WO2022082553A1 - 一种地理围栏数据点密度优化的方法和*** - Google Patents
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Definitions
- the present application relates to the field of computer technology, and in particular, to a method and system for optimizing the density of geofence data points.
- geo-fencing technology has been applied to various fields, such as location judgment of intelligent terminals, judgment of rovers, and so on.
- the geofence is constructed based on the acquired geofence data point set, and the data point quality of the geofence data point set will also affect the quality of the obtained geofence.
- various collection methods such as map marking, sequential collection along the road, etc.
- map marking a lot of road information needs to be considered when collecting sequentially along the road, for example, the length, width, extension direction, number of roadblocks, etc. of the road, a large number of data points will be collected, and there will be a large number of redundant data points in the geofence data point set.
- a large number of redundant data points will make geo-fence-related algorithms such as judging whether the target (such as rover, terminal device, etc.) is located in the geo-fence area requires high computing power when the geo-fence constructed based on the geo-fence data point set is applied. Operational efficiency is low.
- the method includes: acquiring a set of geofence data points, the set of geofence data points including a plurality of data points arranged in the order of collection; and repeating the following steps on the set of geofence data points until the geofence data point is reached
- the set satisfies the first preset condition: the plurality of data points are divided into at least one data point group, and each data point group includes at least 3 data points arranged in sequence;
- the system includes: an acquisition module: used to acquire a geo-fence data point set, the geo-fence data point set includes a plurality of data points arranged in the order of collection; Repeat the following steps until the set of geofence data points satisfies a first preset condition: dividing the plurality of data points into at least one data point group, each of the data point groups including at least three sequentially arranged data points.
- the data points determine the degree of correlation between each of the data points except the first data point and the last data point in each of the data point groups and the straight line formed by the first data point and the last data point; Whether the correlation degree satisfies the second preset condition, if yes, the data point corresponding to the correlation degree is a deleteable point, delete all the deleteable points, and update the data points of the geofence data point set Sort the order and the number of data points to complete a round of data point filtering.
- Another aspect of the present specification provides an apparatus for optimizing the density of geofence data points, including a processor configured to perform a method for optimizing the density of geofence data points.
- Another aspect of the present specification provides a computer-readable storage medium that stores computer instructions, and after the computer reads the computer instructions in the storage medium, the computer executes a method for optimizing the density of geofence data points.
- FIG. 1 is a schematic diagram of an application scenario of a system for optimizing the density of geofence data points according to some embodiments of the present specification
- FIG. 2 is a block diagram of an exemplary geofence data point density optimization system shown in accordance with some embodiments of the present specification
- FIG. 3 is an exemplary flowchart of a method for optimizing geofence data point density according to some embodiments of the present specification
- FIG. 4 is an exemplary flowchart of a method for determining M data point groups according to some embodiments of the present specification.
- system means for distinguishing different components, elements, parts, parts or assemblies at different levels.
- device means for converting signals into signals.
- unit means for converting signals into signals.
- module means for converting signals into signals.
- FIG. 1 is a schematic diagram of an application scenario of a system for optimizing the density of geofence data points according to some embodiments of the present specification.
- Geofence data point density system 100 may include processor 110 , network 120 and storage device 130 .
- the geofence data point density system 100 can be used for data point collection and processing of road-level geofences, geofence construction for location determination of rovers, and geofence construction for location determination of smart terminals.
- the collection of data points for road-level geofences differs from other ways of constructing geofences by marking data points on a map, such as area-level geofence data points. Map markers are difficult to match with actual road coordinates, widths and other data.
- the road-level geofence construction based on road information needs to collect data points sequentially along the road to obtain the geofence data point set. Since a lot of road information needs to be considered during collection, for example, the length, width, extension direction, number of roadblocks, etc.
- the geofence data point density system 100 can reduce road-level geofence data by filtering and removing redundant data points in the road-level geofence data point set by implementing the methods and/or processes disclosed in this specification. number of points to construct a geofence with the optimal density of data points.
