JP7273551B2 - Congestion prediction device, congestion prediction program and congestion prediction method - Google Patents

Description

The present invention relates to a congestion prediction device, a congestion prediction program, and a congestion prediction method for predicting congestion at an access point.

In wireless communication, communication terminal devices move dynamically. When communication terminal equipment concentrates on a specific base station when an event or disaster occurs, the capacity of the base station may exceed its normal capacity and congestion may occur, resulting in communication failure. .

Japanese Patent Laid-Open No. 2004-100002 predicts the location of congestion from the position of the terminal and prevents congestion from occurring. However, the terminal position information alone is insufficient, and it is difficult to predict the occurrence of congestion.

JP-A-10-066138

SUMMARY OF THE INVENTION An object of the present invention is to provide a congestion prediction device that predicts with high accuracy a wireless access point where congestion will occur.

The congestion prediction device of the present invention is
an access point monitoring unit that monitors an access point log in which the number of terminal devices belonging to each access point is registered, and extracts from the access point log a warning access point whose belonging number reaches the warning number;
By referring to the building information in which the position of the building is associated with each building and the access point information in which the position of the access point is associated with each access point, a position adjacent to the security access point is obtained. a building extraction unit for extracting from the building information an adjacent building having a common position with any of the access points in the access point information;
Based on the event information in which the building where the event is held and the schedule where the event is held is associated for each event, and the adjacent building extracted from the building information, the location of the adjacent building is determined. a congestion predictor for predicting whether congestion will occur at the access point having the location.

The congestion prediction unit,
It is determined whether or not the start event, which is the event associated with the adjacent building and whose start date and time indicated by the schedule is included in the determination time period, is present in the event information. Predict whether congestion will occur in the building.

The congestion prediction unit,
When it is predicted that the congestion will occur in the adjacent building, by referring to the access point log and the access point information, the location of the adjacent building is different from the location, and the attribution number is the warning The access points whose number has not reached the number are identified, and it is determined to move the movable mobile antennas connected to the identified access points to the adjacent building where the congestion is predicted to occur.

The congestion prediction device further
A terminal sorting unit is provided for allowing only a specific terminal device to belong to the access point connected to the mobile antenna determined to be placed in the adjacent building.

The congestion prediction program of the present invention is
to the computer,
an access point monitoring process for monitoring an access point log in which the number of terminal devices belonging to each access point is registered, and extracting from the access point log a warning access point whose belonging number has reached the warning number;
By referring to the building information in which the position of the building is associated with each building and the access point information in which the position of the access point is associated with each access point, a position adjacent to the security access point is obtained. a building extraction process for extracting from the building information an adjacent building having a common position with any of the access points in the access point information;
Based on the event information in which the building where the event is held and the schedule where the event is held is associated for each event, and the adjacent building extracted from the building information, the location of the adjacent building is determined. and a congestion prediction process for predicting whether congestion will occur at the access point having the location.

The congestion prediction method of the present invention is
the computer
monitoring an access point log in which the number of terminal devices belonging to each access point is registered, extracting from the access point log a warning access point whose belonging number has reached the warning number;
By referring to the building information in which the position of the building is associated with each building and the access point information in which the position of the access point is associated with each access point, a position adjacent to the security access point is obtained. , extracting from the building information an adjacent building having a common position with any of the access points in the access point information;
Based on the event information in which the building where the event is held and the schedule where the event is held is associated for each event, and the adjacent building extracted from the building information, the location of the adjacent building is determined. Predict whether congestion will occur at the access point with location.

According to the present invention, congestion occurrence access can be performed based on information such as the load status of a plurality of wireless access points, the schedule information of events held in the building where the access points are located, and the positional relationship between the building and the access points. Since the point is predicted, the occurrence of congestion can be predicted with high accuracy. Also, since the movable antenna is moved to the point where congestion is predicted to occur, it is possible to prevent congestion.

