Method, device, electronic device and readable storage medium for selecting detection point

Abstract

The detection point site selection method, device, electronic device and readable storage medium provided by the present invention include: determining the target map grid whose adjacent distance of the center coordinate is greater than or equal to the preset distance threshold according to the total daytime population of each map grid in the target study area, constructing multiple polygonal areas as the user's walking circle based on the target map grid, and the polygonal area is a continuous polygonal area range containing the map grid; determining the valid intersecting map grid corresponding to each polygonal area and determining the population in each polygonal area based on the total daytime population of the valid intersecting map grid; determining the demand for detection points in each polygonal area according to the population and the maximum population detection amount of a single detection point; and determining the target interest point located in the polygonal area as the reference address of the detection point from all the interest points located in the target study area based on the demand. The entire site selection process is efficient and can meet the detection needs.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a detection point site selection method, device, electronic device and readable storage medium. Background Art

[0002] At present, in order to facilitate timely monitoring of residents' health status and understand their quality of life, convenient testing points can be set up in public areas of the city to detect residents' physical condition information and collect residents' life information or opinions.

[0003] Generally, when selecting the site for testing points, how to comprehensively consider the population density of public areas and the maximum load capacity of the testing points to meet the increasingly complex testing needs is a technical problem that needs to be solved. Summary of the invention

[0004] One of the purposes of the present invention is to provide a method, device, electronic device and readable storage medium for detecting point site selection, so as to improve the efficiency and reliability of detecting point site selection, so that the determined detecting point can meet the detecting requirements.

[0005] In a first aspect, the present invention provides a method for selecting a detection point, the method comprising: determining a target map grid whose adjacent distance of a center coordinate is greater than or equal to a preset distance threshold according to the total daytime population corresponding to each map grid in a target study area; wherein the preset distance threshold is the maximum distance a user walks within a predetermined walking time based on a preset walking speed; constructing a plurality of polygonal areas within a target study area based on the target map grid, the polygonal area being a continuous polygonal area range including the map grid; the polygonal area represents the walking circle of the user, the polygonal area being a continuous polygonal area range including the map grid, determining a valid intersecting map grid corresponding to each of the plurality of map grids, and determining a population in each of the polygonal areas based on the total daytime population of the valid intersecting map grids; determining a demand for the detection point in each polygonal area based on the population in each polygonal area and a maximum population detection amount of a single detection point; for each polygonal area, determining a target point of interest located in the polygonal area from all points of interest located in the target study area based on the demand, and using the target point of interest as a reference address of the detection point.

[0006] In a second aspect, the present invention provides a detection point site selection device, comprising: a determination module, for determining a target map grid whose adjacent distance of the center coordinate is greater than or equal to a preset distance threshold according to the total daytime population corresponding to each map grid in the target study area; wherein the preset distance threshold is the maximum distance that a user walks at a preset walking speed within a predetermined walking time; a construction module, for constructing a plurality of polygonal areas within the target study area based on the target map grid, wherein the polygonal areas represent the walking circle of the user, and the polygonal areas are continuous polygonal area ranges containing the map grids; a determination module, for determining, from the plurality of map grids, a valid intersecting map grid corresponding to each polygonal area, and determining the population in each polygonal area based on the total daytime population of the valid intersecting map grids; the determination module, for determining the demand for the detection point in each polygonal area according to the population in each polygonal area and the maximum population detection amount of a single detection point; a site selection module, for determining, for each polygonal area, a target point of interest located in the polygonal area from all points of interest located in the target study area based on the demand, and using the target point of interest as a reference address of the detection point.

[0007] In a third aspect, the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor can execute the computer program to implement the method described in the first aspect.

[0008] In a fourth aspect, the present invention provides a readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in the first aspect.

[0009] The present invention provides a detection point site selection method, device, electronic device and readable storage medium. First, according to the total daytime population corresponding to each map grid in the target study area, the target map grid whose adjacent distance of the center coordinate is greater than or equal to the preset distance threshold is determined; wherein the preset distance threshold is the maximum distance that a user walks at a preset walking speed within a predetermined walking time; then, based on the target map grid, multiple polygonal areas in the target study area are constructed as the walking circle of the user, and the polygonal areas are continuous polygonal area ranges that include the map grids; since the polygonal areas are seamlessly connected and there is no free space between each other, the points of interest in the polygonal areas are subsequently determined. The reference address can avoid omissions. After constructing the polygonal area, the population size in the polygonal area can be determined, and the demand for detection points in each polygonal area can be determined by combining the population size and the maximum population detection volume of a single detection point. Finally, the target interest point in the polygonal area is used as the reference position of the detection point. The embodiment of the present invention utilizes the regional characteristics of the polygonal area in the process of detecting point site selection to avoid omission of interest points and affect the site selection of the detection point. Furthermore, before site selection, the population size and the maximum population detection volume are comprehensively considered to accurately determine the demand for detection points. Finally, the reference position of the detection point can be quickly determined from the interest points in the polygonal area. The entire site selection process is efficient and can meet the detection needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic diagram of an electronic device is also provided for an embodiment of the present invention;

