CN109698942A - A kind of planning operational method of public security video and bayonet reconnaissance optimization - Google Patents
A kind of planning operational method of public security video and bayonet reconnaissance optimization Download PDFInfo
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Abstract
The present invention discloses the planning operational method of a kind of public security video and bayonet reconnaissance optimization, the present invention is based on the data in existing Police Geographic Information System, it is guiding with actual monitored video designs addressing demand, utilize PGIS system, establish public security video and bayonet reconnaissance model, and by model and electronic map match, visual video optimized distribution map is obtained.The present invention utilizes the data resource accumulated for a long time, in conjunction with the requirement of actual police work, the operating method of optimization video and bayonet addressing is proposed, model is closely concluded from practice, avoids the risk brought by application that loses contact with reality because of selected factor, the mathematical model of foundation.
Description
Technical field
The present invention relates to the technical fields of the GIS-Geographic Information System of public safety, in particular with space planning algorithm mould
Type, to plan the planning operational method of public security video and bayonet reconnaissance optimization.
Background technique
Currently, domestic aspect need to generally set the quantity and service half of facility covering though overlay model is widely used
Diameter, and position candidate and Video service radius, therefore overlay model pair can only be previously set for public security video (bayonet) planning
Adaptability is also lacked in public security social security video (bayonet) planning.
External aspect, Robert Bodor, Andrew Drenner (2007) etc. are considering dynamic change areas case, are mentioning
It is a kind of out to be directed to small range area video point optimal configuration algorithm.SamerHanoun, Asim Bhatti etc. (2014) is with ginseng
The number regulation practical coverage area of video surveillance point is monitored video in combination with simulated annealing and neighborhood generating function
Planning.(2014) such as Khaled A, Amrik propose maximum revenue and cost minimization principle, determine region all standing when institute
Monitor video point quantity needed for the monitor video point quantity needed, and covering key area, determines with SmartMax algorithm
Video point programme.
Though existing video planing method has certain reasonability, some also utilizes GIS data and participates in planning, its
There are also lacking in the versatility of method and the normalization of mathematical model, it to be applied to public security social security video (bayonet) choosing
On location, still there is deficiency；Social security video (bayonet) serves primarily in public safety industry, and physical planning must also be with public security public security
" beat, prevent, managing, controlling " business tight association.
Summary of the invention
The main object of the present invention is the planning operational method for proposing a kind of public security video and bayonet reconnaissance optimization, it is intended to
Overcome problem above.
To achieve the above object, the planning operational method of a kind of public security video proposed by the present invention and bayonet reconnaissance optimization,
Include the following steps:
S1. " people, vehicle, case, commercial circle, key unit " five elements are obtained from Police Geographic Information System, and be respectively set
Weighted value；
S2. in the Police Geographic Information System described in S1, step S21, S22, S23, S24, S25 are successively executed；
S21. by the data information of five elements described in S1, input space weight matrix model is calculated, space weight
Output is as a result, obtain the planning information in public security prevention and control area after matrix model calculates；
S22. using administrative division as basic side, Yi Huan province, ring region county, 4 grades of the ring compact community ring of encirclement, is gradually reduced ring city
4 grades of bayonet fences of principle construction of control range；
S23. on the basis of 4 grades of bayonet fences being set in S22, using video plan model, take " people, vehicle, case into account
Four element of part, commercial circle ", the region for carrying out " capping-fixed point-line " refine controlling planning；
S24. consider the influence that video is planned in urban sprawl, establish expansion model；
S25. be based on space map Map compilation theory, take the expansion model in S24 into account on this basis, by quantizating index,
Parameter, threshold value, spatial aggregation establish accurate video planning space cloth point model, complete automatic point selection and calculating to video,
Export corresponding shape file；
S3. the video and bayonet optimization shape file and electronic map obtained by automatic point selection in S25 and after calculating
Match, obtains the video and bayonet distribution map of optimised reconnaissance.
Preferably, Spatial weight matrix model described in S21 are as follows: Wij=[dij]-α·[βij]b, wherein i, j represent four classes
Each individual in element information, is indicated with the closed figure with boundary；dijRepresent each individual mutually it
Between distance；βijRepresent the ratio that i is accounted for the total boundary length of i by the length on the boundary shared j.
Preferably, 4 grades of bayonet fences in S22 are to first pass through construction quality road to obtain corresponding block with train flow analysis
Mouthful, then get up to form closed loop by adjacent bayonet connection, guarantee to be recorded by bayonet when disengaging closed loop.
