and supplementary feature element 3, wherein the supplementary feature element 1, supplementary feature element 2, and supplementary feature element 3 are associated with corresponding matching lock values, and the preliminary image feature elements, preliminary identity credential feature elements, and preliminary environment feature elements are associated with corresponding matching key values;

[0022] Input the preliminary image feature elements, preliminary identity credential feature elements and preliminary environmental feature elements into the feature library for feature element matching, match the preliminary feature elements and supplementary feature elements whose matching lock value and matching key value add up to a preset matching achievement value as a complete feature element, and then match and generate several complete feature elements, assign feature weights to each complete feature element, and each complete feature element is used to characterize the behavior events recorded corresponding to the video images, face information and area environmental monitoring data in the corresponding urban area, and the behavior events include normal events and abnormal events;

[0023] The feature weights assigned by the feature weight assignment include 0 and 1. When the behavior event corresponding to the complete feature element is a normal event, the feature weight assigned to the complete feature element is 0. When the behavior event corresponding to the complete feature element is an abnormal event, the feature weight assigned to the complete feature element is 1.

[0024] After all the complete characteristic elements corresponding to each urban area in the smart city are assigned to the corresponding characteristic weights, the complete characteristic elements under each urban area are marked with their respective corresponding characteristic weights, thereby generating the governance characteristic elements corresponding to each urban area in the smart city.

[0025] Furthermore, the governance characteristic elements of urban areas with the same characteristic weight assignment are integrated to generate several groups of urban area sets, and data analysis is performed on each group of urban area sets to obtain the governance measures for each urban area set. The process includes:

[0026] The urban areas with the same feature weights in several urban areas are classified into a group of urban area sets, the governance feature elements of all urban areas in a group of urban area sets are marked according to the timestamps, and the governance feature elements with the same timestamps in a group of urban area sets are integrated as a set of elements to be analyzed. The corresponding data analysis is performed through the set of elements to be analyzed corresponding to each urban area set, and then the governance event set corresponding to each urban area set is obtained;

[0027] The governance event set includes different types of governance demand events. Different types of governance demand events correspond to different governance measures. The governance measures corresponding to the governance demand events of all urban areas under each urban area set are integrated as the governance measures corresponding to each urban area set.

[0028] Furthermore, the different types of governance demand events and the governance measures corresponding to each type of governance demand event include:

[0029] The types of governance demand events include abnormal public security events recorded by panoramic cameras in each urban area, abnormal entry and exit events recorded by facial recognition devices corresponding to the entrances and exits in each urban area, and abnormal environmental events corresponding to accident-prone points in each urban area;

[0030] The governance measures corresponding to the abnormal public security incidents are public security management measures;

[0031] The governance measures corresponding to the abnormal entry and exit events are entry and exit restriction measures;

[0032] The governance measures corresponding to the abnormal environmental events are environmental supervision measures.

[0033] Furthermore, the process of dividing the governance priorities of the urban areas corresponding to the urban area sets into several groups and executing the governance measures of each urban area set according to the governance priorities includes:

[0034] The characteristic weights of the urban areas included in each group of urban area sets are accumulated, and the accumulated value after the characteristic weights of each urban area set is accumulated is used as the judgment value of the governance priority set of all corresponding urban areas, and the corresponding governance priority from high to low is assigned to each urban area set in the order from large to small judgment values;

