CN105163343B - Risk judgment method and device that the crowd is dense - Google Patents
Risk judgment method and device that the crowd is dense Download PDFInfo
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- CN105163343B CN105163343B CN201510605316.8A CN201510605316A CN105163343B CN 105163343 B CN105163343 B CN 105163343B CN 201510605316 A CN201510605316 A CN 201510605316A CN 105163343 B CN105163343 B CN 105163343B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
Abstract
The present invention provides a kind of the crowd is dense risk judgment method and device, and wherein method includes：The signaling message that the user equipment in first community is reported in current date is obtained, and determines the number of users in first community in each period；It according to the number of users in each period in first community, determines in N number of period before first time period and first time period, each period increased number of users；According to the number of users in the first time period in M days before first community, the average value of the number of users in first time period before determining in M days；According to the increased number of users and the average value, judge first community in the first time period of current date with the presence or absence of the crowd is dense risk；If in the presence of the user equipment into first community sends intensive indicating risk information.The present invention can more accurately obtain the number of users of cell, more accurately judge cell with the presence or absence of the crowd is dense risk.
Description
Technical field
The present invention relates to the communication technology, more particularly to a kind of the crowd is dense risk judgment method and device.
Background technology
With being constantly progressive for urban development, the activity for being related to dense population is more and more, such as various exhibitions, recruitment
Meeting, competitive sports and concert etc. easily cause the generation of the accidents such as swarm and jostlement.Therefore, close to related occasion progress crowd
Degree statistics is very necessary.In addition, crowd density statistical information is in traffic control, business analysis, festivals or holidays trip number system
Many fields such as meter equally have very important significance.
Currently, all relying on each internet quotient (such as Baidu, high moral) offer greatly to the statistics and analysis of crowd's quantity
Applications client is equipped with the applications client of internet quotient on the mobile terminal that user carries, and internet quotient, which passes through to collect, to be used
The location information that family reports can count some region of crowd's quantity.
It is in place of the deficiencies in the prior art, not every user is assembled with applications client, even if being mounted with visitor
Family end, user may not open and use or not in running backgrounds, therefore cannot accurately count crowd's quantity, also not
Can accurately it judge currently with the presence or absence of the crowd is dense risk.
Invention content
The present invention provides a kind of the crowd is dense risk judgment method and device, to solve to be difficult in the prior art accurately
Statistics crowd quantity, the technical issues of can not accurately judging currently with the presence or absence of the crowd is dense risk.
The present invention provides a kind of the crowd is dense risk judgment method, including：
Obtain the signaling message that is reported in current date of user equipment in first community, and according to the signaling message,
Determine the number of users in each period in first community；
According to the number of users in each period in the first community, first time period and the first time period are determined
In preceding N number of period, each period is relative to the increased number of users of previous time period；
According to the number of users in the first time period before the first community in M days, determine in described first M days
The average value of number of users in the first time period；
According to the increased number of users and it is described first M days in the first time period in number of users
Average value judges the first community in the first time period of the current date with the presence or absence of the crowd is dense risk；
If in the presence of the user equipment into the first community sends intensive indicating risk information.
The present invention also provides a kind of the crowd is dense risk judgment devices, including：
Acquisition module, the signaling message reported in current date for obtaining the user equipment in first community；
First determining module, for according to the signaling message, determining the number of users in each period in first community；
Second determining module, for according to the number of users in each period in the first community, determining at the first time
In N number of period before section and the first time period, each period is relative to the increased number of users of previous time period；
Third determining module is used for according to the number of users in the first time period before the first community in M days,
Determine the average value of the number of users in the first time period in described first M days；
Judgment module, for according to the increased number of users and it is first M days described in the first time period in
Number of users average value, judge the first community in the first time period of the current date whether there is people
The intensive risk of group；
Sending module, for that there are crowds in the first time period of the current date to be close in the first community
When collecting risk, then the user equipment into the first community sends intensive indicating risk information.
The crowd is dense risk judgment method and device provided by the invention is existed by obtaining the user equipment in first community
The signaling message that current date reports, to determine the number of users in first community in each period, according to the first community
In number of users in each period, determine that increased number of users of each period and first time period are flat a few days ago
Equal number of users, and with this come judge the first community current date the first time period with the presence or absence of the crowd is dense
Risk can more accurately obtain the number of users of the first community, more accurately judge the first community in institute
First time period is stated with the presence or absence of the crowd is dense risk.
