CN111078759A - Multi-dimensional space-time data collision method, device, equipment and storage medium - Google Patents
Multi-dimensional space-time data collision method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to a multi-dimensional space-time data collision method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring a first data set and a second data set; for each first target object, performing spatial analysis according to the position of each first space station through which the first target object passes and a preset spatial tolerance on the basis of the position of each second space station through which each second target object passes, so as to determine a second target space station in each second space station; based on the time of each second target object passing through a second space station, performing time analysis on the second target space station according to the time of each first space station through which the first target object passes and a preset time tolerance, and determining a collision track data set corresponding to the first target object; and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object. The data collision efficiency is improved, and the real-time performance is good.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a multi-dimensional spatio-temporal data collision method, a device, equipment and a storage medium.
Background
With the advancement of science and technology, data collision is applied to more and more fields, such as the public safety field, and the peer relationship among different people can be calculated by applying a data collision method, so that important clues can be provided for polices when detecting ganged partners, and the data collision method plays an important role in the fields of security implementation, city early warning, case detection and the like.
The existing collision comparison method for massive multidimensional data mainly carries out overall circulation on the massive data in an attribute association mode, and compares whether the data is in a comparison range. On one hand, all data needs to be processed, collision comparison is carried out among billion set data sets, the operation frequency is as high as the square frequency of the data sets, the requirement on system resources is high, the data collision speed is low, the efficiency is low, the real-time performance is poor, and even if distributed calculation is adopted, the timely response of the collision comparison of mass data cannot be met; on the other hand, when a collision is performed among a plurality of data sets, if there is no direct attribute correlation between the data sets, the method of collision comparison cannot solve the problem well.
Disclosure of Invention
In view of the above, a method, an apparatus, a device and a storage medium for multidimensional spatio-temporal data collision are provided to solve the problems of low data collision efficiency and poor real-time performance in the prior art.
The invention adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a multidimensional spatiotemporal data collision method, where the method includes:
acquiring a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object;
for each first target object, based on the position of a second space station through which each second target object passes, performing space buffer tolerance analysis according to the position of each first space station through which the first target object passes and a preset space tolerance to determine a second target space station in each second space station; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object;
and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object.
In a second aspect, an embodiment of the present application provides a multidimensional spatiotemporal data collision device, which includes:
the data acquisition module is used for acquiring a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object;
the data analysis module is used for carrying out space buffer tolerance analysis on each first target object according to the position of each first space station through which the first target object passes and a preset space tolerance based on the position of each second space station through which the second target object passes so as to determine a second target space station in each second space station; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object;
and the data collision module is used for colliding the collision trajectory data set corresponding to each first target object and determining the same-row result of each first target object and each second target object.
In a third aspect, an embodiment of the present application provides an apparatus, including:
a processor, and a memory coupled to the processor;
the memory is used for storing a computer program for executing at least the multi-dimensional spatiotemporal data collision method according to the first aspect of the embodiments of the present application;
the processor is used for calling and executing the computer program in the memory.
In a fourth aspect, the present application provides a storage medium storing a computer program, which when executed by a processor implements the steps of the multidimensional spatiotemporal data collision method according to the first aspect.
By adopting the technical scheme, the first data set and the second data set to be collided are obtained, and then, for each first target object, based on the position of the second space station through which each second target object passes, the spatial buffering tolerance analysis is carried out according to the position of each first space station through which each first target object passes and the preset spatial tolerance so as to determine the second target space station in each second space station, so that the first screening is carried out, and the relevant data of the second space station meeting the requirements on the spatial level are determined; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object, performing secondary screening in this way, and determining related data of the second space station which meets requirements in a time level; and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object. Therefore, the collision comparison of all the data to be collided to a small number of space stations and data sets within the time tolerance range of the stations is performed, the collision data volume is reduced, a large amount of calculation and storage resources do not need to be occupied, the efficiency of the collision comparison of the multidimensional space-time data is greatly improved, and the real-time performance is good.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a multi-dimensional spatiotemporal data collision method according to an embodiment of the present invention;
FIG. 2 is a flow chart of another multi-dimensional spatiotemporal data collision method provided by an embodiment of the invention;
FIG. 3 is a schematic structural diagram of a multi-dimensional spatiotemporal data collision device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
First, data collision applied in the embodiment of the present application will be explained. The data collision analysis is a method for analyzing data by using a computer, combing more than two groups of data sets of the same type, and screening the data sets to obtain intersection through correlation query. For example, in the public security field, data collision analysis refers to a method for supporting police work such as detecting and solving cases, searching for more than two sets of data sets such as vehicle tracks by using known conditions, comparing cross collisions between the data sets by using a computer technology, and performing discrimination analysis on intersection data generated by the comparison.