FIG. 2 is a diagram of the first embodiment and shows a system in which the congestion prediction device 100 is used; FIG. 4 is a diagram of the first embodiment, showing an overview of processing executed by the congestion prediction device 100; FIG. 2 is a diagram of the first embodiment and shows the hardware configuration of the congestion prediction device 100; FIG. 10 is a flowchart showing the operation of the congestion prediction device 100 in the first embodiment; FIG. FIG. 4 is a diagram of the first embodiment and shows access point information 61a; Fig. 10 is a diagram of the first embodiment and shows an access point log 62a in which all conditions are normal; FIG. 10 is a diagram of the first embodiment and shows an access point log 62a with a warning situation; Fig. 10 is a diagram of the first embodiment, showing building information 63a; Fig. 20 is a diagram of the first embodiment and shows schedule information 200a; Fig. 10 is a diagram of the first embodiment and shows prediction information 64a; Fig. 10 is a diagram of the first embodiment and shows antenna information 65a in a state where a mobile antenna 5 is moved; Fig. 10 is a diagram of the first embodiment and shows antenna information 65a in which a mobile antenna 5 and a mobile antenna 6 are moved; Fig. 10 is a diagram of the first embodiment showing antenna information 65a in a state in which the mobile antenna 5 is moved to its original position;

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. In each figure, the same reference numerals are given to the same or corresponding parts. In the description of the embodiments, the description of the same or corresponding parts will be omitted or simplified as appropriate.

(1) Below, an access point may be described as AP. All access points in the following description are wireless access points.
(2) Below, the database is written as DB.
(3) Below, the access point database 61 is described as APDB61.
The access point information 61a stored in the APDB 61 is referred to as AP information 61a. The access point log database 62 is written as AP log DB62. An access point log stored in the AP log DB 62 is referred to as an AP log 62a.

Embodiment 1.
*** Configuration description ***
The congestion prediction device 100 according to the first embodiment will be described with reference to FIGS. 1 to 13. FIG. FIG. 1 shows a system in which a congestion prediction device 100 is used. Connected to the network 500 are the congestion prediction device 100, AP 210, AP 220, and schedule system. The schedule system includes a schedule DB 200 that stores schedule information 200a, which will be described later. Although two APs, AP210 and AP220, are described, this is an example, and the number of APs may be three or more. A movable antenna 210a is connected to the AP 210, and movable antennas 220a and 220b are connected to the AP 220. FIG. The mobile antennas 210a, 220a, and 220b that can be moved may be moved by a moving object such as a drone, or may be carried by a person. A plurality of terminal devices 310 belong to APs 210 and 220 via mobile antennas. The congestion prediction device 100 collects AP logs 62a described later from each AP.

The congestion prediction device 100 includes an access point monitoring unit 10, a building extraction unit 20, a congestion prediction unit 30, and a terminal distribution unit 40. The congestion prediction device 100 also includes an APDB 61 , an AP log DB 62 , a building DB 63 , a prediction DB 64 and an antenna DB 65 .

The APDB 61 stores AP information 61a. The AP log DB 62 stores AP logs 62a. The building DB 63 stores building information 63a. The prediction DB 64 stores prediction information 64a. The antenna DB 65 stores antenna information 65a. APDB 61 to antenna DB 65 and schedule DB 200 will be described later with reference to FIGS. 5 to 13 .