Description of the drawings
Fig. 1 is the flow chart of the risk judgment method that provides that the crowd is dense of the embodiment of the present invention one；
Fig. 2 is the flow chart of the crowd is dense risk judgment method provided by Embodiment 2 of the present invention；
Fig. 3 is the structural schematic diagram of the risk judgment device that provides that the crowd is dense of the embodiment of the present invention three.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The every other embodiment obtained without creative efforts, shall fall within the protection scope of the present invention.
Embodiment one
The embodiment of the present invention one provides a kind of the crowd is dense risk judgment method.Fig. 1 is what the embodiment of the present invention one provided
The flow chart for risk judgment method that the crowd is dense.It, can be with as shown in Figure 1, the crowd is dense in the present embodiment risk judgment method
Including：
Step 101 obtains the signaling message that the user equipment in first community is reported in current date, and according to the letter
Message is enabled, determines the number of users in each period in first community.
The executive agent of the present embodiment can be network side server, the shifting that network side server can be provided in operator
Acquisition obtains all kinds of signaling messages that user equipment is sent in dynamic communication network.Specifically, described in the basis in this step
Signaling message determines the number of users in each period in first community, can specifically include：
Parse the user identity information carried in the signaling message, cell identity information and time point；According to the use
Family identification information, cell identity information and time point determine the number of users in each period in the first community.
Wherein, the user identity information may include the corresponding cell-phone number of user equipment or IMSI；The cell ID
Information may include the corresponding cell id of cell, in addition, at 2G or 3G network, the cell identity information can also include small
The LAC (Location Area Code, Location Area Code) in area, under 4G networks, the cell identity information can also include small
The TAC (Tracking Area Code track area code) in area.
The cell identity information carried in the signaling message sent according to user equipment, it may be determined that the user equipment is worked as
It is preceding whether in first community；According to user identity information and time point, it may be determined that the first community is each in one day
Number of users in period.Network side server can be according to the first community in each period number of users, come
Judge the first community with the presence or absence of the crowd is dense risk.
Step 102, according to the number of users in each period in the first community, determine first time period and described
In N number of period before one period, each period is relative to the increased number of users of previous time period.
Specifically, can multiple periods be divided by one day according to actual needs, for example, when can be one with every 15 seconds
Between section or every 60 seconds be a period.It, can according to the number of users in the first community in daily each period
With determination each period relative to the increased number of users of previous time period, in practical applications, can be reflected with table every
A period increased number of users, as shown in table 1.
Table 1
| Cell ID | T0 | T1 | T2 | T3 | T4 | T5 | …… |
| 1 | A1 | A2 | A3 | A4 | A5 | A6 | …… |
Wherein, TjJ-th of period in indicating one day, AjFor j-th of period of current date in the first community
Increased number of users, for example, A19For the 19th period increased number of users, A20For the 20th period increased use
Amount amount.In the present embodiment, j-th of period increased number of users refers to j-th of period relative to -1 period of jth
Increased number of users, i.e., the difference of the number of users of -1 period of number of users and jth of j-th period, j=1,2,
3…….When being related to across day, the 1st period increased number of users A of current date1Can be the 1st of current date
The difference of the number of users of a period and the number of users of the last one period of the previous day.Table 1 can form one daily,
The increased number of users of each period for facilitating statistics daily.
In this step, can according to the number of users in each period in the first community, determine first time period and
In N number of period before the first time period, each period is relative to the increased number of users of previous time period.N is certainly
So number, can select according to actual needs, such as N can be 21.The first time period can be current period, example
Such as, it is currently 10 minutes 0 point of mornings, the standard for dividing a period according to every 15 seconds, current slot is the 40th of today
Period, then the first time period is the 40th period.
In order to make it easy to understand, being retouched so that N=21, the first time period are the 40th period as an example in the present embodiment
It states.In this step, it can be searched according to table 1 in the 19th to the 40th period, increased number of users (i.e. A of each period19
To A40)。
Step 103, according to the number of users in the first time period before the first community in M days, determine described in
The average value of the number of users in the first time period in first M days.