- the processor 110 may obtain data (eg, a set of geofence data points) from a storage device 130 through a network, and the storage device 130 may also upload data (eg, a set of geofence data points) to the processor 110 through a network.
- the processor 110 and the storage device 130 can also communicate and transmit data with other external devices through the network 120 .
- the processor 110 may execute the action instructions to implement any of the methods for optimizing the density of geofence data points described in this specification.
- the information transfer relationship between the above devices is only an example, and the present application is not limited thereto.
- a storage device 130 may be included in the processor 110 and possibly other system components.
- the processor 110 may process data and/or information obtained from other devices or system components.
- the processor may execute program instructions based on such data, information and/or processing results to perform one or more of the functions described herein.
- processor 110 may include one or more sub-processing devices (eg, single-core processing devices or multi-core multi-core processing devices).
- the processor 110 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), an application specific instruction processor (ASIP), a graphics processor (GPU), a physical processor (PPU), a digital signal processor ( DSP), field programmable gate array (FPGA), programmable logic circuit (PLD), controller, microcontroller unit, reduced instruction set computer (RISC), microprocessor, etc. or any combination of the above.
- CPU central processing unit
- ASIC application specific integrated circuit
- ASIP application specific instruction processor
- GPU graphics processor
- PPU physical processor
- DSP digital signal processor
- FPGA field programmable gate array
- PLD programmable logic circuit
- controller microcontroller
- Storage device 130 may be used to store data and/or instructions.
- the storage device 130 may include one or more storage components, and each storage component may be an independent device or a part of other devices.
- storage device 130 may include random access memory (RAM), read only memory (ROM), mass storage, removable memory, volatile read-write memory, the like, or any combination thereof.
- mass storage may include magnetic disks, optical disks, solid state disks, and the like.
- the storage device 130 may be implemented on a cloud platform.
- Data refers to the digital representation of information, and can include various types, such as binary data, text data, image data, video data, and so on. Instructions are programs that control a device or device to perform a specific function.
- Network 120 may connect components of the system and/or connect portions of the system with external resources.
- the network 120 enables communication between the various components and with other components outside the system, facilitating the exchange of data and/or information.
- the network 120 may be any one or more of a wired network or a wireless network.
- the network 120 may include a cable network, a fiber optic network, a telecommunications network, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN) , Bluetooth network, ZigBee network (ZigBee), near field communication (NFC), intra-device bus, intra-device line, cable connection, etc.
- LAN local area network
- WAN wide area network
- WLAN wireless local area network
- MAN metropolitan area network
- PSTN public switched telephone network
- Bluetooth network ZigBee network
- ZigBee near field communication
- intra-device bus intra-device
- network 150 may include one or more network access points.
- network 120 may include wired or wireless network access points, such as base stations and/or network switching points 120-1, 120-2, . . . , through which one or more components of system 100 may Connect to network 120 to exchange data and/or information.
- FIG. 2 is a block diagram of an exemplary geofence data point density optimization system shown in accordance with some embodiments of the present specification.
- the system 200 for geofence data point density optimization may include an acquisition module 210 , a data point screening module 220 and a data point group determination module 221 .
- the obtaining module 210 may be configured to obtain a set of geofence data points, the set of geofence data points including a plurality of data points arranged in the order of collection.
- the data point set and the data point reference may be made to FIG. 3 and its related description, which will not be repeated here.
- the data point screening module 220 may be configured to repeatedly perform the following steps on the geofence data point set until the geofence data point set satisfies a first preset condition: dividing the plurality of data points into at least one data point group , each said data point group includes at least 3 said data points arranged in sequence; determine each said data point and said first data point except the first data point and last data point in each said data point group and the correlation degree of the straight line formed by the last data point; determine whether the correlation degree satisfies the second preset condition, if yes, then the data point corresponding to the correlation degree is a deleteable point, and all the possible The deletion point is deleted, and the data point arrangement order and the data point quantity of the geofence data point set are updated to complete a round of data point screening.
- the data point screening module 220 may also be used to determine the correlation coefficient between each data point except the first data point and the last data point and the straight line, and to determine the correlation coefficient of each data point except the first data point and the last data point. The distance of the data point from the line.