[0012] Figure 2 A schematic flow chart of a detection point site selection method provided in an embodiment of the present invention;

[0013] Figure 3 A schematic flow chart of step S201 provided in an embodiment of the present invention;

[0014] Figure 4 An example diagram of a circular walking circle provided by an embodiment of the present invention;

[0015] Figure 5 An example diagram of constructing a polygonal area provided by an embodiment of the present invention;

[0016] Figure 6A schematic flow chart of step S203 provided in an embodiment of the present invention;

[0017] Figure 7 A schematic diagram of the distribution of polygonal areas provided by an embodiment of the present invention;

[0018] Figure 8 Another schematic flow chart of the detection point site selection method provided by the embodiment of the present invention;

[0019] Fig. 9 A schematic diagram of the distribution of the merged polygonal areas provided by an embodiment of the present invention;

[0020] Fig.10 A schematic diagram of point of interest data within a polygonal area provided by an embodiment of the present invention;

[0021] Fig.11 One of the magnified effect diagrams of the point of interest data within the polygonal area provided by the embodiment of the present invention;

[0022] Fig.12 The second magnified effect diagram of the point of interest data within the polygonal area provided by the embodiment of the present invention;

[0023] Fig.13 A functional module diagram of a detection point site selection device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0025] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0027] In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. appear to indicate an orientation or position relationship, they are based on the orientation or position relationship shown in the accompanying drawings, or are the orientation or position relationship in which the product of the invention is usually placed when used. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0028] In addition, the terms “first”, “second”, etc., if used, are merely used to distinguish between the descriptions and should not be understood as indicating or implying relative importance.

[0029] It should be noted that, in the absence of conflict, the features in the embodiments of the present invention may be combined with each other.

[0030] At present, in order to facilitate timely monitoring of residents' health status and understand their quality of life, convenient testing points can be set up in public areas of the city to detect residents' physical condition information, collect residents' life information or opinions. At the same time, convenient testing points can also provide testing personnel with a comfortable sampling working environment.

[0031] Usually, in terms of site selection for detection points, in order to meet detection needs, detection points can usually be set up in public areas. However, in terms of site selection, it is necessary to comprehensively consider the population flow in the public area and the daily load of the detection point. Therefore, an embodiment of the present invention provides a method for site selection for detection points.

[0032] First, see Figure 1 , Figure 1 The present invention also provides a schematic diagram of an electronic device, which is used to implement the detection point location selection method in the above embodiment. Figure 1 As shown, the electronic device 100 includes: a memory 101, a processor 102, a communication interface 103, and a bus 104. The memory 101, the processor 102, and the communication interface 103 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0033] Optionally, bus 104 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 1 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0034] In the embodiment of the present invention, the processor 102 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiment of the present invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiment of the present invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor. The software module may be located in the memory 101, and the processor 102 reads the program instructions in the memory 101 and completes the steps of the above method in combination with its hardware.

[0035] In the embodiment of the present invention, the memory 101 may be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), etc., or a volatile memory (volatile memory), such as a RAM. The memory may also be any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in the embodiment of the present invention may also be a circuit or any other device that can realize a storage function, for storing instructions and / or data.

[0036] The memory 101 can be used to store software programs and modules, such as the instructions / modules of the detection point address selection device 300 provided in the embodiment of the present invention, which can be stored in the memory 101 in the form of software or firmware or fixed in the operating system (OS) of the electronic device 100. The processor 102 executes various functional applications and data processing by executing the software programs and modules stored in the memory 101. The communication interface 103 can be used to communicate signaling or data with other node devices.

[0037] See also Figure 2 , Figure 2 A schematic flow chart of a detection point location selection method provided in an embodiment of the present invention. The execution subject of the method may be Figure 1 The electronic device shown, the method may include the following steps:

[0038] S201: Determine the target map grids whose adjacent distances of center coordinates are greater than or equal to a preset distance threshold based on the total daytime population corresponding to each map grid in the target study area; wherein the preset distance threshold is the distance that the user walks at a preset walking speed within the target walking time.

[0039] S202: constructing a plurality of polygonal areas within the target research area based on the target map grid; the polygonal areas represent the walking circle of the user, and the polygonal areas are continuous polygonal area ranges including the map grid.

[0040] S203: Determine the valid intersecting map grids corresponding to each polygonal area from the multiple map grids, and determine the population in each polygonal area based on the total daytime population of the valid intersecting map grids.

