Urban management event processing method and system based on Beidou grid code

Abstract

The invention relates to the technical field of data processing, and particularly discloses a city management event processing method and system based on Beidou grid codes. The method comprises the steps of performing grid coding on geographic space data in a city space range based on Beidou grid codes, and generating a basic grid model; when a city management event is reported, obtaining reported event data; processing the event data to determine the event type, geographic position and attribute of the city management event; determining a Beidou grid code associated with the city management event by using the geographic position; judging whether similar events exist in the city management events or not; if the similar events exist, judging whether the events are repeated events or not; if the city management event is not the repeated event, the event type and attribute of the city management event are mapped to a space grid pointed by the Beidou grid code; and packaging each block of data in the basic grid model to provide the data for a subsequent batch processing flow. Based on the invention, data support can be provided for urban management planning.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method and system for processing urban management events based on Beidou grid codes. Background Art

[0002] With the rapid development of the digital economy, the demand for urban management and services is increasing. The existing urban management system has many deficiencies in data collection, processing and application, such as low data accuracy, poor real-time performance and difficulty in data sharing. Specifically, the inconsistency of systems and data coding methods between industries and departments has caused each industry and local department to act independently and fragmented, making it difficult to integrate, share and open cross-departmental information resources.

[0003] The BeiDou Navigation Satellite System (BDS) has high-precision positioning, wide coverage and strong anti-interference capabilities. The efficient operation of smart cities is inseparable from the unified spatial and temporal reference of data. As an important new infrastructure that provides all-weather, all-day, high-precision positioning, navigation and timing services to global users, the BeiDou system can deeply empower the smart operation and governance of cities. By combining with grid code technology, it can effectively improve the level of intelligence and service quality of urban management.

[0004] Beidou grid code converts traditional longitude and latitude floating-point attribute data into Beidou grid position code and Beidou segmentation time code of one-dimensional integer array, so that the location and time obtained by users are enhanced from simple attribute data to data that can be uniformly identified, directly associated, quickly indexed, easily transmitted, efficiently calculated on a large scale, and displayed in two or three dimensions. Using Beidou grid as a spatial unit can easily index all kinds of data uniformly, and conduct comprehensive data analysis and application based on the grid to solve current technical problems. Simply put, the grid is regarded as a container arranged by position, and various types of data are put into it according to the position, and displayed, analyzed and served according to the container number.

[0005] Beidou grid code technology realizes the encoding of three-dimensional space through one-dimensional integers, which can efficiently realize spatial analysis of data, focusing on solving the problems of location identification, sharing and exchange, and efficient calculation of data in the era of spatial big data, and providing us with new ideas for the organization and management of urban management event big data in spatial dimension. It integrates and connects the data systems of "smart city", "city brain", "city lifeline" and other completed in some regions, so that the global digital data can be strung together into a chain, and the "integrated and one-network" dynamic management, active monitoring and analysis results of the global digital such as civil affairs, environmental protection, emergency, fire protection, transportation, enterprise production safety, and enterprise logistics information monitoring can be realized, which is of great significance for the aggregation, updating, sharing of data, the development and utilization of big data resources, and the promotion of digital transformation and intelligent transformation of manufacturing industry.

[0006] Therefore, a solution is needed to handle urban management events based on Beidou grid code. Summary of the invention

[0007] The present application provides a method and system for processing urban management events based on Beidou grid codes, in an effort to solve or at least alleviate at least one of the above problems.

[0008] According to one aspect of the present application, a method for processing urban management events based on Beidou grid codes is provided, which is suitable for execution in a computing device.

[0009] The method comprises: based on Beidou grid code, grid coding each geographic space data within the urban space range to generate a basic grid model, wherein the basic grid model comprises a plurality of block data, and each block data is indexed by Beidou grid code.

[0010] When a city management event is reported, the reported event data is obtained, and the event data includes at least one of text data, video data, and voice data.

[0011] The event data is processed to determine the event type, geographic location and attributes of the urban management event; the Beidou grid code associated with the urban management event is determined using the geographic location; the Beidou grid code is used to determine whether there are similar events to the urban management event in the basic grid model; if there are similar events, it is determined whether it is a repeated event; if it is not a repeated event, the event type and attributes of the urban management event are mapped to the spatial grid pointed to by the Beidou grid code to update the basic grid model; each block of data in the basic grid model is encapsulated to provide it to the subsequent batch processing flow.

[0012] Optionally, the method according to the present application also includes tracking and evaluating events: tracking the progress of event processing in real time through the platform to ensure that the event is handled in a timely manner. Using the Beidou grid code and the data analysis capabilities of the platform system, statistics and analysis of urban management events are performed to find out high-incidence areas and types, and provide decision support for subsequent urban management. Optionally, in the method according to the present application, based on the Beidou grid code, grid encoding is performed on each geographic spatial data within the urban space to generate a basic grid model, including: obtaining geographic spatial data from multiple data sources, wherein the geographic spatial data includes location information, time information and attribute information; according to the location information, respectively determining the spatial grid to which the corresponding geographic spatial data belongs, wherein the spatial grid is obtained by gridding the urban space based on the Beidou grid code, and each spatial grid has a unique Beidou grid code; the time information and attribute information of each of the geographic spatial data are mapped to the determined spatial grid to generate a basic grid model.

[0013] Optionally, in the method according to the present application, grid data indexing is implemented. A grid coding database (data table) is established, and the grid code is used as the primary key of the index table to form a logically segmented index table based on the earth's spatial position. The grid data table subsystem manages the encoded data through grids and grid codes to implement functions such as data indexing and data index updating. It provides services for grid-based rapid query and retrieval of multi-source heterogeneous big data, and supports business applications such as grid-based computing and analysis.

[0014] Optionally, in the method according to the present application, the codes are dynamically managed. Through the dynamic code management, a data code dynamic update mechanism is constructed to achieve dynamic and regular code updates of dynamic data, static data, historical data, and newly added data.

[0015] Optionally, the method according to the present application also includes: determining the Beidou grid codes of multiple spatial grids contained in the jurisdiction area; using the Beidou grid code to perform statistical analysis on events within the jurisdiction area to determine the management status of the jurisdiction area.

[0016] Optionally, in the method according to the present application, statistical analysis of events within the jurisdiction includes: determining one or more Beidou grid codes corresponding to the scope of each area; based on the determined Beidou grid codes, counting the number of urban management events of each event category in each area, so as to respectively determine the types of high-incidence events and their frequencies in each area.

[0017] Optionally, in the method according to the present application, statistical analysis of events within the jurisdiction includes: counting time information corresponding to urban management events of the same event category within the jurisdiction to determine the time distribution of each event type.

[0018] Optionally, in the method according to the present application, the event data is processed to determine the event type, geographic location and attributes of the urban management event, including: if the event data contains text data, identifying relevant information of the event from the text data; if the event data contains voice data, converting the voice data into text data, and processing the converted text data to identify relevant information of the event; if the event data contains video data, extracting feature data of the video data, and generating relevant information of the event based on the feature data, wherein the feature data includes at least one of equipment, personnel, materials, and regional edges; combining the relevant information to determine the event type, geographic location and attributes of the urban management event.

[0019] Optionally, in the method according to the present application, a video space grid system is constructed, and based on a video grid engine, video space and city-wide grid mapping is achieved, and rapid retrieval of video data based on location and time and rapid query of video-based encoded data are achieved, providing important data support and supplement for pre-event preparation, in-event monitoring, and post-event risk planning.

[0020] Optionally, in the method according to the present application, event types include: city appearance and environment, publicity and advertising, construction management, street order, emergencies and other event types.

[0021] Optionally, in the method according to the present application, event-centered spatiotemporal big data support is implemented. Beidou grid coded data has the advantages of spatial location and time analysis, and can be queried and counted by time range and event name or device name, which greatly facilitates the management and attention of a single device or event. Standard encoding, reconstruction and collection of various types of data in a spatiotemporal range are implemented to form a new data management framework with space as the management object and various types of data falling into the space as attributes. The system encapsulates the data sets that fall into the same grid to form a standard block data set. The system compresses the encapsulated block data and provides it to other business systems through URL links, realizing data sharing and on-demand acquisition services for urban real-time big data.