- the degree of correlation satisfying the second preset condition may include: the correlation coefficient is greater than the first threshold, and the distance is less than the second threshold.
- the first preset condition may include: the number of the data points after the selection of the data points in the current round is the same as the number of the data points after the selection of the data points in the previous round is completed.
- the scale of the coordinate space of the data points may be determined according to the smallest coordinate value of the data point in the geofence data point set.
- the data point screening module 220 further includes a data point group determination module 221, and the data point group determination module 221 may be configured to obtain at least three pieces of the data each time according to the arrangement order of the plurality of data points point as one of the data point groups; based on the arrangement order of the data points in the data point group, the data point groups are sequentially arranged to obtain the at least one data point group.
- the first data point of each data point group is the last data point of the previous data point group.
- the illustrated system and its modules may be implemented in a variety of ways.
- the system and its modules may be implemented in hardware, software, or a combination of software and hardware.
- the hardware part can be realized by using dedicated logic;
- the software part can be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware.
- a suitable instruction execution system such as a microprocessor or specially designed hardware.
- the methods and systems described above may be implemented using computer-executable instructions and/or embodied in processor control code, for example on a carrier medium such as a disk, CD or DVD-ROM, such as a read-only memory (firmware) ) or a data carrier such as an optical or electronic signal carrier.
- the system and its modules of the present application can not only be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc. , can also be implemented by, for example, software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software (eg, firmware).
- the above description of the system 200 for optimizing the density of geofence data points and its modules is only for the convenience of description, and does not limit the description to the scope of the illustrated embodiments. It can be understood that for those skilled in the art, after understanding the principle of the system, various modules may be combined arbitrarily, or a subsystem may be formed to connect with other modules without departing from the principle.
- the acquisition module 210, the data point screening module 220 and the data point group determination module 221 may share one storage module, and each module may also have its own storage module. Such deformations are all within the protection scope of the present application.
- FIG. 3 is an exemplary flowchart of a method for geofence data point density optimization according to some embodiments of the present specification.
- the method 300 for optimizing the density of geofence data points may include:
- Step 310 obtaining a set of geofence data points.
- this step 310 may be performed by the obtaining module 210 .
- a geofence data point set is a set of data points made up of the data points used to construct the geofence.
- a geofence data point set consists of multiple data points in the order in which they were collected. Specifically, the multiple data points may be data points sequentially collected along a road, or a boundary of a selected area such as a residential area, a park, a lake, and the like.
- the data points in the geofence data point set may be arranged in a forward order of the collection order, or may be arranged in a reverse order of the collection order.
- the set of geofence data points may be obtained from a server, terminal, or database.
- the terminal can be used to collect data points, read the data saved by the terminal to obtain the geofence data point set, or the terminal can send the collected data point information to the server or save it to an external database, and obtain the geo-fence data point information from the server or database.
- Fence data point set may be used to collect data points, read the data saved by the terminal to obtain the geofence data point set, or the terminal can send the collected data point information to the server or save it to an external database, and obtain the geo-fence data point information from the server or database.
- further processing may be performed on the geofence data point set, such as data point coordinate transformation, data point statistics, and the like.
- the coordinate space of the data point refers to the coordinate system space used to represent the coordinates of the data point, for example, the CGCS coordinate system space, the WGS coordinate system space, and the UTM coordinate system space can be used as the coordinate space of the data point.
- the scale of the coordinate space of the data points may be adjusted. Specifically, the scale of the coordinate space of the data points may be determined according to the minimum coordinate value of the data points in the geofence data point set.
- the geographic data point set is represented as Data geofence , where the coordinates of the data point a are Point a (X a , Y a ), the scale range of the coordinate space starts from 0, and Min_x and Min_y are the corresponding geofence data points, respectively The smallest X-axis coordinate value and the smallest Y-axis coordinate value in The coordinates are New_Point a (X a -Min_x, Y a -Min_y).
- the coordinate space of the data points may be transformed.
- the data point uses the WGS coordinate system space.
