Method, device and equipment for demographic statistics, medium and program product

Abstract

The invention relates to a demographic method, device and equipment, a medium and a program product in the technical field of communication. The method comprises the following steps: according to a list set of discrete base stations, obtaining a first boundary vertex coordinate set of a minimum polygon capable of covering the discrete base stations, and obtaining a region polygon boundary; based on a polygon external expansion algorithm, performing external expansion on the region polygon boundary to obtain a second polygon boundary vertex coordinate set; eliminating boundary intersection points to obtain a third polygon boundary vertex coordinate set; and according to the boundary vertex coordinate set of the third polygon, obtaining the number of users in a specified base station coverage area through two-stage filtering of a spatial index algorithm and combination of real-time user position data. According to the invention, the area boundary generation method is proposed for the area of a known base station list, spatial index calculation is introduced, and the number of users in the specified base station coverage area is obtained. Precise regional population recognition is realized, and the calculation efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a demographic method, apparatus, device, medium, and program product. Background Art

[0002] The key to population mobility management lies in the identification of migrant population. Traditional methods generally include: population census, checkpoint statistics, sampling prediction, etc., but they are limited by specific factors such as manpower and location, and lack universality, timeliness and accuracy.

[0003] With the rapid development of new digital technologies such as cloud computing, big data, and artificial intelligence, methods based on mobile phone signaling data and dynamic facial recognition have gained widespread application. While operator location signaling data offers advantages such as wide coverage, high user base, and robust data continuity, it also suffers from a significant drawback: poor positioning accuracy. This issue can lead to inaccurate regional population identification, particularly in smaller areas such as scenic spots and shopping malls, where statistical errors can be more severe, hindering the application and effectiveness of location-based big data.

[0004] To solve the above problems, the present invention proposes a real-time regional population identification method based on base station engineering parameter data. Through the boundary generation algorithm and the regional effective base station coverage algorithm, while ensuring efficiency, it supports regional population identification based on base stations (non-regional boundaries) and precise regional population identification based on regional boundaries. Summary of the Invention

[0005] In order to solve the above technical problems, the embodiments of the present disclosure provide a method, apparatus, device, computer storage medium and computer program product for demographic statistics, which realize accurate regional population identification.

[0006] A first aspect of the present disclosure provides a method for demographic statistics, the method comprising: According to the list set of discrete base stations, a first boundary vertex coordinate set of a minimum polygon that can cover the discrete base stations is obtained to obtain a regional polygon boundary; Expanding the polygonal boundary of the region based on a polygonal expansion algorithm to obtain a second polygonal boundary vertex coordinate set; Obtain a set of coordinates of the third polygon boundary vertices by eliminating boundary intersections; According to the third polygon boundary vertex coordinate set, the number of users in the designated base station coverage area is obtained through secondary filtering of a spatial index algorithm and combined with real-time user location data.

[0007] A second aspect of the present disclosure provides a method for demographics, the method comprising: Determining a spatial coverage boundary of a base station, wherein the base station includes an omnidirectional base station and a directional base station; Determine effective base stations in a region using a spatial screening algorithm based on multi-dimensional spatial point index; Based on the spatial index algorithm and the real-time location data of users, the real-time number of users within the effective base stations in the area is determined.

[0008] According to a third aspect of the embodiments of the present disclosure, a demographic device is provided, comprising: The first module is configured to obtain a first boundary vertex coordinate set of a minimum polygon that can cover the discrete base stations according to the list set of discrete base stations, and obtain a regional polygon boundary; The second module is configured to expand the polygonal boundary of the region based on a polygonal expansion algorithm to obtain a second polygonal boundary vertex coordinate set; A third module is configured to obtain a set of coordinates of the third polygon boundary vertices by eliminating boundary intersections; The statistics module is configured to obtain the number of users in the designated base station coverage area based on the third polygon boundary vertex coordinate set through secondary filtering of a spatial index algorithm and in combination with real-time user location data.

[0009] A fourth aspect of the embodiments of the present disclosure provides a demographic device, including: a boundary module configured to determine a spatial coverage boundary of a base station, wherein the base station includes an omnidirectional base station and a directional base station; The valid module is configured to determine valid base stations in the area using a spatial screening algorithm based on a multi-dimensional spatial point index; The comparison module is configured to determine the real-time number of users within the effective base stations in the area based on a spatial index algorithm and the real-time location data of the users.

[0010] According to a fifth aspect of the present disclosure, an electronic device is provided, including: at least one processor; a memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement any one of the methods of the first aspect or the second aspect.

