CN113660623A - Boundary identification method based on mobile phone signaling and related device - Google Patents
Boundary identification method based on mobile phone signaling and related device Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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Abstract
The invention relates to the technical field of big data, and provides a boundary identification method and a related device based on mobile phone signaling, wherein a preset area is divided into a plurality of grids in advance, and the method comprises the following steps: acquiring first data and second data, wherein the first data is acquired at a plurality of preset position points in a preset area, and the second data comprises boundary characteristic data of each grid in a plurality of grids; determining a first boundary of a region to be identified in a preset region according to the first data; determining a second boundary of the area to be identified in the preset area according to the second data; and determining the final boundary of the region to be identified in the preset region according to the first boundary and the second boundary. The invention comprehensively considers various factors influencing boundary identification, realizes accurate identification of the boundary of the region, and can greatly assist in monitoring and management of the region.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a boundary identification method based on mobile phone signaling and a related device.
Background
At present, along with the rapid development of urbanization, the boundaries of cities are also expanding. However, the problem of asynchronous land urbanization and population urbanization is gradually highlighted, and the phenomenon of 'spreading big cakes' in cities is more and more serious. The urban boundary gradually becomes an important hand for planning, managing and monitoring of urban administrative departments, however, the boundary aiming at the actual development status is difficult to accurately define, and becomes a main obstacle in actual monitoring and managing.
Disclosure of Invention
The invention aims to provide a boundary identification method based on mobile phone signaling and a related device, which can accurately identify the boundary of an area and greatly assist in monitoring and managing the area.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides a boundary identification method based on a mobile phone signaling, where a preset area is pre-divided into multiple grids, and the method includes: acquiring first data and second data, wherein the first data is acquired at a plurality of preset position points in the preset area, and the second data comprises boundary characteristic data of each grid in the plurality of grids; determining a first boundary of a region to be identified in the preset region according to the first data; determining a second boundary of the area to be identified in the preset area according to the second data; and determining the final boundary of the region to be identified in the preset region according to the first boundary and the second boundary.
In a second aspect, the present invention provides a boundary identification apparatus based on mobile phone signaling, where a preset area is pre-divided into a plurality of grids, and the apparatus includes: an obtaining module, configured to obtain first data and second data, where the first data is obtained at a plurality of preset location points in the preset area, and the second data includes boundary feature data of each of the plurality of grids; the determining module is used for determining a first boundary of a region to be identified in the preset region according to the first data; the determining module is further configured to determine a second boundary of the to-be-identified area in the preset area according to the second data; and the determining module is further used for determining a final boundary of the region to be identified in the preset region according to the first boundary and the second boundary.
In a third aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the boundary identification method based on mobile phone signaling as described above when executing the computer program.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the above-mentioned boundary identification method based on cell phone signaling.
Compared with the prior art, the method and the device have the advantages that the first boundary of the preset area is determined according to the first data acquired from the multiple preset position points in the preset area, the second boundary of the preset area is determined according to the boundary characteristic data of each grid in the multiple grids, the final boundary of the preset area is determined according to the first boundary and the second boundary, the first data (point location type data) and the second data (surface type data of the boundary characteristics) of the preset position points are combined, multiple factors influencing boundary identification are comprehensively considered, the boundary of the area is accurately identified, and monitoring and management of the area can be greatly assisted.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart illustrating a boundary identification method based on a mobile phone signaling according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention.
Fig. 4 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention.
Fig. 5 is an exemplary graph of a density variation curve provided by an embodiment of the invention.
Fig. 6 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention.
Fig. 7 is an exemplary diagram of a boundary corresponding to the point of interest data in the first boundary according to the embodiment of the present invention.
Fig. 8 is an exemplary diagram of a boundary corresponding to the mobile phone signaling data in the first boundary according to the embodiment of the present invention.
Fig. 9 is an exemplary diagram of a second boundary provided by the embodiment of the invention.
FIG. 10 is an exemplary diagram of the final boundary provided by an embodiment of the present invention.
Fig. 11 is a block diagram of a boundary identification apparatus based on mobile phone signaling according to an embodiment of the present invention.
Fig. 12 is a block diagram of a computer device according to an embodiment of the present invention.
Icon: 10-a computer device; 11-a processor; 12-a memory; 13-a bus; 14-a communication interface; 100-boundary identification device based on mobile phone signaling; 110-an obtaining module; 120-determination module.
