CN111278041A - Method and equipment for determining group behavior place - Google Patents
Method and equipment for determining group behavior place Download PDFInfo
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Abstract
The invention discloses a method and equipment for determining a place where group behaviors occur, which are used for determining the place where the group behaviors occur in time and intelligently evacuating aggregated groups in time. The method comprises the following steps: dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid; processing the sampling data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area; and determining whether the fine grid generates user group aggregation behavior according to the determined terminal behavior parameter warning value corresponding to the fine grid and the terminal behavior parameter in the fine grid area.
Description
Technical Field
The invention relates to the identification of sudden group behaviors, in particular to a method and equipment for determining a group behavior occurrence place.
Background
The modern society is a densely-populated and highly-complex society, and more emergencies and emergencies are faced, and the difficulty and importance of evacuation are more and more prominent. Most of the existing video monitoring systems only monitor and track moving targets in scenes, but identify and understand the behaviors of the moving targets rarely, and although people continuously build larger and larger video monitoring systems, the monitoring systems almost only can provide a tool for recording and evidence obtaining afterwards.
At present, two major challenges are mainly faced in utilizing intelligent video monitoring to evacuate passenger group sudden behaviors:
on one hand, the monitoring scene range is wide, and the sudden behavior pattern of the passenger group is complex. With the popularization of monitoring equipment and the maturity of technology, the range of monitoring scenes is wider and wider, from public squares to the interior of buildings, passenger group activities in different monitoring scenes have different sudden behavior patterns, and the most representative sudden behavior pattern is the gathering and escaping of passenger groups, for example, the passenger groups are in disorder at a certain place in the squares, escape at all places, or escape to an exit at one side, or gather at a certain area on the squares. In the face of such a complex sudden behavior pattern, it is important to perform safe evacuation to be able to determine the occurrence place of the sudden behavior of the passenger group in real time.
On the other hand, it is difficult to detect burst patterns using intelligent video surveillance. For intelligent video monitoring, timely detecting the sudden behavior of a passenger group is an important standard for measuring the effectiveness of a detection method, and timely detection is helpful for sending an alarm and evacuating and escaping the passenger group, so that the loss caused by danger can be minimized, but the prior art cannot realize timely detecting the gathering place of the sudden behavior of the group and cannot timely guide the gathered group to evacuate and escape.
Disclosure of Invention
The invention provides a method and equipment for determining a group behavior place, which can determine the group behavior place in time, intelligently evacuate aggregated groups and ensure safe evacuation of emergency situations in public occasions.
The invention provides a method for determining a group behavior occurrence place, which comprises the following steps:
dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
processing the sampling data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
and determining whether the fine grid generates user group aggregation behavior according to the determined terminal behavior parameter warning value corresponding to the fine grid and the terminal behavior parameter in the fine grid area.
The invention provides a device for determining a group behavior occurrence place, which comprises: a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of:
dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
processing the sampling data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
and determining whether the fine grid generates user group aggregation behavior according to the determined terminal behavior parameter warning value corresponding to the fine grid and the terminal behavior parameter in the fine grid area.
The method and the equipment for determining the group behavior place have the following advantages that:
on one hand, the acquired group data are calculated based on the 5G edge data center platform, so that the calculation amount and the calculation complexity of group behavior detection data preprocessing can be reduced, and the high-speed and even real-time requirements of group behavior detection are met;
on the other hand, the method can determine the place where the group behaviors occur, quickly respond to the sudden aggregation behaviors, intelligently evacuate the aggregated groups, and ensure the safe evacuation of emergency situations in public occasions.
Drawings
FIG. 1 is a diagram of the method steps for determining a venue for a group behavior;
FIG. 2 is a diagram of dividing fine grid regions;
fig. 3 is a diagram of determining a terminal quantity by a remote radio unit RRU.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
To explain the contents of the present invention in more detail, the following description is made specifically for the edge data used in the present invention, as follows:
the edge data center is a data center which is located close to the user side locally and can provide services for the local user, and the local user does not need to access a remote data center, so that the edge data center can provide high-bandwidth and low-delay access application for the user.