[0011] In a sixth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any one of the methods of the first or second aspects mentioned above.

[0012] According to a seventh aspect of the embodiments of the present disclosure, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the demographic method of any one of the first or second aspects described above.

[0013] The disclosed embodiment proposes a real-time regional population identification method based on base station engineering parameter data. Through the boundary generation algorithm and the regional effective base station coverage algorithm, while ensuring efficiency, it supports both regional population identification at non-regional boundaries and precise regional population identification based on regional boundaries. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0015] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0016] Figure 1 A flow chart of a demographic method provided in an embodiment of the present disclosure; Figure 2 A schematic diagram of an algorithm for obtaining a regional polygonal boundary in step S111 of a demographic method provided by an embodiment of the present disclosure; Figure 3 A schematic diagram of an invalid expansion point for boundary expansion provided by an embodiment of the present disclosure; Figure 4 A schematic diagram of a region boundary after eliminating boundary intersections provided in an embodiment of the present disclosure; Figure 5 A flowchart of another demographic method provided by an embodiment of the present disclosure; Figure 6 A schematic diagram of a directional base station coverage range provided in an embodiment of the present disclosure Figure 7 A schematic diagram of a process for determining effective base stations in an area provided by an embodiment of the present disclosure; Figure 8 A schematic structural diagram of a demographic device provided in an embodiment of the present disclosure; Figure 9 A schematic structural diagram of another demographic device provided by an embodiment of the present disclosure; Figure 10 A schematic structural diagram of an electronic device provided in an embodiment of the present disclosure; Figure 11 A schematic diagram of the structure of an exemplary computer system provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features therein can be combined with each other in the absence of conflict.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0019] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0020] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0021] It should be noted that the modifications of “one” and “multiple” mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as “one or more”.

[0022] As the national economy continues to grow in vitality and transportation becomes increasingly convenient, cross-regional population mobility has become the norm. Effective population mobility management is fundamental to promoting sustained and healthy economic development and social harmony and stability. The key to population mobility management lies in identifying the floating population. Traditional methods generally include censuses, checkpoint statistics, and sampling forecasts. However, these methods are limited by specific factors such as manpower and location, and lack universality, timeliness, and accuracy.

[0023] With the rapid development of new digital technologies such as cloud computing, big data, and artificial intelligence, methods based on mobile phone signaling data and dynamic facial recognition have gained widespread application. While operator location signaling data offers advantages such as wide coverage, high user base, and robust data continuity, it also suffers from a significant drawback: poor positioning accuracy. This issue can lead to inaccurate regional population identification, particularly in smaller areas such as scenic spots and shopping malls, where statistical errors can be more severe, hindering the application and effectiveness of location-based big data.

[0024] To solve the above problems, the embodiments of the present disclosure propose a real-time regional population identification method based on base station engineering parameter data. Through the boundary generation algorithm and the regional effective base station coverage algorithm, while ensuring efficiency, it supports both regional population identification based on base stations (non-regional boundaries) and precise regional population identification based on regional boundaries, thereby realizing precise regional population identification and improving computational efficiency.

[0025] Before describing the present disclosure, for ease of understanding, the terms involved in the present disclosure embodiments are first explained.

[0026] Base station engineering parameters: These are crucial parameters for mobile communication base station antenna maintenance and network optimization. These parameters include latitude and longitude, altitude, mounting height, azimuth, and mechanical downtilt, all of which have a decisive impact on the base station's electromagnetic coverage.

[0027] Azimuth: Azimuth is an important concept in base station engineering parameters. It refers to the pointing angle of the base station antenna. Usually, the base station is used as the origin, the north direction of the antenna is 0 degrees or 360 degrees, and then the angle to the direction pointed by the antenna is measured clockwise.

[0028] Regionally valid base stations: The electromagnetic coverage space of the base station intersects with the area of ​​the selected area, and the ratio of the intersection area to the area of ​​the selected area is greater than the threshold ɑ, where ɑ is a defined constant greater than 0 and less than 1.

[0029] The demographic method provided by the embodiment of the present disclosure relies on real-time user location data and operator base station engineering parameter data, and supports both regional demographics with only a base station list but no boundaries and regional demographics with only regional boundaries but no base station list.

[0030] The following combination Figures 1-11 , describes the demographic method, apparatus, device, computer storage medium, and computer program product provided by the embodiments of the present disclosure.