[0022] Optionally, in the method according to the present application, the Beidou grid code is used to determine whether there are similar events to the urban management event from the basic grid model, including: obtaining data associated with the Beidou grid code from the basic grid model; determining whether there are urban management events in the acquired data that are consistent with the event type of the urban management event and belong to the same time period; if so, confirming the existence of similar events.

[0023] Optionally, in the method according to the present application, determining whether it is a repeated event includes: comparing the attributes of the similar event with the attributes of the city management event to see if they are consistent; if not, confirming that it is not a repeated event.

[0024] Optionally, in the method according to the present application, each block data in the basic grid model is encapsulated to provide it to a subsequent batch processing flow, including: according to the area corresponding to the Beidou grid code, the associated block data is sent to the corresponding local department for processing.

[0025] According to another aspect of the present application, a system for processing urban management events based on Beidou grid codes is provided, comprising: a data connection encoding module, adapted to perform grid encoding on various geographic spatial data within the urban space range based on Beidou grid codes to generate a basic grid model; an event reporting processing module, adapted to obtain reported event data when an urban management event is reported, wherein the event data comprises at least one of text data, video data, and voice data; an event preprocessing module, adapted to process the event data to determine the event type, geographic location, and attributes of the urban management event, and to determine the Beidou grid code associated with the urban management event using the geographic location; and adapted to use the Beidou grid code to determine whether there are similar events to the urban management event in the basic grid model, and to determine whether it is a repeated event when there are similar events; a data mapping module, adapted to map the event type and attributes of the urban management event to the spatial grid pointed to by the Beidou grid code when it is not a repeated event, to update the basic grid model; and a grid data analysis module, adapted to encapsulate each block of data in the basic grid model to provide it to a subsequent batch processing flow, and adapted to analyze and process each block of data.

[0026] According to another aspect of the present application, a computing device is provided, comprising: one or more processor memories; one or more programs, wherein the one or more programs are stored in the memories and configured to be executed by one or more processors, and the one or more programs include instructions for executing any of the above methods.

[0027] According to another aspect of the present application, the central server of the computing device is responsible for performing the main computing tasks, such as data processing, analysis, storage, etc. The edge computing node is responsible for obtaining the original data from the video acquisition device, etc., and sending it to the central server after pre-processing.

[0028] According to another aspect of the present application, a computer-readable storage medium storing one or more programs is provided. The one or more programs include instructions. When the instructions are executed by a computing device, the computing device executes any of the methods described above.

[0029] According to another aspect of the present application, a sub-table storage solution is provided. When a layer is converted into a Beidou grid code, the amount of data will be much larger than the original data. Therefore, it is necessary to adopt a sub-table storage solution to improve query efficiency. Specifically, a separate table can be created for the Beidou grid code table corresponding to each layer, and the query can be routed to a specific code table through the primary key of the layer, thereby isolating the layer data.

[0030] According to another aspect of the present application, a computer program product is provided, comprising a computer program / instruction, wherein the computer program / instruction implements the steps of the above-mentioned method when executed by a processor.

[0031] In summary, the Beidou grid code divides the earth's space into multiple levels to form continuous plane or three-dimensional units, called "Beidou grids". Each grid can be assigned a unique and computable code, which can be used as a location identifier for the earth's space area. All information or data on the earth can fall into one or more grids, so the real earth space can be identified, expressed, organized and calculated. The Beidou grid code can be used to analyze space, airspace, underground, urban buildings and facilities to form Beidou map technology, which is a data map system that corresponds to and interacts with the grid space of the physical world and the digital world. By introducing the Beidou grid code engine into the place name and address engine and promoting the place name and address engine, data gridding can be achieved.

[0032] After the data is gridded, it is convenient to attribute each data to different management blocks according to its source to form block data. According to the location where the data is generated, the Beidou grid code technology is used to encode the data and give the data a location grid, which is equivalent to putting the data in a suitable container or physical unit grid. In this way, data belonging to the same physical unit grid can be gathered together, and spatial grids of different sizes form mutual associations and inclusion relationships between data through nested inclusion relationships, providing an analytical basis for data analysis and prediction. These data, through spatial association, constitute a cross-regional, cross-departmental, and cross-level information sharing and linkage mode, changing the traditional aggregation mode that relies on data exchange and sharing, and forming a system for coordinated utilization, co-construction and sharing of urban management data resources.

[0033] According to the solution of this application, the core is to use space-time grid technology to re-code all buildings, equipment, materials, personnel, environment, places, events, etc. within the city, connect to ubiquitous perception data such as the Beidou system, satellite remote sensing, and Internet of Things sensor equipment, and generate a basic grid model indexed by the Beidou grid code.

[0034] Based on this basic grid model, when a city management event is reported, the event data is first processed to determine information such as the event type, geographic location, and attributes; then, the Beidou grid code is determined based on the geographic location, and based on the Beidou grid code, it is further analyzed whether the city management event is a repeated reporting event. If it is not a repeated event, the event type and attributes are mapped to the spatial grid pointed to by the Beidou grid code, and the basic grid model is updated.

[0035] For the basic grid model, the block data can be regularly encapsulated and provided to the subsequent batch processing flow. It can also be analyzed and calculated to determine the management status of each jurisdiction area in the city, thereby providing data support for urban management planning.

[0036] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to achieve the above and related purposes, certain illustrative aspects are described herein in conjunction with the following description and accompanying drawings, which indicate various ways in which the principles applied herein can be practiced, and all aspects and their equivalents are intended to fall within the scope of the claimed subject matter. By reading the following detailed description in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. Throughout the application, the same reference numerals generally refer to the same parts or elements.

[0038] Figure 1 A schematic diagram of a system 100 for processing urban management events based on Beidou grid codes according to some embodiments of the present application is shown;

[0039] Figure 2 A schematic diagram of a computing device 200 according to some embodiments of the present application is shown;

[0040] Figure 3 A schematic flow chart of a method 300 for processing a city management event based on a Beidou grid code according to some embodiments of the present application is shown;

[0041] Figure 4 A schematic diagram of a basic grid model according to some embodiments of the present application is shown;

[0042] Figure 5 A schematic diagram of a video grid engine according to some embodiments of the present application is shown;

[0043] Figure 6 A schematic diagram of the functional architecture of a BeiDou grid base system according to some embodiments of the present application is shown. DETAILED DESCRIPTION

[0044] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0045] Urban management incidents refer to phenomena and behaviors that affect or damage the city's appearance and order due to human or natural factors, and require professional urban management departments to handle and restore them to normal. These incidents are subdivided into the following categories:

[0046] Urban appearance and environment: involving the maintenance and management of the urban appearance and environment, including street cleaning, greening maintenance, etc.;

[0047] Advertising: involves the standardized setting and management of various advertisements in the city to ensure that the advertisements do not affect the city appearance;

[0048] Construction management: involves construction management and regulation during urban construction and renovation, ensuring that construction does not affect citizens' lives and transportation;

[0049] Street order: involves the maintenance of street order, including the management of traffic order, business operations on the road and other issues;

[0050] Emergency events: response and handling of emergencies such as natural disasters, accidents, disasters, public health incidents and social security incidents;

[0051] Other event categories: include some events that are not included in the above categories but fall within the scope of urban management responsibility.

[0052] It can be seen that urban management events are closely related to the data and collaboration of multiple departments. These data and the joint efforts of departments constitute a complete system of urban management, which is of great significance for improving urban operation efficiency, improving the quality of life of residents, and promoting social harmony and stability.