- the coordinate space used by the data point is converted to the UTM coordinate system space.
- the change of the scale range of the coordinate space of the data points can be understood as the coordinate transformation of the coordinate space of the data points to obtain a coordinate system with the data points (Min_x, Min_y) as the origin, so that the data can be effectively reduced. Coordinate value of point a.
- the scale of the coordinate space can be adapted to the range of the coordinate value of the data point.
- the calculated correlation coefficient will not be too large because the coordinate value is too large. If the value is too large, the variation interval of the correlation coefficient equivalent is too small and the difference of the correlation coefficient is too small. After adjustment, it can be more accurately judged whether the data point can be deleted according to whether the correlation coefficient equivalent value meets the conditions. For more details on the calculation of the correlation coefficient, reference may be made to step 324 and its related description, which will not be repeated here.
- Step 320 Repeat the data point screening step on the geofence data point set until the geofence data point set satisfies the first preset condition.
- this step 320 may be performed by the data point screening module 220 .
- Data point filtering refers to filtering the data points in the geofence data point set to delete unnecessary data points, that is, data points that are redundant for building a geofence.
- Repeating the data point filtering step refers to cyclic filtering of the data points in the geofence data point set, in other words, an iteration of the data point filtering.
- cyclic screening that is, the iteration of data point screening, it can be ensured that all redundant data points are screened out as much as possible, and the screening accuracy is improved.
- the first preset condition may mean that the number of data points in the geofence data point set reaches a preset condition, for example, the number reaches a preset value or the number remains stable after multiple screenings, or that the geofence formed by the data points reaches the preset condition. , such as a geofence that completely covers the target area or coincides with the boundary of the target area.
- the fact that the geofence data point set satisfies the first preset condition can be understood as that redundant data points in the geofence data point set have been deleted, and a geofence data point set with better point density is obtained.
- the data point screening step may include:
- Step 322 Divide the N data points into at least one data point group, and each data point group includes at least 3 data points arranged in sequence.
- the data point group refers to a point set composed of multiple data points, and the data point group includes at least 3 data points, for example, may include 3 or 4 or 5 data points.
- the number of data points included in each data point group may be the same or different.
- the order of the data points in the data point group is the order of the data points of the geofence data point set.
- the data points included in each data point group may or may not overlap with the data points in the preceding and following data point groups.
- the number of data point groups may be determined based on the number of data points and the number of data points in the data point group.
- each data point group can include 3 data points
- the number of data point groups can be is 2
- the resulting 2 data point groups are ⁇ a, b, c ⁇ and ⁇ d, e, f ⁇ , or ⁇ a, b, c ⁇ and ⁇ c, d, e ⁇
- each data point group can also include 4 data points
- the number of data point groups can be 1 or 2
- one data point group is ⁇ a, b, c, d ⁇ or ⁇ b, c, d, e ⁇ or ⁇ c , d, e, f ⁇ , get 2 data point groups ⁇ a, b, c, d ⁇ and ⁇ c, d, e, f ⁇ respectively.
- Step 324 Determine the degree of correlation between each of the data points except the first data point and the last data point in each of the data point groups and the straight line formed by the first data point and the last data point.
- the first data point refers to the first data point in the data point group
- the last data point refers to the last data point in the data point group.
- the first data points of the data point groups ⁇ a, b, c ⁇ and the data point groups ⁇ d, e, f ⁇ are the data points a and Data point d
- the last data point is data point c and data point f respectively.
- the straight line formed by the first data point and the last data point refers to a straight line formed by connecting the first data point and the last data point in the coordinate system.
- the straight line can be understood as a linear function determined by the coordinates of the first and last data points.
- the degree of correlation refers to the closeness of the linear relationship between each data point and the straight line, and can also be understood as the degree of fitting between each data point and the straight line.
- the degree of correlation between the data points and the line can be perfectly linear (ie, a perfect fit), less linear (ie, less fit), or more linearly related (ie, more fit).
- the degree of correlation can be determined by calculating the linear correlation value, calculating the value of the degree of fit between the data points and the straight line, and so on.