Detailed Description
In order to make the objects, 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 with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. indicate an orientation or a positional relationship based on that shown in the drawings or that the product of the present invention is used as it is, this is only for convenience of description and simplification of the description, and it does not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention.
Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.
With the rapid development of computer technology, methods for determining the boundary of a central area of a city by using spatio-temporal data have been developed in recent years, mainly covering the following angles:
(1) remote sensing image extraction is adopted, and urban construction land and non-construction land are distinguished through image calibration, interpretation and the like, so that the boundary range of the urban center area is determined.
(2) And (4) extracting a night light image, and determining the boundary range of the central area of the city according to the change of the light brightness.
(3) And gradually searching and determining the boundary range of the urban central area by adopting road network data and road network grades.
(4) And setting a threshold value through grid statistics by adopting taxi taking service data to finally obtain the boundary range of the urban central area.
The above-described method mainly has the following problems:
(1) with a single data source, the characteristics of the different data sources result in inconsistent determined boundaries.
(2) The determination mode based on the remote sensing image and the road network data causes the proportion of the infrastructure indexes to be too heavy, and the mode can cause misjudgment for the urban central area with the empty city.
In addition to the above problems, the inventor has also found that remote sensing images, light images, road network data and taxi service data all belong to data within a preset area range, also called face type data, for face type data, the face type data is easily divided according to grids and processed according to grid units, so as to determine a boundary range according to a processing result, and besides the face type data, other data are also one of indispensable considerations, for example, mobile phone signaling data or interest point data which embody actual activities of people, the data are acquired at preset position points and belong to point type data, and how to combine the face type data and the point type data is a major technical difficulty in comprehensively utilizing multiple data sources to determine boundaries.
In view of this, embodiments of the present application provide a boundary identification method and a related apparatus based on a mobile phone signaling, which combine point location type data and surface type data of boundary features, implement boundary identification using multiple data sources, implement accurate identification of a boundary of an area, and greatly assist in monitoring and managing the area, which will be described in detail below.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for identifying a boundary based on a mobile phone signaling according to an embodiment of the present invention, where the method includes the following steps:
step S100, first data and second data are obtained, where the first data is obtained at a plurality of preset position points in a preset area, and the second data includes boundary feature data of each of a plurality of grids.
In this embodiment, the first data is point type data, such as mobile phone signaling data acquired from a base station, microblog data including a microblog message sending position, and the like, and the second data is surface type data, also referred to as grid surface data or grid surface data, such as lighting brightness in each grid.
In this embodiment, the preset location Point may include a base station, where the first data may include mobile phone signaling data, the preset location Point may further include a location of a Point of Interest (POI), and the first data may further include the number of the POI, where it is to be noted that the first data may include only the mobile phone signaling data, may also include only the number of the POI, and may also include both the mobile phone signaling data and the number of the POI.
As a specific implementation manner, in order to avoid interference caused by noise data in the first data, the first data may be cleaned in advance, for example, when the first data includes cell phone signaling data, the data with ping-pong handover is processed, for a user X in a cross coverage area of a base station a and a base station B, there is an obvious ping-pong handover in the cell phone signaling data, that is, the cell phone network connects to the base station a for a period of time, and connects to the base station B for another period of time, resulting in signaling data that occurs at A, B base station with short-time high frequency, for this case, the cell phone signaling data of the user X may only retain the signaling data generated by the base station with high frequency according to the frequency of the connection with the base stations a and B. When the first data includes the number of points of interest, the points of interest of the same feature may be merged, for example, if the feature is a building, the levels 1, 2, and 3 of the building are office areas of company a, and the levels 4 and 5 of the building are office areas of company B, the number of points of interest of the building is 3 (i.e., the building itself, company a, and company B).
Similarly, in order to avoid interference caused by noise data in the second data, the second data may be previously cleaned, for example, the second data is lighting brightness data, and abnormal lighting brightness data in an area such as an airport and a bonfire tower needs to be removed when identifying a central area of a city.
Step S110, determining a first boundary of a region to be identified in the preset region according to the first data.
In this embodiment, as a specific implementation, the first data may be first converted from point location type data into surface type data, for example, the first data obtained from the preset location point is dispersed in the preset area, so that the surface type data is formed, and then the boundary is determined according to the same processing manner as the second data, so that the determining manners of the first boundary and the second boundary determined according to the second data are more uniform, and the final boundary of the preset area is more easily determined according to the first boundary and the second boundary.