[0053] Beidou grid location code (referred to as Beidou grid code) is a grid location code developed on the basis of Peking University's new geospatial subdivision theory and suitable for the output of various application terminals of the Beidou satellite navigation system. It is designed to adapt to the positioning accuracy of the Beidou system (including the augmentation system), while taking into account the use of people and equipment. It is an important supplement and extension of the latitude and longitude point location coding system. As a basic output of the positioning, navigation and timing system represented by the Beidou system, it assigns values ​​to the regional positions of all things, and can realize the unified identification and expression of global spatial position gridding and one-dimensional integer numbers at the forefront of the information chain, thereby providing better and more convenient spatial information basic services for various applications under big data conditions, and improving the organization, processing, analysis, transmission and application efficiency of geospatial location data.

[0054] Compared with the traditional method of using a pair of longitude and latitude coordinates to represent the location of a point, the Beidou grid code uses a number string of varying lengths to represent a regional location of varying precision. Based on this, the Beidou grid code can effectively express all-round spatial data such as terrain, elevation, and depth. This technically solves the problem of how to identify irregular and non-equal-elevation areas, and fills the gap in the expression of longitude and latitude. Combined with the timing function of the Beidou system, the Beidou grid code has accurate spatiotemporal expression functions and can provide time information for location identification. At the same time, the Beidou grid code can assume the function of indexing by accurately providing spatiotemporal tags, and can cope with various geographic information data, thereby opening up information integration and sharing channels horizontally.

[0055] In the processing of urban management events, the calculation of the relative spatiotemporal relationship between objects is the most basic data requirement. Traditional technologies generally construct matrices to perform floating-point calculations of momentum, which has problems such as large real-time calculations and slow responses. The Beidou grid code itself is a string of binary codes of integers, which improves the calculation efficiency.

[0056] According to the scheme of this application, based on the Beidou grid code, urban management events are uniformly coded and processed, providing important data support and supplement for pre-event preparation, in-event monitoring, and post-event risk planning. This scheme is summarized as follows.

[0057] (1) Beidou Grid Code Technology Foundation

[0058] Beidou grid code is a multi-scale, discrete, global geographic grid coding model suitable for navigation and positioning services developed on the basis of global grid division. This model proposes a unified identification and expression method for global spatial regional location information, which can identify both location and region, and is more in line with human usage habits and characteristics.

[0059] (2) Data collection and integration

[0060] a. Utilize the high-precision positioning capabilities of the Beidou satellite navigation system to collect real-time environmental data from various areas of the city, such as air quality, traffic flow, noise level, etc.

[0061] b. Spatial encoding of the collected data is performed through Beidou grid codes, the urban area is divided into multiple grid units, and the data is mapped to the corresponding grid units to achieve unified organization and integration of data.

[0062] (3) Data analysis and decision support

[0063] a. Conduct statistical analysis on the coded urban environmental data to determine the data patterns and trends of the data characteristics and provide a scientific basis for urban management.

[0064] b. Combine big data analysis technology to explore the correlation and regularity between data and provide decision support for city managers.

[0065] (4) High-precision positioning and navigation technology

[0066] Beidou grid code is one of the important applications of Beidou system. Its encoding and parsing rely on the precise location information provided by Beidou satellite navigation technology. With the continuous improvement and upgrading of Beidou satellite navigation system, its high-precision positioning and navigation capabilities will be further enhanced.

[0067] (5) Cross-domain integration

[0068] The urban management event system based on Beidou grid code is combined with Internet of Things technology to realize intelligent monitoring and management of urban infrastructure; combined with blockchain technology, it can realize data traceability and security assurance.

[0069] Figure 1 FIG. 1 is a schematic diagram of a system 100 for processing city management events based on Beidou grid code according to some embodiments of the present application. Figure 1 As shown, the processing system 100 includes: a data connection encoding module 110, an event reporting processing module 120, an event pre-processing module 130, a data mapping module 140 and a grid data analysis module 150.

[0070] In order to introduce Beidou grid code in case reporting and achieve the purpose of unit grid query, we need two steps: (1) convert the unit grid layer into Beidou grid code storage; (2) realize point-to-surface relationship judgment based on Beidou grid code and obtain the unit grid code where the case is located.

[0071] The data connection and encoding module 110 grids data from different sources and in different formats to form grid data.

[0072] According to the implementation mode of the present application, the data connection encoding module 110 can be connected to various data sources such as various data servers, IoT sensing devices (such as cameras, sensors, etc.) to obtain various geospatial data within the urban space, such as census data, GIS (Geo-Information system, Geographic Information System) data, BIM (Building Information Modeling, Building Information Modeling) data, remote sensing data, weather data, social media data, video data, IoT (Internet of Things) data, etc. In this embodiment, geospatial data refers to data with geographic coordinates, including all data with geographic coordinates in the fields of resources, environment, economy and society, which is a digital description of the spatial characteristics and attribute characteristics of geographic entities. Geospatial data usually includes location information (usually coordinates on the earth), attribute information (characteristics of objects, events or phenomena), and time information (time or span of location and attribute existence). After obtaining geospatial data from multiple data sources, the data connection encoding module 110 performs grid encoding on each geospatial data within the urban space based on the Beidou grid code to generate a basic grid model. Specifically, the urban space is gridded based on the Beidou grid code, and the urban space is divided into multiple spatial grids, each of which corresponds to a certain spatial range, recorded as {longitude interval, latitude interval, altitude interval}. The division accuracy and interval size can be set according to actual application requirements, and this embodiment does not limit this. Afterwards, based on the location information of the geographic spatial data, the spatial grid to which it belongs is determined, and the time information and attribute information are mapped to the determined spatial grid. In this way, the geographic spatial data within the urban space range is converted into spatiotemporal data associated with each spatial grid, and the spatiotemporal data corresponding to each spatial grid is used as a block data, which is associated with the Beidou grid code of the spatial grid to form a block data set with spatiotemporal attributes, that is, a basic grid model.

[0073] In some embodiments, the data connection coding module 110 uses a variety of data connection coding tools to grid data from different sources and in different formats to form grid data. The data connection coding module 110 assigns grid codes to the grids covered by various data organization and management contents, and quickly implements spatial position coding for different information. This includes point coordinate plane coding, line plane coding, polygon plane coding, point three-dimensional coding, line three-dimensional coding, polygon three-dimensional coding and other methods.

[0074] According to some embodiments of the present application, the data access coding module 110 will obtain geospatial data from various data sources in real time or at a fixed time, grid it, and map it to the corresponding spatial grid. In other words, each time the new data is obtained, the basic grid model will be updated to obtain a new basic grid model. Since the geospatial data has time information, the basic grid model can record various historical data and new data based on the time information. It should be noted that the basic grid model described in the present application refers to the basic grid model at the current moment, that is, the latest basic grid model. When there is a city management event reported, the event reporting processing module 120 obtains the reported event data, wherein the event data includes at least one of text data, video data, and voice data. When the reported data is video data, the principle of earth space segmentation is used to map the video content of key parts of the city into the grid data model to realize video data association aggregation, penetration query, on-demand extraction, and spatiotemporal calculation analysis.

[0075] According to this embodiment, urban management events can be reported in real time by staff or by the public. Usually, the reported urban management events will include the geographical location where the event occurred. The reporting personnel can add the geographical location corresponding to the event, or the reported point can be used as the geographical location corresponding to the event. For example, based on the Beidou grid code, a more fine-grained Beidou grid set can be bound in advance according to the outer contour of the building. When collecting household Beidou grid codes, the collector uses the mobile phone positioning longitude and latitude mark as a fixed reference point at the entrance of the first floor of the building, enters the specific room (household) and marks the Beidou grid code corresponding to each household according to the orientation and visual distance, that is, the layered household binding to the Beidou grid code is realized. In the inspection and reporting stage, the floor and household are directly selected for the location where the specific event occurred, and a more accurate Beidou grid code can be obtained. In the disposal stage, the floor and household can be accurately located according to the Beidou grid code plus the floor code, that is, indoor positioning, to realize the corresponding disposal transfer process.

