CN111625591A - Track rule analysis method for realizing information visualization - Google Patents
Track rule analysis method for realizing information visualization Download PDFInfo
- Publication number
- CN111625591A CN111625591A CN202010413429.9A CN202010413429A CN111625591A CN 111625591 A CN111625591 A CN 111625591A CN 202010413429 A CN202010413429 A CN 202010413429A CN 111625591 A CN111625591 A CN 111625591A
- Authority
- CN
- China
- Prior art keywords
- track
- grid
- tracks
- grids
- information visualization
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012800 visualization Methods 0.000 title claims abstract description 32
- 238000004458 analytical method Methods 0.000 title claims abstract description 19
- 230000009191 jumping Effects 0.000 claims abstract description 18
- 238000000034 method Methods 0.000 claims abstract description 15
- 238000012544 monitoring process Methods 0.000 claims abstract description 4
- 230000011218 segmentation Effects 0.000 claims abstract description 4
- 230000000694 effects Effects 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 6
- 230000000007 visual effect Effects 0.000 abstract description 7
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/26—Visual data mining; Browsing structured data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2477—Temporal data queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Probability & Statistics with Applications (AREA)
- Mathematical Physics (AREA)
- Fuzzy Systems (AREA)
- Remote Sensing (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a track rule analysis method for realizing information visualization, which comprises the following steps: step S1, acquiring all tracks collected by the monitoring equipment; step S2, dividing a given geographic space into a plurality of grids; step S3, sorting all the tracks according to time; step S4, determining the grids of each track according to a grid segmentation method; step S5, counting the number n of tracks in each grid; step S6, counting the track jumping times m among different grids; step S7, the acquired information is output and visualized. The method and the device realize efficient analysis of the law information implicit in the track aiming at the mass track with the same characteristics, and realize visual and visual display of the behavior law characteristics implicit in the mass track by displaying the behavior law characteristics implicit in the mass track on the map by using limited circles and straight lines, thereby improving the security analysis efficiency and facilitating the work of security workers.
Description
Technical Field
The invention relates to a track rule analysis method for realizing information visualization, in particular to a track rule analysis method for realizing information visualization.
Background
At present, a plurality of monitoring devices in a security system can acquire a large amount of behavior track data, wherein the behavior track data comprises data such as human faces, MAC, IMSI, IMEI and the like; the behavior rule characteristics of the characteristics are hidden in all track data belonging to the same characteristics, such as information of main activity routes, main activity places and the like, the information plays an important role in scenes of personnel positioning, habit analysis and the like, for a large amount of track data of a given characteristic, the hidden rule information in the track cannot be efficiently analyzed in the prior art, visual display of the analyzed rule information cannot be realized, troubles are caused to the work of security workers, and the security analysis efficiency is low.
Accordingly, the prior art is deficient and needs improvement.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a track rule analysis method for realizing information visualization.
The technical scheme of the invention is as follows:
a track law analysis method for realizing information visualization comprises the following steps:
step S1, acquiring all tracks collected by the monitoring equipment;
step S2, dividing a given geographic space into a plurality of grids;
step S3, sorting all the tracks according to time;
step S4, determining the grids of each track according to a grid segmentation method;
step S5, counting the number n of tracks in each grid;
step S6, counting the track jumping times m among different grids;
step S7, the acquired information is output and visualized.
Further, the trajectory obtained in step S1 includes one or more of face data, MAC data, IMSI data, and IMEI data.
Further, the step S2 is implemented by generating a code with a length of seven through a Geohash algorithm, so as to divide a given geographic space into a plurality of grids.
Further, the step S2 is implemented by reserving codes formed by three decimal places of longitude and latitude, so as to divide the given geographic space into a plurality of grids.
Further, the implementation manner of step S4 is to generate a code with a length of seven by using a Geohash algorithm according to the longitude and latitude of each track, so as to determine the grid to which the track belongs.
Further, the step S4 is implemented by reserving codes formed by three digits after the decimal point of the longitude and latitude of each track, so as to determine the grid to which the track belongs.
Further, the step S6 is realized by each track tiThe associated grid giThe number of the tracks is increased by one and then is matched with the grid g which the previous track belongs toi-1Comparing to realize the statistics of the track jumping times m among different grids;
wherein, if grid gi-1Not equal to grid giI.e. gi-1And giIs two grids, grid gi-1To grid giThe track jumping times between the two is increased by one, otherwise, the jumping is not carried out.