In this embodiment, the area to be identified in the preset area refers to an area of a specified type in the preset area, for example, the area to be identified may be a city central area in the preset area, or may be a non-city central area in the preset area.
Step S120, determining a second boundary of the to-be-identified region in the preset region according to the second data.
In this embodiment, as a specific implementation manner, the second boundary of the preset area may be determined according to a density variation condition of the second data in the preset area, for example, taking the area to be identified as an urban central area, taking a sub-area in the preset area, of which the density variation satisfies a preset condition, as the urban central area, and taking the remaining sub-areas, of which the density variation does not satisfy the preset condition, as a non-urban central area, thereby obtaining the second boundary of the urban central area in the preset area.
Step S130, determining a final boundary of the to-be-identified region in the preset region according to the first boundary and the second boundary.
In this embodiment, because the first boundary and the second boundary are based on different data sources, the first boundary and the second boundary are different, as a specific implementation manner, the final boundary of the region to be identified in the predetermined region may be obtained by fusing the first boundary and the second boundary, and according to actual needs, the fusion manner may use an intersection of the first boundary and the second boundary, or a union of the first boundary and the second boundary as the final boundary.
According to the method provided by the embodiment, the first data and the second data are combined, and various factors influencing boundary identification are comprehensively considered, so that the boundary of the area is accurately identified, and the monitoring and management of the area can be greatly assisted.
Referring to fig. 2, fig. 2 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention, where step S110 includes the following sub-steps:
substep S1101, allocating the first data to a plurality of grids to obtain grid data of each grid, wherein a set of all grid data is equal to the first data.
In this embodiment, for example, the preset area is divided into 9 grids in advance: a11 to A33, as shown in Table 1.
TABLE 1
| A11 | A12 | A13 |
| A21 | A22 | A23 |
| A31 | A32 | A33 |
Taking any one preset position point 1 as an example, the preset position point 1 is located in the a22 grid (A3 × 3 grid is formed with the preset position point as the center), the first data is 7, which indicates that there are 7 users, and the values assigned to each grid after the first data is assigned to a11 to a33 are shown in table 2.
TABLE 2
| 0 | 1 | 0 |
| 1 | 3 | 1 |
| 0 | 1 | 0 |
In table 2, the grid closer to the preset position point 1 has the larger number of users assigned thereto, and it should be noted that table 2 is only one specific assignment method, and other assignment methods may be determined according to actual scenes. For example, the number of the preset positions in the preset range of point 1 is the same, and the number of the preset positions outside the preset range is set to 0.
In this embodiment, this way of distributing the first data to the plurality of grids is also referred to as a kernel density implementation, and this implementation needs to select appropriate parameters, which are used to characterize the distribution principle or the distribution way, and the parameters may include the grid size, the radius of the data radiation, and the like.
And a substep S1102, determining a mutation threshold according to all the grid data, wherein the mutation threshold is used for representing that the density change of the grid data meets a preset condition.
In this embodiment, the density of the mesh data may be a ratio of the mesh data to the corresponding mesh area, and the mesh data value may also be directly used on the premise that the mesh sizes are consistent.
And a substep S1103 of dividing the plurality of grids according to the mutation threshold to obtain a first boundary.
In this embodiment, as a specific implementation manner, a grid with grid data greater than a mutation threshold is determined as a to-be-identified area, and a grid with grid data less than or equal to the mutation threshold is determined as another area, so that a first boundary can be obtained, taking the to-be-identified area as a city central area as an example, if the first data is mobile phone signaling data, population density is relatively large for the city central area, and thus the embodied mobile phone signaling data density is obviously also relatively high, and mobile phone signaling data density of a non-city central area is relatively low, if the first mobile phone is interest point data, interest point data density of the city central area is relatively high, and interest point data density of the non-city central area is relatively low, so that the first boundary of the city central area can be obtained, and the boundary of the non-city central area can also be considered to be obtained.
In the method provided by this embodiment, the first data serving as the point location type data is converted into the plane type data by allocating the first data to the multiple grids, so that the first boundary determined according to the converted plane type data and the second boundary determined by the same plane type data are easier to merge.
On the basis of fig. 2, an embodiment of the present invention further provides a specific implementation manner for obtaining grid data of each grid, please refer to fig. 3, fig. 3 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention, and sub-step S1101 includes the following sub-steps:
in the sub-step S11010, a target grid among a plurality of grids covered by each preset location point service range is obtained.
