JP5979352B2 - Information processing apparatus, movement prediction system, and movement prediction method - Google Patents

Description

  The present invention relates to an information processing apparatus, a movement prediction system, a movement prediction method, and the like.

  In order to ascertain the number of customers in building plans for commercial facilities, etc., the concentration of people in a specific area is predicted. In addition, in order to confirm whether a safe evacuation can be performed at the time of a disaster in an area such as a station where the population is likely to concentrate, movement prediction of people, cars, etc. may be performed.

  For example, Patent Literature 1 uses a communication log when a radio base station and a mobile station (for example, a communication terminal such as a mobile phone) communicate, and aggregates the liquid population by associating with a population accommodation facility. We propose a system that estimates with high accuracy.

JP 2010-200823 A

  Here, it is generally known that not only human behavior but also vehicle flow and animal behavior change due to sudden weather fluctuations such as guerrilla heavy rain, a sudden rise in temperature due to the Fern phenomenon, and sudden strong winds. In such a case, if an accurate prediction can be made with respect to the actual weather fluctuations, it is possible to take appropriate measures such as vehicle traffic guidance and installation of a net for animals.

  For example, when it rains suddenly, the peak of congestion may be brought forward than usual in restaurants in commercial facilities. In such a case, as a restaurant, there is a desire to rush preparations and increase the number of customers.

  Furthermore, for example, in a facility that is used as a temporary evacuation site due to rapid weather fluctuations, an accurate prediction result may be required as to whether or not more people are still evacuating from the viewpoint of ensuring safety.

  The invention of Patent Document 1 analyzes communication in units such as January, for example, and does not estimate the fluid population in response to sudden weather fluctuations. Nor does it provide a means to predict rapid climate change.

  The present invention has been made in view of the above problems, and according to some aspects of the present invention, a local weather change is predicted, and the movement and distribution of a moving body due to the weather change are determined. It is possible to provide a movement prediction system and a movement prediction method that generate movement prediction information for predicting with high accuracy.

  SUMMARY An advantage of some aspects of the invention is to solve at least a part of the problems described above, and the invention can be implemented as the following aspects or application examples.

[Application Example 1]
The information processing apparatus according to this application example associates the environment prediction unit that predicts the environmental change of the region using the environment information of the region where the moving body moves, and the environment information and the position of the moving body. A correspondence data generation unit that generates correspondence data, a prediction result of the environment prediction unit, and the correspondence data are used to predict a position where the moving body moves, and movement including the predicted position information of the moving body A movement prediction information generation unit that generates prediction information.

  According to the information processing apparatus according to this application example, by providing the environment prediction unit, the environment change of the region (hereinafter also simply referred to as “region”) in which the moving body moves based on the environment information is predicted. In addition, by providing a correspondence data generation unit, correspondence data in which the environment information and the position of the moving body are associated with each other is generated. Then, the movement prediction information generation unit generates the movement prediction information including the predicted position information of the moving body using the prediction result of the environment prediction unit and the corresponding data.

  At this time, the information processing apparatus according to this application example can recognize a local weather change in real time by including the environment prediction unit. And the correlation information with the prediction result of an environment prediction part is extracted from the corresponding | compatible data accumulated, or the positional information on a moving body is estimated by analyzing in time series. Here, since the correspondence data is data in which the position of the past moving body and the actual environment information are associated with each other, the prediction accuracy can be improved.

  Therefore, according to the information processing apparatus according to this application example, it is possible to predict a local weather change and accurately predict the movement and distribution of the moving body due to the weather change.

  Note that the extraction of the association rule and the analysis in time series are one of data mining methods, and the frequent pattern may be extracted by other methods to predict the position information of the moving object.

  Moreover, environmental information is the environmental data regarding the weather measured, for example by the environment measuring device distributed in the area | region. As environmental data, for example, one or more data such as humidity, wind direction, wind speed, rainfall, air quality, etc. may be used in addition to atmospheric pressure and temperature.

  The correspondence data associates the environmental data with the position of the moving object. For example, it may be converted into data in the form of a table. The moving body may be individually converted into data, but may be handled collectively within a range where the position of the moving body can be predicted, that is, within a range where the tendency can be grasped. At this time, the calculation load for predicting the position of the moving body can be reduced.

  By knowing such movement prediction information, for example, department stores and the like can predict customer acquisition, and restaurants can predict the peak of congestion. In addition, it can be used for efficient traffic control by predicting traffic concentration on tourist spots, around stations, and roads around shops where congestion is expected. In addition, in a facility used as an evacuation site at the time of a disaster, it is possible to predict whether danger will occur due to excessive concentration of people.