FIG. 2 is a diagram showing an overview of processing executed by the congestion prediction device 100. As shown in FIG. There are buildings 1 to 4. An AP is arranged in each building. Each AP is equipped with a mobile antenna. AP1 to AP6 are shown in FIG. In FIG. 2, descriptions such as (a, b) indicate positions. With respect to the number of terminal devices belonging to each AP, it is assumed that the number of warning terminals causing congestion is 200, and congestion occurs when the number of terminal devices belonging to each AP is 400 or more. At present, the number of terminals belonging to AP1 is 300 units, and the number of terminals belonging to AP2 is 200 units. The congestion prediction device 100 learns this situation based on the AP log DB 62 . In addition, the congestion prediction device 100 determines that an event has started in the building 2 before a certain time that is the judgment time from the current time, or that an event has started in the building 2 after a certain time that is the judgment time from the current time. will start based on the schedule DB 200. In that case, the congestion prediction device 100 predicts that 300 units of AP1 and 200 units of AP2 will belong to AP3 of building 2 . In this case, the congestion prediction device 100 predicts that a total of 500 terminal devices will belong to AP3 and congestion will occur at AP3, and connects to AP5, which is close to AP3 and has a smaller number of terminals to which the terminal devices belong. An instruction to move the movable antenna 5 to the building 2 is issued. The mobile antenna 5 moved to the building 2 associates the terminal device located in the building 2 with the AP 5 . Congestion of the AP 3 of the building 2 can be prevented in advance by the above operation.

FIG. 3 shows the hardware configuration of the congestion prediction device 100. As shown in FIG. The congestion prediction device 100 is a computer. The congestion prediction device 100 includes a processor 110 and other hardware such as a main storage device 120, an auxiliary storage device 130, an input IF 140, an output IF 150 and a communication IF 160. Note that IF indicates an interface. Processor 110 is connected to and controls other hardware via signal lines 170 .

The congestion prediction device 100 includes an access point monitoring unit 10, a building extraction unit 20, a congestion prediction unit 30, and a terminal distribution unit 40 as functional elements. The access point monitoring unit 10 , building extraction unit 20 , congestion prediction unit 30 and terminal distribution unit 40 are realized by the congestion prediction program 101 .

A processor 110 is a device that executes the congestion prediction program 101 . The congestion prediction program 101 is a program that implements the functions of the access point monitoring unit 10 , the building extraction unit 20 , the congestion prediction unit 30 and the terminal distribution unit 40 . The processor 110 is an IC (Integrated Circuit) that performs arithmetic processing. Specific examples of the processor 110 are a CPU (Central Processing Unit), a DSP (Digital Signal Processor), and a GPU (Graphics Processing Unit).

The main memory device 120 is a storage device. Specific examples of the main memory device 120 are SRAM (Static Random Access Memory) and DRAM (Dynamic Random Access Memory). The main memory device 120 holds the computation results of the processor 110 .

The auxiliary storage device 130 is a storage device that stores data in a non-volatile manner. A specific example of the auxiliary storage device 130 is an HDD (Hard Disk Drive). The auxiliary storage device 130 is a portable recording medium such as an SD (registered trademark) (Secure Digital) memory card, a NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, and a DVD (Digital Versatile Disk). There may be. The auxiliary storage device 130 stores a congestion prediction program 101, an APDB 61, an AP log DB 62, a building DB 63, a prediction DB 64, and an antenna DB 65. Data such as the congestion prediction program 101, APDB 61, AP log DB 62, building DB 63, prediction DB 64, and antenna DB 65 are stored in another device such as a cloud server. may be obtained.

The input IF 140 is a port to which various devices are connected and data is input from the various devices. The output IF 150 is a port to which various devices are connected and data is output from the processor 110 to the various devices. Communication IF 160 is a communication port for the processor to communicate with other devices. The congestion prediction device 100 acquires the AP log 62a via the communication IF 160 and refers to the schedule DB 200 via the communication IF 160. FIG.

The processor 110 loads the congestion prediction program 101 from the auxiliary storage device 130 to the main storage device 120, reads the congestion prediction program 101 from the main storage device 120, and executes it. The main storage device 120 stores not only the congestion prediction program 101 but also an OS (Operating System). The processor 110 executes the congestion prediction program 101 while executing the OS. The congestion prediction device 100 may include multiple processors that substitute for the processor 110 . These multiple processors share the execution of the congestion prediction program 101 . Each processor, like the processor 110, is a device that executes the congestion prediction program 101. FIG. Data, information, signal values, and variable values used, processed, or output by the congestion prediction program 101 are stored in the main memory 120, the auxiliary memory 130, or the registers or cache memory within the processor 110. FIG.