Specifically, M is natural number, can be selected according to actual needs, such as M can be 7.According to the first community
Number of users in first M days in daily special time period, it may be determined that number of users in the first M days special time periods it is flat
Mean, or the average establishes a table, as shown in table 2.
Table 2
| Cell ID | T0 | T1 | T2 | T3 | T4 | T5 | …… |
| 1 | C1 | C2 | C3 | C4 | C5 | C6 | …… |
Wherein, CjFor the average value of the number of users of first M days j-th of period in the first community.For example, C1For
The average value of the number of users of first M days the 1st periods.Table 2 can also form one daily, facilitate j-th of the time of statistics
Historical user's quantity of section.
In the present embodiment, the first time period is the 40th period, therefore, can be according to described the in the present embodiment
Number of users before one cell in M days in daily 40th period determines the number of users in preceding M days the 40th periods
Average C40。
Step 104, according to the increased number of users and it is first M days described in the first time period in use
The average value of amount amount judges that the first community is close with the presence or absence of crowd in the first time period of the current date
Collect risk.
This step is according to the A19To A40With the C40Come in the 40th period with the presence or absence of the crowd is dense risk
It judges.Wherein, the A19To A40When each in several periods for being the 40th period and the front indicated
Between section number of users increasing degree, the C40What is indicated is the number of users of the 40th period in being averaged a few days ago
Value, passes through the A19To A40With the C40It can reflect the increasing value and history average of number of users, therefore, according to
The A19To A40With the C40Come the risk that judges that the crowd is dense, compared to a fixed threshold value come the wind that judges that the crowd is dense
Danger, obtained judging result are more in line with the special properties of the first community, can more accurately reflect that described first is small
Area is in the first time period with the presence or absence of the crowd is dense risk.
Wherein, according to the A19To A40With the C40Come the method for the risk that judges that the crowd is dense can there are many.This implementation
It, can be to the A in example19-A40Judged respectively with the C40, as the A19-A40With the C40Meet certain item respectively
When part, it is believed that risk that the first community has that the crowd is dense.
Specifically, the first community is in the 40th period risk that has that the crowd is dense, A19To A40The item that should meet
Part is：A19To A40In this 22 numerical value, the number of the numerical value more than 0 has reached the first predetermined threshold value, and any two is adjacent
Numerical value at least one be more than 0.If meeting above-mentioned condition, illustrate from the 19th period to the 40th period, institute
The number of users for stating first community is substantially at the state gradually increased, therefore the first community can within the 40th period
There can be the crowd is dense risk, conversely, then illustrate that the number of users increasing degree of the first community is little, it at this time can be temporary
Think the first community there is no the crowd is dense risks within the 40th period.
First predetermined threshold value can be preset according to actual conditions, for example, as N=21, described first is pre-
If threshold value can be 18.
The first community is in the 40th period risk that has that the crowd is dense, C40The condition that should meet is：Described
Number of users of one cell within the 40th period of current date and the C40Between difference be more than the second predetermined threshold value,
Second predetermined threshold value can be preset according to actual conditions.If meeting above-mentioned condition, when illustrating the 40th of current date
Between number of users in section than a few days ago with many more than the number of users of period, therefore the first community is in the 40th period
Interior there may be the crowd is dense risks, conversely, then illustrating number of users in the 40th period of current date compared to preceding
Do not increase significantly within several days, can temporarily think at this time the first community within the 40th period there is no the crowd is dense
Risk.
As the A19-A40With the C40Simultaneously when meeting respective decision condition, it is believed that the first community is the
The risk that has that the crowd is dense in 40 periods；Work as A19-A40It is unsatisfactory for condition or C40When being unsatisfactory for condition, it may be considered that
There is no the crowd is dense risks within the 40th period for the first community.
If step 105, in the presence of user equipment into the first community sends intensive indicating risk information.
Aforementioned several steps in through this embodiment, it can be determined that current slot with the presence or absence of the crowd is dense risk,
In current slot there is no when the crowd is dense risk, can continue to carry out the number of users of cell without any operation
Monitoring can be informed by the intensive indicating risk information described in user if current slot has the crowd is dense risk
There may be the crowd is dense risks for first community, ask user separate as possible.In addition to sending institute to the user in the first community
It states other than intensive indicating risk information, the intensive indicating risk letter can also be sent to the peripheral cell of the first community
Breath.