[0031] Figure 1 A flow chart of a demographic method provided by an embodiment of the present disclosure is shown as follows: Figure 1 As shown, for a population identification scenario with an existing regional base station list, in order to avoid correlation matching of the full amount of data, the embodiment of the present disclosure proposes a borderless regional population identification method, which includes: S111. Obtain, based on the list set of discrete base stations, a first boundary vertex coordinate set of a minimum polygon that can cover the discrete base stations, to obtain a regional polygon boundary; The list set of discrete base stations is defined as:

[0032] in, An object containing the longitude and latitude information of a base station. lng is the longitude of the base station cell, and lat is the latitude of the base station cell.

[0033] In one embodiment, Figure 2 A demographic method according to an embodiment of the present disclosure provides a schematic diagram of an algorithm for obtaining a polygonal boundary of a region in step S111, as shown in FIG. Figure 2 As shown, step S111 includes: S1111. According to the list set of discrete base stations, find the point with the largest latitude and the smallest longitude, and record it as point p 1; For a list of known discrete base stations, find the point with the largest latitude and the smallest longitude, and record it as point ; like Figure 2 In the upper left corner of the diagram, the point with the largest latitude and the smallest longitude is point A. Point A is recorded as p 1.

[0034] S1112, starting point As the origin, make a ray in the east direction, scan clockwise, and find the point scanned when the rotation angle is the smallest, recorded as ; like Figure 2 The diagram in the upper left corner shows that point A is the origin, and a ray is drawn in the east direction, scanning clockwise. The point scanned when the rotation angle is the smallest is point B, which is recorded as .

[0035] S1113, since Start with As the origin, Make a ray in the direction, scan clockwise, and find the point where the rotation angle is the smallest one by one, recorded as until the starting point is found Until, where n is a natural number; like Figure 2 The icon in the upper right corner of the Point is the origin, Direction is to make a ray, that is, take point B as the origin, make a ray in the AB direction, scan clockwise, and find the point where the rotation angle is the smallest as point C, recorded as point; like Figure 2 The icon in the lower left corner of the Point is the origin, Direction is to make a ray, that is, take point C as the origin, make a ray in the BC direction, scan clockwise, and find the point scanned when the rotation angle is the smallest as point D, recorded as point; And so on, until the starting point is found. So far, if Figure 2 As shown in the lower right corner, the scan continues until point A is found.

[0036] S1114. Record the points retrieved during the search process in sequence, and record them as the first boundary vertex coordinate set of the minimum polygon boundary containing the base station: .

[0037] S112. Expand the polygonal boundary of the region based on a polygonal expansion algorithm to obtain a second polygonal boundary vertex coordinate set; According to the polygon expansion algorithm, the region polygon boundary generated in step S111 is appropriately expanded to generate a second polygon boundary vertex coordinate set: .

[0038] S113. Obtain a set of coordinates of the third polygon boundary vertices by eliminating boundary intersections. Figure 3 A schematic diagram of an invalid expansion point of a boundary expansion provided by an embodiment of the present disclosure, such as Figure 3 As shown, after the regional polygon boundary is expanded, there will be boundary crossings. Such crossing boundaries are not friendly to spatial index calculations, so the crossing boundary situations must be eliminated.

[0039] Exemplarily, step S113 includes: S1131. Split the boundary of the second polygon boundary vertex coordinate set into a set of directed line segments connected end to end. ; The coordinate set of the second polygon boundary vertices The boundary of the ; S1132, calculate the intersection points of all directed line segments in sequence to form an ordered set of intersection points ; S1133. Based on the generated intersection point set, a new set of directed line segments connected end to end is formed. ; S1134, traverse the directed line segment set in sequence , add the valid expansion points into the valid expansion point set to obtain the coordinate set of the third polygon boundary vertices.

[0040] Exemplarily, step S1134 includes: S11341, traverse the directed line segment set in sequence , calculate each point The number of times as the starting point, the point with a number as the starting point greater than 1 is recorded as a valid expansion point; Traverse in sequence , calculate each point As the number of starting points, if a point is used as a starting point more than 1, it means that the point is a valid expansion point; if a point is used as a starting point more than 1, it means that the point is an invalid expansion point. The intersection of the directed line segments in ; Traverse in sequence Set, for each starting point of a line segment ,if Is an outward expansion valid point, then include this point in the final outward expansion valid point set; if If a point is an invalid point for expansion, all directed line segments after the point are ignored until the next directed line segment starting from the point.