[Application Example 2]
In the information processing apparatus according to the application example, the correspondence data generation unit may generate the correspondence data in which the mobile objects are classified into groups using map information of the area.

[Application Example 3]
In the information processing apparatus according to the application example, the movement prediction information generation unit may generate the movement prediction information filtered by the group.

[Application Example 4]
In the information processing apparatus according to the application example described above, the movement prediction information generation unit may generate a distribution on the map of the moving body as the position information using map information of the region.

  According to the information processing apparatus according to these application examples, the correspondence data generation unit classifies the moving objects into groups and generates correspondence data. At this time, by grouping together moving bodies having the same properties, it is possible to easily grasp the tendency of the moving bodies to move and to predict with high accuracy.

  The group is determined by, for example, the movement of the moving body and the map information. For example, when a certain moving body is on a road and moving at a speed of 50 km / h or more, it can be classified into a group called vehicles. And it becomes easy to grasp the tendency of movement by distinguishing a vehicle and a person according to a group.

  Further, for example, when a certain moving body stays in a place that is an office building for a long time according to the map information, it can be classified into a group different from the shoppers of other shopping centers. As described above, by classifying the groups as finely as possible, it is possible to more easily grasp the tendency of each group to which the moving body moves. Moreover, if a tendency can be grasped | ascertained appropriately, also about the prediction of the positional information on a moving body, accuracy can be improved.

  Here, the movement prediction information generation unit may generate movement prediction information by performing filtering in groups. Here, filtering refers to selecting according to conditions, for example, selecting only a shopper as a moving object. At this time, it is possible to efficiently generate only the required movement prediction information.

  Further, the movement prediction information generation unit may generate the distribution of the moving object on the map as the position information using the map information of the area. At this time, the predicted position information of the moving body can be displayed visually and in an easily understandable manner using a map. In addition, for example, even when there are many target moving bodies (for example, several thousand to several tens of thousands), since the individual moving bodies are not displayed but are displayed as distributions, the prediction result can be easily communicated. .

[Application Example 5]
The information processing apparatus according to the application example described above may target at least one of a person, a vehicle, and an animal as the moving body.

  According to the information processing apparatus according to this application example, at least one of a person, a vehicle, and an animal is a moving body. The moving body is not limited to a specific object, but may be not only a person but also a vehicle such as an automobile or a two-wheeled vehicle, an animal, or the like. In addition, only vehicles and animals can be targeted according to the area and purpose.

  For example, only the vehicle may be targeted for the purpose of grasping the traffic volume. At this time, the moving body includes a person, and only the vehicle may be selected by the above filtering. Further, when the area is farmland and the information processing apparatus is used as a countermeasure for damage to crops, only animals may be targeted.

[Application Example 6]
The movement prediction system according to this application example includes any one of the information processing apparatuses described above and a plurality of environment measurement apparatuses arranged in a distributed manner in the region.

  According to the movement prediction system according to this application example, environmental conditions are analyzed in real time using environment information measured by each of a plurality of environmental measurement devices distributed and arranged in a region where the moving body moves. Therefore, the environment change in the area can be predicted more accurately, and the information processing apparatus can generate more accurate movement prediction information.

[Application Example 7]
In the movement prediction method according to this application example, the step of predicting the environmental change of the area using the environmental information of the area where the moving body moves, and the correspondence data associating the environmental information with the position of the moving body Generating a predicted position of the moving body using the predicted environment change of the region and the corresponding data, and generating movement prediction information including the predicted position information of the moving body Including the steps of:

[Application Example 8]
The program according to this application example associates a computer with an environment prediction unit that predicts an environment change in the area using environment information of the area in which the moving body moves, and the environment information and the position of the moving body. A correspondence data generation unit that generates correspondence data, a prediction result of the environment prediction unit, and the correspondence data are used to predict a position where the moving body moves, and includes predicted position information of the moving body It is made to function as a movement prediction information generation part which generates movement prediction information.

[Application Example 9]
The recording medium according to the application example is a recording medium in which the program according to the application example is recorded.