In the congestion prediction program 101, the access point monitoring unit 10, the building extraction unit 20, the congestion prediction unit 30, and the terminal sorting unit 40 are replaced with "processing", "procedure", or "process". Alternatively, it is a program that causes a computer to execute each step.

The congestion prediction method is a method performed by the congestion prediction device 100, which is a computer, executing the congestion prediction program 101. FIG. The congestion prediction program 101 may be stored in a computer-readable recording medium and provided, or may be provided as a program product.

***Description of operation***
FIG. 4 is a flowchart for explaining the operation of the congestion prediction device 100. As shown in FIG.
The operation of the congestion prediction device 100 will be described with reference to FIG. Figures in parentheses in FIG. 4 indicate the subject of the action. The operation of the congestion prediction device 100 corresponds to a congestion prediction method. The operation of the congestion prediction device 100 corresponds to the processing of the congestion prediction program 101. FIG.

<Step S11>
The access point monitoring unit 10 monitors the AP log 62a in which the number of terminal devices belonging to each AP is registered, and extracts from the AP log 62a the warning access point whose belonging number has reached the warning number. Specifically, the operation of the access point monitoring unit 10 is as follows.
In step S11, the access point monitoring unit 10 refers to the AP log 62a of the AP log DB 62 and monitors the number of terminal devices 310 belonging to each access point.
FIG. 5 shows AP information 61a stored in the APDB 61. As shown in FIG. The AP information 61a has columns of the AP name, the antenna connected to the AP, the position of the AP, the number of warning terminals, and the number of congested terminals where congestion occurs.
FIG. 6 shows an AP log 62a stored in the AP log DB 62. As shown in FIG. The AP log 62a has columns of log ID, AP name, time, number of terminals at that time, and status. FIG. 6 shows the AP log 62a at the current time “2019/1/16 9:00”. The number of affiliated terminals of AP1 to AP6 has not reached the number of alert terminals (FIG. 5), and the "alert" statuses of AP1 to AP6 are all normal.

<Step S12>
In step S12, the access point monitoring unit 10 refers to the AP log 62a of the AP log DB 62 to determine whether or not there is an AP in which the number of attached terminal devices exceeds the warning value.
FIG. 7 shows the AP log 62a one hour after the AP log 62a of FIG. In FIG. 7, the number of attached terminals of AP1 and AP2 is 200 or more, and the "warning" statuses of both AP1 and AP2 are "warning". By referring to the AP log 62a of FIG. 7, the access point monitoring unit 10 extracts AP1 and AP2 from the AP log 62a as APs to which the terminal devices having the warning value or more belong. The number of terminals belonging to AP1 is 300, the number of terminals belonging to AP2 is 200, and the access point monitoring unit 10 recognizes the number of terminals belonging to AP1 and the number of terminals belonging to AP2.

<Step S13>
The building extraction unit 20 refers to the building information 63a in which the positions of the buildings are associated with each building and the AP information 61a in which the positions of the APs are associated with each AP, thereby identifying positions adjacent to the security access points. Then, from the building information 63a, an adjacent building having a common position with any AP of the AP information 61a is extracted. Specifically, it is as follows. In step S13, the building extraction unit 20 compares the combination of APs exceeding the warning value with adjacent APs in the building DB, and extracts the building to which the terminal device is to be moved.
FIG. 8 shows building information 63a stored in the building DB 63. As shown in FIG. In this example, in step S12, the access point monitoring unit 10 extracts AP1 and AP2 as APs having the number of attributions equal to or greater than the warning value. The building information 63a has columns of building IDs, building names, building positions, and adjacent APs adjacent to the building. In the building information 63a, building 2 and building 4 have AP1 and AP2 as adjacent APs. The building extraction unit 20 extracts buildings 2 and 4 having AP1 and AP2 as adjacent APs from the building information 63a.