For example, the processing mode of the edge data center is applied to the internet of vehicles, and the internet of vehicles can reach a specified security level through the low-delay processing of the edge data center, wherein the server based on the edge data center can be sunk to each node at the edge of the network, so that the network delay is saved.
Specifically, the edge data center can be used as a server arranged at the edge of each community network, and various collected sample data are processed through the server arranged at the edge of the network.
In this embodiment, a method for Edge computing of an Edge data center is applied to process sampled data of a terminal in the fine grid area, the Edge computing of the Edge data center is a floor deployment of intelligent cloud computing, the Edge computing is applied to a local part of the internet of things to implement data looping, a terminal behavior parameter warning value corresponding to the fine grid can be determined through Edge computing (Edge computing), a terminal behavior parameter in the fine grid area is determined, and further, intelligentization of full-layer domains such as data decision, behavior feedback, automatic networking, load balancing and the like is implemented, and the application can also be independently and flexibly operated without cloud computing, so that an "ecology" of the internet of things is formed in a small range of an application scene.
Based on the specific characteristics of ultra-low time delay, ultra-high speed and massive connection of the 5G network, when a large amount of data needs to be calculated locally and a terminal is issued, the edge data center under the 5G network can be used for processing the large amount of data more timely and efficiently.
The edge data center in this embodiment is a 5G edge data center application layer, and the 5G edge data center application layer is formed by an application server and is responsible for processing analysis of data edge calculation, providing an application interface, and displaying data.
The method for determining the occurrence place of the group behaviors is used for performing edge calculation on public places with aggregated groups by using an edge data center, determining the occurrence place of the group behaviors in time, determining the occurrence place of the group behaviors, and performing evacuation guidance on users with group events by using existing equipment of the public places such as broadcasting or video and the like in time, particularly determining the accident place of the fire in time when the emergency event such as the fire occurs, and performing safe evacuation guidance on the groups.
The specific implementation of the method is shown in fig. 1, and the implementation steps are as follows:
step 101: dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
step 102: processing the sampled data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
step 103: and determining whether the fine grid generates user group aggregation behavior according to the terminal behavior parameter warning value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area.
In implementation, the environment attribute is different environment attributes determined according to different purposes of different building areas, so that grid areas with different environment attributes are determined.
Specifically, in order to determine a grid area of the environment attribute, and thus determine a place where the user group gathering behavior occurs, the environment area needs to be divided into grid areas of different environment attributes according to the usage of the building environment area. Taking the west lan station as an example, the environment area of the west lan station can be divided into the following grid areas with different environment attributes according to different purposes:
the system comprises south and north station houses, an overhead waiting hall, south and north city galleries, overhead lanes, a passenger platform, platform rainsheds and logistics channels;
in implementation, the grid region is determined, that is, the occurrence positions of the aggregation behaviors of the user group in the grid region are determined, and in order to reduce the range of the determined occurrence positions of the aggregation behaviors of the user group as much as possible, each grid region can be divided into at least one fine grid;
as shown in fig. 2, a grid area covering the elevated layer ticket region is divided into 4 fine grids: covering the northwest of the elevated ticket checking area, covering the northeast of the elevated ticket checking area, covering the southwest of the elevated ticket checking area and covering the southeast of the elevated ticket checking area; divide a grid area of the canopy of the covering station layer into 4 fine grids: the platform layer rain shed comprises a west-north side covering the platform layer rain shed, a east-north side covering the platform layer rain shed, a west-south side covering the platform layer rain shed and an east-south side covering the platform layer rain shed.
In implementation, the edge-based data center may be a 5G edge data center, and the sampling data of the terminal in the fine grid area may be a terminal behavior parameter in the radio remote unit RRU and/or a terminal behavior parameter determined by SIM card identification information of the terminal.