[0041] S204: Determine the demand for detection points in each polygonal area according to the population in each polygonal area and the maximum population detection quantity of a single detection point.

[0042] S206: For each polygonal area, based on the demand, determine the target interest point located in the polygonal area from all the interest points located in the target research area, and use the target interest point as the reference address of the detection point.

[0043] In the above detection point site selection method, first, according to the total daytime population corresponding to each map grid in the target study area, the target map grid whose adjacent distance of the center coordinate is greater than or equal to the preset distance threshold is determined; wherein the preset distance threshold is the distance walked by the user at the preset walking speed within the target walking time, and then multiple polygonal areas in the target study area are constructed based on the target map grid. Since the polygonal areas are seamlessly connected and there is no free space between each other, the reference address is subsequently determined in the points of interest within the polygonal area to avoid omission. After the polygonal area is constructed, the population in the polygonal area can be determined, and the demand for detection points in each polygonal area is determined in combination with the population and the maximum population detection amount of a single detection point. Finally, the target points of interest within the polygonal area are used as the reference position of the detection point. In the detection point site selection process, the embodiment of the present invention utilizes the regional characteristics of the polygonal area to avoid the omission of the points of interest and the impact on the detection point site selection. Furthermore, before the site selection, the population and the maximum population detection amount are comprehensively considered to accurately determine the demand for the detection point. Finally, the reference position of the detection point can be quickly determined from the points of interest in the polygonal area. The entire site selection process is efficient and can meet the detection needs.

[0044] The above steps will be described in detail below with reference to the relevant drawings.

[0045] In step S201, target map grids whose adjacent distances of center coordinates are greater than or equal to a preset distance threshold are determined according to the total daytime population corresponding to each map grid in the target study area.

[0046] Among them, the preset distance threshold is the maximum distance that the user walks within the preset walking time based on the preset walking speed. In the embodiment of the present invention, the purpose of arranging the detection points is to facilitate the public, so the point location can be selected within the walking circle that people can reach, so that anyone can reach the detection point in a short time at any location. Generally speaking, a detection point can be set according to 3,000 people and a 15-minute walking circle. Therefore, the embodiment of the present invention can first determine a distance threshold based on this setting requirement, that is, the maximum distance (for example, 1.5 kilometers) that the user walks within the preset walking time (for example, the above-mentioned 15 minutes) based on the preset walking speed (the average speed of people's normal walking, such as walking one hundred meters per minute), and then divide the appropriate walking circle in the map grid where the adjacent distance is greater than or equal to the preset distance threshold, which can just meet the setting requirements.

[0047] Therefore, the embodiment of the present invention can determine the walking circle that meets the detection requirements from the target map grids in the target research area whose adjacent distances are greater than or equal to the preset distance threshold based on the preset distance threshold.

[0048] In the embodiment of the present invention, the target research area may be a specific administrative region such as a certain province, a certain city or a certain country.

[0049] In the process of drawing the walking circle, the embodiment of the present invention is constructed based on the map grid in the target research area. The map grid is also called Geohash grid, which can improve the efficiency of constructing polygonal areas.

[0050] Geohash grid refers to the use of the geohash algorithm to encode the geographical location of a certain area or the entire map according to the Geohash code, which will result in a grid, that is, a geohash grid. Geohash is an address code that can encode two-dimensional longitude and latitude into a one-dimensional string. The finer the recursive granularity of the code, the smaller the rectangular area of ​​the grid, and the longer the length of the geohash code, the more accurate the Geohash code. The accuracy of the generated grid and the actual geography for different code lengths is as follows (the length of the Geohash string code corresponds to the grid size).

[0051] Therefore, before executing step S201, the embodiment of the present invention can first divide the target study area to obtain multiple map grids corresponding to the target study area. It is also noted that in the process of determining the population of the polygonal area, it is determined based on the total daytime population of the map grid. Therefore, after determining the map grid, the total daytime population in each map grid can also be determined. Therefore, before executing step S201, the following steps can be performed:

[0052] a1: Divide the target research area into multiple map grids.

[0053] In an embodiment of the present invention, the map of the target study area can be pre-divided into multiple grids, and the grid division can adopt the GeoHash algorithm, which is essentially a way of spatial indexing. Its basic principle is to understand the earth as a two-dimensional plane, and recursively decompose the plane into smaller sub-blocks, each of which has the same code within a certain latitude and longitude range. Depending on the accuracy, the segmentation level of GeoHash is generally 1 to 12 levels, where 1 to 12 represents the length of the string of the grid code. The larger the length, the higher the accuracy. The embodiment of the present invention can adopt different segmentation levels according to actual needs. For example, a 7-level GeoHash segmentation level is adopted, that is, the string length is 7.