[0035] All urban areas corresponding to each urban area set execute corresponding governance measures in order of governance priority from high to low, and then solve the corresponding governance demand events under each urban area until all governance measures under all urban area sets are implemented.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows: by arranging data collection equipment in several urban areas of the smart city to collect corresponding governance-related data, and binding the governance-related data with the area information of each urban area, integrating them as the governance data set of the current smart city, performing data cleaning, feature element mining, feature element matching and feature weight assignment on the governance data set to generate the governance feature elements corresponding to each urban area in the smart city, integrating the governance feature elements of urban areas with the same feature weight assignment, and then generating several groups of urban area sets, analyzing the data of each group of urban area sets to obtain the governance measures of each urban area set, and finally dividing the governance priorities of the urban areas corresponding to the several groups of urban area sets, and executing the governance measures corresponding to each urban area set according to the governance priorities. On the one hand, relatively standardized governance feature elements are constructed for each urban area under the smart city, the data quality of governance-related data is unified, and the subsequent analysis of the governance needs of the smart city is convenient; on the other hand, accurate analysis of the governance needs of the urban areas is achieved, and corresponding governance measures are obtained, so as to realize the timely resolution of governance demand events under the urban areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0038] like Figure 1 As shown, it is applied to the smart city data element governance system, including a cloud platform, and the cloud platform is communicatively connected with a data acquisition module, a data processing module, a data analysis module and a city governance module;

[0039] The data collection module arranges corresponding data collection equipment in several urban areas of the smart city, collects governance-related data of each urban area through the data collection equipment, and binds the governance-related data with the area information of each urban area, and then integrates them as the governance data set of the current smart city;

[0040] The data processing module is used to perform data cleaning, feature element mining, feature element matching and feature weight assignment on the current smart city governance data set, thereby generating governance feature elements corresponding to each urban area in the smart city;

[0041] The data analysis module is used to integrate the governance characteristic elements of urban areas with the same characteristic weight assignment, thereby generating several groups of urban area sets, performing data analysis on each group of urban area sets, and then obtaining governance measures for each urban area set;

[0042] The urban governance module is used to divide the governance priorities of urban areas corresponding to several groups of urban area sets, and execute governance measures for each urban area set according to the governance priorities.

[0043] It should be further explained that, in the specific implementation process, corresponding data collection equipment is arranged in several urban areas of the smart city. The process of collecting governance-related data of each urban area through the data collection equipment includes:

[0044] The smart city is divided into several urban areas, and the urban areas are numbered, and the number is recorded as i, then i = 1, 2, 3, ..., n, where n is a natural number greater than 0, starting from number i = 1, the corresponding data collection equipment is arranged in each urban area in turn;

[0045] The data acquisition equipment includes a panoramic camera, a face recognition device, a sensor module and a data control terminal; wherein the panoramic camera is used to monitor the urban area in real time, and then collect video images of each urban area; the face recognition device is arranged at the entrance and exit of the residential area, community and other public places in each urban area, and is used to record the face information of each person passing through the entrance and exit;

[0046] The sensor module includes a temperature sensor, a humidity sensor and a noise sensor;

[0047] The sensor modules are arranged at several accident-prone points corresponding to each urban area, and the ambient temperature, ambient humidity and ambient noise values ​​of all accident-prone points in each urban area are obtained, and the ambient temperature, ambient humidity and ambient noise values ​​corresponding to each accident-prone point are integrated as the environmental monitoring data of the current accident-prone point, and the environmental monitoring data of all accident-prone points in the same urban area are integrated as the area environmental monitoring data of each urban area;

[0048] The ambient temperature, ambient humidity and ambient noise values ​​are collected by a temperature sensor, a humidity sensor and a noise sensor respectively;

[0049] Integrate the video images, facial information and environmental monitoring data of each urban area, and then construct the corresponding governance-related data for each urban area.

[0050] It should be further explained that in the specific implementation process, the process of binding the governance-related data with the district information of each urban district and then integrating it as the current smart city governance data set includes:

[0051] Obtaining a number of district information, including the location of the district office, the district administrative code, the contact information of the district management personnel, and the tracking information corresponding to each accident-prone point in the urban district, including the location coordinates of the accident-prone point, the contact information of the relevant person in charge, and the dispatch authority of the panoramic camera corresponding to the accident-prone point;

[0052] Each area information is associated with a corresponding area frame boundary, and the area frame boundary is used to indicate the boundary range of the urban area corresponding to each area information;

[0053] The governance-related data of the urban area numbered i is recorded as ZL-Data[i], and the actual area boundary of each urban area corresponding to the governance-related data is obtained. The current actual area boundary is compared with several area frame boundaries, and then the comparison coincidence rate is obtained, and the comparison coincidence rate is recorded as Ch. The coincidence rate threshold is set and recorded as Ch 阈值 ;