In addition, when judging the first community risk that has that the crowd is dense, Internet resources can also be scheduled, be
The first community distributes more carryings, link circuit resource, ensures the normal communication of the first community；It can also be by described
There are the departments such as the warning information real-time informing traffic of the crowd is dense risk, public security in one cell, disposed by these departments relevant
Action, alleviates the degree of crowding of the first community；It can also be carried out according to the number of users variation tendency of the first community
Base station and cell capacity-enlarging planning.
In practical applications, the network side server can receive the signaling that the user equipment of multiple cells uploads simultaneously
Message, and judge each cell in multiple cells with the presence or absence of the crowd is dense risk according to the method in the present embodiment.Due to
The number of users in cell is determined by acquiring the signaling message of user equipment to report, in the present embodiment as long as user equipment is opened
Machine will constantly carry out reporting for signaling message, therefore, method described in the present embodiment compared with the existing technology for can be more
Add the number of users accurately obtained in cell.
The crowd is dense risk judgment method provided in this embodiment, by obtaining the user equipment in first community current
The signaling message that date reports, to determine the number of users in first community in each period, according to each in the first community
Number of users in period determines increased number of users of each period and first time period in average use a few days ago
Amount amount, and with this come judge the first community current date the first time period with the presence or absence of the crowd is dense wind
Danger, can more accurately obtain the number of users of the first community, more accurately judge the first community described
First time period is with the presence or absence of the crowd is dense risk.
Embodiment two
Second embodiment of the present invention provides a kind of the crowd is dense risk judgment methods, and the present embodiment is on the basis of embodiment one
On, step 104 is refined.Fig. 2 is the flow chart of the crowd is dense risk judgment method provided by Embodiment 2 of the present invention.
As shown in Fig. 2, the crowd is dense in this implementation risk judgment method, may include：
Step 201 obtains the signaling message that the user equipment in first community is reported in current date, and according to the letter
Message is enabled, determines the number of users in each period in first community.
Step 202, according to the number of users in each period in the first community, determine first time period and described
In N number of period before one period, each period is relative to the increased number of users of previous time period.
Step 203, according to the number of users in the first time period before the first community in M days, determine described in
The average value of the number of users in the first time period in first M days.
Wherein, step 201 is similar with the realization method of the step 101 in embodiment one to step 103 to step 203, this
It is repeated no more in embodiment.
Step 204, judge whether the current first time period and its and the first time period before N number of period
In, each period is all higher than 0 and increased number of users of each period relative to the increased number of users of previous time period
It is lasting to increase.
In the present embodiment, or it is described for the 40th period, N=21 with the first time period.This step
In, it needs to judge A19To A40Whether the following conditions are met：A19To A40It was all higher than for 0 (i.e. the 19th period to the 40th period
In, in each period 0) increased number of users is all higher than；Aj＞ Aj-1, j=20,21 ... 40 (i.e. each period increases
The number of users added persistently increases).
If it is not, then can temporarily think the first community, in the 40th period, there is no the crowd is dense risks.
Step 205, if so, according to the average value of the number of users in the first time period in described first M days with
And the number of users in the first time period of the current date, calculate the first time period of the current date
Intensive risk probability.
In previous step, if A19To A40Meet condition, then illustrates that the first community may be deposited in the 40th period
It, can be further according to C in the crowd is dense risk40And the number of users in the 40th period of today, to judge today
The intensive risk probability P of 40th period.
It specifically, can be first according to the average value C of the number of users in the 40th period in first M days40And it is modern
Number of users in its 40th period determines the number of users in the 40th period of today and the C40Between difference
Value, is denoted as λ；
Then, according to the difference λ, the intensive risk probability P of the 40th period of today is calculated：
Under normal circumstances, the number of users of today of first community a certain period with a few days ago with the number of users of period
It is much the same, occurs unless there are special event, crowd is caused largely to assemble.Therefore, it can reflect first with normal distribution
Number of users in cell is fitted further according to a large amount of user data, and analysis obtains formula (1), passes through formula (1) basis
Today and number of users a few days ago are more in line with actual conditions come the judgement for the risk that carries out that the crowd is dense, also more accurate.
Step 206 judges whether the intensive risk probability P is more than 0.5, if so, determining the first community in institute
The risk that has that the crowd is dense is stated in the first time period of current date, and the user equipment into the first community is sent
Intensive indicating risk information.