Examples
FIG. 1 is a flowchart of a multi-dimensional spatiotemporal data collision method according to an embodiment of the present invention, which can be implemented by the multi-dimensional spatiotemporal data collision apparatus according to an embodiment of the present invention, and the apparatus can be implemented in software and/or hardware. Referring to fig. 1, the method may specifically include the following steps:
s101, a first data set and a second data set to be collided are obtained.
Specifically, two groups of data are generally subjected to collision comparison to determine the association relationship of the data in the current application scenario, where two data sets are used as an example, when there are multiple data sets, two of the data sets may be selected to perform data collision, and then the obtained result may be applied to perform collision with other data sets.
The first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object. Optionally, the first space station is a monitoring gate or a communication base station, and the second space station is a monitoring gate or a communication base station. In a specific example, the first space station is a monitoring gate, and the first target object is a vehicle; the second space station is a communication base station, and the second target object is a person with a mobile phone. In this example, the location of the handset through the base station may be used to represent the real-time location of the handset or person.
Optionally, the first data set and the second data set are both data of a preset region acquired within a preset time period. The preset first data set and the preset second data set are both from the same preset time period and from the same preset area, so that the data processing efficiency can be improved, and the problem of large data calculation amount caused by collision of data of which the time level and the space level do not meet the conditions is solved.
For example, the preset time period may be 8 to 9 points, and the preset region may be a middle guancun. Assuming that there are 10 monitoring bayonets in the preset area, which are respectively represented by a bayonet a, a bayonet b, a bayonet c, a bayonet d, a bayonet e, a bayonet f, a bayonet g, a bayonet h, a bayonet i and a bayonet j, and all vehicles do not necessarily pass through the bayonets; assuming that there are 10 base stations in the preset area, which are respectively represented by base station J1, base station J2, base station J3, base station J4, base station J5, base station J6, base station J7, base station J8, base station J9, and base station J10, all people do not necessarily pass through these base stations. Assume that 10 vehicles are included in the first data set, denoted as vehicle a, vehicle B, vehicle C, vehicle D, vehicle E, vehicle G, vehicle H, vehicle I, and vehicle J, respectively; assume that the second data set includes 10 people, denoted by A, B, C, D, E, F, G, X, N, and B, respectively.
In a specific example, table 1 shows 10 pieces of data in the first data set, that is, which vehicle passes through which gate at what time, which may be denoted as X; table 2 shows 10 pieces of data in the second data set, i.e. which person passed through which base station at what time, which can be denoted as Y. Here, the person refers to a person with a mobile phone.
TABLE 1 data records of a first data set
| Data numbering | First target object | Bayonet | Elapsed time |
| 1 | Vehicle A | Bayonet a | 8:00:00 |
| 2 | Vehicle B | Bayonet c | 8:01:01 |
| 3 | Vehicle C | Bayonet f | 8:02:15 |
| 4 | Vehicle D | Bayonet h | 8:15:07 |
| 5 | Vehicle E | Bayonet d | 8:23:15 |
| 6 | Vehicle F | Bayonet b | 8:23:15 |
| 7 | Vehicle G | Bayonet g | 8:29:55 |
| 8 | Vehicle H | Bayonet i | 8:38:16 |
| 9 | Vehicle I | Bayonet j | 8:41:25 |
| 10 | Vehicle J | Bayonet e | 8:59:15 |
TABLE 2 data records of a second data set
| Data numbering | Second target object | Bayonet | Elapsed time |
| 11 | First of all | Base station J1 | 8:00:01 |
| 12 | Second step | Base station J5 | 8:01:05 |
| 13 | C3 | Base station J8 | 8:01:15 |
| 14 | T-shirt | Base station J2 | 8:09:07 |
| 15 | Wu Ying (five-element) | Base station J9 | 8:11:22 |
| 16 | Has already got | Base station J6 | 8:19:15 |
| 17 | G type | Base station J7 | 8:22:45 |
| 18 | Pungent food | Base station J4 | 8:35:16 |
| 19 | None | Base station J10 | 8:29:25 |
| 20 | Hair removing device | Base station J3 | 8:52:08 |
S102, for each first target object, based on the position of a second space station through which each second target object passes, performing space buffer tolerance analysis according to the position of each first space station through which the first target object passes and a preset space tolerance to determine a second target space station in each second space station; and based on the time of each second target object passing through the second space station, performing time buffer tolerance analysis on the second target space station according to the time of each first space station passing through by the first target object and a preset time tolerance so as to determine a collision track data set corresponding to the first target object.