[0076] According to the implementation mode of the present application, the reported event data will be preprocessed first. On the one hand, the event preprocessing module 130 processes the event data to determine the event type, geographical location and attributes of the urban management event. In some embodiments, the event types include: urban environment, publicity and advertising, construction management, street order, emergencies and other event types. As described above. Attributes include other information related to the urban management event, such as motion trajectory, feature status, land feature, component facilities, environmental information, etc.

[0077] On the other hand, the event preprocessing module 130 determines whether it is a repeated event through preprocessing. If it is a repeated event, no batch forwarding processing is performed, thereby reducing the situation of repeated reporting and reducing management costs.

[0078] Specifically, the Beidou grid code associated with the city management event is determined using the geographic location; then, the Beidou grid code is used to determine whether there are similar events to the city management event from the basic grid model, and if there are similar events, whether it is a repeated event is determined. In some embodiments of the present application, events that belong to the same event type, the same time period (such as the same day), and are very close are considered to be similar cases. If the attributes of similar events are mostly consistent, they are considered to be repeated events; conversely, if most of the attributes are inconsistent, they are considered not to be repeated events.

[0079] If the current city management event is not a repeated event, the data mapping module 140 maps the event type and attributes of the city management event to the spatial grid pointed to by the Beidou grid code to update the basic grid model.

[0080] The grid data analysis module 150 encapsulates each block of data in the basic grid model to provide it to the subsequent batch processing flow.

[0081] In some embodiments, the grid data analysis module 150 compresses the encapsulated block data and provides it to the back-end business system through a URL link for subsequent batch processing. Specifically, the grid data analysis module 150 can send it to the corresponding local department (such as community, street, district) for processing according to the area corresponding to the spatial grid. At the same time, it can also be sent to the corresponding business system according to the type of event. For example, for urban environment events, it can be handed over to the corresponding sanitation department for processing; for street order events, it can be handed over to the corresponding traffic management department for processing.

[0082] The grid data analysis module 150 can also analyze and process each piece of data to provide data support for monitoring and risk planning of urban management events.

[0083] The grid data analysis module 150 provides various types of grid data analysis and computing services, including core functions such as basic operations, spatial object grid mapping, spatial relationship calculation - grid & grid, spatial relationship calculation - grid set & grid set, spatial analysis, etc. Code conversion, grid code conversion between binary, quaternary, and decimal.

[0084] In some embodiments, the grid data analysis module 150 performs statistical analysis of rebound-prone points through Beidou grid codes, statistically analyzes the distribution of rebound-prone points (multiple reports of the same type of cases) and case types in the jurisdiction, effectively analyzes which areas frequently occur which types of problems, focuses on the key and difficult-to-solve problems in daily urban management, and effectively handles and optimizes management methods.

[0085] In some embodiments, the grid data analysis module 150 performs statistical analysis of similar cases through the Beidou grid code. In business, cases of the same subcategory, the same time period (such as the same day), and close distance are considered similar cases, and corresponding optimization processing can be performed in the transfer process.

[0086] In other embodiments, the grid data analysis module 150 uses the basic grid model to perform statistical analysis on urban management events, such as statistically analyzing the distribution of various types of urban management events, statistically analyzing the time distribution and regional distribution of urban management events, etc., to reflect the weak links and urgent problems in urban management.

[0087] In addition, the processing system 100 adopts sub-table storage. When a layer is converted into a Beidou grid code, the amount of data will be much larger than the original data. The use of a sub-table storage solution can improve query efficiency.

[0088] According to the processing system 100 of the present application, its core is to use space-time grid technology to re-code all buildings, equipment, materials, personnel, environment, places, events, etc. within the city, and connect to ubiquitous perception data such as Beidou system, satellite remote sensing, and Internet of Things sensor equipment to generate a basic grid model indexed by Beidou grid code.

[0089] Based on this basic grid model, when a city management event is reported, the event data is first processed to determine information such as the event type, geographic location, and attributes; then, the Beidou grid code is determined based on the geographic location, and based on the Beidou grid code, it is further analyzed whether the city management event is a repeated reporting event. If it is not a repeated event, the event type and attributes are mapped to the spatial grid pointed to by the Beidou grid code, and the basic grid model is updated.

[0090] For the basic grid model, the block data can be regularly encapsulated and provided to the subsequent batch processing flow. It can also be analyzed and calculated to determine the management status of each jurisdiction area in the city, thereby providing data support for urban management planning.

[0091] The processing system 100 according to the present application may be implemented by one or more computing devices. Figure 2 FIG. 2 shows a schematic diagram of a computing device 200 according to some embodiments of the present application. It should be noted that: Figure 2 The computing device 200 shown is only an example. In practice, the computing device used to implement the method of the present application can be any type of device, and its hardware configuration can be different from the above. Figure 2 The computing device 200 shown is the same as Figure 2 The computing device 200 shown is different. In practice, the computing device used to implement the embodiment of the present application can be Figure 2The hardware components of the computing device 200 shown are increased or deleted, and the present application does not limit the specific hardware configuration of the computing device.

[0092] like Figure 2 In a basic configuration, computing device 200 includes at least one processing unit 202 and system memory 204. According to one aspect, depending on the configuration and type of computing device, processing unit 202 can be implemented as a processor. System memory 204 includes, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories. According to one aspect, system memory 204 includes operating system 205 and program modules 206.

[0093] According to one aspect, operating system 205 is suitable for controlling the operation of computing device 200, for example. Furthermore, examples are practiced in conjunction with graphics libraries, other operating systems, or any other application programs, and are not limited to any particular application or system. Figure 2 This basic configuration is illustrated in FIG. 2 by those components within dashed line 208. According to one aspect, computing device 200 has additional features or functionality. For example, according to one aspect, computing device 200 includes additional data storage devices (removable and / or non-removable), such as magnetic disks, optical disks, or tapes. Such additional storage Figure 2 2 is illustrated by removable storage 209 and non-removable storage 210.

[0094] As stated above, according to one aspect, program modules are stored in the system memory 204. According to one aspect, the program modules may include one or more application programs, and the present application does not limit the types of application programs, for example, the application programs may include: email and contact applications, word processing applications, spreadsheet applications, database applications, slide show applications, drawing or computer-aided applications, web browser applications, etc.

[0095] According to one aspect, the examples may be practiced on a circuit comprising discrete electronic components, a packaged or integrated electronic chip containing logic gates, a circuit utilizing a microprocessor, or a single chip containing electronic components or a microprocessor. Figure 2Each or many components shown in can be integrated in a system on chip (SOC) on a single integrated circuit to practice examples. According to one aspect, such a SOC device may include one or more processing units, a graphics unit, a communication unit, a system virtualization unit, and various application functions, all of which are integrated (or "burned") into a chip substrate as a single integrated circuit. When operated via SOC, the functions described in the present application can be operated via a dedicated logic integrated with other components of a computing device 200 on a single integrated circuit (chip). Other technologies that can perform logical operations (such as AND, OR, and NOT) can also be used to practice embodiments of the present application, including but not limited to mechanical, optical, fluid, and quantum technologies. In addition, embodiments of the present application can be practiced in a general-purpose computer or in any other circuit or system.

[0096] According to one aspect, the computing device 200 may also have one or more input devices 212, such as a keyboard, a mouse, a pen, a voice input device, a touch input device, a VR motion capture input device, etc. Output devices 214 may also be included, such as a display, a speaker, a printer, etc. The aforementioned devices are examples and other devices may also be used. The computing device 200 may include one or more communication connections 216 that allow communication with other computing devices 218. Examples of suitable communication connections 216 include, but are not limited to: RF transmitters, receivers and / or transceiver circuits; Universal Serial Bus (USB), parallel and / or serial ports.