[0041] S11342. Add the valid expansion points to the valid expansion point set to obtain a set of coordinates of the third polygon boundary vertices.

[0042] All valid expansion points are included in the expansion valid point set, and the final expansion valid point set is obtained to obtain the third polygon boundary vertex coordinate set, which is the vertex coordinate set of the expansion polygon covering the discrete base station position.

[0043] For example, when eliminating intersections, an outward expansion boundary may be generated by using a method of a region center and a maximum coverage radius.

[0044] Figure 4 A schematic diagram of the region boundary after eliminating the boundary intersection provided by the embodiment of the present disclosure, such as Figure 4 As shown in FIG, the outermost boundary is the regional boundary effect after the boundary intersection points are finally eliminated.

[0045] S114 . Obtain the number of users in the designated base station coverage area based on the third polygon boundary vertex coordinate set through secondary filtering using a spatial index algorithm and in combination with real-time user location data.

[0046] By combining the third polygon boundary vertex coordinate set obtained in step S113 with the secondary filtering of the spatial index algorithm and the real-time user location data, the number of users in the designated base station coverage area can be obtained in real time and efficiently.

[0047] In the embodiments of the present disclosure, for the areas of the known base station list, this proposal proposes a method for generating area boundaries. Based on this algorithm, the area screening error caused by area selection is first avoided; and through the generated area boundaries, the spatial index calculation is introduced to avoid the association operation of the full amount of user location data with the known base station list, which has the effect of improving computing efficiency and reducing computing resource overhead.

[0048] Figure 5 A flow chart of another demographic method provided in an embodiment of the present disclosure is provided. For scenarios with existing regional boundaries, in order to determine the accuracy of regional population screening, a precise regional population identification method based on base station working parameters is proposed. The base station working parameter data required for this method are shown in Table 1.

[0049] Table 1

[0050] like Figure 5 As shown, the method includes: S511. Determine a spatial coverage boundary of a base station, where the base station includes an omnidirectional base station and a directional base station.

[0051] Base stations are divided into directional base stations and omnidirectional base stations. The antenna coverage angle of an omnidirectional base station is 360 degrees, and the boundary of its coverage range can be regarded as the projection of a cylinder with the base station location as the center and the base station coverage radius on the earth's surface.

[0052] Figure 6 A schematic diagram of a directional base station coverage range provided by an embodiment of the present disclosure is shown in FIG. Figure 6 As shown, the coverage boundary of the directional base station can be approximated as Figure 6 The process of determining the spatial coverage boundary of a directional base station is as follows: S5111. Obtain a spatial coverage boundary angle of the base station cell according to the azimuth angle and the base station cell coverage angle.

[0053] First, a coordinate system is established with the base station's latitude and longitude as the vertices, defining the direction of the X-axis as due east and the direction of the Y-axis as due north.

[0054] The spatial coverage boundary angle of the base station cell is calculated based on the azimuthAngle azimuth angle and the degRange base station cell coverage angle, where leftDegree and rightDegree are the angles between the two boundaries of the base station cell sector and the positive direction of the Y axis. The calculation formula is as follows:

[0055]

[0056] in, and They are the angles between the two boundaries of the base station cell sector and the positive direction of the Y axis (that is, the north direction).

[0057] S5112. Obtain the coordinates of the other two vertices of the base station cell coverage triangle boundary according to the spatial coverage boundary angle of the base station cell.

[0058] One vertex of the base station cell coverage triangle boundary is the base station. According to leftDegree and rightDegree, calculate the coordinates of the other two vertices of the base station cell coverage triangle boundary. and Substitute the following formula to obtain the latitude and longitude coordinates of the other two vertices of the base station cell coverage triangle boundary.

[0059]

[0060]

[0061] S5113. Obtain the spatial coverage area of ​​the base station cell according to the coordinates of the vertices of the base station cell coverage triangle boundary.

[0062] The base station cell spatial coverage area area is calculated based on the coordinates of the base station cell coverage triangle boundary vertices obtained in step S5112.

[0063] S512: Determine valid base stations in the area using a spatial screening algorithm based on a multi-dimensional spatial point index.

[0064] Figure 7 A schematic diagram of a process for determining effective base stations in an area provided by an embodiment of the present disclosure is shown as follows: Figure 7 As shown, S512 includes the following steps: S5121, determine whether the area is a polygon; If the target area is a polygon, calculate the center point p of the polygon; if the target area is a circle, ignore this step; S5122. Determine the spatial expansion area of ​​the target area; If the target area is a polygon, calculate the distance between the boundary vertices and the center point p in sequence and take the farthest distance d; if the target area is a circle, ignore this step; S5123. Screening base stations within the space expansion area; A spatial screening algorithm based on a multidimensional space point index is used to select the base station set stations contained in a circular area with a center point p (if it is a circular area, the center point p is the center of the circular area) and a radius of d+r (if it is a circular area, d is the radius of the circular area).