In this embodiment, the first data includes point location data obtained by each preset location point, and in order to reasonably allocate the point location data of each preset location point, the point location data is allocated according to a grid covered by a service range of each preset location point, and the point location data of each preset location point is allocated only in a target grid covered by the service range of the preset location point. For example, if the mesh covered by the base station 1 is A, B, C, the point location data acquired from the base station a is only allocated to the mesh A, B, C, and is not allocated to other meshes.
In the substep S11011, the point location data of each preset location point is allocated to the target grid of each preset location point, and finally, the grid data of each grid is obtained.
In this embodiment, if two preset location points cover the same grid, the data allocated to the grid by the two preset location points may be summed. For example, if the preset location point 1 covers the grid A, B, C, the allocated point location data are 20, 15, and 10, respectively, the preset location point 2 covers the grid C, D, E, and the allocated point location data are 5, 3, and 1, respectively, then the grid data of the grid C is: 10+ 5-15.
According to the method provided by the embodiment, the point location data of each preset position point is distributed to the target grids covered by the point location data, so that the finally obtained grid data of each grid are more reasonable, and the final recognition result is more accurate.
On the basis of fig. 2, an embodiment of the present invention further provides a specific implementation manner for determining a sudden change threshold, please refer to fig. 4, where fig. 4 is a flowchart illustrating another boundary identification method based on mobile phone signaling provided in the embodiment of the present invention, and sub step S1102 includes the following sub steps:
in the sub-step S11020, the total area of the grid in which the grid data is within each preset interval is calculated.
In this embodiment, the preset intervals are determined according to all the grid data, the range of the preset intervals may be determined according to the range of the grid data, the number of the preset intervals and the range of each preset interval may be determined according to the distribution of the values of the grid data, and of course, the range, the number and the range of each preset interval may also be determined according to the needs of the actual application scenario, for example, the number of the preset intervals is 6, the maximum value is M, and the ranges are respectively: [0, M), [20, M), [40, M), [60, M), [80, M), [100, M.
In the substep S11021, a density variation curve is generated according to each preset interval and the corresponding total area.
In the substep S11022, the mesh data corresponding to the point with the maximum gradient in the density variation curve is determined as the mutation threshold.
In this embodiment, as a specific embodiment, in the density variation curve, the grid data corresponding to the point where the area gradient changes most is identified from high to low in density, and the value of the grid data is determined as the abrupt change threshold. Referring to fig. 5, fig. 5 is an exemplary diagram of a density variation curve according to an embodiment of the invention.
According to the method provided by the embodiment, the mutation threshold can be quickly and accurately determined through the density change curve, and finally, the accuracy and efficiency of boundary identification are improved.
Referring to fig. 6, fig. 6 is a flowchart illustrating another boundary identification method based on mobile phone signaling according to an embodiment of the present invention, where step S130 includes the following sub-steps:
and a substep S1301, determining the intersection of the first boundary and the second boundary as the final boundary of the region to be identified in the preset region.
In this embodiment, the intersection of the first boundary and the second boundary is determined as the final boundary, and since the first boundary and the second boundary are determined based on different data sources, the final boundary reflects the influence of the characteristics of each of the multiple data sources in boundary identification, so that the identification accuracy is higher.
It should be noted that, if the first data includes two types of data, for example, the mobile phone signaling data and the interest point data, the first boundary includes a boundary of the to-be-identified region determined according to the mobile phone signaling data and a boundary of the to-be-identified region determined according to the interest point, the processing procedure may be: according to the mobile phone signaling data, determining a boundary corresponding to the mobile phone signaling data by adopting substeps S1101-S1103 and substeps S11010-S11011 and S11020-S11022, determining a boundary corresponding to the point of interest data by adopting substeps S1101-S1103 and substeps S11010-S11011 and S11020-S11022 according to the point of interest data, and finally determining a final boundary of the region to be identified according to the boundary corresponding to the mobile phone signaling data in the first boundary, the boundary corresponding to the point of interest data and the second boundary.