In addition, after determining the first community the crowd is dense risk probability, can also search with it is described first small
The adjacent multiple cells in area, and determine that there are crowds in the first time period of the current date in the multiple cell
These cells are denoted as second community by the cell of intensive risk, judge the number of the second community and the multiple cell
Whether the ratio of sum is more than third predetermined threshold value, if so, judging the first community described the of the current date
One period, there is also the crowd is dense risks.
For example, the third predetermined threshold value can be 80%, if in multiple cells adjacent with first community, have more than
There is the crowd is dense risk in 80% cell, at this time can be to it may be considered that there is also the crowd is dense risks for first community
User equipment in the first community sends intensive indicating risk information.
The crowd is dense risk judgment method provided in this embodiment, can to carry out, the crowd is dense according to normal distyribution function
The judgement of risk so that the actual conditions of the first community can be conformed better to the risk judgment of first community；In addition,
By the crowd is dense for the peripheral cell of first community state, carry out first community described in auxiliary judgment the crowd is dense state, energy
It is enough that more fully first community is judged with the presence or absence of risk.
On the basis of the technical solution that above-described embodiment provides, it is preferred that can also be to the first community not
The next time, the crowd is dense, and risk is predicted.Specifically, the prediction technique may include：
According to intensive risk probability of the first community in the continuous K period in each period, determine described in
Intensive risk probability predicted value Q of the first community within next period of the continuous K periodk+1：
Wherein, XiFor predetermined coefficient, PiFor the intensive risk probability of i-th of period in the continuous K period.
K can according to the pre-set natural number of actual conditions, it is assumed that K 5, current slot are the 5th period,
Then can be according to the 1st intensive risk probability to the 5th period, the intensive risk probability to determine the 6th period is pre-
Measured value.
Specifically, Q6=X1*P1+X2*P2+X3*P3+X4*P4+X5*P5, wherein P1To P5Can be to be calculated according to formula (1)
The 1st intensive risk probability to the 5th period gone out.
It, can also basis other than it can determine the intensive risk probability predicted value of subsequent time period of current slot
Formula (2) determine current slot after several periods intensive risk probability predicted value.
For example, it is assumed that current slot is the 5th period, then it can be according to the 3rd period to the 7th period
Intensive risk probability calculates the intensive risk probability predicted value of the 8th period：Q8=X1*P1+X2*P2+X3*P3+X4*P4+
X5*P5, wherein P1To P5For the 3rd intensive risk probability to the 7th period, because being currently the 5th period, because
This, the intensive risk probability of the 6th and the 7th period can't determine, can be with the 6th and the 7th period it is intensive
Risk probability predicted value replaces intensive risk probability.
Since crowd massing degree is not instantly increased under micro-scale, the intensive risk of subsequent time period is general
Rate predicted value is to have certain correlation with preceding several periods, this correlation passes through predetermined coefficient XiTo reflect.This
In embodiment, the value of Xi is as follows：Xk=0.8；Xk-1=(1-Xk)*0.8；Xk-2=(1-Xk-Xk-1)*0.8；…….
Intensive risk probability and predetermined coefficient according to the first community in continuous multiple periods, can be to future
With the presence or absence of the crowd is dense, risk is predicted in several periods, if predicting the first community in some following time
There is the crowd is dense risk in section, then can send prompt message to user, user be facilitated to plan the stroke of oneself in advance.
On the basis of the technical solution that above-described embodiment provides, it is preferred that judging the first community described
After the risk that has that the crowd is dense in the first time period of current date, it can also continue to acquisition and obtain the first community
Number of users in the subsequent period of time of the first time period；And it is full there are the continuous L period in subsequent period of time
Foot is when requiring as follows, releases the first community the crowd is dense risk：
In the continuous L period, each period is respectively less than relative to the increased number of users of previous time period
0 and each period increased number of users persistently reduce, and the intensive risk probability in each period is respectively less than 0.5.
If meeting above-mentioned condition, it may be considered that future time of the first community in the continuous L period
There is no the crowd is dense risks for section, and can send intensive risk to user at this time releases information, facilitate described in user understands in time
First community has released intensive risk.