[0097] The term computer-readable media as used in this application includes computer storage media. Computer storage media may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (e.g., computer-readable instructions, data structures, or program modules). System memory 204, removable storage 209, and non-removable storage 210 are all examples of computer storage media (i.e., memory storage). Computer storage media may include random access memory (RAM), read-only memory (ROM), electrically erasable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical storage, cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other products that can be used to store information and can be accessed by computing device 200. According to one aspect, any such computer storage media may be part of computing device 200. Computer storage media do not include carrier waves or other propagated data signals.

[0098] According to one aspect, communication media is implemented by computer readable instructions, data structures, program modules, or other data in a modulated data signal (e.g., a carrier wave or other transport mechanism), and includes any information delivery media. According to one aspect, the term "modulated data signal" describes a signal that has one or more characteristics set or changed in a manner that encodes information in the signal. By way of example and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.

[0099] In an embodiment according to the present application, the computing device 200 is configured to execute the method 300 for processing city management events based on Beidou grid code according to the present application. The program module 206 includes a plurality of program instructions for executing the method 300 for processing city management events based on Beidou grid code, and these program instructions can instruct the processing unit 202 to execute the method 300 of the present application.

[0100] Figure 3 A flowchart of a method 300 for processing urban management events based on Beidou grid codes according to some embodiments of the present application is shown.

[0101] It should be noted that the method 300 can be executed by the aforementioned processing system 100. Therefore, the contents of the method 300 and the aforementioned processing system 100 complement each other, and the relevant parts will not be repeated here.

[0102] The overall design of the urban management event processing method based on Beidou grid code mainly includes the following parts:

[0103] (1) Front-end application layer: The front-end application layer is the interface for the system to interact with users. It is mainly responsible for receiving urban management event information input by users and displaying the processing results. This layer includes mobile applications (such as mobile APP) and web applications. Users can use these applications to report events, query, and perform statistics. Functional design includes the following aspects.

[0104] Event reporting: Users can report city management events by taking photos, providing text descriptions, etc.

[0105] Event query: Users can query reported events based on event type, time, location, and other conditions.

[0106] Statistical analysis: The system provides various statistical reports and charts to help users understand the distribution and trends of urban management events.

[0107] (2) Backend service layer: The backend service layer is the core processing part of the system, responsible for receiving event information from the front-end application layer, and performing event processing, distribution, tracking and feedback. This layer includes event processing module, distribution module, tracking module and feedback module. Functional design includes the following aspects. Event processing: preliminary screening, classification and marking of received urban management events.

[0108] Event distribution: Distribute events to corresponding departments or personnel based on event type and urgency.

[0109] Event tracking: Track the progress and results of event processing in real time to ensure that the event is properly handled.

[0110] Feedback mechanism: Provide users with feedback on event processing results to improve user satisfaction.

[0111] (3) Data management layer: The data management layer is responsible for storing and managing relevant data of urban management events, including event information, grid code information, processing results, etc. This layer uses efficient database technology to ensure the integrity, security and accessibility of data. The functional design includes the following aspects.

[0112] Data storage: Use relational database or non-relational database to store urban management event data.

[0113] Data backup and recovery: Back up data regularly to ensure data security; when data is lost or damaged, it can be restored quickly.

[0114] Data access control: Set up permission controls to ensure that only authorized users can access sensitive data.

[0115] (4) Beidou Grid Code Service Layer: The Beidou Grid Code Service Layer is responsible for providing Beidou Grid Code division, encoding, parsing and location services. This layer interacts with the front-end application layer and the back-end service layer to achieve accurate positioning and rapid processing of urban management events. The functional design includes the following aspects.

[0116] Grid division and coding: According to urban management requirements, the urban area is divided into several grids and each grid is assigned a unique code.

[0117] Grid code analysis: The grid code in the received urban management event information is analyzed into specific geographic location information.

[0118] Location service: Provides location query, positioning navigation and other services based on Beidou grid code.

[0119] (5) Network communication layer: The network communication layer is responsible for data transmission and communication between the front-end application layer, back-end service layer, data management layer, and Beidou grid code service layer. This layer uses efficient, secure, and reliable communication protocols and technologies to ensure the real-time and security of data transmission. The functional design includes the following aspects.

[0120] Data transmission: HTTP, HTTPS, WebSocket and other protocols are used for data transmission.

[0121] Data encryption and security: Use encryption technologies such as SSL / TLS to protect the security of data transmission.

[0122] Load balancing and fault tolerance: Improve the system's concurrent processing capabilities through load balancing technology; ensure that the system can still operate normally under high load or fault conditions through fault tolerance mechanism.

[0123] like Figure 3 As shown, the method 300 starts at step S310. In S310, the data connection encoding module 110 performs grid encoding on each geographic space data within the urban space based on the Beidou grid code to generate a basic grid model. According to this embodiment, the basic grid model includes multiple block data, and each block data is indexed by the Beidou grid code.

[0124] In some embodiments, the base mesh model is generated as follows.

[0125] The first step is to obtain geospatial data from multiple data sources, where the geospatial data includes location information, time information, and attribute information. Attribute information includes, for example, device ID, device status, weather conditions, event content description, video content, etc., which is information describing the relevant characteristics of the geospatial data.

[0126] In the second step, for each piece of geographic spatial data, the spatial grid to which the corresponding geographic spatial data belongs is determined according to the location information of the geographic spatial data, where the spatial grid is obtained by gridding the urban space based on the Beidou grid code, and each spatial grid has a unique Beidou grid code.

[0127] The third step is to map the time information and attribute information of each geographic spatial data to the determined spatial grid to generate a basic grid model.

[0128] Optionally, the spatial position and time of each department's historical data and newly added data (components, events) can be coded. For data with clear spatial information, their spatial information can be directly converted into grid codes. For data without clear spatial information, multi-level information associations can be established to achieve unified coding and mutual association of various spatial data.

[0129] Figure 4A schematic diagram of a basic grid model according to some embodiments of the present application is shown, where the urban space range is divided into multiple three-dimensional spatial grids. When the geographic spatial data within the urban space range (including data related to urban management events) is mapped to each spatial grid, each spatial grid corresponds to a block of data, thus forming a basic grid model. Figure 4 In each spatial grid, data such as time information, event type, device ID, event content description, etc. are stored, and these data are associated with the Beidou grid code. In other words, the Beidou grid code is used as the index of the block of data. The basic grid model manages the encoded data through grids and grid codes to achieve functions such as data indexing and data index updating. It provides services for grid-based fast query and retrieval of multi-source heterogeneous big data, and supports business applications such as grid-based computing and analysis.

[0130] In S320, when a city management event is reported, the event reporting processing module 120 obtains the reported event data. The event data includes at least one of text data, video data, and voice data.

[0131] Urban management events can be reported by staff, the public, or sensors deployed in the urban environment. For example, when a monitoring device deployed on a street identifies a traffic accident, it proactively reports the current video data for a period of time to the system 100. For another example, when a fire alarm device deployed in a scenic area, factory area, office building, etc. detects a smoke alarm, it proactively reports the current data to the system 100.

[0132] In one embodiment, grid workers or other relevant personnel in urban management discover urban management events and report event information through mobile devices or dedicated terminals. At the same time, on-site positioning is performed. The Beidou grid code is used to accurately locate the specific location where the event occurred. The Beidou grid code can provide a globally unified, unique and high-precision location identifier to ensure the accuracy of the event location. After that, relevant event information is reported.

[0133] According to an implementation of the present application, the event reporting processing module 120 can be coupled to various mobile devices (such as mobile phones), computing devices, and Internet of Things devices (such as monitoring equipment, environmental sensors, etc.) to obtain event data of urban management events.

[0134] It should be understood that when a city management event occurs, multiple devices may report the event data of the event separately, and the reporting time may be inconsistent. In addition, the description of the same city management event can be text, voice, video or image. Therefore, in the subsequent processing, the reported city management events need to be pre-processed, and then transferred to the subsequent business process for processing after screening.

[0135] In S330, the event data is processed to determine the event type, geographical location and attributes of the urban management event.

[0136] First, different methods are used to process different types of event data, as described below.