Further, the step S7 is implemented by outputting the number n of tracks per grid and the number m of track jumps between different grids, and performing visualization processing on the map according to the output number n of tracks and the number m of track jumps, where the visualization processing includes track information visualization and route information visualization.
Furthermore, each grid is represented by a circle on the map, wherein the circle center is the center of the grid, the radius r is in direct proportion to the number n of the tracks contained in the grid, and the radius r and the number n of the tracks meet the formula r being 2+ log (n), that is, the main activity site of the target object is visually and visually displayed through the area with the larger circle in the map.
Further, the route information visualization is realized by adopting a straight line on a map to represent a track jumping relation between different grids, wherein a line width c of the straight line is in direct proportion to a track jumping frequency m, the line width c of the straight line and the jumping frequency m of a track cluster meet a formula c being 1+ log (m), namely, a main activity route of a display target object is visually visualized through a thicker straight line in the map.
By adopting the scheme, the invention has the following beneficial effects:
the method and the device realize efficient analysis of the law information implicit in the track aiming at the mass track with the same characteristics, and realize visual and visual display of the behavior law characteristics implicit in the mass track by displaying the behavior law characteristics implicit in the mass track on the map by using limited circles and straight lines, thereby improving the security analysis efficiency and facilitating the work of security workers.
Drawings
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 structures shown in the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a trajectory regularity analysis method for implementing information visualization according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The invention is described in detail below with reference to the figures and the specific embodiments.
Referring to fig. 1, the present invention provides a trajectory regularity analysis method for implementing information visualization, including the following steps:
step S1, acquiring all tracks collected by the monitoring equipment;
step S2, dividing a given geographic space into a plurality of grids;
step S3, sorting all the tracks according to time;
step S4, determining the grids of each track according to a grid segmentation method;
step S5, counting the number n of tracks in each grid;
step S6, counting the track jumping times m among different grids;
step S7, the acquired information is output and visualized.
In this embodiment, the trajectory obtained in step S1 includes one or more of face data, MAC data, IMSI data, and IMEI data.
In this embodiment, the implementation of step S2 is to generate a code with a length of seven by using a Geohash algorithm, so that a given geographic space can be divided into a number of grids of about 150 meters by 150 meters;
the step S4 is implemented by generating a code with a length of seven by using a Geohash algorithm according to the longitude and latitude of each track, so as to determine the grid to which the track belongs.
In another preferred embodiment, the step S2 is implemented by reserving codes formed by three digits after the decimal point of longitude and latitude, that is, the codes corresponding to the longitude and latitude (112.708439, 23.342711) are 11270823342, so that the given geographic space can be divided into a plurality of grids of about 100 meters by 100 meters;
the step S4 is implemented by reserving codes formed by three digits after the decimal point of the longitude and latitude of each track, so as to determine the grid to which the track belongs.
In the present embodiment, the step S6 is realized by each track tiThe associated grid giThe number of the tracks is increased by one and then is matched with the grid g which the previous track belongs toi-1Comparing to realize the statistics of the track jumping times m among different grids; in particular, if grid gi-1Not equal to grid giI.e. grid gi-1And grid giIs two grids, grid gi-1To grid giThe track jumping times between the two paths are increased by one, otherwise, the two paths are not jumped;
it is worth mentioning that each grid corresponds to a code, so that the grid g can be comparedi-1And grid giWhether the codes of (a) are the same or not to judge the grid gi-1And grid giThe relationship (2) of (c).
In this embodiment, the step S7 is implemented by outputting the number n of tracks per grid and the number m of track jumps between different grids, and performing visualization processing on the map according to the output number n of tracks and the number m of track jumps, where the visualization processing includes track information visualization and route information visualization;
furthermore, each grid is represented by a circle on a map, wherein the circle center is the center of the grid, the radius r is in direct proportion to the number n of tracks contained in the grid, and the radius r and the number n of tracks meet the formula r being 2+ log (n), namely, the main activity site of the target object is visually and visually displayed through the area with the larger circle in the map;
further, the route information visualization is realized by adopting a straight line on a map to represent the track jumping relation between different grids, wherein the line width c of the straight line is in direct proportion to the track jumping times m, the line width c of the straight line and the jumping times m of the track cluster meet the formula c being 1+ log (m), namely, the main activity route of the target object is visually visualized through the thicker straight line in the map.