Embodiment three
The embodiment of the present invention three provides a kind of the crowd is dense risk judgment device.Fig. 3 is what the embodiment of the present invention three provided
The structural schematic diagram of the crowd is dense risk judgment device.As shown in figure 3, the crowd is dense in the present embodiment risk judgment device,
May include：
Acquisition module 301, the signaling message reported in current date for obtaining the user equipment in first community；
First determining module 302, for according to the signaling message, determining the number of users in each period in first community
Amount；
Second determining module 303 is used for according to the number of users in each period in the first community, when determining first
Between in N number of period before section and the first time period, each period is relative to the increased number of users of previous time period；
Third determining module 304, for according to the number of users in the first time period before the first community in M days
Amount, determines the average value of the number of users in the first time period in described first M days；
Judgment module 305, for according to the increased number of users and it is first M days described in the first time
The average value of number of users in section, judges whether the first community deposits in the first time period of the current date
In the crowd is dense risk；
Sending module 306, for there are people in the first time period of the current date in the first community
When the intensive risk of group, then the user equipment into the first community sends intensive indicating risk information.
It is close can be specifically used for the crowd executed described in embodiment one for the crowd is dense in the present embodiment risk judgment device
Collect risk judgment method, specific implementation is similar with embodiment one, and this embodiment is not repeated.
The crowd is dense in the present embodiment risk judgment device, can be arranged in network side server, in practical application
In, it can be divided in IuCS and IuPS mouthfuls of 2G or 3G network, the S1-MME mouth links of 4G networks, the light path separated and institute
It states network side server to be connected, the crowd is dense in the network side server, and risk judgment device can be according to network interface
In all kinds of signaling messages, to cell, risk judges with the presence or absence of the crowd is dense, in this way will not to existing network service,
Load etc. has an impact.
The crowd is dense risk judgment device provided in this embodiment, by obtaining the user equipment in first community current
The signaling message that date reports, to determine the number of users in first community in each period, according to each in the first community
Number of users in period determines increased number of users of each period and first time period in average use a few days ago
Amount amount, and with this come judge the first community in the first time period with the presence or absence of the crowd is dense risk, can be more
The number of users of the first community is accurately obtained, more accurately judges that the first community is in the first time period
It is no to there is the crowd is dense risk.
On the basis of the technical solution that above-described embodiment provides, it is preferred that first determining module 302, specifically
It can be used for：
Parse the user identity information carried in the signaling message, cell identity information and time point；
According to the user identity information, cell identity information and time point, each period in the first community is determined
Interior number of users.
On the basis of the technical solution that above-described embodiment provides, it is preferred that the judgment module 305, it specifically can be with
For：
Judge whether the current first time period and its and the first time period before N number of period in, Mei Geshi
Between section be all higher than 0 relative to the increased number of users of previous time period and each period increased number of users persistently increases；
If so, according to the average value of the number of users in the first time period in described first M days and described working as
Number of users in the first time period on preceding date, determines the number of users in the first time period of the current date
Difference between amount and the average value；
According to the difference, the intensive risk probability P of the first time period of the current date is calculated：
Wherein, λ is the number of users in the first time period of the current date and the difference between the average value
Value；
Judge whether the intensive risk probability P is more than 0.5；
If so, determining the first community wind that has that the crowd is dense in the first time period of the current date
Danger.
On the basis of the technical solution that above-described embodiment provides, it is preferred that the judgment module 305 can also be used
In：
According to intensive risk probability of the first community in the continuous K period in each period, determine described in
Intensive risk probability predicted value Q of the first community within next period in the continuous K periodk+1：
Wherein, XiFor predetermined coefficient, PiFor the intensive risk probability of i-th of period in the continuous K period.
On the basis of the technical solution that above-described embodiment provides, it is preferred that the judgment module 305 can also be used
In：
Judge the first community in the first time period of the current date and exist the crowd is dense risk it
Afterwards, acquisition obtains number of users of the first community in the subsequent period of time of the first time period；
According to the number of users in the subsequent period of time, when judging to whether there is continuous L in the subsequent period of time
Between section meet following require：In the continuous L period, each period is relative to the increased number of users of previous time period
Amount is respectively less than 0 and each period increased number of users is persistently reduced, and the intensive risk probability in each period is equal
Less than 0.5；
If so, judging subsequent time period of the first community in the continuous L period, there is no the crowd is dense
Risk.