As an optional implementation manner, the terminal behavior parameter in the fine grid region is any one or any multiple of the following parameters determined according to the sampling data of the terminal in the fine grid region, and includes:
terminal number, traffic growth, and overflow rate probability.
In an implementation, the terminal behavior parameter alert value is also any one or any plurality of the following parameters determined according to the sampling data of the terminal in the fine grid area, and includes:
terminal number, traffic growth, and overflow rate probability.
Specifically, the terminal behavior parameter alert value is obtained by performing edge calculation on terminal sampling data in a pre-divided fine grid region based on an edge data center under the condition that a user group aggregation behavior does not occur, that is, under a normal condition, the obtained terminal behavior parameter alert value is judged based on common sense, the movement of group users under the normal condition is orderly, the positions of the group users are distributed according to a certain rule, that is, the positions of the terminals in the fine grid region are distributed according to a certain rule, and the interactive data between the terminals in the fine grid region and network equipment has a certain regularity, so that the terminal behavior parameter alert value of each fine grid region under the normal condition can be determined according to the terminal behavior parameter value in each fine grid region.
The terminal behavior parameter warning value in the fine grid area is lower than the terminal behavior parameter value under the normal condition in the fine grid area.
For example: the fine grid area is a subway station, the terminal behavior parameter value in the fine grid area is telephone traffic increase amount, the subway station is a transfer station, when a train arrives at the subway station, a user finishes getting on or off the train in a short time, the user to get off the train is centralized to go out of the train along a side platform, the user to be transferred enters another line platform along a transfer line, if the user to get off the train or the user to be transferred starts to talk or surf the internet at the moment, the telephone traffic in the fine grid area can be judged to rise sharply according to the interactive data of the terminal and the network equipment, which shows that under normal conditions, after the subway station enters the train, the telephone traffic in the fine grid area appears a peak on the transfer line or the off-line, if the subway station enters the train for 5 times in one hour, the telephone traffic in the fine grid area appears a peak for 5 times in one hour, which shows the interactive data of the terminal and the network equipment in the fine grid area, under normal conditions, the terminal behavior parameters in the fine grid region may be averaged to determine the terminal behavior parameter alert value in the setting time under normal conditions, or the terminal behavior parameters in the fine grid region may be summed to determine the terminal behavior parameter alert value in the setting time under normal conditions, which is not limited in this embodiment.
The terminal behavior parameters in the fine grid region correspond to the terminal behavior parameter alert values, that is, when the terminal behavior parameters in the fine grid region are the number of terminals, the terminal behavior parameter alert values corresponding to the fine grid are the number of terminals in the fine grid region when no group aggregation behavior occurs in the fine grid region; when the terminal behavior parameters in the fine grid region are the traffic growth amount and the overflow rate probability, and the terminal behavior parameter warning value corresponding to the fine grid is the traffic growth amount and the overflow rate probability in the fine grid region when the group aggregation behavior does not occur in the fine grid region.
The number of terminals in the terminal behavior parameter values can indicate the number of users using the terminals in the fine grid region, the traffic increase amount can indicate whether the traffic of the users using the terminals in the fine grid region for voice call is increased compared with the normal traffic in the time period, so as to determine whether the group aggregation behavior occurs in the fine grid region, the overflow rate probability can indicate the total number of overflow times and the total number of pilot calls of the users using the terminals in the fine grid region on a signaling channel SDCCH, and the total number of overflow times and the total number of pilot calls in the time period are increased compared with the normal situation, so as to determine whether the users in the fine grid region have the group aggregation behavior, so that according to whether the number of terminals, the traffic increase amount and the overflow rate probability in the fine grid region are higher than the normal standard, thereby determining that a user in the fine grid area has a group gathering behavior.
As an optional implementation, determining the number of terminals according to the sampling data of the terminals in the fine grid region includes:
and determining the number of the terminals in each fine grid area according to the SIM card identification information of the user identification card in the sampling data of the terminals in each fine grid area.