Still in the above example, if the first target object is the vehicle a, the step is described by taking the vehicle a as an example, that is, in the first data set, all data related to the vehicle a, denoted as X1, are first selected, and then the data in the second data set is analyzed based on each piece of data of the vehicle a. Here, the data that the vehicle a passes through the gate a at 8 points is explained, and the same processing is applied to other data of the vehicle a or data of other vehicles.
In this specific example, the first step is to perform spatial buffer tolerance analysis on the data in the second data set according to a preset spatial tolerance, that is, to perform the first screening, and the second spatial site in the screened result is referred to as a second target spatial site. Specifically, taking the data that the vehicle a passes through the gate a at 8 points as an example, at this time, the position of each base station that each person passes through and the position of the gate a are combined with a preset spatial tolerance to perform spatial buffering tolerance analysis, a part of second spatial station stations and corresponding data whose spatial positions do not meet the requirements are filtered, and the rest are called as second target spatial stations and are marked as X11.
And secondly, performing time buffer tolerance analysis, namely, screening for the second time on the data in the second data set corresponding to the second target space station according to the preset time tolerance. Specifically, the time elapsed by each person in the second target space station and the 8 points are combined with the preset time tolerance to perform time buffer tolerance analysis, so that the second space station with a part of time not meeting the requirement and the corresponding data are filtered. Therefore, the result obtained by screening the second data set with the data that the vehicle a passes through the checkpoint a at 8 points as the reference is obtained, and then, the processing of the first step and the second step is performed on each piece of data related to the vehicle a, so that the collision trajectory data set corresponding to the vehicle a is obtained.
S103, collision is carried out on the collision track data set corresponding to each first target object, and the results of the same row of each first target object and each second target object are determined.
Specifically, at least one corresponding collision trajectory data set can be calculated for each target object, and then data collision is performed according to use requirements, for example, the vehicle a appears in 4 checkpoints between 8 points and 8:20, the vehicle a appears in 6 base stations between 8 points and 8:20, the positions of the 4 checkpoints and the positions of the 6 base stations meet a preset spatial tolerance, and the time of occurrence of the two stations meets a preset time tolerance. At this time, it is determined that the vehicle a and the first are in the same-line relationship.
Exemplary, commonly used "data collision analysis" methods are mainly: firstly, collision is carried out by utilizing the powerful table processing function of EXCEL; utilizing an Access database SQL language to perform collision; the collision is performed by using universal collision software such as BCompare. The application range of data collision mainly comprises: case investigation, personnel arrest or other public security management, etc. For example, the peer relationship in the above example can be applied to a scenario in which only the mobile phone communication information is acquired, but the suspected object is not clear, and the case is a current scurry case. In the embodiment of the present application, any of the above data collision methods may be applied, and is not limited herein.
By adopting the technical scheme, the first data set and the second data set to be collided are obtained, and then, for each first target object, based on the position of the second space station through which each second target object passes, the spatial buffering tolerance analysis is carried out according to the position of each first space station through which each first target object passes and the preset spatial tolerance so as to determine the second target space station in each second space station, so that the first screening is carried out, and the relevant data of the second space station meeting the requirements on the spatial level are determined; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object, performing secondary screening in this way, and determining related data of the second space station which meets requirements in a time level; and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object. Therefore, the collision comparison of all the data to be collided to a small number of space stations and data sets within the time tolerance range of the stations is performed, the collision data volume is reduced, a large amount of calculation and storage resources do not need to be occupied, the efficiency of the collision comparison of the multidimensional space-time data is greatly improved, and the real-time performance is good.