Preferably, video plan model described in S23 is divided into capping control model and position control mode；
The calculation formula of model is expanded described in S24 are as follows:
Wherein λiFor flare factor, as i=1, λ1For road network flare factor, as i=2, λ2For unit flare factor；
As i=3, λ3For completed region of the city flare factor；N is planning year；XiTo expand factor total amount, as i=1, X for the year1For
Road network total mileage；As i=2, X2For unit POI sum；As i=3, X3For the City Building gross area；YiFor the previous year
Expansion factor total amount；
Video planning space cloth point model in S25 is divided into bayonet and capping video reconnaissance model, crossing video reconnaissance mould
Type, key unit's reconnaissance model, sdi video plan point set site selection model；The input quantity of video plan model are as follows:
A is region and grade road intersection point collection,
H be Expressway Service, charge station, entrance point set,
R is the intersection point set rejected after the path of internal road,
C is information point point set,
S is that spacing encryption point set is pressed in too long section,
P be Expressway Service, charge station, entrance point,
The expansion model in input quantity combination public security prevention and control area is calculated, and obtains corresponding bayonet and capping video reconnaissance mould
Type, crossing video reconnaissance model, key unit's reconnaissance model, sdi video plan point set site selection model.
Preferably, the bayonet and capping video reconnaissance model are as follows:
Preferably, the crossing video reconnaissance model are as follows:
Wherein f (AiRi) it is point selection function, f (ωi, Dij) indicate 4 kinds of selecting predictors functions, ωiIndicate 4 kinds of factor power
Weight, DijIndicate 4 kinds of factor density values at i-th of crossing, g (Ri, Ri-1) two crossing point distance selection sums.
Preferably, key unit's reconnaissance model are as follows:
Wherein, f () indicates that information vertex type selects function, T key unit type.
Preferably, the space planning point set site selection model are as follows:
P=A1∪R1∪C1∪S
F (x) ∈ { 1,2,3...n }, h (x) ∈ { 1,2,3...n }
Wherein: λ1Indicate urban sprawl coefficient, λ2Indicate road flare factor, λ3Indicate unit flare factor, f (ti, γi)
Crossing coefficient sum, tiCrossing type, γiNumber of track-lines, d indicate that section encrypts spacing, LiIndicate road section length, h (ti) indicate single
Potential coefficient function, RiIndicate flat type G1() ask set in number of elements function,Indicate bracket function.
Preferably, capping control model be planning S22 in 4 grades of bayonet fences after, according to basic policing administration unit,
Scattered compact community, small towns street, natural village etc. carry out face covering inspection and leak repairing, guarantee that passing in and out these Regional Road Networks has video point
Distribution；
Preferably, position control mode completes sdi video and layouts according to " fixed point-is screened, and-vacuating-determines coefficient " four steps；
Fixed point is classified to break classification of city, the original deployed to ensure effective monitoring and control of illegal activities entirely according to " intersection+key unit+solid prevention and control point "
Then；
Screening carries out intersection including the use of " people, vehicle, case, commercial circle " four element coverage and hotspot density
Screening determines the intersection for the video that needs to deploy to ensure effective monitoring and control of illegal activities, and according to the rank, importance and scale of unit, screens key unit, presses
Point, bridge, tunnel, overpass, underpass are looked at according to the threshold extraction prefectures and cities Gao Kong of excavation, arranges video from top to bottom
Point；
It vacuates, the minimum spacing threshold value excavated according to big data, to overstocked road, unit, three-dimensional prevention and control space cloth
Point is deleted；
Determining coefficient then includes that cloth dot factor is determined by two crossing type, road track number dimensions, and rank is pressed by key unit
Determine cloth dot factor.
It compares and the prior art, the beneficial effects of the present invention are:
Existing facility site selection model and video site selecting method can not fully meet social security video monitoring addressing at it
In the case where it is required that, the technical program quantizating index, founding mathematical models establish bayonet, video electronic fence；Secondly, from controlling
The actual combat demand of security protection control is set out, and closed loop spatial modeling planing method is constructed, it is ensured that boundary under each space scale,
Route, node have video monitoring to be controlled.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described.It should be evident that the accompanying drawings in the following description is only this
The section Example of invention to those skilled in the art without creative efforts, can also be according to this
A little attached drawings obtain other attached drawings.