<Step S14>
The congestion prediction unit 30 predicts the position of the adjacent building and the Predict whether congestion will occur at APs that have a common location. The schedule information 200a is event information. The congestion prediction unit 30 determines whether or not the event information includes a start event, which is an event associated with an adjacent building and whose start date and time indicated by the schedule is included in the determination time period. The congestion prediction unit 30 predicts whether or not congestion will occur in adjacent buildings based on the determination result. Here, the determination time zone is, for example, a range of +3 hours and -3 hours from the current time at which it is determined whether or not the start event exists in the event information. If the current time is 10:00 am, the range is from 7:00 am to 1:00 pm.
Specifically, it is as follows.
In step S14, the congestion prediction unit 30 selects, from among the buildings extracted from the building information 63a by the building extraction unit 20, the building where the event scheduled to be held before or after the current time will be held. Narrow down.
FIG. 9 shows schedule information 200a stored in the schedule DB 200. As shown in FIG. The schedule information 200a is event information. The schedule information 200a has columns of event name, start time, end time, building ID, and expected number of people. The start time and end time indicate date and time. The expected number of people is the number of terminal devices that are expected to belong. The congestion prediction unit 30, by referring to the schedule information 200a, predicts that congestion will occur in Building 2 of Buildings 2 and 4 having AP1 and AP2 as adjacent APs. Specifically, the congestion prediction unit 30 predicts congestion as follows. According to the schedule information 200a, the event "Lecture by Mr. A" having the opening time of "2019/1/16 12:00" which is the latest to the current time "2019/1/16 10:00" will be held in the building T2. determined to be. The planned number of events “Lecture by Mr. A” is 150. The position of the building T2 is (c, d) from the building information 63a, and AP3 is arranged in the building T2 from the AP information 61a. AP3 has 400 congested terminals. On the other hand, the numbers of attached terminals of AP1 and AP2 extracted in step S12 are 300 and 200, respectively.
Therefore, the congestion prediction unit 30 predicts that the maximum predicted number of terminals belonging to building 2 at position (c, d) is 500, which is the sum of 200 and 300. The congestion prediction unit 30 registers the predicted number of terminal devices in the prediction DB 64 as prediction information 64a.
FIG. 10 shows the schedule information 200a showing the prediction information 64a stored in the prediction DB 64. The schedule information 200a includes the prediction ID, the position where the occurrence of congestion is expected, and the maximum number of terminals that can be expected to belong to the position where the occurrence of congestion is expected. has a column of FIG. 10 shows the result of the congestion prediction unit 30 predicting 500 as the maximum predicted number of terminals belonging to the building 2 at position (c, d) and registering it in the prediction DB 64 .

<Step S15>
When the congestion prediction unit 30 predicts that congestion will occur in the adjacent building, the congestion prediction unit 30 refers to the AP log 62a and the AP information 61a to determine that the location is different from the location of the adjacent building, and that the number of belongings is the warning number. Identify the APs that are not reached. The congestion prediction unit 30 decides to move the movable antenna connected to the specified AP to the adjacent building where congestion is predicted to occur.
Specifically, it is as follows.
In step S<b>15 , the congestion prediction unit 30 executes antenna movement processing to move the mobile antenna to the building registered in the prediction DB 64 . The congestion prediction unit 30 refers to the prediction information 64a registered in the prediction DB 64 and executes antenna movement processing. The congestion prediction unit 30 refers to the APDB 61, the AP log DB 62, the prediction DB 64, and the antenna DB 65, and extracts antennas to be moved as follows.
FIG. 11 shows antenna information 65a stored in the antenna DB 65. As shown in FIG. The antenna information 65a targets all mobile antennas and has columns of the antenna ID of the mobile antenna, the current position of the mobile antenna, and the column of usability indicating whether or not the mobile antenna is currently usable. In the usability column, 1 indicates unusable and 0 indicates usable. The mobile antenna is "usable=1" if the current position is a moved position, and is "usable=0" if the current position is not a moved position. The congestion prediction unit 30 records the antenna information 65a. The content of the antenna information 65a referred to this time is the content recorded last time by the congestion prediction unit 30 . The congestion prediction unit 30 is a movable mobile antenna that is connected to an AP whose belonging count is not alert among APs that are close to the position (predicted position) registered in the prediction information 64a, and whose usability=0. Extract the moving antenna. In this example, as shown in FIG. 2 , the congestion prediction unit 30 determines to move the mobile antenna 5 connected to the AP 5 whose position is (m, n) to the building 2 . When the movement of the mobile antenna is determined, the congestion prediction unit 30 includes information specifying the mobile antenna to be moved and the position of the movement destination for the base station apparatus of the AP to which the mobile antenna to be moved is connected. Send a movement instruction signal. The base station side manually or automatically moves the mobile antenna according to the movement instruction signal.