[0137] If the event data contains text data, where the text data may be multiple words, a sentence, one or more paragraphs of text, etc., then the relevant information of the event is identified from the text data through algorithms such as keyword extraction and semantic analysis. Keywords may include time information, location information, etc. This embodiment does not limit the specific algorithm used to identify the relevant information of the event from the text data.

[0138] If the event data includes voice data, the voice data is first converted into text data through speech-to-text technology (TTS), and then the converted text data is processed (as described in the previous step) to identify relevant information of the event.

[0139] If the event data contains video data (including image data), the feature data of the video data is first extracted, wherein the feature data includes at least one of equipment, personnel, materials, and regional edges. For example, one or more targets in the video data are identified through algorithms such as target detection (targets such as personnel, equipment, materials, etc.); edge information in the video data is determined through algorithms such as edge detection, and then the outline of buildings and mountains in the video data is obtained. Afterwards, relevant information of the event is generated based on the above feature data.

[0140] According to the implementation mode of the present application, any information extracted from the event data can be used as relevant information about the event, including but not limited to: the upload object ID or terminal device ID, the location and time of the event, status information, processing status, event type, nature of the event, etc.

[0141] Secondly, the event type, geographical location and attributes of the urban management event are determined in combination with the relevant information. The event type can be described in the foregoing description and can be set in advance by the system 100.

[0142] In some embodiments, the event type can be determined by the staff manually selecting when reporting the urban management event, or can be determined based on relevant information. For example, if the relevant information includes construction, urban construction and other information, the event type is confirmed to be construction management; if the relevant information includes traffic and other information, the event type is confirmed to be street order.

[0143] In some embodiments, regarding the determination of the geographical location, the reported event data usually includes the geographical location and time information. If not, the reported geographical location and time are used as the geographical location and time information of the event.

[0144] In S340, the Beidou grid code associated with the urban management event is determined using the geographical location.

[0145] In some embodiments, the spatial grid to which the geographical location belongs is determined, and the Beidou grid code of the spatial grid is the Beidou grid code associated with the urban management event. The geographical location can be a specific coordinate or a street or place name, which can be converted into longitude, latitude and altitude coordinates to match the corresponding spatial grid (or Beidou grid code). Figure 5 FIG. 4 shows a schematic diagram of a video grid engine according to some embodiments of the present application. Figure 5 , process the data obtained from maps (including terrain, roads, water systems, houses, etc.), images, CAD drawings (including various equipment, place information), as well as video acquisition equipment, sensors and other sensing devices, and generate the global space-time grid foundation, that is, the basic grid model, based on the Beidou grid. For the above-mentioned reported data that is video data, the video space grid is determined based on the Beidou grid using the principle of earth space segmentation. At the same time, by identifying the video content, the content attributes it contains are determined, such as operations, work areas, personnel, facilities, materials, etc. By mapping the video content of key parts of the city to the grid data model (i.e. Figure 5 In the global spatiotemporal grid foundation shown in , the identified content attributes are associated with the grid to achieve video data association aggregation, penetration query, on-demand extraction and spatiotemporal calculation analysis. The main functions include video grid space recovery, video grid splicing, video grid associated data function, grid information display, query, and video grid data analysis.

[0146] In S350, the Beidou grid code is used to determine whether there are similar events in the urban management event from the basic grid model.

[0147] As mentioned above, according to the implementation mode of the present application, urban management events of the same event type, the same time period (such as the same day), and a close distance are considered to be similar cases and can be optimized accordingly in the transfer process.

[0148] In some embodiments, similar events are determined as follows.

[0149] First, data associated with the Beidou grid code is obtained from the basic grid model. In other words, block data associated with the Beidou grid code is obtained.

[0150] Afterwards, it is determined whether there is an urban management event in the acquired data that is consistent with the event type of the urban management event and belongs to the same time period. In other words, urban management events of "the same event type" and "time information belonging to a predetermined time period" are further extracted from the block data. In this embodiment, the predetermined time period is determined based on the time information of the current urban management event, and can be accurate to days, hours, and minutes.

[0151] If there is an urban management event that is consistent with the event type of the urban management event and belongs to the same time period, then this event is confirmed to be a similar event to the urban management event, that is, a similar event exists.

[0152] If there are similar events, then in S360, it is further determined whether the similar events are repeated events. For example, on the same street, multiple urban management events of road occupation or disorderly parking of motor vehicles (street order type) may occur on the same day. They are similar events, but not necessarily repeated events. Therefore, according to this application, it is necessary to judge according to the preset logic: whether similar events are repeated events. If they are repeated events, they will not be forwarded (because the urban management events stored in the block data have been forwarded), thereby reducing the situation of repeated reporting and reducing management costs.

[0153] In this embodiment, the attributes of the similar event are compared with the attributes of the city management event to see if they are consistent. If the current city management event contains multiple similar events, they are compared separately. Optionally, the attributes of the event contain multiple information, and when more than half of the information is consistent, it is confirmed that the attributes of the similar event are consistent with the attributes of the current city management event. If the attributes are consistent, it is confirmed as duplicate information and no subsequent processing is performed.

[0154] If they are inconsistent, confirm that it is not a duplicate event and proceed to the next steps.

[0155] According to the implementation of the present application, S330 - S360 are all executed by the event preprocessing module 130 , and the relevant parts are not repeated here.

[0156] If it is not a repeated event, then in S370, the data mapping module 140 maps the event type and attributes of the city management event to the spatial grid pointed to by the Beidou grid code (determined via S340) to form new block data, that is, update the basic grid model.

[0157] According to the embodiment of the present application, each spatial grid may contain more than one city management event, and each city management event is taken as a piece of data to record the event ID, event type, time information, other attributes, etc. Table 1 exemplarily shows the data contained in a block of data.

[0158] Table 1 Block data (example)

[0159]

[0160] In S380 , the grid data analysis module 150 may periodically encapsulate each block of data in the basic grid model to provide it to a subsequent batch processing flow.

[0161] According to the present application, standard encoding, reconstruction and collection of various types of data in the same space-time range are realized through block data. In this way, the basic network model is a new data management framework that takes space as a management object and various types of data falling into the space as attributes. In some embodiments, in addition to encapsulating various data in the same space grid to form standard block data, the encapsulated block data will also be compressed and provided to other business systems through URL links.

[0162] Specifically, according to the area corresponding to the Beidou grid code, the associated block data is sent to the corresponding local department for processing. For example, if the area pointed to by the Beidou grid code is urban area A, the block data corresponding to the Beidou grid code is sent to the department of urban area A for processing. The local department can be a community, street, district, etc., which is not limited in this embodiment.

[0163] Furthermore, when encapsulating block data, the data of each urban management event involved can also be analyzed, such as sending each piece of data to the corresponding business system according to the event type. Continuing with the above example, the event type in the block data is further analyzed. If the event type is urban appearance and environment, the data is sent to the sanitation department of urban area A for processing.

[0164] In addition, basic urban management data such as administrative grids, business-specific grids, industry management grids, underground pipeline data and other vector data, or the geographic location of reported urban management events, are often confidential data. These data are prone to security risks when they are queried and transmitted, especially when transmitted over the public network. Traditional declassification and desensitization algorithms mainly remove sensitive objects, coordinates and offsets, etc. After the introduction of the Beidou grid code, the Beidou grid code is used to replace the specific location information, that is, the coordinate points of these data objects are converted to the Beidou grid code of corresponding accuracy, the accuracy of the coordinate points is reduced, and the two-dimensional information is reduced in dimension, thereby realizing the declassification of the geometric information of the vector data, improving the security of the data, and reducing security risks.

[0165] In some other embodiments, the method 300 further includes: based on the basic grid model, analyzing and calculating the block data, including basic operations, spatial object grid mapping, spatial relationship calculation, etc. Specifically, the Beidou grid codes of the multiple spatial grids included in the jurisdiction are determined; then, these Beidou grid codes are used to perform statistical analysis on events in the jurisdiction to determine the management status of the jurisdiction.