Compared with the prior art, the invention has the following beneficial effects:
the method and the device realize efficient analysis of the law information implicit in the track aiming at the mass track with the same characteristics, and realize visual and visual display of the behavior law characteristics implicit in the mass track by displaying the behavior law characteristics implicit in the mass track on the map by using limited circles and straight lines, thereby improving the security analysis efficiency and facilitating the work of security workers.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A track law analysis method for realizing information visualization is characterized by comprising the following steps:
step S1, acquiring all tracks collected by the monitoring equipment;
step S2, dividing a given geographic space into a plurality of grids;
step S3, sorting all the tracks according to time;
step S4, determining the grids of each track according to a grid segmentation method;
step S5, counting the number n of tracks in each grid;
step S6, counting the track jumping times m among different grids;
step S7, the acquired information is output and visualized.
2. The trajectory rules analysis method for realizing information visualization according to claim 1, wherein the trajectory obtained in step S1 includes one or more of face data, MAC data, IMSI data, and IMEI data.
3. The method for analyzing trajectory rules for visualizing information as in claim 1, wherein said step S2 is implemented by generating a code with a length of seven through a Geohash algorithm, so as to divide a given geographic space into a plurality of grids.
4. The method for analyzing trajectory rules for visualizing information as in claim 1, wherein said step S2 is implemented by preserving the codes of three decimal places of longitude and latitude, so as to divide the given geographic space into several grids.
5. The method for analyzing track rules for realizing information visualization according to claim 3, wherein the step S4 is implemented by generating a code with a length of seven according to the longitude and latitude of each track by using a Geohash algorithm, so as to determine the grid to which the track belongs.
6. The method for analyzing track rules for realizing information visualization according to claim 4, wherein the step S4 is implemented by reserving codes formed by three digits after the decimal point of the longitude and latitude of each track, so as to determine the grid to which the track belongs.
7. The method for analyzing track regularity by visualizing information as claimed in claim 1, wherein the step S6 is implemented by using each track tiThe associated grid giThe number of the tracks is increased by one and then is matched with the grid g which the previous track belongs toi-1Comparing to realize the statistics of the track jumping times m among different grids;
wherein, if grid gi-1Not equal to grid giI.e. gi-1And giIs two grids, grid gi-1To grid giThe track jumping times between the two is increased by one, otherwise, the jumping is not carried out.
8. The method for analyzing track rules for realizing information visualization according to claim 1, wherein the step S7 is implemented by outputting the number n of tracks per grid and the number m of track jumps between different grids, and performing visualization processing on the map according to the output number n of tracks and the number m of track jumps, wherein the visualization processing includes track information visualization and route information visualization.
9. The method for analyzing track rules for realizing information visualization according to claim 8, wherein the track information visualization is realized by representing each grid by a circle on a map, wherein a circle center is a center of the grid, a radius r is proportional to a number n of tracks included in the grid, and the radius r and the number n of tracks satisfy a formula r-2 + log (n), that is, a main activity place for displaying the target object visually visualized through a region with a larger circle in the map.