[0054] For example, if the target research area is China, a nationwide grid can be established with a longitude range of 73.0 degrees east to 135.1 degrees east longitude and a latitude range of 3.5 degrees north to 53.5 degrees north latitude. The grid side is about 150 meters long. The national grids can be numbered in order from east to west and from north to south. Use R-tree index to create indexes for spatial data to improve query efficiency.

[0055] a2: Obtain signaling data within the target study area and within the target time period.

[0056] It is understandable that the communication data between the mobile phone user and the transmitting base station or micro station begins to be generated as long as the user uses the mobile phone and the operator's words are displayed on the mobile phone screen. Mobile phone signaling is a control instruction in the communication system that can guide the terminal, switching system and transmission system to operate in coordination, establish a temporary communication channel between designated terminals, and maintain the normal operation of the network itself. The data packet will contain the latitude and longitude information of the mobile phone's location.

[0057] a3: Based on the location information of all signaling data, the number of users corresponding to the signaling data whose location information is within the map grid and whose residence time within the map grid is greater than or equal to the preset time is determined as the total daytime population of the map grid.

[0058] In the embodiment of the present invention, the location information refers to the latitude and longitude of the signaling data, and the total daytime population can be the total daytime population, wherein the user can define the daytime duration according to actual needs, for example, the time period between 7 am and 19 pm can be defined as daytime. The above-mentioned residence duration can be set according to actual needs, for example, the residence duration can be set to 3 hours, which is not limited here.

[0059] During the implementation process, for each map grid, the longitude and latitude of the map grid and the mobile phone signaling data packet can be intersected according to the four longitudes and latitudes connected end to end in the Geohash grid using the database's own intersection function to obtain the signaling data located in the map grid. Then, based on the time information of the signaling data, the signaling data whose residence time in the map grid is greater than or equal to the preset time can be determined, and the number of users corresponding to these signaling data is recorded as the total daytime population.

[0060] After obtaining the map grids and the total daily population corresponding to each map grid, step S201 in the embodiment of the present invention can be executed. The following is an implementation method for determining the target map grid. Figure 3 , Figure 3 A schematic flow chart of step S201 provided in an embodiment of the present invention:

[0061] S201-1: Create a temporary table, and write the map grid corresponding to the maximum daytime total population as the target map grid into the temporary table.

[0062] S201-2: For each map grid except the map grid corresponding to the maximum daytime total population, calculate the adjacent distance between the center coordinate of the map grid and the center coordinate of each target map grid in the temporary table in descending order of the daytime total population;

[0063] S201 - 3 : If the adjacent distance is greater than or equal to the preset distance threshold, the map grid corresponding to the adjacent distance is written into the temporary table as the target map grid.

[0064] S201-4: If the adjacent distance is less than a preset distance threshold, the map grid corresponding to the adjacent distance is discarded.

[0065] To facilitate understanding of the above implementation, it is assumed that there are target map grids G1 to G10. For ease of execution, G1 to G10 can be first arranged in descending or ascending order according to the total daytime population. The embodiment of the present invention takes descending order as an example. The sorted target map grids are assumed to be G10>G9>...>G2>G1. An empty temporary table is created, and then G10 is written into the temporary table as the first target map grid. Then, the adjacent distance between the center coordinates of G9 and the center coordinates of G10 is compared to see whether it is greater than 1.5 kilometers. If so, G9 is written into the temporary table. At this time, two target map grids G9 and G10 already exist in the temporary table. Then, the adjacent distance between the center coordinates of G8 and the center coordinates of G9 and G10 is compared to see whether it is greater than or equal to 1.5 kilometers. If so, G8 is written into the temporary table. If not, G8 is discarded, and so on, until G1 is compared. At this time, the adjacent distance between any two map grids in the temporary table is greater than or equal to 1.5 kilometers.

[0066] After obtaining the target map grid, a circular walking circle that meets the layout requirements can be obtained by taking the center coordinates of each target map grid as the origin and drawing a circle with a radius of half the length of the preset distance, such as Figure 4 As shown, Figure 4 An example diagram of a circular walking circle provided by an embodiment of the present invention, from Figure 4 It can be seen that there is still a part of blank area between the circles that has not been taken into consideration, so the location selection based on this walking circle is relatively inaccurate. In order to make use of the above blank area, the embodiment of the present invention uses a polygonal area to represent the user's walking circle. Since the polygonal areas can be seamlessly connected with each other and there is very little free space between them, the situation where there is too much blank space between the circular walking circles is avoided. Therefore, in step S202, the embodiment of the present invention constructs a new walking circle, namely a polygonal area, based on the determined target map grid.

[0067] In step S202, based on the target map grid, multiple polygonal areas are constructed within the target research area; the polygonal areas represent the user's walking circle.