- the degree of correlation may be determined by determining a correlation coefficient between each of the data points except the first data point and the last data point and the straight line.
- the correlation coefficient refers to a numerical representation of a linear relationship, and the larger the correlation coefficient value, the higher the degree of correlation. For example, a correlation coefficient of 0.9 represents a higher degree of correlation than a correlation coefficient of 0.7.
- the correlation coefficient can be calculated according to residual, total dispersion, etc. Specifically, the following formula can be used to calculate:
- any effective calculation method can also be adopted to calculate the correlation coefficient between the data point and the straight line.
- the Pearson correlation coefficient calculation method is not limited to the calculation method shown in the formula (1), and this specification does not limit the calculation method of the correlation coefficient between the above two.
- the degree of correlation may also be determined by determining the distance between each of the data points except the first data point and the last data point and the straight line.
- Absolute distance is inversely proportional to the degree of correlation. That is, the larger the absolute distance is, the smaller the corresponding degree of correlation is.
- the absolute distance D between the data point b and the straight line ac formed by the data points a and c can be expressed as:
- A, B, C are all calculation parameters
- x 0 and y 0 are the coordinates of data point b respectively value.
- Step 326 determine whether the degree of correlation satisfies the second preset condition, if yes, then the data point corresponding to the degree of correlation is a point that can be deleted, delete all the points that can be deleted, and update the geo-fence data
- the sequence of data points and the number of data points in the point set completes a round of data point filtering.
- the second preset condition may refer to the degree of correlation between the data points of the geofence data point set and the straight line reaching a preset threshold, or other preset conditions obtained by further processing based on the degree of correlation.
- the second preset condition may be a preset threshold.
- the preset threshold may be a preset threshold of the correlation coefficient
- the correlation coefficient may be compared with the preset threshold
- the correlation coefficient greater than the preset threshold may be used as a criterion for determining whether the degree of correlation satisfies the second preset condition.
- the preset threshold of the correlation coefficient is 0.8
- the calculated correlation coefficient between the data point b and the straight line ac is 0.85
- the degree of correlation between the data point b and the straight line ac satisfies the predetermined threshold.
- the preset threshold value may also be the preset threshold value of the distance between each data point and the straight line, the distance can be compared with the preset threshold value, and the distance is smaller than the preset threshold value as the determination of whether the degree of correlation satisfies the second preset condition. standard. Taking the data point group ⁇ a, b, c ⁇ as an example, the preset threshold of the distance is 2 cm, and the calculated distance between the data point b and the straight line ac is 0.7, then the degree of correlation between the data point b and the straight line ac satisfies the preset condition . It should be noted that the size of the preset threshold value can be determined through experimental data, and can also be adjusted according to the actual situation, and this specification does not limit the determination and size range of the preset threshold value.
- the preset threshold of the correlation coefficient may be referred to as a first threshold
- the preset threshold of the distance between each data point and the straight line may be referred to as a second threshold
- the correlation coefficient may be greater than the first threshold
- the distance Being less than the second threshold is taken as the second preset condition that the correlation degree satisfies.
- the degree of correlation between the data point b and the straight line formed by the data point a and the data point c satisfies the second preset condition.
- the correlation coefficient and the distance reference may be made to step 324 and its related description, which will not be repeated here.
- the geofence data point set can be filtered from the geofence data point set on the basis of a single filtering condition. Do not overscale when deleting points. Deleting data points that are too large can be understood as, after deleting the filtered points that can be deleted, the geofence formed by the geofence data point set has a large boundary change compared with the actual road boundary or area, so that according to the above Geofences created by geofence datasets no longer cover the target area accurately.
- the data point corresponding to the degree of correlation satisfying the second preset condition is a deleteable point, that is, the data point satisfies any one of the aforementioned degree of correlation and meets the second preset condition, then the data point can be collected from the geofence data point set delete. After the deleteable points are deleted, the order of data points and the number of data points N in the geofence data point set will be updated to complete a round of data point filtering.