[0054] Ch ≥ Ch 阈值 The area information of the urban area corresponding to the boundaries of all areas is marked as the information to be bound corresponding to the current governance-related data, and the one with the highest Ch value in the information to be bound is selected to bind with the current governance-related data, thereby building the corresponding binding relationship;

[0055] Wherein, the area information bound to the governance-related data of the urban area numbered i is recorded as PQ-Info[i], and the binding relationship between the governance-related data of the urban area numbered i and its corresponding area information is recorded as BD[i], then BD[i] = {ZL-Data[i], PQ-Info[i]};

[0056] Ch<Ch 阈值 The area information of the urban area corresponding to the area frame boundary is marked as unmatched information, and no operation is performed;

[0057] After the governance-related data of each urban area is bound to the area information corresponding to the urban area, the governance-related data corresponding to all urban areas are integrated and then used as the governance data set of the current smart city.

[0058] It should be further explained that in the specific implementation process, the process of data cleaning and feature element mining of the current smart city governance data set includes:

[0059] The data cleaning of the smart city governance data set includes data review, missing value processing, duplicate value processing, outlier correction and data format correction, and the data review, missing value processing, duplicate value processing, outlier correction and data format correction are performed in sequence;

[0060] Conduct data review to locate missing data, duplicate data, and abnormal data in the governance data set, perform missing value processing on missing data, and then convert the missing data into complete data, remove duplicate data through duplicate value processing, perform outlier correction on abnormal data, and then convert the abnormal data into normal data;

[0061] Correct the data format of the governance data set after converting missing data into complete data, removing duplicate data, and converting abnormal data into normal data, and then uniformly convert the data parts in the governance data set that do not meet the preset standard data format into the standard data format;

[0062] Through data cleaning, the current smart city governance data set is transformed into a corresponding standard data set, and feature element mining is performed on the standard data set to generate a number of preliminary feature elements. The preliminary feature elements include preliminary image feature elements generated after feature element mining of video images in each urban area, preliminary identity credential feature elements generated after feature element mining of facial information, and preliminary environmental feature elements generated after feature element mining of area environmental monitoring data.

[0063] It should be further explained that, in the specific implementation process, the process of matching characteristic elements and assigning characteristic weights to generate the corresponding governance characteristic elements for each urban area in the smart city includes:

[0064] Setting an element library, wherein the element library stores a plurality of supplementary feature elements corresponding to the preliminary image feature elements, the preliminary identity credential feature elements, and the preliminary environment feature elements, wherein the supplementary feature element corresponding to the preliminary image feature element is identified as supplementary feature element one, the supplementary feature element corresponding to the preliminary identity credential feature element is identified as supplementary feature element two, and the supplementary feature element corresponding to the preliminary environment feature element is identified as supplementary feature element three;

[0065] The supplementary element 1, supplementary element 2 and supplementary element 3 are associated with corresponding matching lock values, and the preliminary image feature element, preliminary identity credential feature element and preliminary environment feature element are associated with corresponding matching key values;

[0066] Inputting the preliminary image feature elements, preliminary identity credential feature elements and preliminary environment feature elements into the feature library for feature element matching, matching the preliminary feature elements and the supplementary feature elements whose matching lock value and matching key value add up to a preset matching achievement value as a complete feature element, and then matching to generate a number of complete feature elements;

[0067] Assigning feature weights to each complete feature element, specifically: each complete feature element is used to characterize the behavior events recorded corresponding to the video images, face information, and area environmental monitoring data in the corresponding urban area, and the behavior events include normal events and abnormal events;

[0068] The feature weight assigned by the feature weight assignment includes 0 and 1. When the behavior event corresponding to the complete feature element is a normal event, the feature weight assigned to the complete feature element is 0. When the behavior event corresponding to the complete feature element is an abnormal event, the feature weight assigned to the complete feature element is 1.