[0068] With respect to the above step S202, an embodiment of the present invention provides an implementation method, that is, step S202 may include the following steps:

[0069] a1: Determine the adjacent map grids corresponding to each target map grid;

[0070] a2: Construct multiple triangular areas based on the center coordinates of each map grid and the corresponding center coordinates of each adjacent map grid.

[0071] a2: Connect the intersection points of the perpendicular bisectors of each side of each triangular area to obtain a polygonal area.

[0072] In an embodiment of the present invention, the setting requirements of each detection point are taken into consideration. For example, a detection point can usually be set according to 3,000 people and a 15-minute walking circle. Therefore, in the process of constructing the polygonal area, the spacing between each map grid can be fully considered to ensure seamless connection between polygonal areas.

[0073] To facilitate understanding of the above steps a1 to a2, please refer to Figure 5 , Figure 5 An example diagram of constructing a polygonal area provided by an embodiment of the present invention.

[0074] like Figure 5As shown, there are 7 target map grids, among which the adjacent target map grids of target map grid 1 are target map grids 2-6. The center coordinates of each target map grid are connected to obtain 6 triangular areas. For each triangular area, each side can be vertically bisected to obtain the perpendicular bisectors of each side. The perpendicular bisectors of each side finally intersect at one point. The intersection points of these perpendicular bisectors are connected to obtain a polygonal area. For each target map grid, a polygonal area can be obtained in the above manner. In the above manner, a seamlessly connected polygonal area is finally obtained.

[0075] from Figure 5 It can be seen that Figure 5 A polygon is constructed by one of the target map grids and its multiple adjacent target map grids. Each target map grid can find its corresponding adjacent map grid. Then, if there are common edges between the triangular areas constructed between each target map grid and the adjacent map grids, the polygon finally constructed also has common edges, such as Figure 6 As shown, Figure 6 The distribution diagram of the polygonal areas provided in the embodiment of the present invention shows that the polygonal areas obtained by the above implementation method can be evenly distributed on the map of the target research area, and multiple polygons can be closely connected with very little free space between each other, thus avoiding the situation where too much blank space is left between the circular walking circles.

[0076] In step S203, the valid intersecting map grids corresponding to each polygonal area are determined from the plurality of map grids, and the population in each polygonal area is determined based on the total daytime population of the valid intersecting map grids.

[0077] In the embodiment of the present invention, the valid intersecting map grids corresponding to each polygonal area may be determined first, and then the sum of the target statistical population corresponding to each of the valid intersecting map grids may be used as the population of each polygonal area.

[0078] In the embodiment of the present invention, a valid intersecting map grid is a map grid that intersects with a polygon and whose center coordinates are within the polygon area, wherein the intersection includes: the map grid is within the polygon area, and the map grid and the polygon area partially overlap.

[0079] As an optional implementation, the effective intersection map grid with the polygonal area can be calculated by, but is not limited to, the spatial algorithm ST_Intersection(geom,geom).

[0080] Continue to see Figure 5, the target map grid 1, map grids 8 and 9 are all located within the polygonal area, and map grids 10 and 11 partially overlap with the polygonal area. Then the target map grid 1, map grids 8 and 9 are all valid intersecting map grids. If the center coordinates of map grids 10 and 11 are within the polygonal area, they are valid intersecting map grids. If they are not within the polygonal area, they are not valid intersecting map grids.

[0081] Therefore, the implementation of the above step S203 can refer to Figure 7 , Figure 7 The schematic flow chart of step S203 provided in the embodiment of the present invention may include the following steps:

[0082] S203-1: for each polygonal area, determine from all map grids that the map grids that have overlapping areas with the polygonal area and whose center coordinates are located within the polygonal area are valid intersecting map grids;

[0083] S203-2: The sum of the total daytime population corresponding to all valid intersecting map grids is taken as the population in the polygonal area.

[0084] After determining the population of each polygonal area, the number of detection points required in each polygonal area can be determined based on the maximum detection population data of the detection points. In this way, the set detection points can meet the detection needs of the polygonal area.

[0085] In step S204, the demand for detection points in each polygonal area is determined according to the population in each polygonal area and the maximum population detection quantity of a single detection point.

[0086] In the embodiment of the present invention, the quotient obtained by dividing the population by the maximum population detection amount is used as the demand.

[0087] In an optional implementation, in actual situations, due to the uneven distribution of population density in the polygon area, the number of people in the polygon area does not meet the single-day load. In this case, the polygons need to be merged. Therefore, please refer to Figure 8 , Figure 8 Another schematic flow chart of the detection point site selection method provided by the embodiment of the present invention, after step S204, the following steps may also be performed:

[0088] S205: Merge polygonal areas where the population is less than the maximum population detection amount.