In implementation, the number of the terminals is determined by sampling the SIM card identification information in the data.
Specifically, each intelligent terminal is provided with an SIM card for normal use of network data service, each SIM card number ICCID is unique, the number of the terminals can be counted by collecting the ICCID, and if the terminal is a mobile subscriber, the number of the mobile subscriber can be counted by collecting the IMSI.
In the concrete implementation, if all mobile, Unicom and telecommunication users are counted, the workload is too large, therefore, only the number of the mobile users is counted according to the mobile user identification IMSI, and finally the number of all terminal users is calculated according to the proportion of the mobile, Unicom and telecommunication users.
In implementation, the number of terminals in the fine grid area interacting with the RRU currently is determined according to the remote radio RRU device, as shown in fig. 3.
The RRU device mainly performs filtering, signal amplification, and up-down conversion processing on radio frequency signals, and uses a digital intermediate frequency technology to realize conversion from intermediate frequency analog signals to baseband digital signals. Determining the number of terminals in a fine grid area through terminal voice/data in the fine grid area which is detected by RRU equipment and interacts with RRU currently, wherein the specific method comprises the following steps:
the base station is configured to be S/2/3/3, and the carrier frequency number of each sector in the three sectors is 2, 3 and 3 respectively;
1 carrier frequency needs to be configured with 8 channels, 2 carrier frequencies need to be configured with 16 channels, and 1 of the 16 channels is selected as a Broadcast Control Channel (BCCH) transmission Control signal;
if the rest 15 channels are all used as traffic channels tch (traffic channel) to transmit voice/data traffic;
if the remaining 15 channels meet the requirement that 15 full-rate users simultaneously talk or 30 half-rate users simultaneously talk, the call loss is 2%;
the traffic volume corresponding to 15 channels is determined to be 5.411Erl according to an Ireland B capacity table, and the traffic volume of each user is determined to be 0.025Erl according to a traffic model, so that the capacity is 5.411/0.025 is 216.44, namely the number of users is 216.44.
In fig. 3, the grid area is identified as qilihe _ lang west station _ E607528, which is divided into 8 fine grid areas: the number of users in the district is specified in the normal course of the original user number and the new user number in the waiting area, and the difference between the number of users in the waiting area and the new user number is set in the fine-grained region, wherein the normal user number is specified in the normal course of the user number in the waiting area, and the normal user number is specified in the fine-grained region, no user population gathering behavior occurs within the fine grid area.
As an optional implementation manner, determining the traffic increase amount and the overflow rate probability according to the sampling data of the terminal in the fine grid region includes:
and determining the traffic increase amount and the overflow rate probability in each fine grid area according to the voice data transmitted in the voice channel and the signaling data transmitted in the signaling channel in the sampling data of the terminal in each fine grid area.
In the implementation, the signaling data transmitted by the signaling channel comprises the total number of traffic overflow times and the total number of traffic call trial times in the independent dedicated control channel SDCCH;
the voice data transmitted in the voice channel comprises the total number of voice overflow and the total number of voice call trial.
And (3) the overflow probability of the fine grid region is equal to the number of times that the overflow rate of the fine grid region exceeds a set threshold/the total traffic statistic report number of times of the fine grid region is equal to 100%.
The fine grid area overflow rate is the traffic overflow rate of the SDCCH in the fine grid area; or
Voice overflow rate of voice channel in fine grid region;
the traffic overflow rate of the SDCCH can be calculated by the following formula:
the traffic overflow rate of the SDCCH is the total number of times of SDCCH overflow during busy hour/the total number of times of SDCCH call test during busy hour;
the speech overflow rate can be calculated by the following formula:
the voice overflow rate of the voice channel is equal to the total number of times of overflowing of the voice channel in busy hour/the total number of times of trying calling of the voice channel in busy hour; the busy hour is defined as the time period for counting the maximum value of the voice data of the voice channel according to the time period in 24 hours a day, and if the time period is defined as 10: 00-11: 00 in the morning, the busy hour can be defined.