Fig. 1 is the flow chart of planing method of the present invention；
The embodiments will be further described with reference to the accompanying drawings for technological means and technical effect of the invention.
Specific embodiment
Below in conjunction with attached drawing of the invention, technical solution in the embodiment of the present invention carries out clear, complete, in detail
Description.Obviously, the described embodiments are merely a part of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, those skilled in the art's every other embodiment obtained without creative efforts,
It shall fall within the protection scope of the present invention.
In addition, being somebody's turn to do " first ", " second " etc. if relating to the description of " first ", " second " etc. in the embodiment of the present invention
Description be used for description purposes only, be not understood to indicate or imply its relative importance or implicitly indicate indicated skill
The quantity of art feature." first " is defined as a result, the feature of " second " can explicitly or implicitly include at least one spy
Sign.
The planning operational method of a kind of public security video proposed by the present invention and bayonet reconnaissance optimization, includes the following steps:
The first step obtains " people, vehicle, case, commercial circle, key unit " five elements from Police Geographic Information System, and respectively
Weighted value is set；
Second step, by the data information of five elements in the first step, input space weight matrix model, Wij=[dij]-α·
[βij]bCalculated, wherein i, j represent each individual in four class element informations, with the closed figure with boundary come
It indicates, dijRepresent the mutual distance of each individual, βijRepresenting i, by the length on the boundary shared j to account for the total boundary i long
The ratio of degree；Output is as a result, obtain the planning information in public security prevention and control area after Spatial weight matrix model calculates；
Third step, using administrative division as basic side, Yi Huan province, ring region county, 4 grades of the ring compact community ring of encirclement, gradually contracts at ring city
4 grades of bayonet fences of principle construction of minor control field；4 grades of bayonet fences are to first pass through construction quality road to obtain with train flow analysis
Get up to form closed loop to corresponding bayonet, then by adjacent bayonet connection, guarantees to be recorded by bayonet when disengaging closed loop；
4th step, on the basis of 4 grades of bayonet fences being set in three steps, using video plan model, take into account " people,
Four element of vehicle, case, commercial circle ", the region for carrying out " capping-fixed point-line " refine controlling planning；Video plan model, is divided into
Capping control model and position control mode；
Capping control model, for after 4 grades of bayonet fences in planning S22, according to basic policing administration unit, scattered poly-
The covering inspection of the carry out faces such as area, small towns street, natural village and leak repairing are occupied, guarantees that passing in and out these Regional Road Networks has the distribution of video point；
Position control mode completes sdi video and layouts according to " fixed point-is screened, and-vacuating-determines coefficient " four steps；Fixed point is to break city
Classification, the principle deployed to ensure effective monitoring and control of illegal activities entirely according to " intersection+key unit+solid prevention and control point "；Screening including the use of " people, vehicle,
Four element coverage of case, commercial circle " and hotspot density screen intersection, determine the road for the video that needs to deploy to ensure effective monitoring and control of illegal activities
Intersection key unit is screened, according to the threshold extraction prefectures and cities high-altitude of excavation according to the rank, importance and scale of unit
Point, bridge, tunnel, overpass, underpass are looked at, arranges video point from top to bottom；It vacuates, is excavated according to big data
The minimum spacing threshold value come is layouted and is deleted to overstocked road, unit, three-dimensional prevention and control space；Coefficient then includes by crossing class
Two type, road track number dimensions determine cloth dot factor, and key unit determines the 5th step of cloth dot factor by rank, by the 4th step
Four models export to Police Geographic Information System with shape format, are matched with electronic map, and video optimized choosing is obtained
Location figure；
5th step considers the influence that video is planned in urban sprawl, establishes expansion model；Expand the calculation formula of model
Are as follows:
Wherein λiFor flare factor, as i=1, λ1For road network flare factor, as i=2, λ2For unit flare factor；
As i=3, λ3For completed region of the city flare factor；N is planning year；XiTo expand factor total amount, as i=1, X for the year1For
Road network total mileage；As i=2, X2For unit POI sum；As i=3, X3For the City Building gross area；YiFor the previous year
Expansion factor total amount；
6th step is based on space map Map compilation theory, takes the expansion model in S24 into account on this basis, is referred to by quantization
Mark, parameter, threshold value, spatial aggregation establish accurate video planning space cloth point model, complete automatic point selection and meter to video
It calculates, exports corresponding shape file；Video planning space cloth point model, is divided into bayonet and capping video reconnaissance model, crossing regard
Frequency reconnaissance model, key unit's reconnaissance model, sdi video plan point set site selection model；The input quantity of video plan model are as follows:
A is region and grade road intersection point collection,
H be Expressway Service, charge station, entrance point set,
R is the intersection point set rejected after the path of internal road,
C is information point point set,
S is that spacing encryption point set is pressed in too long section,
P be Expressway Service, charge station, entrance point,
The expansion model in input quantity combination public security prevention and control area is calculated, and obtains corresponding bayonet and capping video reconnaissance mould
Type, crossing video reconnaissance model, key unit's reconnaissance model, sdi video plan point set site selection model.