10. The method for analyzing track laws for realizing information visualization according to claim 8, wherein the route information visualization is realized by using a straight line on a map to represent a track jump relationship between different grids, wherein a line width c of the straight line is proportional to a track jump time m, and the line width c of the straight line and the track jump time m of a track cluster satisfy a formula c-1 + log (m), that is, a main active route of a target object is visually visualized through a thicker straight line in the map.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010413429.9A CN111625591A (en) | 2020-05-15 | 2020-05-15 | Track rule analysis method for realizing information visualization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010413429.9A CN111625591A (en) | 2020-05-15 | 2020-05-15 | Track rule analysis method for realizing information visualization |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111625591A true CN111625591A (en) | 2020-09-04 |
Family
ID=72260597
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010413429.9A Pending CN111625591A (en) | 2020-05-15 | 2020-05-15 | Track rule analysis method for realizing information visualization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111625591A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170010101A1 (en) * | 2015-07-06 | 2017-01-12 | International Business Machines Corporation | Hybrid road network and grid based spatial-temporal indexing under missing road links |
| CN109446264A (en) * | 2018-09-10 | 2019-03-08 | 桂林电子科技大学 | One kind is based on the visual city mobile data analysis method of stream |
| CN109947758A (en) * | 2019-04-03 | 2019-06-28 | 深圳市甲易科技有限公司 | A kind of route crash analysis method in Behavior-based control track library |
| CN110019175A (en) * | 2019-04-03 | 2019-07-16 | 深圳市甲易科技有限公司 | A kind of region crash analysis method in Behavior-based control track library |
| CN110334171A (en) * | 2019-07-05 | 2019-10-15 | 南京邮电大学 | It is a kind of based on the space-time of Geohash with object method for digging |
| CN111143500A (en) * | 2019-12-27 | 2020-05-12 | 中国联合网络通信集团有限公司 | Visualized area calculation method, terminal, control device and storage medium |
-
2020
- 2020-05-15 CN CN202010413429.9A patent/CN111625591A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170010101A1 (en) * | 2015-07-06 | 2017-01-12 | International Business Machines Corporation | Hybrid road network and grid based spatial-temporal indexing under missing road links |
| CN109446264A (en) * | 2018-09-10 | 2019-03-08 | 桂林电子科技大学 | One kind is based on the visual city mobile data analysis method of stream |
| CN109947758A (en) * | 2019-04-03 | 2019-06-28 | 深圳市甲易科技有限公司 | A kind of route crash analysis method in Behavior-based control track library |
| CN110019175A (en) * | 2019-04-03 | 2019-07-16 | 深圳市甲易科技有限公司 | A kind of region crash analysis method in Behavior-based control track library |
| CN110334171A (en) * | 2019-07-05 | 2019-10-15 | 南京邮电大学 | It is a kind of based on the space-time of Geohash with object method for digging |
| CN111143500A (en) * | 2019-12-27 | 2020-05-12 | 中国联合网络通信集团有限公司 | Visualized area calculation method, terminal, control device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Hjalmars et al. | Childhood leukaemia in Sweden: using GIS and a spatial scan statistic for cluster detection | |
| CN106708955B (en) | Thermodynamic diagram generation method and equipment | |
| CN103020222B (en) | For the visual method for digging of vehicle GPS data analysis and exception monitoring | |
| Scholz et al. | Detection of dynamic activity patterns at a collective level from large-volume trajectory data | |
| Giovanella et al. | The family health strategy coverage in Brazil: what reveal the 2013 and 2019 national health surveys | |
| Aziz et al. | Spatial pattern of 2009 dengue distribution in Kuala Lumpur using GIS application | |
| CN109977109B (en) | Track data accompanying analysis method | |
| CN107563549B (en) | BIM (building information modeling) -based escape path generation method, device and equipment | |
| CN109977108B (en) | Behavior trajectory library-based multi-trajectory collision analysis method | |
| CN104182594A (en) | Method for drawing power system wind area graph | |
| CN110019175B (en) | Regional collision analysis method based on behavior track library | |
| CN111738558B (en) | Visualization method, device, equipment and storage medium for behavior risk identification | |
| CN109947758A (en) | A kind of route crash analysis method in Behavior-based control track library | |
| CN111291216A (en) | Method and system for analyzing foothold based on face structured data | |
| CN111625591A (en) | Track rule analysis method for realizing information visualization | |
| CN117095353B (en) | Dynamic monitoring method, system and medium for combat exercise | |
| CN111400424B (en) | GIS-based automatic identification method and device for abnormal personnel aggregation | |
| CN111581274A (en) | Track rule analysis method for realizing information visualization | |
| CN113011098B (en) | Lightning activity rule analysis display model and system for power transmission corridor area | |
| CN116450958A (en) | Detection point address selection method and device, electronic equipment and readable storage medium | |
| CN111143500A (en) | Visualized area calculation method, terminal, control device and storage medium | |
| CN110837504A (en) | Industrial control system abnormal system event identification method | |
| CN110502424A (en) | A kind of performance data processing method of application software, device, system and terminal | |
| CN115905435A (en) | Signaling data analysis method and device based on space-time polymerization intermediate state | |
| CN113052486A (en) | Monitoring point location layout evaluation method and device, electronic equipment and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200904 |