[0069] After all the complete characteristic elements corresponding to each urban area in the smart city are assigned to the corresponding characteristic weights, the complete characteristic elements under each urban area are marked with their respective corresponding characteristic weights, thereby generating the governance characteristic elements corresponding to each urban area in the smart city.

[0070] It should be further explained that, in the specific implementation process, the governance characteristic elements of urban areas with the same characteristic weight assignment are integrated to generate several groups of urban area sets, and data analysis is performed on each group of urban area sets to obtain the governance measures for each urban area set. The process includes:

[0071] Classify urban areas with the same feature weights among several urban areas into a set of urban areas, and mark the governance feature elements of all urban areas in the set of urban areas according to timestamps, where the timestamp is the time when the behavior event corresponding to the governance feature element occurs in the corresponding urban area in the smart city;

[0072] Integrate a group of governance feature elements with the same timestamp under a set of urban area sets as a set of elements to be analyzed, perform corresponding data analysis through the set of elements to be analyzed corresponding to each urban area set, and then obtain the corresponding governance event set under each urban area set, wherein the governance event set includes different types of governance demand events;

[0073] The different types of governance demand events correspond to different governance measures;

[0074] The governance measures corresponding to the governance demand events of all urban areas under each urban area set are integrated and then used as the corresponding governance measures for each urban area set.

[0075] The types of governance demand events include abnormal public security events recorded by panoramic cameras in each urban area, abnormal entry and exit events recorded by facial recognition devices corresponding to the entrances and exits in each urban area, and abnormal environmental events corresponding to accident-prone points in each urban area;

[0076] The governance measures corresponding to the abnormal public security events are public security management measures, and the content of the public security management measures is: notify the district managers of the corresponding urban districts through the district managers' contact information, and the district managers check the abnormal public security events recorded and generated by the corresponding panoramic cameras in the current urban district, and the district managers solve the abnormal public security events according to the district management rules;

[0077] The governance measures corresponding to the abnormal entry and exit events are entry and exit restriction measures, and the content of the entry and exit restriction measures is: the facial information corresponding to the abnormal entry and exit events is included in the preset blacklist. When the facial information included in the blacklist is again entered into the face recognition device at the entrance and exit of the urban area, a voice message of "no entry" is broadcast, and the opening of the gate at the entrance and exit is stopped to restrict the communication of the person corresponding to the facial information at the entrance and exit, thereby completing the abnormal entry and exit event;

[0078] The control measures corresponding to the abnormal environmental events are environmental supervision measures, and the contents of the environmental supervision measures are: pushing the tracking information of the accident-prone points corresponding to the abnormal environmental events to the environmental supervision responsible personnel, and the environmental supervision responsible personnel will go to the accident-prone points to conduct on-site supervision and maintenance according to the tracking information.

[0079] It should be further explained that, in the specific implementation process, the process of dividing the governance priorities of the urban areas corresponding to several groups of urban area sets and executing the governance measures of each urban area set according to the governance priorities includes:

[0080] The characteristic weights of the urban areas included in each group of urban area sets are accumulated, and the accumulated value after the characteristic weights of each urban area set is accumulated is used as the judgment value of the governance priority set of all corresponding urban areas, and the corresponding governance priority from high to low is assigned to each urban area set in the order from large to small judgment values;

[0081] All urban areas corresponding to each urban area set execute corresponding governance measures in order of governance priority from high to low, and then solve the corresponding governance demand events under each urban area until all governance measures under all urban area sets are implemented.

[0082] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Applied to the smart city data element management system, including the cloud platform, characterized in that: The cloud platform is communicatively connected with a data acquisition module, a data processing module, a data analysis module and an urban governance module; The data collection module arranges corresponding data collection equipment in several urban areas of the smart city, collects governance-related data of each urban area through the data collection equipment, and binds the governance-related data with the area information of each urban area, and then integrates them as the governance data set of the current smart city; The data processing module is used to perform data cleaning, feature element mining, feature element matching and feature weight assignment on the current smart city governance data set, thereby generating governance feature elements corresponding to each urban area in the smart city; The data analysis module is used to integrate the governance characteristic elements of urban areas with the same characteristic weight assignment, thereby generating several groups of urban area sets, performing data analysis on each group of urban area sets, and then obtaining governance measures for each urban area set; The urban governance module is used to divide the governance priorities of urban areas corresponding to several groups of urban area sets, and execute governance measures for each urban area set according to the governance priorities.