On the basis of the technical solution that above-described embodiment provides, it is preferred that the judgment module 305 can also be used
In：
Search the multiple cells adjacent with the first community；
Determine in the multiple cell the risk that has that the crowd is dense in the first time period of the current date
The number of second community；
Judge whether the ratio of the number of the second community and the sum of the multiple cell is more than predetermined threshold value；
If so, judging that the first community has the crowd is dense wind in the first time period of the current date
Danger.
One of ordinary skill in the art will appreciate that：Realize that all or part of step of above method embodiment can pass through
The relevant hardware of program instruction is completed, and program above-mentioned can be stored in a computer read/write memory medium, the program
When being executed, step including the steps of the foregoing method embodiments is executed；And storage medium above-mentioned includes：ROM, RAM, magnetic disc or light
The various media that can store program code such as disk.The module in device in embodiment can describe to be distributed according to embodiment
In the device of embodiment, respective change can also be carried out and be located in one or more devices different from the present embodiment.Above-mentioned reality
The module for applying example can be merged into a module, can also be further split into multiple submodule.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (10)
1. a kind of the crowd is dense risk judgment method, which is characterized in that including：
The signaling message that the user equipment in first community is reported in current date is obtained, and according to the signaling message, is determined
Number of users in first community in each period；
According to the number of users in each period in the first community, before determining first time period and the first time period
In N number of period, each period is relative to the increased number of users of previous time period；
According to the number of users in the first time period before the first community in M days, determine described in described first M days
The average value of number of users in first time period；
According to the increased number of users and it is described first M days in the first time period in number of users be averaged
Value judges the first community in the first time period of the current date with the presence or absence of the crowd is dense risk；
If in the presence of the user equipment into the first community sends intensive indicating risk information；
Number of users in the first time period according to the increased number of users and in first M days described
Average value, judge the first community in the first time period of the current date with the presence or absence of the crowd is dense risk,
It specifically includes：
Judge whether current first time period and its and the first time period before N number of period in, each period is opposite
It is all higher than 0 in the increased number of users of previous time period and each period increased number of users persistently increases；
If so, according to the average value of the number of users in the first time period in described first M days and described working as the day before yesterday
Number of users in the first time period of phase, determine number of users in the first time period of the current date with
Difference between the average value；
According to the difference, the intensive risk probability P of the first time period of the current date is calculated：
Wherein, λ is the number of users in the first time period of the current date and the difference between the average value；
Judge whether the intensive risk probability P is more than 0.5；
If so, determining the first community risk that has that the crowd is dense in the first time period of the current date.
2. according to the method described in claim 1, it is characterized in that, described according to the signaling message, determine in first community
Number of users in each period, specifically includes：
Parse the user identity information carried in the signaling message, cell identity information and time point；
According to the user identity information, cell identity information and time point, determine in the first community in each period
Number of users.
3. according to the method described in claim 1, it is characterized in that, further including：
According to intensive risk probability of the first community in the continuous K period in each period, described first is determined
Intensive risk probability predicted value Q of the cell within next period in the continuous K periodk+1：
Wherein, XiFor predetermined coefficient, PiFor the intensive risk probability of i-th of period in the continuous K period.
4. according to the method described in claim 1, it is characterized in that, judging institute of the first community in the current date
After stating in first time period the risk that has that the crowd is dense, further include：
Acquisition obtains number of users of the first community in the subsequent period of time of the first time period；
According to the number of users in the subsequent period of time, judge to whether there is the continuous L period in the subsequent period of time
Meet following require：In the continuous L period, each period is equal relative to the increased number of users of previous time period
Less than 0 and each period increased number of users is persistently reduced, and the intensive risk probability in each period is respectively less than
0.5；
If so, judging subsequent time period of the first community in the continuous L period, there is no the crowd is dense risks.
5. according to claim 1-4 any one of them methods, which is characterized in that further include：
Search the multiple cells adjacent with the first community；
Determine in the multiple cell to there is that the crowd is dense in the first time period of the current date the second of risk
The number of cell；
Judge whether the ratio of the number of the second community and the sum of the multiple cell is more than predetermined threshold value；
If so, judging that the first community has the crowd is dense risk in the first time period of the current date.