In practice, the determined traffic/uplink RLC throughput (bps) in the fine grid area changes when aggregation action occurs, for example: the fine grid area is a square, when aggregation occurs in the fine grid area, the traffic/uplink RLC throughput rate of the fine grid area is 6.3ERL/20Mbps, and under the normal condition that aggregation does not occur, the traffic/uplink RLC throughput rate of the fine grid area is 5.6ERL/8Mbps, so when aggregation occurs in the fine grid area, the traffic/uplink RLC throughput rate is greatly increased higher than that of the fine grid area under the normal condition, and the voice/traffic overflow rate may exceed 20%.
The throughput rate is an average rate of successful delivery of data through a communication channel or a node in a unit time, and generally, in units of bits per second (bps), the higher the uplink RLC throughput rate is, which means that the higher the traffic volume is, the more likely congestion occurs in a voice data transmission channel.
In implementation, the edge data center is used for processing the sampling data of the terminal in the fine grid area, and determining the terminal behavior parameter warning value corresponding to the fine grid under normal conditions, taking a western lanzhou passenger station as a grid area for example, and dividing the western lanzhou passenger station into 14 fine grid areas, as shown in fig. 2, the specific implementation steps are as follows:
step 201: predefining the maximum number of users in each fine grid area as a reference value of a terminal behavior parameter of each fine grid area;
step 202: establishing a rectangular coordinate system, and equally dividing an x axis and a y axis where each fine grid region is located into N equal parts to obtain N unit fine grid regions corresponding to each fine grid region;
specifically, the unit fine grid region is defined as: (A1i，B2i) Wherein:
the int function is to take integer value for the value in the function, i is from 1 to n, which represents the number of unit fine grid, the unit fine grid area is a rectangular space, which can realize the calculation of terminal behavior parameters of the fine grid area according to the coordinate position change, the length and width of the rectangular space are dalAnd dblAs shown in the following formula:
d abovealN equal parts of the fine area grid are divided on the x axis, and the length of the unit fine grid area on the x axis is obtained, wherein the length of the unit fine grid area on the x axis is equal to the length of the unit fine area grid from end a1 to start a 1;
dblthe length of the unit fine grid region on the y-axis is obtained by equally dividing the fine region grid by n on the y-axis, wherein the length of the unit fine grid region on the y-axis is equal to the length of the fine region grid from the end b2 to the start b 2.
Step 203: initializing the behavior parameters of each unit fine grid terminal;
specifically, the number of terminals in the fine grid area of each unit is defined as 1, the traffic increase amount is defined as 1, and the probability of overflow rate is defined as 1;
step 204: determining the behavior parameters of the unit fine grid terminal in the fine grid area;
specifically, the terminal behavior parameter is related to the position of the unit fine grid, that is, the terminal behavior parameter in the unit fine grid region is expressed as follows:
in the formula, ytData compression coefficients for predefined fine grid termination behavior parameters, (a1, B2) are initial cell fine grid regions;
wherein, WirThe maximum value of the terminal behavior parameter in the predefined fine grid area.
Step 205: determining the behavior parameters of the fine grid terminal where the fine grid of the unit is located;
according to the position of the current cell fine grid region (A1)i，B2i) Determining the current terminal behavior parameters;
determining a behavior parameter of the missing terminal according to the position of the fine grid region of the current unit;
according to the current terminal behavior parameters and the missed terminal behavior parameters, determining the actual terminal behavior parameters of the unit fine grid region as follows:
the actual terminal behavior parameter is the current terminal behavior parameter plus the omitted terminal behavior parameter;
wherein, the terminal behavior parameter is any one of the following parameters:
probability of overflow rate, traffic growth, number of terminals.