2. According to claim 1, the data element management system for smart cities is characterized in that: Corresponding data collection equipment is arranged in several urban areas of the smart city. The process of collecting governance-related data of each urban area through the data collection equipment includes: The smart city is divided into several urban areas and numbered, and the number is recorded as i, i = 1, 2, 3, ..., n, where n is a natural number greater than 0. Starting from number i = 1, corresponding data collection equipment is arranged in each urban area in turn. The data collection equipment includes a panoramic camera, a face recognition device, a sensor module, and a data control terminal; The panoramic camera is used to monitor the urban area in real time, and then collect video images of each urban area. The face recognition equipment is arranged at the entrances and exits of the residential areas, communities and other public places in each urban area, and is used to enter the facial information of each person passing through the entrances and exits. The sensor modules are arranged at a number of accident-prone points corresponding to each urban area, and then the environmental monitoring data of all accident-prone points in each urban area are obtained, and the environmental monitoring data of all accident-prone points in the same urban area are integrated and used as the area environmental monitoring data of each urban area. The video images, facial information and area environmental monitoring data of each urban area are integrated, and then the corresponding governance-related data for each urban area are constructed.

3. The data element management system for smart cities according to claim 2 is characterized in that: The process of binding governance-related data with the district information of the respective city districts and then integrating them as the governance data set of the current smart city includes: Get several area information, each area information is associated with the corresponding area frame boundary, record the governance-related data of the urban area numbered i as ZL-Data[i], get the actual area boundary of the urban area corresponding to each governance-related data, compare the current actual area boundary with several area frame boundaries, and then get the comparison overlap rate, record the comparison overlap rate as Ch, set the overlap rate threshold, and record it as Ch 阈值 ; Ch ≥ Ch 阈值 The area information of the urban area corresponding to the boundaries of all areas is marked as the information to be bound corresponding to the current governance-related data, and the one with the highest Ch value in the information to be bound is selected to bind with the current governance-related data, and then a binding relationship is established. The area information bound to the governance-related data of the urban area numbered i is recorded as PQ-Info[i], and the binding relationship between the governance-related data of the urban area numbered i and its corresponding area information is recorded as BD[i], then BD[i] = {ZL-Data[i], PQ-Info[i]}; Ch<Ch 阈值 The area information of the urban area corresponding to the area frame boundary is marked as unmatched information, and no operation is performed. After the governance-related data of each urban area is bound to the area information corresponding to the urban area, the governance-related data corresponding to all urban areas are integrated and used as the governance data set of the current smart city.

4. The data element management system for smart cities according to claim 3 is characterized in that: The process of data cleaning and feature element mining for the current smart city governance data set includes: The data cleaning of the smart city governance data set includes data review, missing value processing, duplicate value processing, outlier correction and data format correction. Data review is performed to locate the missing data, duplicate data and abnormal data in the governance data set, and missing value processing is performed on the missing data to convert the missing data into complete data. Duplicate data is removed through duplicate value processing, and outlier correction is performed on abnormal data to convert abnormal data into normal data. Correct the data format of the governance data set after converting missing data into complete data, removing duplicate data, and converting abnormal data into normal data, and then uniformly convert the data parts in the governance data set that do not meet the preset standard data format into the standard data format; Through data cleaning, the current smart city governance data set is transformed into a corresponding standard data set, and feature element mining is performed on the standard data set to generate a number of preliminary feature elements. The preliminary feature elements include preliminary image feature elements corresponding to the video images of each urban area, preliminary identity credential feature elements corresponding to facial information, and preliminary environmental feature elements corresponding to the area environmental monitoring data.