It should be noted that, according to the second data, an implementation manner of determining the second boundary of the to-be-identified region in the preset region is the same as the substeps S1102 to S1103 and the substeps S11020 to S11022 in the step S110, for example, as a specific implementation manner, taking the second data as the lighting brightness, each grid corresponds to one lighting brightness value, and according to the lighting brightness values of all grids, a lighting abrupt change threshold is determined, where the lighting abrupt change threshold is used to indicate that the density change of the lighting brightness values meets the lighting change condition. And dividing the grids according to the light mutation threshold to obtain a second boundary, namely determining the grids with the light brightness values larger than the light mutation threshold in all the grids as areas to be identified, and determining the grids with the light brightness values smaller than or equal to the light mutation threshold in all the grids as other areas, thereby obtaining the second boundary. Further, the sudden change threshold value can be determined in a manner similar to the substeps S11020 to S11022, and the total area of the grid with the light brightness value in each preset brightness value interval is calculated; and generating a light brightness change curve according to each preset brightness value interval and the corresponding total area. And determining the light brightness value corresponding to the maximum gradient point in the light brightness change curve as the light sudden change threshold, and taking the area to be identified as a city central area, wherein the light brightness value of the city central area is far higher than that of a non-city central area, so that the grid with the light brightness value higher than the light sudden change threshold is determined as the city central area, and the grid with the light brightness value lower than or equal to the light sudden change threshold is determined as the non-city central area, so that a second boundary of the city central area can be obtained, and the boundary of the non-city central area can also be considered to be obtained.
In order to more intuitively embody the identification process of the method in the embodiment, a specific identification example is given in the embodiment of the present invention, where the first data is mobile phone signaling data and interest point data, and the second data is a light brightness value, please refer to fig. 7 to 10, fig. 7 is an exemplary diagram of a boundary corresponding to the interest point data in the first boundary provided in the embodiment of the present invention, fig. 8 is an exemplary diagram of a boundary corresponding to the mobile phone signaling data in the first boundary provided in the embodiment of the present invention, and fig. 9 is an exemplary diagram of the second boundary provided in the embodiment of the present invention. Fig. 10 is an exemplary diagram of a final boundary provided in an embodiment of the present invention, where the final boundary in fig. 10 is an intersection of a boundary corresponding to the point of interest in the first boundary, a boundary corresponding to the mobile phone signaling data in the first boundary, and a second boundary, and taking an area to be identified as a city center area as an example, the mobile phone signaling data is dense (i.e., densely populated), the density of the point of interest is high, and an area with bright light is the city center area.
In order to perform the corresponding steps of the boundary identification method based on the mobile phone signaling in the foregoing embodiment and various possible implementations, an implementation of the boundary identification apparatus 100 based on the mobile phone signaling is given below. Referring to fig. 11, fig. 11 is a block diagram illustrating a boundary identification apparatus 100 based on mobile phone signaling according to an embodiment of the present invention. It should be noted that the basic principle and the generated technical effect of the boundary identifying device 100 based on the mobile phone signaling provided in the present embodiment are the same as those of the above embodiments, and for the sake of brief description, no reference is made to this embodiment portion.
The boundary identifying device 100 based on the mobile phone signaling comprises an obtaining module 110 and a determining module 120.
The obtaining module 110 is configured to obtain first data and second data, where the first data is obtained at a plurality of preset position points in a preset area, and the second data includes boundary feature data of each of a plurality of grids.
The determining module 120 is configured to determine a first boundary of the to-be-identified area in the preset area according to the first data.
The determining module 120 is further configured to determine a second boundary of the to-be-identified area in the preset area according to the second data.
The determining module 120 is further configured to determine a final boundary of the to-be-identified region in the preset region according to the first boundary and the second boundary.
As a specific embodiment, the determining module 120 is specifically configured to: distributing the first data to a plurality of grids to obtain grid data of each grid, wherein the aggregate of all the grid data is equal to the first data; determining a mutation threshold according to all the grid data, wherein the mutation threshold is used for representing that the density change of the grid data meets a preset condition; and dividing the grids according to the mutation threshold value to obtain a first boundary.
As a specific embodiment, the first data includes point location data obtained from each preset location point, and the determining module 120 is specifically configured to, when configured to allocate the first data to the multiple grids and obtain grid data of each grid: acquiring a target grid in a plurality of grids covered by each preset position point service range; and distributing the point location data of each preset position point to the target grid of each preset position point, and finally obtaining the grid data of each grid.