- the obtained 2 data point groups are ⁇ a, b, c ⁇ and ⁇ d, e, f ⁇ , the degree of correlation between data point b and data point e satisfies the second preset condition, and is a point that can be deleted.
- the geofence data point set after updating the number of data points and the order of data points can be used for the next round of data point filtering.
- the first preset condition may be: the number of the data points after the selection of the data points in the current round is the same as the number of the data points after the selection of the data points in the previous round. That is, when the preset condition is met, the number of data point sets remains stable and no longer changes. It can be considered that all deleteable points have been filtered out, that is, the point density optimization of the geofence data point set is completed.
- the starting data point for each round of data point screening may vary.
- the grouping when at least one data group is obtained by grouping the geofence data point set, the grouping may start from the first data point sequentially arranged in the geofence data point set, that is, the starting data The point is the first data point in the order, or it can be grouped from the second data point in the order or other data points in the geofence data point set, that is, the starting data point is the second data point in the order.
- the starting data point of one round of data point screening is the first data point arranged in sequence
- the starting data point of the next round of data point screening may be the second data point or other data points arranged in sequence.
- the number M of a data point group may be set first, M data point groups are sequentially selected from the data point set, and data point screening is performed on the M data point groups, Then continue to select M data point groups from the data point set to filter the data points until all the data points in the data point set are selected and filtered.
- the previous round of M data point groups can be screened, and the first data point group of the data point group that has not been continuously screened for deleteable points can be selected.
- the data points of are the starting data points of the next round of M data point groups.
- FIG. 4 For more content of the method for determining at least one data point group, reference may be made to FIG. 4 and related descriptions thereof, which will not be repeated here.
- multiple rounds of data point screening can be performed alternately with the first point as the starting point or the second point as the starting point, ensuring that as many data points as possible can be judged whether they can be deleted, and more accurately find the deleteable data points. point.
- the data points are grouped, and whether the data points are deleteable points is determined according to the calculated correlation between each data point and the straight line formed by the first data point and the last data point in the data point group, Therefore, redundant data points can be efficiently and accurately screened out and deleted, so as to achieve efficient and accurate point density optimization of the geofence data point set.
- FIG. 4 is an exemplary flowchart of a method for determining at least one data point group according to some embodiments of the present specification.
- the method 400 may include:
- Step 410 according to the arrangement order of the plurality of data points, at least three data points are taken each time as one of the data point groups.
- this step 410 may be performed by the data point group determination module 221 .
- the arrangement order of the data points in the data point group is the arrangement order of the data points of the geofence data point set.
- you can follow the data point order of the geofence data point set you can start from the first data point, or start from the second data point or other data points, and you can take at least 3 data points each time (you can is 3, 4, or 5) as a group of data points.
- Step 420 Arrange the data point groups in sequence based on the arrangement order of the data points in the data point group to obtain the at least one data point group.
- this step 420 may be performed by a data point group determination module.
- the at least one data point group can be obtained by arranging the respective data point groups in sequence according to the arrangement order corresponding to the above data point groups.
- the first data point as the starting point or the second data point as the starting point can be alternately performed.
- the data point filtering operation can ensure that as many data points as possible in the geofence data point set are judged whether they are deleteable points, and the data point filtering is more accurate.
- the first data point of each said data point group is the said data point of the previous said data point group last data point.
- each time 3 data points are taken as a data point group, starting from the second data point From the point group, the first data point of each data point group is the last data point of the previous data point group, and the data point groups ⁇ a, b, c ⁇ and ⁇ c, d, e ⁇ .
- the data points in the sequentially arranged data point groups can be connected end to end, which can further ensure that as many data points as possible are determined to be deleteable points, and the data point selection is more accurate.
- Embodiments of the present specification also provide an apparatus, including a processor configured to perform the aforementioned method for optimizing the density of geofencing data points.