[0065] S5124. Calculate the coverage range and area of ​​the base station in sequence; According to the base station coverage range calculation method, traverse the stations set, calculate the coverage space boundary baseStaionBoundary of each base station in turn, and calculate the coverage space area baseStationArea of ​​the base station based on the boundary; S5125. Calculate the spatial intersection area of ​​the base station coverage and the target area in sequence; Traverse the stations collection and calculate the intersection area of ​​each base station and the target area in turn.

[0066] S5126. Calculate the ratio of the intersection area to the area of ​​the base station in sequence; Calculate ratio = intersectionArea / baseStationArea.

[0067] S5127. Retain the base stations whose ratios are greater than a preset threshold.

[0068] If the ratio>= ɑ, the base station is retained; if the ratio<ɑ, the base station is removed, where ɑ is a preset threshold.

[0069] S513: Determine the real-time number of users within the effective base stations in the area based on the spatial index algorithm and the real-time location data of the users.

[0070] Based on the spatial index algorithm and the user's real-time location data, the number of users in the circular area with point p (if it is a circular area, the center point p is the center of the circular area) as the center and d+r (if it is a circular area, d is the radius of the circular area) as the radius obtained in steps S5121-S5123 is initiatory_result.

[0071] It can be understood that a spatial index is a data structure used to accelerate spatial data queries. It organizes and arranges spatial data according to certain rules to establish an index structure, allowing us to quickly locate spatial objects related to the query conditions without traversing all the data. Furthermore, the base station codes in the real-time location data of users within the effective base stations in the area are compared with the base station codes in the effective base station working parameters in the area. Users with consistent comparison results are retained to obtain the real-time number of users within the effective base stations in the area. The real-time location data of the initiatory_result users can be traversed and the base station codes in the location data are compared with the base station codes in the effective base station working parameters in the area. If they are consistent, the user is retained; if they are inconsistent, the user is eliminated. The final set of users retained is the accurate real-time population of the area.

[0072] In the disclosed embodiments, a precise regional population identification algorithm based on base station operating parameters is proposed for areas with known regional boundaries. First, the algorithm uses base station operating parameters to calculate the base station coverage boundary and spatial coverage area, providing a reference for precise population identification later in the algorithm. Second, based on data such as the base station coverage boundary, the base station coverage area, and the known regional boundaries, the algorithm calculates the base stations with effective coverage within the region's perimeter. Finally, by comparing the location data of people surrounding the region with valid base stations, accurate regional population identification results are obtained. This solution eliminates base station antennas located within the region, near the region boundary, and with azimuths pointing outside the region. It also includes base station antennas located outside the custom region, near the region boundary, and with azimuths pointing in the direction of the region. This prevents people within the region from being screened by the region due to connecting to base stations outside the region, and prevents people outside the region from being screened by the custom region due to connecting to base stations within the region, thereby improving the accuracy of regional population screening.

[0073] The disclosed embodiments, based on a boundary generation algorithm and a regional effective base station screening algorithm, achieve efficient and accurate identification of regional populations in both scenarios with and without regional boundaries. The above technical solution has the advantages of strong real-time performance, high coverage, and good continuity and dynamism when implementing regional user statistics. It has high application and social value in demographic statistics, specific area monitoring, and understanding of population mobility patterns, such as emergency population mobility monitoring and early warning. Furthermore, the above technical solution can also be combined with other data sources to identify and analyze population attributes, such as socioeconomic attributes and commuting travel characteristics.

[0074] The above is only a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements, optimizations and modifications without departing from the principles of the present invention, and these should also be considered within the scope of protection of the present invention.

[0075] Figure 8 A schematic diagram of a demographic device provided in an embodiment of the present disclosure is shown in FIG. Figure 8 As shown, the demographic device 800 includes: The first module 801 is configured to obtain a first boundary vertex coordinate set of a minimum polygon that can cover the discrete base stations according to the list set of discrete base stations, and obtain a regional polygon boundary; The second module 802 is configured to expand the polygonal boundary of the region based on a polygonal expansion algorithm to obtain a second polygonal boundary vertex coordinate set; The third module 803 is configured to obtain a set of coordinates of the third polygon boundary vertices by eliminating boundary intersections; The statistics module 804 is configured to obtain the number of users in the designated base station coverage area based on the third polygon boundary vertex coordinate set, through secondary filtering of a spatial index algorithm and in combination with real-time user location data.