As a specific embodiment, a plurality of preset intervals are predetermined according to all the grid data, and the determining module 120 is specifically configured to, when determining the abrupt change threshold according to all the grid data: calculating the total area of the grids of which the grid data are positioned in each preset interval; generating a density change curve according to each preset interval and the corresponding total area; and determining the grid data corresponding to the point with the maximum gradient in the density change curve as a mutation threshold.
As a specific embodiment, the determining module 120 is specifically configured to: and determining the intersection of the first boundary and the second boundary as the final boundary of the region to be identified in the preset region.
As a specific implementation manner, the preset location point includes a location of the base station, and the first data is mobile phone signaling data acquired from the base station.
As a specific implementation manner, the preset location point further includes a location of the interest point, and the first data is the number of the interest points located at the location of the interest point.
Referring to fig. 12, fig. 12 is a block diagram of a computer device 10 according to an embodiment of the present invention, where the computer device 10 includes a processor 11, a memory 12, a bus 13, and a communication interface 14. The processor 11 and the memory 12 are connected by a bus 13, and the processor 11 communicates with an external device via a communication interface 14.
The processor 11 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 11. The Processor 11 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components.
The memory 12 is used for storing a program, for example, the boundary identification device 100 based on the mobile phone signaling in the embodiment of the present invention, each boundary identification device 100 based on the mobile phone signaling includes at least one software functional module which can be stored in the memory 12 in a form of software or firmware (firmware), and the processor 11 executes the program after receiving an execution instruction to implement the boundary identification method based on the mobile phone signaling in the embodiment of the present invention.
The Memory 12 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory). Alternatively, the memory 12 may be a storage device built in the processor 11, or may be a storage device independent of the processor 11.
The bus 13 may be an ISA bus, a PCI bus, an EISA bus, or the like. Fig. 12 is represented by only one double-headed arrow, but does not represent only one bus or one type of bus.
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the above boundary identification method based on mobile phone signaling.
In summary, an embodiment of the present invention provides a boundary identification method and a related apparatus based on a mobile phone signaling, where a preset area is pre-divided into a plurality of grids, and the method includes: acquiring first data and second data, wherein the first data is acquired at a plurality of preset position points in a preset area, and the second data comprises boundary characteristic data of each grid in a plurality of grids; determining a first boundary of a region to be identified in a preset region according to the first data; determining a second boundary of the area to be identified in the preset area according to the second data; and determining the final boundary of the region to be identified in the preset region according to the first boundary and the second boundary. Compared with the prior art, the method and the device have the advantages that the first boundary of the preset area is determined according to the first data acquired from the multiple preset position points in the preset area, the second boundary of the preset area is determined according to the boundary characteristic data of each grid in the multiple grids, the final boundary of the preset area is determined according to the first boundary and the second boundary, the first data (point location type data) and the second data (surface type data of the boundary characteristics) of the preset position points are combined, multiple factors influencing boundary identification are comprehensively considered, the boundary of the area is accurately identified, and monitoring and management of the area can be greatly assisted.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A boundary identification method based on mobile phone signaling is characterized in that a preset area is divided into a plurality of grids in advance, and the method comprises the following steps:
acquiring first data and second data, wherein the first data is acquired at a plurality of preset position points in the preset area, and the second data comprises boundary characteristic data of each grid in the plurality of grids;
determining a first boundary of a region to be identified in the preset region according to the first data;
determining a second boundary of the area to be identified in the preset area according to the second data;
and determining the final boundary of the region to be identified in the preset region according to the first boundary and the second boundary.
2. The method for identifying a boundary based on mobile phone signaling according to claim 1, wherein the step of determining the first boundary of the area to be identified in the preset area according to the first data comprises:
distributing the first data to the multiple grids to obtain grid data of each grid, wherein a set of all the grid data is equal to the first data;
determining a mutation threshold according to all the grid data, wherein the mutation threshold is used for representing that the density change of the grid data meets a preset condition;
and dividing the grids according to the mutation threshold to obtain the first boundary.
3. The boundary identification method based on mobile phone signaling according to claim 2, wherein the first data includes point location data obtained from each of the preset location points, and the step of allocating the first data to the plurality of grids to obtain the grid data of each of the grids includes:
acquiring a target grid in the multiple grids covered by each preset position point service range;
and distributing the point location data of each preset position point to a target grid of each preset position point, and finally obtaining the grid data of each grid.