FIG. 2 is a flowchart of a multi-dimensional spatiotemporal data collision method according to another embodiment of the present invention, which is implemented on the basis of the above embodiments. Referring to fig. 2, the method may specifically include the following steps:
s201, a first data set and a second data set to be collided are obtained.
S202, aiming at each first target object, determining the position of each first space station through which the first target object passes, and aiming at each first space station, screening out a second space station, of the second space stations through which each second target object passes, of which the position difference with the first space station is smaller than a preset space tolerance, as a second target space station; determining the time of the first target object passing each first space station, and screening out a second target space station with the time difference with the first space station smaller than a preset time tolerance from each second target space station as a third target space station aiming at each passing time; and taking the data set matched by the third target space station in the second data set as a collision track data set corresponding to the first target object.
Specifically, still taking the data in table 1 and table 2 as an example, the vehicle a passes through the gate a at 8 points, and regarding the data of the vehicle a and the gate a, in table 2, with reference to the position of the gate a, the base stations whose distance from the gate a is smaller than the preset spatial tolerance are screened out as the second target space stations, for example, the screened base stations in table 2 are J1, J3, J4, J8, and J10. In a specific example, the predetermined spatial tolerance is denoted as d, d is a constant representing a distance, such as 100 meters, i.e. the distance between the positions of the 5 base stations and the position of the mount a is less than 100 meters. Thus, 4 data items numbered 11, 13, 14 and 16 are screened from the second data set. Then, based on the time at 8 points and a preset time tolerance, for example, 20 minutes, the 4 pieces of data all meet the time tolerance condition. Thus, such third target space sites are J1, J2, J6 and J8; in a specific example, the preset time tolerance is denoted as s, s is a parameter indicating time, for example, 15 minutes, and the collision trajectory data set corresponding to the vehicle a is the data set of the 4 base stations. Similarly, the above processing is performed for each piece of data in the first data set.
S203, calculating the number of times of the same row of each first target object and each second target object according to the collision track data set corresponding to each first target object.
Specifically, the vehicle a corresponds to a collision trajectory data set W1, and the vehicle B corresponds to trajectory data sets W2 and … …. Thus, it was possible to count the occurrence of formazan 2 times in W1, the occurrence of formazan 5 times in W2, and so on. Here, the collision trajectory data set is described only with the vehicle a, and the collision trajectory data set is determined for each of the remaining vehicles.
S204, if the number of times of the same row meets a preset condition of the same row, determining the same row relation of the first target object and the second target object corresponding to the number of times of the same row.
Specifically, if the preset co-traveling condition is more than 3 times, the co-traveling relationship between the vehicle B and the first vehicle can be determined in the above example.
It should be noted that the above example is merely for explanation, and in an actual application, a large amount of data is included, and a case where the vehicle a passes through the gate a and the vehicle B passes through the gate a multiple times is also included. In addition, in the above example, the second data set is data of a person passing through the base station with a mobile phone, and in practical application, the second data set may be data of another vehicle passing through another gate, so that the co-traveling situation between vehicles can be judged.
In the embodiment of the application, in combination with the position of each first space station through which each first target passes, a second station, of second space stations through which each second target object passes, whose position difference from the first space station is smaller than a preset space tolerance is taken as a second target space station; then, continuing screening, taking a second target space station with the time difference with the first space station smaller than the preset time tolerance as a third target space station, and so on, and performing the same processing on the data in each first data set to obtain a collision track data set corresponding to each first target object; and then, the number of times of the same row in the collision process is compared, and the same row relation of the first target object and the second target object is determined, so that the collision and comparison efficiency of the multi-dimensional space-time data is greatly improved.
In addition, in the related art, generally, for different spatial position data among a plurality of data sets, a mapping relationship among the plurality of data sets at different positions is established through preprocessing, the spatial relationship is converted into an attribute relationship, and then cyclic comparison is performed according to an attribute association mode, so as to achieve the purpose of collision comparison. Compared with the prior art, the method and the device can also be applied to multi-thread concurrent analysis to achieve the purpose of rapidly analyzing the result; in addition, attribute association is not needed, and the expandability and the effectiveness of data are improved.