5. The data element management system for smart cities according to claim 4 is characterized in that: The process of matching characteristic elements and assigning characteristic weights to generate the corresponding governance characteristic elements for each urban area in the smart city includes: An element library is set to store a plurality of supplementary feature elements corresponding to the preliminary image feature elements, preliminary identity credential feature elements, and preliminary environment feature elements, and the elements are respectively identified as supplementary feature element 1, supplementary feature element 2, and supplementary feature element 3, wherein the supplementary feature element 1, supplementary feature element 2, and supplementary feature element 3 are associated with corresponding matching lock values, and the preliminary image feature elements, preliminary identity credential feature elements, and preliminary environment feature elements are associated with corresponding matching key values; Input the preliminary image feature elements, preliminary identity credential feature elements and preliminary environmental feature elements into the feature library for feature element matching, match the preliminary feature elements and supplementary feature elements whose matching lock value and matching key value add up to a preset matching achievement value as a complete feature element, and then match and generate several complete feature elements, assign feature weights to each complete feature element, and each complete feature element is used to characterize the behavior events recorded corresponding to the video images, face information and area environmental monitoring data in the corresponding urban area, and the behavior events include normal events and abnormal events; The feature weights assigned by the feature weight assignment include 0 and 1. When the behavior event corresponding to the complete feature element is a normal event, the feature weight assigned to the complete feature element is 0. When the behavior event corresponding to the complete feature element is an abnormal event, the feature weight assigned to the complete feature element is 1. After all the complete characteristic elements corresponding to each urban area in the smart city are assigned to the corresponding characteristic weights, the complete characteristic elements under each urban area are marked with their respective corresponding characteristic weights, thereby generating the governance characteristic elements corresponding to each urban area in the smart city.

6. The data element management system for smart cities according to claim 5 is characterized in that: The process of integrating the governance characteristic elements of urban areas with the same characteristic weight assignment to generate several groups of urban area sets, performing data analysis on each group of urban area sets, and then deriving the governance measures for each urban area set includes: The urban areas with the same feature weights in several urban areas are classified into a group of urban area sets, the governance feature elements of all urban areas in a group of urban area sets are marked according to the timestamps, and the governance feature elements with the same timestamps in a group of urban area sets are integrated as a set of elements to be analyzed. The corresponding data analysis is performed through the set of elements to be analyzed corresponding to each urban area set, and then the governance event set corresponding to each urban area set is obtained; The governance event set includes different types of governance demand events. Different types of governance demand events correspond to different governance measures. The governance measures corresponding to the governance demand events of all urban areas under each urban area set are integrated as the governance measures corresponding to each urban area set.

7. The data element management system for smart cities according to claim 6 is characterized in that: The different types of governance demand events and the governance measures corresponding to each type of governance demand event include: The types of governance demand events include abnormal public security events recorded by panoramic cameras in each urban area, abnormal entry and exit events recorded by facial recognition devices corresponding to the entrances and exits in each urban area, and abnormal environmental events corresponding to accident-prone points in each urban area; The governance measures corresponding to the abnormal public security incidents are public security management measures; The governance measures corresponding to the abnormal entry and exit events are entry and exit restriction measures; The governance measures corresponding to the abnormal environmental events are environmental supervision measures.

8. The data element management system for smart cities according to claim 7 is characterized in that: The process of dividing the governance priorities of the urban areas corresponding to several groups of urban area sets and executing the governance measures of each urban area set according to the governance priorities includes: The characteristic weights of the urban areas included in each group of urban area sets are accumulated, and the accumulated value after the characteristic weights of each urban area set is accumulated is used as the judgment value of the governance priority set of all corresponding urban areas, and the corresponding governance priority from high to low is assigned to each urban area set in the order from large to small judgment values; All urban areas corresponding to each urban area set execute corresponding governance measures in order of governance priority from high to low, and then solve the corresponding governance demand events under each urban area until all governance measures under all urban area sets are implemented.

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