- the method for optimizing the density of geofence data points may include: acquiring a set of geofence data points, the set of geofence data points including a plurality of data points arranged in the order of collection; and repeating the following steps for the set of geofence data points , until the geofence data point set satisfies the first preset condition: dividing the plurality of data points into at least one data point group, each of the data point groups including at least 3 of the data points arranged in sequence; Determine the degree of correlation between each of the data points except the first data point and the last data point in each of the data point groups and the straight line formed by the first data point and the last data point; determine whether the degree of correlation is If the second preset condition is met, if yes, the data point corresponding to the degree of correlation is a deleteable point, delete all the deleteable points, and update the
- Embodiments of the present specification further provide a computer-readable storage medium, where the storage medium stores computer instructions, and after the computer reads the computer instructions in the storage medium, the computer executes the aforementioned method for optimizing the density of geofence data points.
- the method for optimizing the density of geo-fence data points may include: acquiring a set of geo-fence data points, the set of geo-fence data points including a plurality of data points arranged in a collection sequence; and repeating the following steps for the set of geo-fence data points , until the geofence data point set satisfies the first preset condition: dividing the plurality of data points into at least one data point group, each of the data point groups including at least 3 of the data points arranged in sequence; Determine the degree of correlation between each of the data points except the first data point and the last data point in each of the data point groups and the straight line formed by the first data point and the last data point; determine whether the degree of correlation is If the second preset condition is met, if yes,
- the possible beneficial effects of the embodiments of this specification include, but are not limited to: (1) by grouping data points, and calculating the correlation between each data point in the data point group and the straight line formed by the first data point and the last data point To determine whether a data point is a deleteable point or not, to achieve efficient and accurate point density optimization for the geofence data point set; (2) Select the starting point of the point by changing the data point group, and the starting point of the data point for multiple rounds of data point screening.
- the correlation coefficient is greater than the first threshold value and the distance is less than the second threshold value to determine that the correlation degree satisfies the second preset condition, so as to further ensure that when selecting the deleteable points from the geofence data point set, the scale will not be too large, ensuring that the constructed Effective coverage of geofencing.
- the possible beneficial effects may be any one or a combination of the above, or any other possible beneficial effects.
- aspects of this specification may be illustrated and described in several patentable categories or situations, including any new and useful process, machine, product, or combination of matter, or combinations of them. of any new and useful improvements. Accordingly, various aspects of this specification may be performed entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of hardware and software.
- the above hardware or software may be referred to as a "data block”, “module”, “engine”, “unit”, “component” or “system”.
- aspects of this specification may be embodied as a computer product comprising computer readable program code embodied in one or more computer readable media.
- a computer storage medium may contain a propagated data signal with the computer program code embodied therein, for example, on baseband or as part of a carrier wave.
- the propagating signal may take a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination.
- Computer storage media can be any computer-readable media other than computer-readable storage media that can communicate, propagate, or transmit a program for use by coupling to an instruction execution system, apparatus, or device.
- Program code on a computer storage medium may be transmitted over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or a combination of any of the foregoing.
- the computer program coding required for the operation of the various parts of this manual may be written in any one or more programming languages, including object-oriented programming languages such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python etc., conventional procedural programming languages such as C language, Visual Basic, Fortran2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages.
- the program code may run entirely on the user's computer, or as a stand-alone software package on the user's computer, or partly on the user's computer and partly on a remote computer, or entirely on the remote computer or processing device.
- the remote computer can be connected to the user's computer through any network, such as a local area network (LAN) or wide area network (WAN), or to an external computer (eg, through the Internet), or in a cloud computing environment, or as a service Use eg software as a service (SaaS).