[0089] In an embodiment of the present invention, if the population size within a polygonal area is less than the maximum population detection value of a single point, adjacent polygons of the polygonal area can be found, and then the adjacent polygons that do not satisfy the requirement that the population size is less than the maximum population detection value of a single point can be merged with the polygonal area.

[0090] As an optional implementation, the above step S205 may be performed as follows:

[0091] c1: For each polygonal area, if the population is less than the maximum population detection amount, determine the adjacent polygonal areas of the polygonal area.

[0092] As an optional implementation, the adjacent polygonal areas corresponding to each polygonal area may be calculated by using the spatial algorithm ST_Touches(geometry, geometry).

[0093] c2: If there is an adjacent polygonal area whose population is less than the maximum population detection amount, the polygonal area is merged with the adjacent polygonal area;

[0094] c3: When the population of the polygon area is greater than or equal to the maximum population detection, stop merging.

[0095] For example, assuming that the population of a certain polygonal area A is less than the maximum population detection amount, it is determined that there are two adjacent polygonal areas B and C in the polygonal area.

[0096] Case 1: If the populations of adjacent polygonal areas B and C are both greater than or equal to the maximum population detection, A is not considered.

[0097] Case 2: If the population of B and C are both less than the maximum population detection, then one of the adjacent polygonal areas (B or C) can be merged with A to obtain the merged polygonal area (assuming it is AB). If the population of AB is still less than the maximum population detection, continue to merge AB and C. If the population of AB is greater than or equal to the maximum population detection, no further merging will be performed and AB is the final polygon.

[0098] Case 3: If the population of only one of the adjacent polygonal areas among B and C is less than the maximum population detection value, then this adjacent polygonal area will be merged with A.

[0099] Through the above implementation Figure 6 The polygonal areas shown are merged to obtain Fig. 9 The merged polygons shown can ensure that the population in each polygon area meets the daily load. Based on the merged polygon areas, step S206 can be executed.

[0100] In step S205, for each polygonal area, based on the demand, a target point of interest located in the polygonal area is determined from all points of interest located in the target research area, and the target point of interest is used as a reference address of the detection point.

[0101] In the embodiment of the present invention, a point of interest (POI), also known as an information point, is a term in a geographic information system, and generally refers to all geographical objects that can be abstracted as points, especially some geographical entities that are closely related to people's lives, such as schools, banks, restaurants, gas stations, hospitals, supermarkets, etc. Fig.10 As shown, Fig.10 A schematic diagram of point of interest data within a polygonal area provided by an embodiment of the present invention, Fig.11 and Fig.12 They are Fig.10 The enlarged effect diagram.

[0102] As an optional implementation, the point data of interest in the target study area can be acquired in advance, such as by purchasing it from a map service provider or obtaining it from public map service information. The acquired point data of interest can add a B-tree index according to the point category to increase the subsequent query speed.

[0103] As an optional implementation, the above step S206 may be performed as follows:

[0104] d1: Determine a first target interest point whose adjacent distance is greater than a first preset distance from the candidate interest points located within the polygonal area.

[0105] In the embodiment of the present invention, the interest points intersecting with the polygon may be calculated using, but not limited to, the spatial algorithm ST_Contains (geometryA, geometryB) as candidate interest points.

[0106] d2: if the number of the first target POIs is less than the required number, determine the number of remaining target POIs;

[0107] d3: From the remaining candidate interest points except the first target interest point, determine the second target interest point whose adjacent distance is greater than the second preset distance, and use the first target interest point and the first target interest point as the reference address of the detection point, wherein the first preset distance is greater than the second preset distance.

[0108] In an embodiment of the present invention, a target point of interest is determined from candidate points of interest based on two conditions: demand and distance between the points. Therefore, an embodiment of the present invention provides two distance thresholds, namely a first preset distance and a second preset distance, wherein the first preset distance is greater than the second preset distance, and the judgment priority of the first preset distance is greater than the second preset distance.

[0109] For example, assuming that the first preset distance is 200 meters and the second preset distance is 100 meters, then the embodiment of the present invention first selects the candidate interest points with an adjacent distance greater than 200 meters from the candidate interest points as the target interest points. If the number of candidate interest points with an adjacent distance greater than 200 meters does not meet the demand, the remaining demand is then determined, and then the candidate interest points with an adjacent distance greater than 200 meters can be selected from the remaining candidate interest points as the target interest points.

[0110] The first target interest point and the second target interest point determined by the above implementation are both reference positions of the detection point in the embodiment of the present invention.

[0111] Based on the same inventive concept, the embodiment of the present invention also provides a detection point location selection device, see Fig.13 , Fig.13 This is a functional module diagram of the detection point site selection device provided in an embodiment of the present invention. The detection point site selection device 300 can be stored in the operating system (OS) of the electronic device 100 in the form of software or firmware.