[0076] In some embodiments, the first module 801 includes: The first search module is configured to find the point with the largest latitude and the smallest longitude according to the list set of discrete base stations, and record it as point p 1; The second search module is configured to start at As the origin, make a ray in the east direction, scan clockwise, and find the point scanned when the rotation angle is the smallest, recorded as ; The third search module is configured to Start with As the origin, Make a ray in the direction, scan clockwise, and find the point where the rotation angle is the smallest one by one, recorded as until the starting point is found So far, where n is a natural number; The recording module is configured to sequentially record the points retrieved during the search process as a set of first boundary vertex coordinates of the minimum polygon boundary containing the base station: .

[0077] In some embodiments, the third module 803 includes: A splitting module is configured to split the boundary of the second polygon boundary vertex coordinate set into a set of directed line segments connected end to end ; The intersection module is configured to calculate the intersection points of all directed line segments in sequence to form an ordered set of intersection points. ; The collection module is configured to form a new set of directed line segments connected end to end based on the generated intersection set ; The traversal module is configured to traverse the set of directed line segments in sequence , add the valid expansion points into the valid expansion point set to obtain the coordinate set of the third polygon boundary vertices.

[0078] In some embodiments, the traversal module includes: The calculation module is configured to traverse the set of directed line segments in sequence , calculate each point The number of times as the starting point, the point with a number as the starting point greater than 1 is recorded as a valid expansion point; The collection module is configured to include the valid outward expansion points into the outward expansion valid point set to obtain the third polygon boundary vertex coordinate set.

[0079] Figure 9 A structural diagram of another demographic device provided in an embodiment of the present disclosure is shown as follows: Figure 9 As shown, the demographic device 900 includes: Boundary module 901 is configured to determine a spatial coverage boundary of a base station, wherein the base station includes an omnidirectional base station and a directional base station; The valid module 902 is configured to determine valid base stations in the area based on a spatial screening algorithm based on a multi-dimensional spatial point index; The comparison module 903 is configured to determine the real-time number of users within the effective base stations in the area based on the spatial index algorithm and the real-time location data of the users.

[0080] In some embodiments, the boundary module 901 includes: A coverage module is configured to obtain a spatial coverage boundary angle of a base station cell according to an azimuth angle and a base station cell coverage angle; A vertex module is configured to obtain the coordinates of two other vertices of the base station cell coverage triangle boundary according to the spatial coverage boundary angle of the base station cell; The area module is configured to obtain the base station cell spatial coverage area according to the coordinates of the base station cell coverage triangle boundary vertices.

[0081] In some embodiments, the validation module 902 includes: a determination module configured to determine a spatial expansion area of ​​a target area; A screening module is configured to screen base stations within the spatial expansion area; a range module configured to sequentially calculate the coverage range and area of ​​the base station; An intersection module is configured to sequentially calculate the spatial intersection area between the coverage area of ​​the base station and the target area; a ratio module, configured to sequentially calculate the ratio of the intersection area to the area of ​​the base station; The reservation module is configured to reserve base stations whose ratios are greater than a preset threshold.

[0082] In some embodiments, the comparison module 903 includes: A user module is configured to determine users within the effective base stations in the area based on a spatial index algorithm and real-time user location data; The real-time module is configured to compare the base station codes in the real-time location data of users within the effective base stations in the area with the base station codes in the working parameters of the effective base stations in the area, retain the users with the same comparison results, and obtain the real-time number of users within the effective base stations in the area.

[0083] The implementation process of the functions and effects of each module in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0084] Figure 10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure is shown in FIG. Figure 10 As shown, an embodiment of the present disclosure also provides an electronic device, which includes at least one processor 1001 and a memory 1002 coupled to the processor 1001, and the memory 1002 is used to store executable instructions of at least one processor 1001, wherein the at least one processor 1001 is used to execute instructions to implement the steps of the above-mentioned method of the embodiment of the present disclosure.

[0085] The processor 1001 can also be referred to as a central processing unit (CPU), which can be an integrated circuit chip with signal processing capabilities. Each step in the method described in the embodiments of the present disclosure can be performed by hardware integrated logic circuits in the processor 1001 or by software instructions. The processor 1001 can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method described in the embodiments of the present disclosure can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can be located in memory 1002, such as a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The processor 1001 reads the information in the memory 1002 and, in conjunction with its hardware, completes the steps of the method described above.