[0166] Among them, the city contains multiple jurisdictions, and each jurisdiction contains multiple districts. The statistical analysis of events within the jurisdiction includes:

[0167] (1) Determine one or more Beidou grid codes corresponding to the scope of each area; based on the determined Beidou grid codes, count the number of urban management events of each event category in each area to determine the types and frequencies of high-incidence events in each area, and analyze the distribution of easy-to-rebound points (multiple reports of the same type of urban management cases) and event types in each area or jurisdiction, and then analyze what types of problems frequently occur in those areas;

[0168] (2) Count the time information corresponding to urban management events of the same event category within the jurisdiction to determine the time distribution of each event type, and then analyze which time periods need to focus on which types of issues;

[0169] (3) Count the frequency of various urban management events occurring in the city during different time periods, thereby providing data support for urban management planning.

[0170] Figure 6 The functional architecture diagram of the grid base system according to some embodiments of the present application is shown. Based on the architecture, the method 300 of the present application can be executed. In some embodiments, the system architecture is used as a supplementary description of the aforementioned system 100.

[0171] like Figure 6 As shown in the figure, the system architecture is based on the Beidou grid coding standard system, including: data layer, coding layer, index layer, engine layer, support layer, and service layer. It is mainly used for data security and operation and maintenance system.

[0172] The data layer can come from multiple data sources, including but not limited to spatiotemporal information cloud platform, building data, Internet of Things data, human-house law data, video data, urban component / event data, field data, socio-economic data and other data.

[0173] The data obtained by the data layer is handed over to the encoding layer and encoded by the grid data encoding tool. When encoding, historical data and new data can be distinguished. After each new data is added, only the new part is encoded. The specific method can be referred to the previous content, which will not be repeated here.

[0174] The index layer mainly includes data mapping and synchronization mechanisms. By introducing a grid partition index table, parallel data indexing is performed based on the new GeoSOT earth partition and coding theory when facing the needs of rapid extraction and calculation of massive data. This subsystem uses the earth partition grid code (and time partition code) as the primary key of the index table. On the premise of not demolishing or rebuilding the existing system, the partition index data corresponding to each level of partition facets are associated to form a partition index table that is logically based on the earth's spatial position, realizing the unified organization and parallel calculation of big data across databases and information systems.

[0175] The grid-division index table is equivalent to establishing a container for the entire earth space, and all spatial objects will be registered in the container. The primary key of the grid-division index table uses position coding, which has the clustering of space + scale. It can use the interval inclusion method to perform large-scale queries, which is very suitable for data indexing of very large data scales; after coding segmentation, it can represent the earth space location range of different scales, different regions, and different sizes. Any region is seamless and independent of each other. The grid-division index table is suitable for large-scale distributed deployment and services.

[0176] The engine layer provides an intermediate support system for grid computing engine services for upper-layer application systems through the Beidou grid data engine, which mainly includes basic operations, encoding conversion, spatial operations, spatial measurement, topological operations and other major functions.

[0177] Optionally, the grid computing algebra library adopts a 2n one-dimensional integer coding design to reduce complex three-dimensional spatial operations to one dimension, avoiding traditional longitude and latitude floating-point operations, and is very suitable for complex calculations of massive spatial data; a set of coded algebraic calculation methods based on binary bit operation mechanisms (AND, OR, NOT, left shift, right shift, mask, etc.) are designed to replace traditional (longitude and latitude, time) floating-point addition / subtraction / multiplication / division / exponential / logarithmic / trigonometric functions and other complex calculations with binary bit operations, and the computing efficiency is improved by several to dozens of times compared with the traditional longitude and latitude point coordinate system.

[0178] The supporting layer includes the grid data model and the grid data registration and parsing subsystem.

[0179] For two-dimensional grids and three-dimensional grids, the grid data model can be divided into plane grid data graphs and three-dimensional grid data graphs. Through the data three-dimensional visual subsystem, the grid data model is used for global spatial, real-time and dynamic visualization of multi-source heterogeneous data. The grid code in the grid data model represents the location of the grid, and the attributes of the grid are used to associate multi-source external data. When the external data changes, the grid attributes are automatically associated with the changed data through the grid code, realizing real-time data update and dynamic aggregation. The global three-dimensional grid data model annotates the multi-source heterogeneous data in an all-round way in terms of "positioning, qualitative and quantitative", realizing a single picture display.

[0180] Optionally, grid data identification registration and resolution services are provided for urban components, urban events, spatial addresses, industrial Internet and mass users, and data identification and registration, grid sign tag registration, beacon perception and resolution, data domain name resolution and other functions are realized through the grid data registration and resolution subsystem. Among them, the grid data registration and resolution subsystem uses the Beidou grid and coding identification method to replace the traditional object ID method, and fully identifies and manages everything in space, including people, things, objects, organizations, etc., which is the information foundation for ubiquitous access, ubiquitous perception, ubiquitous identification, and ubiquitous computing of digital twin cities.

[0181] Optionally, the service layer introduces a data service subsystem, which mainly includes data duty, query retrieval, extraction and distribution, and spatiotemporal analysis. The specific description of each functional module is as follows:

[0182] Data duty module: real-time display of the distribution of indexed data, data import and update status, data query and distribution, and other utilization conditions;

[0183] Query and retrieval module: realize one-click penetration query, support multiple query methods such as grid, polygon, and division boundary, and provide attribute query of different phase states in the same space;

[0184] Extraction and distribution module: discretizes data by grid, extracts required data by grid or grid combination, distributes data extraction results, and provides data interface to realize data sharing;

[0185] Space-time analysis module: performs statistical analysis such as spatial overlay calculation, spatial cluster analysis, space-time comprehensive analysis, and real-time operations such as dynamic trajectory calculation according to grids or grid combinations.

[0186] The service layer also includes interface services and tools, providing grid layers, interface calls, and secondary development toolkits.

[0187] In summary, according to the method for processing urban management events based on Beidou grid codes in this application, its core is to use space-time grid technology to re-code all buildings, equipment, materials, personnel, environment, places, events, etc. within the city, and connect to ubiquitous perception data such as Beidou system, satellite remote sensing, and Internet of Things sensor equipment to generate a basic grid model indexed by Beidou grid codes.

[0188] Based on this basic grid model, when a city management event is reported, the event data is first processed to determine information such as the event type, geographic location, and attributes; then, the Beidou grid code is determined based on the geographic location, and based on the Beidou grid code, it is further analyzed whether the city management event is a repeated reporting event. If it is not a repeated event, the event type and attributes are mapped to the spatial grid pointed to by the Beidou grid code, and the basic grid model is updated.

[0189] For the basic grid model, the block data can be regularly encapsulated and provided to the subsequent batch processing flow. It can also be analyzed and calculated to determine the management status of each jurisdiction area in the city, thereby providing data support for urban management planning.

[0190] For example, statistical analysis of rebound points can be conducted. When an event is reported, the Beidou grid code of the corresponding accuracy of the event is obtained in real time, or the Beidou grid code of the corresponding accuracy is associated with the closed event. The Beidou grid code can be used to statistically analyze the distribution of rebound points (multiple reports of the same type of event) and event types in the jurisdiction, and effectively analyze which areas frequently have which types of problems, which is conducive to focusing on the key and difficult-to-solve problems in daily urban management, and effectively handling and optimizing management methods.

[0191] Another example is the statistical analysis of similar events. In business, events of the same subcategory, the same time period (such as the same day), and close distance are considered similar cases, and corresponding optimization processing can be performed in the forwarding process. When a user reports a case, the coordinates are matched with the Beidou grid code of the corresponding accuracy, and the grid code is used to match the reported events that have been associated with the grid code. If a similar event can be matched, it is automatically determined whether it is a repeated event based on the preset logic. If it is a duplicate, it will not be forwarded, thereby reducing the situation of duplicate reporting and reducing management costs.