[0112] like Fig.13 As shown, the detection point site selection device 300 provided in the embodiment of the present invention may include: a determination module 310 , a construction module 310 , a determination module 310 and a site selection module 330 .

[0113] The determination module 310 is used to determine the target map grids whose adjacent distances of the center coordinates are greater than or equal to a preset distance threshold based on the total daytime population corresponding to each map grid in the target study area; wherein the preset distance threshold is the maximum distance a user can walk within a predetermined walking time based on a preset walking speed.

[0114] A construction module 320 is used to construct a plurality of polygonal areas within the target research area based on the target map grid; the polygonal areas represent the walking circle of the user, and the polygonal areas are continuous polygonal area ranges including the map grid;

[0115] A determination module 310 is used to determine the valid intersecting map grid corresponding to each polygonal area from the plurality of map grids, and determine the population in each polygonal area based on the total daytime population of the valid intersecting map grids;

[0116] A determination module 310 is used to determine the demand for detection points in each polygonal area according to the population in each polygonal area and the maximum population detection quantity of a single detection point;

[0117] The site selection module 330 is used to determine the target interest points within each polygonal area from all the interest points within the target research area based on the demand, and determine the reference address of the detection point based on the target interest points and the walking circle.

[0118] It is understandable that the construction module 320, the determination module 310 and the site selection module 330 can be executed in coordination. Figure 2 Each step in the process is performed to achieve the corresponding technical effect.

[0119] In an optional implementation, the detection point site selection device 300 may further include a merging module for merging polygonal areas whose population is less than the maximum population detection amount.

[0120] In an optional embodiment, the merging module is specifically used to: for each polygonal area, if the population size is less than the maximum population detection amount, determine the adjacent polygonal areas of the polygonal area; if there is an adjacent polygonal area with a population size less than the maximum population detection amount, merge the polygonal area with the adjacent polygonal area; when the population size of the polygonal area is greater than or equal to the maximum population detection amount, stop merging.

[0121] In an optional embodiment, the determination module 310 is specifically used to: for each polygonal area, determine from all map grids that the map grids that overlap with the polygonal area and whose center coordinates are located within the polygonal area are valid intersecting map grids; and take the sum of the total daytime population corresponding to all valid intersecting map grids as the population within the polygonal area.

[0122] In an optional embodiment, the site selection module 330 is specifically used to: determine a first target interest point whose adjacent distance is greater than a first preset distance from candidate interest points located in the polygonal area; if the number of first target interest points is less than the demand, determine the remaining number of target interest points; determine a second target interest point whose adjacent distance is greater than a second preset distance from the remaining candidate interest points other than the first target interest point, and use the first target interest point and the first target interest point as reference addresses of the detection point, wherein the first preset distance is greater than the second preset distance.

[0123] In an optional implementation, the determination module 310 is specifically used to: create a temporary table, and write the map grid corresponding to the maximum daytime total population as the target map grid into the temporary table; for each map grid except the map grid corresponding to the maximum daytime total population, calculate the adjacent distance between the center coordinates of the map grid and the center coordinates of each target map grid in the temporary table in descending order of the daytime total population; if the adjacent distance is greater than or equal to a preset distance threshold, write the map grid corresponding to the adjacent distance into the temporary table as the target map grid; if the adjacent distance is less than the preset distance threshold, discard the map grid corresponding to the adjacent distance.

[0124] In an optional embodiment, the detection point site selection device 300 may also include a division module and an acquisition module; the division module is used to divide the target study area into multiple map grids; the acquisition module is used to obtain signaling data within the target study area within a target time period; the determination module 310 is also used to determine the number of users corresponding to the signaling data whose location information is located within the map grid and whose residence time within the map grid is greater than or equal to a preset time as the total daytime population of the map grid based on the location information of all signaling data.

[0125] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A detection point site selection method, characterized in that: The method comprises: According to the total daytime population corresponding to each map grid in the target study area, determine the target map grid whose adjacent distance of the center coordinate is greater than or equal to a preset distance threshold; wherein the preset distance threshold is the maximum distance that a user can walk within a predetermined walking time based on a preset walking speed; Based on the target map grid, construct multiple polygonal areas within the target research area, including: determining the adjacent map grids corresponding to each target map grid, constructing multiple triangular areas according to the central coordinates of each map grid and the central coordinates corresponding to each adjacent map grid, connecting the intersection points of the perpendicular bisectors of each side of each triangular area to obtain the polygonal area; the polygonal area represents the walking circle of the user; the polygonal area is a continuous polygonal area range containing the map grid; Determine a valid intersecting map grid corresponding to each polygonal area from the plurality of map grids, and determine the population in each polygonal area based on the total daytime population of the valid intersecting map grids; Determine the demand for the detection points in each of the polygonal areas according to the population in each of the polygonal areas and the maximum population detection quantity of a single detection point; For each of the polygonal areas, based on the demand, a target point of interest located in the polygonal area is determined from all points of interest located in the target research area, and the target point of interest is used as a reference address of the detection point.