Specifically, the x-axis is operated, the terminal behavior parameters of the current unit fine grid on the x-axis are determined, and the integral value of the current unit fine grid on the x-axis in the fine grid area is obtainedIMiADetermining the terminal behavior parameters in the current fine grid region according to the following formula:
Q＝IMiA+βQ-Gv；
the β Q is the terminal behavior parameter missing at the previous position of the current fine grid region, β is the terminal behavior parameter retention coefficient, and Gv is the unrecognized data volume.
And determining the terminal behavior parameters of the fine grid region of the cell that should be on the y-axis, referring to step 205, which is not described herein again.
When the unit fine grid performs terminal behavior parameter calculation on the x axis, the unit fine grid is specified to perform calculation not only on the x axis of the fine grid where the unit fine grid is located, but also on the x axis where two regions of the fine grid and the fine grid adjacent to the fine grid intersect.
Step 206: determining a behavior parameter average value corresponding to the fine grid;
and (3) according to the determined fine grid terminal behavior parameters of the unit fine grid, referring to the maximum number of the users in each fine grid region predefined in the step (1), determining the fine grid terminal behavior parameters as behavior parameter average values corresponding to the fine grids.
Specifically, the obtained terminal behavior parameter average value is compared with the maximum number of users in the predefined fine grid area, and whether the obtained terminal behavior parameter average value is reasonable and correct is determined.
Step 207: and determining a terminal behavior parameter warning value corresponding to the fine grid.
And determining that the terminal behavior parameter warning value corresponding to the fine grid is a value slightly smaller than the determined terminal behavior parameter average value, wherein the specific size can be defined by a user.
Specifically, when any one of the determined terminal behavior parameters in the fine grid area is higher than the corresponding terminal behavior parameter alert value, it is determined that a user group gathering behavior occurs in the fine grid area.
As an optional implementation manner, determining whether a user group aggregation behavior occurs in the fine grid according to the terminal behavior parameter alert value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area, includes:
and when the terminal behavior parameters in the fine grid region are determined to exceed the terminal behavior parameter warning values corresponding to the fine grid, determining whether the fine grid generates user group aggregation behaviors.
As an optional implementation manner, after determining that the user group aggregation behavior occurs on the fine grid, the method further includes:
and determining the evacuation path of the user group in the fine grid with the user group gathering behavior according to the position of the fine grid with the user group gathering behavior and the number of users in other fine grid areas except the fine grid with the user group gathering behavior.
Taking the western blue station as an example, the western blue station is taken as a grid area and is divided into a plurality of fine grids, and the method comprises the following steps: and the platform, the stairs and the entrance/exit determine the position of the safety channel in the fine grid area according to the determined position of the fine grid, determine the possible congestion of the fine grid area with a large number of users according to the number of the users in other fine grid areas except the fine grid with the user group gathering behavior, and avoid the possible congestion fine grid area when determining the evacuation path.
In implementation, a terminal behavior parameter warning value in a fine grid area under a normal condition within a preset time period is determined in advance based on an edge data center and is used as reference data of the terminal behavior parameter in the fine grid area;
and when the terminal behavior parameter of the fine grid area in the set time period is determined to be higher than the reference data, determining an evacuation path.
As an optional implementation, after determining the evacuation path of the user group in the fine grid where the user group aggregation behavior occurs, the method further includes:
and carrying out evacuation guidance on the user groups in the fine grid according to the determined evacuation route in the form of broadcast notification or video playing.
As an optional implementation, the evacuation guidance has the following three ways:
normal evacuation guidance: broadcasting notification and video playing;
general evacuation guidance: wired/wireless transmission audio/video playing, digital playing and intelligent control;
emergency evacuation guidance: alarm break-in broadcasting and two-way talkback broadcasting systems.
In summary, the method provided by this embodiment can determine the number of users in the fine grid area, timely determine behavior parameter information included in the behaviors of the users in the fine grid area, and determine the occurrence of the group aggregation behavior according to the behavior parameters, thereby improving the accuracy and time efficiency of determination, reducing the false alarm rate, and providing more valuable information for solving the group aggregation behavior in the public places.