6. a kind of the crowd is dense risk judgment device, which is characterized in that including：
Acquisition module, the signaling message reported in current date for obtaining the user equipment in first community；
First determining module, for according to the signaling message, determining the number of users in each period in first community；
Second determining module, for according to the number of users in each period in the first community, determine first time period and
In N number of period before the first time period, each period is relative to the increased number of users of previous time period；
Third determining module, for according to the number of users in the first time period before the first community in M days, determining
The average value of the number of users in the first time period in described first M days；
Judgment module, for according to the increased number of users and it is first M days described in the first time period in use
The average value of amount amount judges that the first community is close with the presence or absence of crowd in the first time period of the current date
Collect risk；
Sending module, for there is the crowd is dense wind in the first time period of the current date in the first community
When dangerous, then the user equipment into the first community sends intensive indicating risk information；
The judgment module, is specifically used for：
Judge whether current first time period and its and the first time period before N number of period in, each period is opposite
It is all higher than 0 in the increased number of users of previous time period and each period increased number of users persistently increases；
If so, according to the average value of the number of users in the first time period in described first M days and described working as the day before yesterday
Number of users in the first time period of phase, determine number of users in the first time period of the current date with
Difference between the average value；
According to the difference, the intensive risk probability P of the first time period of the current date is calculated：
Wherein, λ is the number of users in the first time period of the current date and the difference between the average value；
Judge whether the intensive risk probability P is more than 0.5；
If so, determining the first community risk that has that the crowd is dense in the first time period of the current date.
7. device according to claim 6, which is characterized in that first determining module is specifically used for：
Parse the user identity information carried in the signaling message, cell identity information and time point；
According to the user identity information, cell identity information and time point, determine in the first community in each period
Number of users.
8. device according to claim 6, which is characterized in that the judgment module is additionally operable to：
According to intensive risk probability of the first community in the continuous K period in each period, described first is determined
Intensive risk probability predicted value Q of the cell within next period in the continuous K periodk+1：
Wherein, XiFor predetermined coefficient, PiFor the intensive risk probability of i-th of period in the continuous K period.
9. device according to claim 6, which is characterized in that the judgment module is additionally operable to：
After judging that the first community has the crowd is dense risk in the first time period of the current date, adopt
Collection obtains number of users of the first community in the subsequent period of time of the first time period；
According to the number of users in the subsequent period of time, judge to whether there is the continuous L period in the subsequent period of time
Meet following require：In the continuous L period, each period is equal relative to the increased number of users of previous time period
Less than 0 and each period increased number of users is persistently reduced, and the intensive risk probability in each period is respectively less than
0.5；
If so, judging subsequent time period of the first community in the continuous L period, there is no the crowd is dense risks.
10. according to claim 6-9 any one of them devices, which is characterized in that the judgment module is additionally operable to：
Search the multiple cells adjacent with the first community；
Determine in the multiple cell to there is that the crowd is dense in the first time period of the current date the second of risk
The number of cell；
Judge whether the ratio of the number of the second community and the sum of the multiple cell is more than predetermined threshold value；
If so, judging that the first community has the crowd is dense risk in the first time period of the current date.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1901725A (en) * | 2005-07-19 | 2007-01-24 | 深圳市建恒工业自控系统有限公司 | Statistic system and method for crowd short-term density |
| CN102215468A (en) * | 2010-04-02 | 2011-10-12 | 广东宜通世纪科技股份有限公司 | Crowd distribution monitoring method and system |
| CN104202719A (en) * | 2014-08-14 | 2014-12-10 | 长安通信科技有限责任公司 | People number testing and crowd situation monitoring method and system based on position credibility |
| CN104835016A (en) * | 2015-05-27 | 2015-08-12 | 北京搜狐新媒体信息技术有限公司 | Crowd density calculation method and device |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1901725A (en) * | 2005-07-19 | 2007-01-24 | 深圳市建恒工业自控系统有限公司 | Statistic system and method for crowd short-term density |
| CN102215468A (en) * | 2010-04-02 | 2011-10-12 | 广东宜通世纪科技股份有限公司 | Crowd distribution monitoring method and system |
| CN104202719A (en) * | 2014-08-14 | 2014-12-10 | 长安通信科技有限责任公司 | People number testing and crowd situation monitoring method and system based on position credibility |
| CN104835016A (en) * | 2015-05-27 | 2015-08-12 | 北京搜狐新媒体信息技术有限公司 | Crowd density calculation method and device |
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