4. The boundary identification method based on mobile phone signaling according to claim 2, wherein a plurality of preset intervals are predetermined according to all the grid data, and the step of determining the abrupt change threshold according to all the grid data comprises:
calculating the total area of the grids of the grid data in each preset interval;
generating a density change curve according to each preset interval and the corresponding total area;
and determining the grid data corresponding to the point with the maximum gradient in the density change curve as the mutation threshold.
5. The method for identifying a boundary based on mobile phone signaling according to claim 1, wherein the step of determining the final boundary of the to-be-identified area in the preset area according to the first boundary and the second boundary comprises:
and determining the intersection of the first boundary and the second boundary as the final boundary of the region to be identified in the preset region.
6. The method as claimed in claim 1, wherein the predetermined location point includes a location of a base station, and the first data is cell phone signaling data obtained from the base station.
7. The method as claimed in claim 1, wherein the preset location point further includes a location of an interest point, and the first data is a number of interest points located at the location of the interest point.
8. A boundary identification device based on mobile phone signaling is characterized in that a preset area is divided into a plurality of grids in advance, and the device comprises:
an obtaining module, configured to obtain first data and second data, where the first data is obtained at a plurality of preset location points in the preset area, and the second data includes boundary feature data of each of the plurality of grids;
the determining module is used for determining a first boundary of a region to be identified in the preset region according to the first data;
the determining module is further configured to determine a second boundary of the to-be-identified area in the preset area according to the second data;
and the determining module is also used for determining the final boundary of the region to be identified in the preset region according to the first boundary and the second boundary.
9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the cell phone signaling-based boundary identification method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the cell phone signaling-based boundary identification method according to any one of claims 1 to 7.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106899932A (en) * | 2015-12-21 | 2017-06-27 | 清华大学 | It is a kind of to enliven density of population monitoring method and system |
| CN107205220A (en) * | 2016-03-18 | 2017-09-26 | 中国移动通信集团江苏有限公司 | A kind of method and device of determination region stream of people's quantity |
| US20180074195A1 (en) * | 2016-09-14 | 2018-03-15 | Garmin Switzerland Gmbh | Determining a boundary enclosing a region of interest for a body of water |
| CN110533038A (en) * | 2019-09-04 | 2019-12-03 | 广州市交通规划研究院 | A method of urban vitality area and inner city Boundary Recognition based on information data |
| CN111382330A (en) * | 2020-03-10 | 2020-07-07 | 智慧足迹数据科技有限公司 | Land property identification method and device, electronic equipment and storage medium |
| CN111651545A (en) * | 2020-06-03 | 2020-09-11 | 南京图申图信息科技有限公司 | Urban marginal area extraction method based on multi-source data fusion |
| CN112257207A (en) * | 2020-10-27 | 2021-01-22 | 智慧足迹数据科技有限公司 | Road network boundary determining method and device, electronic equipment and storage medium |
| CN113205042A (en) * | 2021-04-30 | 2021-08-03 | 武汉大学 | Method and system for identifying multi-level boundaries of city |
-
2021
- 2021-08-16 CN CN202110939197.5A patent/CN113660623B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106899932A (en) * | 2015-12-21 | 2017-06-27 | 清华大学 | It is a kind of to enliven density of population monitoring method and system |
| CN107205220A (en) * | 2016-03-18 | 2017-09-26 | 中国移动通信集团江苏有限公司 | A kind of method and device of determination region stream of people's quantity |
| US20180074195A1 (en) * | 2016-09-14 | 2018-03-15 | Garmin Switzerland Gmbh | Determining a boundary enclosing a region of interest for a body of water |
| CN110533038A (en) * | 2019-09-04 | 2019-12-03 | 广州市交通规划研究院 | A method of urban vitality area and inner city Boundary Recognition based on information data |
| CN111382330A (en) * | 2020-03-10 | 2020-07-07 | 智慧足迹数据科技有限公司 | Land property identification method and device, electronic equipment and storage medium |
| CN111651545A (en) * | 2020-06-03 | 2020-09-11 | 南京图申图信息科技有限公司 | Urban marginal area extraction method based on multi-source data fusion |
| CN112257207A (en) * | 2020-10-27 | 2021-01-22 | 智慧足迹数据科技有限公司 | Road network boundary determining method and device, electronic equipment and storage medium |
| CN113205042A (en) * | 2021-04-30 | 2021-08-03 | 武汉大学 | Method and system for identifying multi-level boundaries of city |
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