Bayonet and capping video reconnaissance model are as follows:
Crossing video reconnaissance model are as follows:
Wherein f (AiRi) it is point selection function, f (ωiDij) indicate 4 kinds of selecting predictors functions, ωiIndicate 4 kinds of factor power
Weight, DijIndicate 4 kinds of factor density values at i-th of crossing, g (Ri, Ri-1) two crossing point distance selection sums.
Key unit's reconnaissance model are as follows:
Wherein, f () indicates that information vertex type selects function, T key unit type.
Space planning point set site selection model are as follows:
P=A1∪R1∪C1∪S
F (x) ∈ { 1,2,3..n }, h (x) ∈ { 1,2,3...n }
Wherein: λ1Indicate urban sprawl coefficient, λ2Indicate road flare factor, λ3Indicate unit flare factor, f (ti, γi)
Crossing coefficient sum, tiCrossing type, γiNumber of track-lines, d indicate that section encrypts spacing, LiIndicate road section length, h (ti) indicate single
Potential coefficient function, RiIndicate flat type G1() ask set in number of elements function,Indicate bracket function.
7th step, the video obtained by automatic point selection in the 6th step and after calculating and bayonet optimization shape file and electronics
Map match obtains the video and bayonet distribution map of optimised reconnaissance.
In the present embodiment, it is set out with police service actual demand, based on the Various types of data accumulated in recent years, Cong Zhongti
Refining and excavation public security video construction patterns, and all kinds of security monitoring inner parameters and installation parameter are had studied to the shadow of scope of sight
It rings, reduces theoretical and actual gap, significantly reduce the risk that conventional method is detached from practice.
The above content is merely a preferred embodiment of the present invention, and is not intended to limit the scope of the invention, all at this
Under the inventive concept of invention, using equivalent structure transformation made by description of the invention and accompanying drawing content, or directly/use indirectly
It is included in other related technical areas in scope of patent protection of the invention.
Claims (10)
1. the planning operational method of a kind of public security video and bayonet reconnaissance optimization, which comprises the steps of:
S1. the data of " people, vehicle, case, commercial circle, key unit " five elements are obtained from Police Geographic Information System, and are set respectively
Set weighted value；
S2. in the Police Geographic Information System described in S1, step S21, S22, S23, S24, S25 are successively executed；
S21. by the data information of five elements described in S1, input space weight matrix model is calculated, Spatial weight matrix
Output is as a result, obtain the planning information in public security prevention and control area after model calculates；
S22. using administrative division as basic side, ring city, ring region county, 4 grades of the ring compact community ring of encirclement, control is gradually reduced in Yi Huan province
4 grades of bayonet fences of principle construction of range；
S23. on the basis of 4 grades of bayonet fences being set in S22, using video plan model, take into account " people, vehicle, case,
Four element of commercial circle ", the region for carrying out " capping-fixed point-line " refine controlling planning；
S24. consider the influence that video is planned in urban sprawl, establish expansion model；
S25. be based on space map Map compilation theory, take the expansion model in S24 into account on this basis, by quantizating index, parameter,
Threshold value, spatial aggregation establish accurate video planning space cloth point model, complete automatic point selection and calculating to video, output phase
The shape file answered；
S3. the video and bayonet optimization shape file and electronic map match obtained by automatic point selection in S25 and after calculating, obtains
To the video and bayonet distribution map of optimised reconnaissance.
2. the method according to claim 1, wherein Spatial weight matrix model described in S21 are as follows: Wij=
[dij]-α·[βij]b, wherein i, j represent each individual in four class element informations, with the closed figure with boundary come
It indicates；dijRepresent the mutual distance of each individual；βijRepresenting i, by the length on the boundary shared j to account for the total boundary i long
The ratio of degree.