[0086] Figure 11 This is a schematic diagram of the structure of an exemplary computer system provided by an embodiment of the present disclosure. According to various operations / processes of the embodiments of the present disclosure, when implemented by software and / or firmware, data can be transmitted from a storage medium or a network to a computer system with a dedicated hardware structure, for example, Figure 11 The computer system 1100 shown is installed with the programs constituting the software. When the various programs are installed, the computer system can perform various functions, including the functions described above.

[0087] Computer system 1100 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are intended to be examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0088] like Figure 11 As shown, computer system 1100 includes a computing unit 1101, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1102 or a computer program loaded from a storage unit 1108 into a random access memory (RAM) 1103. RAM 1103 may also store various programs and data required for the operation of computer system 1100. Computing unit 1101, ROM 1102, and RAM 1103 are interconnected via a bus 1104. An input / output (I / O) interface 1105 is also connected to bus 1104.

[0089] Several components within computer system 1100 are connected to I / O interface 1105, including an input unit 1106, an output unit 1107, a storage unit 1108, and a communication unit 1109. Input unit 1106 can be any type of device capable of inputting information into computer system 1100. Input unit 1106 can receive input numeric or character information and generate key input signals related to user settings and / or function control of an electronic device. Output unit 1107 can be any type of device capable of presenting information and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. Storage unit 1108 may include, but is not limited to, a magnetic disk or an optical disk. Communication unit 1109 allows computer system 1100 to exchange information / data with other devices over a network, such as the Internet, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver and / or chipset, such as a Bluetooth™ device, a Wi-Fi device, a WiMax device, a cellular communication device, and / or the like.

[0090] The computing unit 1101 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 1101 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1101 performs the various methods and processes described above. For example, in some embodiments, the methods described above in the embodiments of the present disclosure may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 1108. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device via the ROM 1102 and / or the communication unit 1109. In some embodiments, the computing unit 1101 may be configured to perform the methods described above in the embodiments of the present disclosure by any other suitable means (e.g., via firmware).

[0091] An embodiment of the present disclosure provides a computer-readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the above-mentioned method of the embodiment of the present disclosure.

[0092] The computer-readable storage medium may be a volatile memory, such as a random-access memory (RAM); or a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD); or may be a device including one or any combination of the above memories, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc.

[0093] It should be noted that the computer-readable storage medium described above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. Computer-readable storage media may include, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wire, optical cable, RF (radio frequency), or any suitable combination thereof.

[0094] An embodiment of the present disclosure provides a computer program product, including a computer program, which implements the steps of the above demographic method when executed by a processor.

[0095] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the computer, partially on the computer, as a standalone software package, partially on the computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0096] The modules, components, or units described in the embodiments of the present disclosure may be implemented in software or hardware. The names of the modules, components, or units do not necessarily limit the modules, components, or units themselves.

[0097] The functions described above herein may be at least partially performed by one or more hardware logic components. For example, and without limitation, exemplary hardware logic components that may be used include: a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), an application specific standard product (ASSP), a system on a chip (SOC), a complex programmable logic device (CPLD), and the like.

[0098] It should be noted that, in this document, terms such as "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0099] The foregoing description is intended only to provide specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments described herein, but rather to be construed in the broadest manner consistent with the principles and novel features claimed herein.

Claims

1. A method of demographics, characterized in that The method comprises: According to the list set of discrete base stations, a first boundary vertex coordinate set of a minimum polygon that can cover the discrete base stations is obtained to obtain a regional polygon boundary; Expanding the polygonal boundary of the region based on a polygonal expansion algorithm to obtain a second polygonal boundary vertex coordinate set; Obtain a set of coordinates of the third polygon boundary vertices by eliminating boundary intersections; According to the third polygon boundary vertex coordinate set, the number of users in the designated base station coverage area is obtained through secondary filtering of a spatial index algorithm and combined with real-time user location data.

2. The method according to claim 1, characterized in that The step of obtaining, based on the list set of discrete base stations, a first boundary vertex coordinate set of a minimum polygon capable of covering the discrete base stations, and obtaining the regional polygon boundary comprises: According to the list of discrete base stations, find the point with the largest latitude and the smallest longitude, and record it as point p 1; Starting point As the origin, make a ray in the east direction, scan clockwise, and find the point scanned when the rotation angle is the smallest, recorded as ; since Start with As the origin, Make a ray in the direction, scan clockwise, and find the point where the rotation angle is the smallest one by one, recorded as until the starting point is found So far, where n is a natural number; The points retrieved during the search are recorded in sequence as the first boundary vertex coordinate set of the minimum polygon boundary containing the base station: .