- LAN local area network
- WAN wide area network
- SaaS software as a service
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Abstract
Description
Claims (16)
- 一种地理围栏数据点密度优化的方法,其特征在于,包括:获取地理围栏数据点集,所述地理围栏数据点集包括按采集顺序排列的多个数据点;对所述地理围栏数据点集重复执行以下步骤,直至所述地理围栏数据点集满足第一预设条件:将所述多个数据点分为至少一个数据点组,每个所述数据点组包括顺序排列的至少3个所述数据点;确定各个所述数据点组中除首位数据点和末位数据点外的各个所述数据点与所述首位数据点和所述末位数据点所构成直线的相关程度;判断所述相关程度是否满足第二预设条件,若是,则所述相关程度对应的所述数据点为可删除点,将所有所述可删除点删除,并更新所述地理围栏数据点集的数据点排列顺序和数据点数量,完成一轮数据点筛选。
- 如权利要求1所述的方法,所述数据点的坐标空间的尺度根据所述地理围栏数据点集中所述数据点的最小坐标值确定。
- 如权利要求1所述的方法,所述至少一个数据点组的确定方法包括:按照所述多个数据点的所述排列顺序每次取至少3个所述数据点作为一个所述数据点组;基于所述数据点组的所述数据点的所述排列顺序,对所述数据点组依次排列,得到所述至少一个数据点组。
- 如权利要求3所述的方法,所述依次得到的所述至少一个数据点组中,从第2个所述数据点组起,每一个所述数据点组的所述首位数据点是前一个所述数据点组的所述末位数据点。
- 如权利要求1所述的方法,所述确定所述数据点组中除所述首位数据点和所述末位数据点外的各个所述数据点与所述首位数据点和所述末位数据点所构成直线的相关程度包括:确定除所述首位数据点和所述末位数据点外的各个所述数据点与所述直线的相关系数,以及确定除所述首位数据点和所述末位数据点外的各个所述数据点与所述直线的 距离。
- 如权利要求5所述的方法,所述相关程度满足第二预设条件包括:所述相关系数大于第一阈值,以及所述距离小于第二阈值。
- 如权利要求1所述的方法,所述第一预设条件包括:本轮所述数据点筛选完成后的所述数据点数量与前一轮所述数据点筛选完成后的所述数据点数量相同。
- 一种地理围栏数据点密度优化的***,其特征在于,所述***包括:获取模块:用于获取地理围栏数据点集,所述地理围栏数据点集包括按采集顺序排列的多个数据点;数据点筛选模块:用于对所述地理围栏数据点集重复执行以下步骤,直至所述地理围栏数据点集满足第一预设条件:将所述多个数据点分为至少一个数据点组,每个所述数据点组包括顺序排列的至少3个所述数据点;确定各个所述数据点组中除首位数据点和末位数据点外的各个所述数据点与所述首位数据点和所述末位数据点所构成直线的相关程度;判断所述相关程度是否满足第二预设条件,若是,则所述相关程度对应的所述数据点为可删除点,将所有所述可删除点删除,并更新所述地理围栏数据点集的数据点排列顺序和数据点数量,完成一轮数据点筛选。
- 如权利要求8所述的***,所述数据点的坐标空间的尺度根据所述地理围栏数据点集中所述数据点的最小坐标值确定。
- 如权利要求8所述的***,所述数据点筛选模块还包括数据点组确定模块,用于:按照所述多个数据点的所述排列顺序每次取至少3个所述数据点作为一个所述数据点组;基于所述数据点组的所述数据点的所述排列顺序,对所述数据点组依次排列,得到所述至少一个数据点组。
- 如权利要求10所述的***,所述依次得到的所述至少一个数据点组中,从第2个所述数据点组起,每一个所述数据点组的所述首位数据点是前一个所述数据点组的所述末位数据点。
- 如权利要求8所述的***,所述数据点筛选模块还用于:确定除所述首位数据点和所述末位数据点外的各个所述数据点与所述直线的相关系数,以及确定除所述首位数据点和所述末位数据点外的各个所述数据点与所述直线的距离。
- 如权利要求12所述的***,所述相关程度满足第二预设条件包括:所述相关系数大于第一阈值,以及所述距离小于第二阈值。
- 如权利要求8所述的***,所述第一预设条件包括:本轮所述数据点筛选完成后的所述数据点数量与前一轮所述数据点筛选完成后的所述数据点数量相同。
- 一种地理围栏数据点密度优化的装置,包括处理器,所述处理器用于执行如权利要求1~7任一项所述的地理围栏数据点密度优化的方法。
- 一种计算机可读存储介质,所述存储介质存储计算机指令,当计算机读取存储介质中的计算机指令后,计算机执行如权利要求1~7任一项所述的地理围栏数据点密度优化的方法。
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