3. according to the method described in claim 2, it is characterized in that, 4 grades of bayonet fences in S22, are to first pass through construction quality
Road obtains corresponding bayonet with train flow analysis, then gets up to form closed loop by adjacent bayonet connection, guarantee disengaging closed loop when all
It can be recorded by bayonet.
4. according to the method described in claim 3, it is characterized in that, video plan model described in S23, is divided into capping control mould
Formula and position control mode；
The calculation formula of model is expanded described in S24 are as follows:
Wherein λiFor flare factor, as i=1, λ1For road network flare factor, as i=2, λ2For unit flare factor；Work as i=
When 3, λ3For completed region of the city flare factor；N is planning year；XiTo expand factor total amount, as i=1, X for the year1For road network
Total mileage；As i=2, X2For unit POI sum；As i=3, X3For the City Building gross area；YiFor the previous year expansion
Factor total amount
Video planning space cloth point model in S25, be divided into bayonet and capping video reconnaissance model, crossing video reconnaissance model,
Key unit's reconnaissance model, sdi video plan point set site selection model；The input quantity of video plan model are as follows:
A is region and grade road intersection point collection,
H be Expressway Service, charge station, entrance point set,
R is the intersection point set rejected after the path of internal road,
C is information point point set,
S is that spacing encryption point set is pressed in too long section,
P be Expressway Service, charge station, entrance point,
The expansion model in input quantity combination public security prevention and control area is calculated, obtain corresponding bayonet and capping video reconnaissance model,
Crossing video reconnaissance model, key unit's reconnaissance model, sdi video plan point set site selection model.
5. according to the method described in claim 4, it is characterized in that, the bayonet and capping video reconnaissance model are as follows:
6. according to the method described in claim 4, it is characterized in that, the crossing video reconnaissance model are as follows:
Wherein f (AiRi) it is point selection function, f (ωiDij) indicate 4 kinds of selecting predictors functions, ωiIndicate 4 kinds of Factor Weights, Dij
Indicate 4 kinds of factor density values at i-th of crossing, g (Ri, Ri-1) two crossing point distance selection sums.
7. according to the method described in claim 4, it is characterized in that, key unit's reconnaissance model are as follows:
Wherein, f () indicates that information vertex type selects function, T key unit type.
8. according to the method described in claim 4, it is characterized in that, the sdi video plans point set site selection model are as follows:
P=A1∪R1∪C1∪S
F (x) ∈ { 1,2,3...n }, h (x) ∈ { 1,2,3...n }
Wherein: λ1Indicate urban sprawl coefficient, λ2Indicate road flare factor, λ3Indicate unit flare factor, f (ti, γi) crossing
Coefficient sum, tiCrossing type, γiNumber of track-lines, d indicate that section encrypts spacing, LiIndicate road section length, h (ti) indicate system of units
Number function, RiIndicate flat type G1() ask set in number of elements function,Indicate bracket function.
9. according to claim 5 or 6 or 7 or 8 described in any item planing methods, which is characterized in that the capping control model
For planning S22 in 4 grades of bayonet fences after, according to basic policing administration unit, scattered compact community, small towns street, natural village
Equal carry out face covering checks and leak repairing, guarantees that passing in and out these Regional Road Networks has the distribution of video point.
10. according to claim 5 or 6 or 7 or 8 described in any item planing methods, which is characterized in that the position control mode
According to " fixed point-is screened, and-vacuating-determines coefficient " four steps, completes sdi video and layout；
Fixed point is classified to break classification of city, the principle deployed to ensure effective monitoring and control of illegal activities entirely according to " intersection+key unit+solid prevention and control point "；
Screening sieves intersection including the use of " people, vehicle, case, commercial circle " four element coverage and hotspot density
Choosing determines the intersection for the video that needs to deploy to ensure effective monitoring and control of illegal activities, and according to the rank, importance and scale of unit, screens key unit, according to
The threshold extraction prefectures and cities Gao Kong of excavation looks at point, bridge, tunnel, overpass, underpass, arranges video from top to bottom
Point；
It vacuates, the minimum spacing threshold value excavated according to big data, overstocked road, unit, three-dimensional prevention and control space cloth is clicked through
Row is deleted；
Determining coefficient then includes that cloth dot factor is determined by two crossing type, road track number dimensions, and key unit is determined by rank
Cloth dot factor.
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