Example two
Based on the same inventive concept, the invention also provides equipment for determining the occurrence places of the group behaviors, and the specific implementation of the equipment can be referred to the description of the embodiment part of the method, and repeated parts are not described again.
The apparatus comprises: a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor is configured to perform the following steps:
dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
processing the sampled data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
and determining whether the fine grid generates user group aggregation behavior according to the terminal behavior parameter warning value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area.
As an optional implementation, the processor is further configured to:
and determining the grid areas with different environmental attributes according to different purposes of different building areas.
As an optional implementation manner, after determining that the user group aggregation behavior occurs on the fine grid, the method further includes:
and determining the evacuation path of the user group in the fine grid with the user group gathering behavior according to the position of the fine grid with the user group gathering behavior and the number of users in other fine grid areas except the fine grid with the user group gathering behavior.
As an optional implementation manner, the terminal behavior parameter is any one or any multiple of the following parameters determined according to the sampling data of the terminal in the fine grid region, and includes:
terminal number, traffic growth, and overflow rate probability.
As an optional implementation, determining the number of terminals according to the sampling data of the terminals in the fine grid region includes:
and determining the number of the terminals in each fine grid area according to the SIM card identification information of the user identification card in the sampling data of the terminals in each fine grid area.
As an optional implementation manner, determining the traffic increase amount and the overflow rate probability according to the sampling data of the terminal in the fine grid region includes:
and determining the traffic increase amount and the overflow rate probability in each fine grid area according to the voice data transmitted in the voice channel and the signaling data transmitted in the signaling channel in the sampling data of the terminal in each fine grid area.
As an optional implementation manner, the signaling data transmitted by the signaling channel includes total number of traffic overflow and total number of traffic call attempts in the independent dedicated control channel SDCCH;
the voice data transmitted in the voice channel comprises the total number of voice overflow and the total number of voice call trial.
As an optional implementation manner, the determining whether the fine grid has the user group aggregation behavior according to the terminal behavior parameter alert value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area includes:
and when the terminal behavior parameters in the fine grid region are determined to exceed the terminal behavior parameter warning values corresponding to the fine grid, determining whether the fine grid generates user group aggregation behaviors.
As an optional implementation, after determining the evacuation path of the user group in the fine grid where the user group aggregation behavior occurs, the method further includes:
and carrying out evacuation guidance on the user groups in the fine grid according to the determined evacuation route in the form of broadcast notification or video playing.
EXAMPLE III
Based on the same inventive concept, the invention further provides a computer storage medium, and specific implementation of the computer storage medium can be referred to the description of the method embodiment part, and repeated details are not repeated.
A computer storage medium having a computer program stored thereon, the program when executed by a processor implementing the steps of:
dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
processing the sampled data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
and determining whether the fine grid generates user group aggregation behavior according to the terminal behavior parameter warning value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (19)
1. A method of determining a venue for a group behavior, the method comprising:
dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
processing the sampling data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
and determining whether the fine grid generates user group aggregation behavior according to the determined terminal behavior parameter warning value corresponding to the fine grid and the terminal behavior parameter in the fine grid area.
2. The method according to claim 1, characterized in that the grid areas of different environmental properties are determined according to different uses of different building areas.
3. The method of claim 1, wherein after determining that the fine grid has a user population gathering behavior, further comprising:
and determining the evacuation path of the user group in the fine grid with the user group gathering behavior according to the position of the fine grid with the user group gathering behavior and the number of users in other fine grid areas except the fine grid with the user group gathering behavior.
4. The method according to claim 1, wherein the terminal behavior parameters are any one or more of the following parameters determined from the sampled data of the terminals in the fine grid region, including:
terminal number, traffic growth, and overflow rate probability.
5. The method of claim 4, wherein determining the number of terminals from the sampled data for the terminals in the fine grid region comprises:
and determining the number of the terminals in each fine grid area according to the SIM card identification information of the user identification card in the sampling data of the terminals in each fine grid area.