<Step S16>
The terminal sorting unit 40 performs terminal sorting processing to allow only a specific terminal device to belong to the AP connected to the mobile antenna determined to be placed in the adjacent building. In other words, the terminal distribution unit 40 assigns only specific terminal devices to APs connected to mobile antennas determined to be placed in adjacent buildings.
Specifically, it is as follows.
In step S16, the terminal sorting unit 40 carries out a sorting process of sorting the terminal devices. The sorting process refers to a process of separating the terminal device belonging to the AP located in the building (adjacent building) determined as the moving destination of the mobile antenna and the terminal device belonging to the AP to which the mobile antenna is connected. As a specific example, the terminal distribution unit 40 assigns the terminal devices of students of a specific school to the AP to which the mobile antenna is connected, and assigns the other terminal devices to the building determined as the destination of the mobile antenna. Such is the case for attribution to the AP of the location.

<Step S17>
In step S17, the congestion prediction unit 30 refers to the AP log DB 62 to determine whether or not the number of mobile terminals belonging to the AP to which the mobile antenna is connected is equal to or greater than the warning value. After monitoring for a certain period of time, if the warning value is raised (NO in step S17), the congestion prediction unit 30 moves the mobile antenna to the initial position (step S20). In this example, in FIG. 1, an instruction to move the mobile antenna 5 from the building 2 to the position (m, n) of the AP 5 is generated and transmitted to the base station apparatus of the AP 5 to which the moving mobile antenna 5 is connected. do. In this case, the congestion prediction unit 30 updates the antenna DB 65 .
FIG. 12 shows the antenna DB 65 updated when the congestion prediction unit 30 decides to move the mobile antenna 5 to the position (m, n) of the AP 5, which is the initial position. In FIG. 12, the position of ANT5 is changed from (c, d) to (m, n).

<Step S18>
If it is determined in step S17 that the number of mobile terminals belonging to the AP to which the mobile antenna is connected is greater than or equal to the warning value (YES in step S17), the mobile antenna of the neighboring AP is further moved. This is because when the number of belonging APs to which mobile antennas are connected is greater than or equal to the warning value, it is assumed that the current number of antennas is insufficient, so the antennas are further moved from nearby APs. In this example, the congestion prediction unit 30 determines to move the mobile antenna 6 of AP6 to building 2 in FIG. At this time, the congestion prediction unit 30 updates the antenna DB 65 .
FIG. 13 shows the antenna DB 65 updated when the congestion prediction unit 30 decides to move the mobile antenna 6 to the position (c, d) of the building 2 .
<Step S19>
In step S19, similarly to step S17, the congestion prediction unit 30 determines whether the status of the AP connected to the moved mobile antenna is equal to or higher than the warning value. If it is equal to or greater than the caution value, the process proceeds to step S18, and if it is less than the caution value, the process proceeds to step S20.

*** Effect of Embodiment 1 ***
(1) According to the congestion prediction device 100 of Embodiment 1, it is possible to predict the occurrence of AP congestion and prevent the occurrence of congestion.
(2) In addition, the congestion prediction device 100 moves mobile antennas connected to other APs to the AP predicted to be congested, so that the terminal device attempting to belong to the AP predicted to be congested is notified that the congestion is predicted. At the location of the predicted AP, it is attributed to other APs. Therefore, idle APs can be effectively utilized.
(3) Since the congestion prediction device 100 allocates APs installed in other places to terminal devices at AP positions where congestion is expected, the number of APs to be installed can be reduced.