[0192] Optionally, in the method of the present application, the encapsulation of each block data in the basic grid model to provide it to a subsequent batch processing flow includes: sending the associated block data to the corresponding territorial department for processing according to the area corresponding to the Beidou grid code.

[0193] Optionally, a computing device is also included, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method described above.

[0194] Optionally, a computer-readable storage medium storing one or more programs is also included, wherein the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device executes the method as described above.

[0195] Optionally, a computer program product is also included, including a computer program / instruction, wherein the computer program / instruction implements the method described above when executed by a processor.

[0196] The various techniques described herein may be implemented in combination with hardware or software, or a combination thereof. Thus, the method and apparatus of the present application, or certain aspects or portions of the method and apparatus of the present application may be in the form of program codes (i.e., instructions) embedded in a tangible medium, such as a removable hard disk, a USB flash drive, a floppy disk, a CD-ROM, or any other machine-readable storage medium, wherein when the program is loaded into a machine such as a computer and executed by the machine, the machine becomes a device for practicing the present application.

[0197] In the case where the program code is executed on a programmable computer, the computing device generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. The memory is configured to store the program code; the processor is configured to execute the method of the present application according to the instructions in the program code stored in the memory.

[0198] By way of example and not limitation, readable media include readable storage media and communication media. Readable storage media stores information such as computer readable instructions, data structures, program modules or other data. Communication media generally embody computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and include any information transfer medium. Any combination of the above is also included within the scope of readable media.

[0199] In the description provided herein, algorithms and displays are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the examples of the present application. According to the above description, it is obvious to construct the structure required for such systems. In addition, the present application is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described herein, and the above description of specific languages ​​is to disclose the preferred implementation of the present application.

[0200] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0201] Those skilled in the art will appreciate that the modules or units or components of the devices in the examples disclosed herein may be arranged in the devices described in the embodiment, or alternatively may be located in one or more devices different from the devices in the examples. The modules in the foregoing examples may be combined into one module or may be divided into multiple submodules.

[0202] Those skilled in the art will appreciate that the modules in the devices in the embodiments can be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and in addition they can be divided into multiple submodules or subunits or subassemblies. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification and all processes or units of any method or device disclosed in this manner can be combined in any combination. Unless otherwise clearly stated, each feature disclosed in this specification can be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0203] Furthermore, those skilled in the art will appreciate that although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features from different embodiments is meant to be within the scope of the present application and to form different embodiments.

[0204] In addition, some of the embodiments are described herein as methods or combinations of method elements that can be implemented by a processor of a computer system or by other devices that perform the functions. Therefore, a processor with necessary instructions for implementing the method or method elements forms a device for implementing the method or method elements. In addition, the elements described herein of the device embodiments are examples of devices that are used to implement the functions performed by the elements for the purpose of implementing the disclosure.

[0205] As used herein, unless otherwise specified, the use of ordinal numbers "first," "second," "third," etc. to describe common objects merely refers to different instances of similar objects and is not intended to imply that the objects so described must have a given order in time, space, order, or in any other manner. In addition, the quantifier "plurality" means "two" and / or "more than two."

[0206] Although the present application is described according to a limited number of embodiments, it will be appreciated by those skilled in the art, with the benefit of the above description, that other embodiments may be envisioned within the scope of the present application thus described. In addition, it should be noted that the language used in this specification is selected primarily for the purpose of readability and teaching, rather than for the purpose of explaining or limiting the subject matter of the present application. Therefore, many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. For the scope of the present application, the disclosure made to the present application is illustrative, not restrictive, and the scope of the present application is defined by the appended claims.

Claims

1. A method for processing urban management events based on Beidou grid code, suitable for execution in a computing device, the method comprising: Based on the Beidou grid code, grid coding is performed on each geographic spatial data within the urban space to generate a basic grid model, wherein the basic grid model includes a plurality of block data, and each block data is indexed by the Beidou grid code; When a city management event is reported, obtaining the reported event data, wherein the event data includes at least one of text data, video data, and voice data; Processing the event data to determine the event type, geographic location and attributes of the urban management event; Determine the Beidou grid code associated with the urban management event using the geographical location; Using the Beidou grid code, judging from the basic grid model whether there is a similar event in the urban management event; If there are similar events, determine whether they are repeated events; If it is not a repeated event, the event type and attributes of the urban management event are mapped to the spatial grid pointed to by the Beidou grid code to update the basic grid model; Each block of data in the basic grid model is encapsulated to provide it to the subsequent batch processing flow.

2. The method according to claim 1, wherein the grid coding of each geographic space data within the urban space range is performed based on the Beidou grid code to generate a basic grid model, comprising: Acquire geospatial data from multiple data sources, wherein the geospatial data includes location information, time information, and attribute information; According to the location information, respectively determine the spatial grids to which the corresponding geographic spatial data belongs, wherein the spatial grids are obtained by gridding the urban space based on the Beidou grid code, and each spatial grid has a unique Beidou grid code; The time information and attribute information of each of the geographic spatial data are mapped to the determined spatial grid to generate a basic grid model.

3. The method according to claim 1 or 2, further comprising: Determine the Beidou grid codes of multiple spatial grids contained in the jurisdiction; The Beidou grid code is used to perform statistical analysis on events within the jurisdiction area to determine the management status of the jurisdiction area.

4. The method of claim 3, wherein: The statistical analysis of events within the jurisdiction includes: Determine one or more Beidou grid codes corresponding to the range of each area; Based on the determined Beidou grid code, the number of urban management events of each event category in each area is counted to determine the types of high-incidence events and their frequencies in each area.

5. The method according to claim 3 or 4, wherein: The statistical analysis of events within the jurisdiction includes: The time information corresponding to the urban management events of the same event category within the jurisdiction area is counted to determine the time distribution of each event type.

6. The method according to any one of claims 1 to 5, wherein: The processing of the event data to determine the event type, geographic location and attributes of the urban management event includes: If the event data includes text data, identifying relevant information of the event from the text data; If the event data includes voice data, converting the voice data into text data, and processing the converted text data to identify relevant information of the event; If the event data includes video data, extracting feature data of the video data, and generating relevant information of the event based on the feature data, wherein the feature data includes at least one of equipment, personnel, materials, and area edges; In combination with the relevant information, the event type, geographical location and attributes of the urban management event are determined.

7. The method according to any one of claims 1 to 6, wherein: The event types include: urban appearance and environment, publicity and advertising, construction management, street order, emergencies and other event types.

8. The method according to any one of claims 1 to 4, wherein: The using the Beidou grid code to judge from the basic grid model whether there is a similar event to the urban management event includes: Acquire data associated with the Beidou grid code from the basic grid model; Determine whether there is an urban management event of the same event type as the urban management event and belonging to the same time period in the acquired data; If so, it is confirmed that similar events exist.

9. The method according to any one of claims 1 to 8, wherein: The determination of whether it is a repeated event includes: Compare the attributes of similar events with the attributes of the city management event to see if they are consistent; If they are inconsistent, confirm that they are not duplicate events.

10. The urban management event processing system based on Beidou grid code includes: The data connection coding module is suitable for grid coding various geographic spatial data within the urban space based on the Beidou grid code to generate a basic grid model; An event reporting processing module, adapted to obtain reported event data when an urban management event is reported, wherein the event data includes at least one of text data, video data, and voice data; An event preprocessing module, adapted to process the event data to determine the event type, geographic location and attributes of the urban management event, and determine the Beidou grid code associated with the urban management event using the geographic location; It is also suitable to use the Beidou grid code to determine whether there are similar events in the urban management event from the basic grid model, and when there are similar events, determine whether it is a repeated event; A data mapping module, adapted to map the event type and attribute of the urban management event to the spatial grid pointed to by the Beidou grid code to update the basic grid model when it is not a repeated event; The grid data analysis module is suitable for encapsulating each block of data in the basic grid model to provide it to the subsequent batch processing flow, and is also suitable for analyzing and processing each block of data.

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