6. The method of claim 4, wherein determining the traffic growth and the probability of overflow rate according to the sampled data of the terminal in the fine grid region comprises:
and determining the traffic increase amount and the overflow rate probability in each fine grid area according to the voice data transmitted in the voice channel and the signaling data transmitted in the signaling channel in the sampling data of the terminal in each fine grid area.
7. The method according to claim 6, characterized in that the signaling data transmitted by the signaling channel comprises the total number of traffic overflow and the total number of traffic call attempts in the independent dedicated control channel SDCCH;
the voice data transmitted in the voice channel comprises the total number of voice overflow and the total number of voice call trial.
8. The method according to any one of claims 1 to 7, wherein determining whether the fine grid has a user group aggregation behavior according to the terminal behavior parameter alert value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area comprises:
and when the terminal behavior parameters in the fine grid region are determined to exceed the terminal behavior parameter warning values corresponding to the fine grid, determining whether the fine grid generates user group aggregation behaviors.
9. The method of claim 3, wherein determining the evacuation path for the user population in the fine grid in which the user population gathering behavior occurs further comprises:
and carrying out evacuation guidance on the user groups in the fine grid according to the determined evacuation route in the form of broadcast notification or video playing.
10. An apparatus for determining a venue of a group behavior, the apparatus comprising: a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of:
dividing the monitored environment area into grid areas corresponding to different environment attributes, and dividing each grid area into at least one fine grid;
processing the sampling data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameter warning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area;
and determining whether the fine grid generates user group aggregation behavior according to the determined terminal behavior parameter warning value corresponding to the fine grid and the terminal behavior parameter in the fine grid area.
11. The apparatus of claim 10, wherein grid areas of different environmental attributes are determined for different uses of different building areas.
12. The apparatus of claim 10, wherein after determining that the fine grid has a user crowd gathering behavior, further comprising:
and determining the evacuation path of the user group in the fine grid with the user group gathering behavior according to the position of the fine grid with the user group gathering behavior and the number of users in other fine grid areas except the fine grid with the user group gathering behavior.
13. The apparatus according to claim 10, wherein the terminal behavior parameters are any one or more of the following parameters determined from the sampled data of the terminals in the fine grid region, including:
terminal number, traffic growth, and overflow rate probability.
14. The apparatus of claim 13, wherein determining the number of terminals from the sampled data for the terminals in the fine grid region comprises:
and determining the number of the terminals in each fine grid area according to the SIM card identification information of the user identification card in the sampling data of the terminals in each fine grid area.
15. The apparatus of claim 13, wherein determining the traffic increase and the probability of overflow rate according to the sampled data of the terminal in the fine grid region comprises:
and determining the traffic increase amount and the overflow rate probability in each fine grid area according to the voice data transmitted in the voice channel and the signaling data transmitted in the signaling channel in the sampling data of the terminal in each fine grid area.
16. The apparatus according to claim 15, wherein the signaling data transmitted by the signaling channel comprises the total number of traffic overflow and the total number of traffic call attempts in the independent dedicated control channel SDCCH;
the voice data transmitted in the voice channel comprises the total number of voice overflow and the total number of voice call trial.
17. The apparatus according to any one of claims 10 to 16, wherein determining whether the fine grid has a user group aggregation behavior according to the terminal behavior parameter alert value corresponding to the determined fine grid and the terminal behavior parameter in the fine grid area comprises:
and when the terminal behavior parameters in the fine grid region are determined to exceed the terminal behavior parameter warning values corresponding to the fine grid, determining whether the fine grid generates user group aggregation behaviors.
18. The apparatus of claim 12, wherein after determining the evacuation path for the user population in the fine grid in which the user population gathering behavior occurs, further comprising:
and carrying out evacuation guidance on the user groups in the fine grid according to the determined evacuation route in the form of broadcast notification or video playing.
19. A computer storage medium having a computer program stored thereon, the program, when executed by a processor, implementing the steps of the method according to any one of claims 1 to 9.
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