3. The method according to claim 1 or 2, characterized in that Obtaining a set of coordinates of the third polygonal boundary vertices by eliminating boundary intersections includes: Split the boundary of the second polygon's boundary vertex coordinate set into a set of directed line segments connected end to end ; Calculate the intersection points of all directed line segments in sequence to form an ordered set of intersection points ; Based on the generated intersection set, a new set of directed line segments connected end to end is formed ; Traverse the set of directed line segments in sequence , add the valid expansion points into the valid expansion point set to obtain the coordinate set of the third polygon boundary vertices.

4. The method according to claim 3, characterized in that The directed line segment set is traversed in sequence , add the valid expansion points into the valid expansion point set, and obtain the coordinate set of the third polygon boundary vertices including: Traverse the set of directed line segments in sequence , calculate each point The number of times as the starting point, the point with a number as the starting point greater than 1 is recorded as a valid expansion point; The valid expansion points are added to the valid expansion point set to obtain a set of coordinates of the third polygon boundary vertices.

5. A method of demographics, characterized in that The method comprises: Determining a spatial coverage boundary of a base station, wherein the base station includes an omnidirectional base station and a directional base station; Determine effective base stations in a region using a spatial screening algorithm based on multi-dimensional spatial point index; Based on the spatial index algorithm and the real-time location data of users, the real-time number of users within the effective base stations in the area is determined.

6. The method according to claim 5, characterized in that If the base station is a directional base station, determining the spatial coverage boundary of the base station includes: Obtaining the spatial coverage boundary angle of the base station cell according to the azimuth angle and the base station cell coverage angle; According to the spatial coverage boundary angle of the base station cell, the coordinates of the other two vertices of the base station cell coverage triangle boundary are obtained; The spatial coverage area of ​​the base station cell is obtained according to the coordinates of the vertices of the base station cell coverage triangle boundary.

7. The method according to claim 5, characterized in that The spatial screening algorithm based on the multidimensional spatial point index to determine the effective base stations in the area includes: Determine the spatial expansion area of ​​the target area; Screening base stations within the spatial expansion area; Calculate the coverage and area of ​​the base station in turn; Calculate the spatial intersection area between the base station coverage and the target area in sequence; Calculate the ratio of the intersection area to the area of ​​the base station in sequence; The base stations with a ratio greater than a preset threshold are retained.

8. The method according to claim 5, characterized in that Determining the number of real-time users within the effective base stations in the area based on the spatial index algorithm and the real-time user location data includes: Determine users within the valid base stations in the area based on a spatial index algorithm and real-time user location data; The base station codes in the real-time location data of users within the effective base stations in the area are compared with the base station codes in the working parameters of the effective base stations in the area, and users with consistent comparison results are retained to obtain the real-time number of users within the effective base stations in the area.

9. A demographic device, characterized in that include: The first module is configured to obtain a first boundary vertex coordinate set of a minimum polygon that can cover the discrete base stations according to the list set of discrete base stations, and obtain a regional polygon boundary; The second module is configured to expand the polygonal boundary of the region based on a polygonal expansion algorithm to obtain a second polygonal boundary vertex coordinate set; A third module is configured to obtain a set of coordinates of the third polygon boundary vertices by eliminating boundary intersections; The statistics module is configured to obtain the number of users in the designated base station coverage area based on the third polygon boundary vertex coordinate set through secondary filtering of a spatial index algorithm and in combination with real-time user location data.

10. A demographic device, characterized in that include: a boundary module configured to determine a spatial coverage boundary of a base station, wherein the base station includes an omnidirectional base station and a directional base station; The valid module is configured to determine valid base stations in the area using a spatial screening algorithm based on a multi-dimensional spatial point index; The comparison module is configured to determine the real-time number of users within the effective base stations in the area based on a spatial index algorithm and the real-time location data of the users.

11. An electronic device, characterized in that: include: at least one processor; a memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the method according to any one of claims 1 to 4 or claims 5 to 7.

12. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method according to any one of claims 1 to 4 or claims 5 to 7.

13. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the demographic method according to any one of claims 1 to 4 or claims 5 to 7 are implemented.

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