2. The method according to claim 1, characterized in that Before determining the demand for the detection points in each of the polygonal areas according to the population in each of the polygonal areas and the maximum population detection quantity of a single detection point, the method further includes: The polygonal areas where the population is less than the maximum population detection amount are merged.

3. The method according to claim 1, characterized in that Determining valid intersecting map grids corresponding to the polygonal area from the plurality of map grids, and determining the population in each polygonal area based on the total daytime population of the valid intersecting map grids, including: For each polygonal area, from all the map grids, determine the map grids that have overlapping areas with the polygonal area and whose center coordinates are located within the polygonal area as the valid intersecting map grids; The sum of the total daytime population corresponding to all the valid intersecting map grids is taken as the population within the polygonal area.

4. The method according to claim 1, characterized in that For each polygonal area, based on the demand, a target point of interest located in the polygonal area is determined from all points of interest located in the target research area, and the target point of interest is used as a reference address of the detection point, including: Determining, from the candidate interest points located within the polygonal area, a first target interest point whose adjacent distance is greater than a first preset distance; If the number of the first target points of interest is less than the required number, determining the number of remaining target points of interest; From the remaining candidate interest points except the first target interest point, determine the second target interest point whose adjacent distance is greater than the second preset distance, and use the first target interest point and the first target interest point as reference addresses of the detection point, wherein the first preset distance is greater than the second preset distance.

5. The method according to claim 1, characterized in that According to the total daytime population corresponding to each map grid in the target study area, the target map grids whose adjacent distances of the center coordinates are greater than or equal to the preset distance threshold are determined, including: Create a temporary table, and write the map grid corresponding to the maximum daytime total population as the target map grid into the temporary table; For each of the map grids except the map grid corresponding to the maximum daytime total population, calculate the adjacent distance between the center coordinate of the map grid and the center coordinate of each of the target map grids in the temporary table in descending order of the daytime total population; If the adjacent distance is greater than or equal to the preset distance threshold, writing the map grid corresponding to the adjacent distance as the target map grid into the temporary table; If the adjacent distance is less than the preset distance threshold, the map grid corresponding to the adjacent distance is discarded.

6. The method according to claim 2, characterized in that Merging the polygonal areas where the population is less than the maximum population detection amount comprises: For each of the polygonal areas, if the population is less than the maximum population detection amount, determine the adjacent polygonal areas of the polygonal area; If there is an adjacent polygonal area whose population is less than the maximum population detection amount, merging the polygonal area with the adjacent polygonal area; When the population of the polygonal area is greater than or equal to the maximum population detection amount, the merging is stopped.

7. The method according to claim 1, characterized in that Before constructing a plurality of polygonal areas within the target study area, the method further includes: Dividing the target research area to obtain a plurality of map grids; Acquire signaling data within a target time period in the target study area; Based on the location information of all the signaling data, the number of users corresponding to the signaling data whose location information is located in the map grid and whose residence time in the map grid is greater than or equal to the preset time is determined as the total daytime population of the map grid.

8. A detection point site selection device, characterized in that: include: A determination module is used to determine, based on the total daytime population corresponding to each map grid in the target study area, target map grids whose adjacent distances of center coordinates are greater than or equal to a preset distance threshold; wherein the preset distance threshold is a maximum distance that a user can walk within a predetermined walking time based on a preset walking speed; A construction module is used to construct multiple polygonal areas within the target research area based on the target map grid, including: determining the adjacent map grids corresponding to each target map grid, constructing multiple triangular areas according to the central coordinates of each map grid and the central coordinates corresponding to each adjacent map grid, and connecting the intersection points of the perpendicular bisectors of each side of each triangular area to obtain the polygonal area; the polygonal area represents the walking circle of the user; the polygonal area is a continuous polygonal area range containing the map grid; The determination module is used to determine the valid intersecting map grid corresponding to each polygonal area from the plurality of map grids, and determine the population in each polygonal area based on the total daytime population of the valid intersecting map grids; The determination module is used to determine the demand for the detection points in each of the polygonal areas according to the population in each of the polygonal areas and the maximum population detection quantity of a single detection point; A site selection module is used to determine, for each polygonal area, a target point of interest located in the polygonal area from all points of interest located in the target research area based on the demand, and use the target point of interest as a reference address of the detection point.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor can execute the computer program to implement the method according to any one of claims 1 to 7.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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