FIG. 3 is a schematic structural diagram of a multi-dimensional spatiotemporal data collision apparatus according to an embodiment of the present invention, which is suitable for performing a multi-dimensional spatiotemporal data collision method according to an embodiment of the present invention. As shown in fig. 3, the apparatus may specifically include: a data acquisition module 301, a data analysis module 302, and a data collision module 303.
The data acquisition module 301 is configured to acquire a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object; a data analysis module 302, configured to perform, for each first target object, based on a position of a second space station through which each second target object passes, spatial buffer tolerance analysis according to the position of each first space station through which the first target object passes and a preset spatial tolerance, so as to determine a second target space station in each second space station; based on the time of each second target object passing through a second space station, performing time buffer tolerance analysis on the second target space station according to the time of each first space station passing through by the first target object and a preset time tolerance so as to determine a collision track data set corresponding to the first target object; the data collision module 303 is configured to collide the collision trajectory data set corresponding to each first target object, and determine the results of the same row of each first target object and each second target object.
By adopting the technical scheme, the first data set and the second data set to be collided are obtained, and then, for each first target object, based on the position of the second space station through which each second target object passes, the spatial buffering tolerance analysis is carried out according to the position of each first space station through which each first target object passes and the preset spatial tolerance so as to determine the second target space station in each second space station, so that the first screening is carried out, and the relevant data of the second space station meeting the requirements on the spatial level are determined; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object, performing secondary screening in this way, and determining related data of the second space station which meets requirements in a time level; and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object. Therefore, the collision comparison of all the data to be collided to a small number of space stations and data sets within the time tolerance range of the stations is performed, the collision data volume is reduced, a large amount of calculation and storage resources do not need to be occupied, the efficiency of the collision comparison of the multidimensional space-time data is greatly improved, and the real-time performance is good.
Further, the data analysis module includes a first data analysis submodule and a second data analysis submodule, and the first data analysis submodule is specifically configured to:
and for each first target object, determining the position of each first space station through which the first target object passes, and screening out a second space station, of the second space stations through which each second target object passes, of which the position difference with the first space station is smaller than a preset space tolerance, as a second target space station.
Further, the second data analysis sub-module is specifically configured to:
for each first target object, determining the time of the first target object passing each first space station, and for each passing time, screening out second space stations of which the time difference of the first space stations in the second space stations through which each second target object passes is smaller than a preset time tolerance; and taking a data set matched by the second space station in the second data set as a collision track data set corresponding to the first target object.
Further, the data collision module 303 is specifically configured to:
calculating the number of times of the same row of each first target object and each second target object according to the collision track data set corresponding to each first target object;
and if the number of times of the same row meets a preset same row condition, determining the same row relation of the first target object and the second target object corresponding to the number of times of the same row.
Further, the first data set and the second data set are both data of a preset area acquired within a preset time period.
Further, the first space station is a monitoring gate or a communication base station, and the second space station is a monitoring gate or a communication base station.
The multi-dimensional spatiotemporal data collision device provided by the embodiment of the invention can execute the multi-dimensional spatiotemporal data collision method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
An embodiment of the present invention further provides an apparatus, please refer to fig. 4, where fig. 4 is a schematic structural diagram of an apparatus, and as shown in fig. 4, the apparatus includes: a processor 410, and a memory 420 coupled to the processor 410; the memory 420 is used for storing a computer program for performing at least the multi-dimensional spatiotemporal data collision method in the embodiment of the present invention; the processor 410 is used to invoke and execute computer programs in memory; the multi-dimensional spatio-temporal data collision method at least comprises the following steps: acquiring a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object; for each first target object, based on the position of the second space station through which each second target object passes, performing spatial buffering tolerance analysis according to the position of each first space station through which the first target object passes and a preset spatial tolerance to determine a second target space station in each second space station; based on the time of each second target object passing through a second space station, performing time buffer tolerance analysis on the second target space station according to the time of each first space station passing through by the first target object and a preset time tolerance so as to determine a collision track data set corresponding to the first target object; and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object.