Although the first embodiment has been described above, one of the first embodiments may be partially implemented. Alternatively, two or more of the first embodiment may be partially combined and implemented. The present invention is not limited to Embodiment 1, and various modifications are possible as required.

AP access point, 10 access point monitoring unit, 20 building extraction unit, 30 congestion prediction unit, 40 terminal sorting unit, 61 AP DB, 61a AP information, 62 AP log, 62a AP log, 63 building DB, 63a building information, 64 prediction DB, 64a prediction information, 65 antenna DB, 65a antenna information, 90 electronic circuit, 91 signal line, 100 congestion prediction device, 101 congestion prediction program, 110 processor, 120 main storage device, 130 auxiliary storage device, 140 input IF, 150 output IF, 160 communication IF, 170 signal line, 200 schedule DB, 210,220 access point, 210a, 220a, 220b mobile antenna, 310 terminal device, 400 building, 500 network.

Claims (6)

an access point monitoring unit that monitors an access point log in which the number of terminal devices belonging to each access point is registered, and extracts from the access point log a warning access point whose belonging number reaches the warning number;
By referring to the building information in which the position of the building is associated with each building and the access point information in which the position of the access point is associated with each access point, a position adjacent to the security access point is obtained. a building extraction unit for extracting from the building information an adjacent building having a common position with any of the access points in the access point information;
Based on the event information in which the building where the event is held and the schedule where the event is held is associated for each event, and the adjacent building extracted from the building information, the location of the adjacent building is determined. and a congestion prediction unit that predicts whether or not congestion will occur at the access point having the location. The congestion prediction unit,
It is determined whether or not the start event, which is the event associated with the adjacent building and whose start date and time indicated by the schedule is included in the determination time period, is present in the event information. The congestion prediction device according to claim 1, which predicts whether or not congestion will occur in a building. The congestion prediction unit,
When it is predicted that the congestion will occur in the adjacent building, by referring to the access point log and the access point information, the location of the adjacent building is different from the location, and the attribution number is the warning Identifying the access points whose number has not reached the number, and determining to move a movable mobile antenna connected to the identified access point to the adjacent building where the congestion is predicted to occur, or The congestion prediction device according to claim 2. The congestion prediction device further
4. The congestion prediction device according to claim 3, further comprising a terminal sorting unit that recognizes attribution of only a specific terminal device to said access point connected to said mobile antenna determined to be placed in said adjacent building. to the computer,
an access point monitoring process for monitoring an access point log in which the number of terminal devices belonging to each access point is registered, and extracting from the access point log a warning access point whose belonging number has reached the warning number;
By referring to the building information in which the position of the building is associated with each building and the access point information in which the position of the access point is associated with each access point, a position adjacent to the security access point is obtained. a building extraction process for extracting from the building information an adjacent building having a common position with any of the access points in the access point information;
Based on the event information in which the building where the event is held and the schedule where the event is held is associated for each event, and the adjacent building extracted from the building information, the location of the adjacent building is determined. and a congestion prediction process for predicting whether or not congestion will occur at the access point having the location. the computer
monitoring an access point log in which the number of terminal devices belonging to each access point is registered, extracting from the access point log a warning access point whose belonging number has reached the warning number;
By referring to the building information in which the position of the building is associated with each building and the access point information in which the position of the access point is associated with each access point, a position adjacent to the security access point is obtained. , extracting from the building information an adjacent building having a common position with any of the access points in the access point information;
Based on the event information in which the building where the event is held and the schedule where the event is held is associated for each event, and the adjacent building extracted from the building information, the location of the adjacent building is determined. A congestion prediction method for predicting whether congestion will occur at said access point having a location.

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