The embodiment of the present invention further provides a storage medium, where the storage medium stores a computer program, and when the computer program is executed by a processor, the method implements the steps in the method for collision of dimensional spatiotemporal data in the embodiment of the present invention: acquiring a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object; for each first target object, based on the position of the second space station through which each second target object passes, performing spatial buffering tolerance analysis according to the position of each first space station through which the first target object passes and a preset spatial tolerance to determine a second target space station in each second space station; based on the time of each second target object passing through a second space station, performing time buffer tolerance analysis on the second target space station according to the time of each first space station passing through by the first target object and a preset time tolerance so as to determine a collision track data set corresponding to the first target object; and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that the terms "first," "second," and the like in the description of the present invention are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present invention, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A multi-dimensional spatiotemporal data collision method is characterized by comprising the following steps:
acquiring a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object;
for each first target object, based on the position of a second space station through which each second target object passes, performing space buffer tolerance analysis according to the position of each first space station through which the first target object passes and a preset space tolerance to determine a second target space station in each second space station; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object;
and carrying out collision on the collision track data set corresponding to each first target object, and determining the results of the same row of each first target object and each second target object.
2. The method according to claim 1, wherein for each first target object, based on the position of the second spatial site through which the respective second target object passes, performing spatial buffer tolerance analysis according to the position of the respective first spatial site through which the first target object passes and a preset spatial tolerance to determine a second target spatial site in the respective second spatial site, comprises:
and for each first target object, determining the position of each first space station through which the first target object passes, and screening out a second space station, of second space stations through which the second target object passes, of which the position difference with the first space station is smaller than a preset space tolerance, as a second target space station.
3. The method of claim 2, wherein for each first target object, performing a time buffer tolerance analysis according to the time of the respective first space station passed by the first target object and a preset time tolerance based on the time of the respective second target space station passed by the respective second target object to determine a collision trajectory data set corresponding to the first target object comprises:
for each first target object, determining the time of the first target object passing each first space station, and for each passing time, screening out a second target space station, of the second target space stations, of which the time difference with the first space station is smaller than a preset time tolerance, as a third target space station; and taking a data set matched by the third target space station in the second data set as a collision track data set corresponding to the first target object.
4. The method of claim 1, wherein the step of colliding the collision trajectory data set corresponding to each first target object and determining the results of the same row of each first target object and each second target object comprises:
calculating the number of times of the same row of each first target object and each second target object according to the collision track data set corresponding to each first target object;
and if the number of times of the same row meets a preset same row condition, determining the same row relation of the first target object and the second target object corresponding to the number of times of the same row.
5. The method of claim 1, wherein the first data set and the second data set are both data of a preset area acquired within a preset time period.
6. The method of claim 1, wherein the first space station is a monitoring gate or a communication base station, and the second space station is a monitoring gate or a communication base station.
7. A multi-dimensional spatiotemporal data collision device, comprising:
the data acquisition module is used for acquiring a first data set and a second data set to be collided; the first data set comprises positions and elapsed time of first space stations passed by each first target object, and the second data set comprises positions and elapsed time of second space stations passed by each second target object;
the data analysis module is used for carrying out space buffer tolerance analysis on each first target object according to the position of each first space station through which the first target object passes and a preset space tolerance based on the position of each second space station through which the second target object passes so as to determine a second target space station in each second space station; based on the time of each second target object passing through a second target space station, performing time buffer tolerance analysis according to the time of each first target object passing through each first space station and a preset time tolerance to determine a collision trajectory data set corresponding to the first target object;
and the data collision module is used for colliding the collision trajectory data set corresponding to each first target object and determining the same-row result of each first target object and each second target object.
8. The apparatus of claim 7, wherein the data analysis module comprises a first data analysis sub-module and a second data analysis sub-module, the first data analysis sub-module being specifically configured to:
and for each first target object, determining the position of each first space station through which the first target object passes, and screening out a second space station, of second space stations through which the second target object passes, of which the position difference with the first space station is smaller than a preset space tolerance, as a second target space station.
9. An apparatus, comprising:
a processor, and a memory coupled to the processor;
the memory for storing a computer program for performing at least the multi-dimensional spatiotemporal data collision method of any one of claims 1-6;
the processor is used for calling and executing the computer program in the memory.
10. A storage medium storing a computer program which, when executed by a processor, performs the steps of the method of collision of multidimensional spatiotemporal data according to any one of claims 1 to 6.
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