FIG. 1A to FIG. 1C are explanatory diagrams of an outline of a movement prediction system. FIGS. 2A to 2C are diagrams showing examples of the appearance of mobile terminals and information terminals. The figure which shows the structural example of the movement prediction system of 1st Embodiment. The figure which shows the structural example of an environmental measurement apparatus. The figure which shows the structural example of a mobile terminal. The figure which shows the structural example of the information terminal in 1st Embodiment. The figure which shows the structural example of the server in 1st Embodiment. FIG. 8A to FIG. 8D are diagrams illustrating examples of prediction results of environmental changes. FIG. 9A to FIG. 9B are diagrams showing examples of groups and correspondence tables. The figure which shows an example of the flowchart of the process of the server in 1st Embodiment. The figure which shows an example of the flowchart of the process of the information terminal in 1st Embodiment. The figure which shows an example of the display screen of an information terminal. The figure which shows the structural example of the information terminal in 2nd Embodiment. The figure which shows the structural example of the server in 2nd Embodiment. The figure which shows an example of the flowchart of the process of the information terminal in 2nd Embodiment. The figure which shows an example of the flowchart of the process of the server in 2nd Embodiment.

  DESCRIPTION OF EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. The embodiments described below do not unduly limit the contents of the present invention described in the claims. Also, not all of the configurations described below are essential constituent requirements of the present invention.

1. 1. First embodiment 1-1. Overview of Movement Prediction System FIGS. 1A to 1C are explanatory diagrams of an overview of a movement prediction system. In the movement prediction system of the first embodiment, as shown in FIG. 1A, a plurality of environment measurement devices 2 (displayed by white circles) are several tens of meters in a target area where movement of a moving body is predicted. Dispersed and arranged at intervals of several hundred meters. This area may include buildings 99 such as commercial facilities, public facilities, private houses, and station buildings in addition to roads. The movement prediction system predicts movement positions of a plurality of moving bodies 7 (for example, people, vehicles, animals, etc.) in an area in association with environmental information.

  The environmental measuring device 2 may not be arranged at a uniform density, and may be dense depending on the location. For example, the density of the environmental measurement device 2 may be high around the road, and the density of the environmental measurement device 2 may be low in other locations. In places where the density is low, the distance between the environmental measuring devices 2 may be several kilometers.

  These environmental measurement devices 2 form an environmental measurement network in the area, and each environmental measurement device 2 measures environmental data such as the current weather and transmits it to a server (not shown).

  Moreover, in the movement prediction system of this embodiment, the mobile body 7 carries the mobile terminal 6, as shown in FIG.1 (B)-FIG.1 (C). In the example of FIG. 1B, the moving body 7 is a person, and in the example of FIG. 1C, the moving body 7 is an automobile.

  The mobile terminal 6 may be anything that moves together with the mobile body 7 to generate position information of the mobile body 7 and transmits it to a server (not shown). In the example of FIG. 1B, the mobile terminal 6 is worn on the wrist like a wristwatch, and in the example of FIG. 1C, a car navigation device serves as the mobile terminal 6.

  The moving body 7 is not limited to a target, and may be an animal having a collar type mobile terminal 6 or a bicycle with the mobile terminal 6 attached thereto.

  The server predicts the temporal transition of the environment in the area from the time series of the environmental data measured in real time by each environmental measuring device 2. Further, the server receives the position information of the moving body 7 from the mobile terminal 6. Then, the server predicts the subsequent position of the moving object using the environmental prediction result and the position information of the moving object, and generates movement prediction information including the predicted position information. After that, the server transmits the movement prediction information to the information terminal, and the owner of the information terminal can know the predicted position information of the moving body, and can be used for, for example, customer acquisition prediction.

  FIGS. 2A, 2 </ b> B, and 2 </ b> C are diagrams illustrating an example of the appearance of the information terminal 5 and the mobile terminal 6. For example, the information terminal 5 and the mobile terminal 6 may be of a wristwatch type as shown in FIG. 2A, or may be put in a pocket of clothes or a band as shown in FIG. It may be of a type that is fixed to the body of the moving body 7 or clothes with a clip. Moreover, the navigation terminal which can be attached to the fixing tool of the moving body 7 like a vehicle may be sufficient. Alternatively, the information terminal 5 and the mobile terminal 6 may be terminals such as a smartphone or a mobile phone as shown in FIG.

  As described above, the mobile terminal 6 moves together with the mobile object 7, generates position information of the mobile object 7, and transmits it to the server. The information terminal 5 receives movement prediction information from the server. Therefore, in the case of the mobile terminal 6, the operation unit 40 and the display unit 70 may not be provided in FIGS. 2 (A) to 2 (C).

  In the case of the information terminal 5, the owner or the like switches the screen by operating the operation unit 40, and the movement prediction information received from the server is displayed on the display unit (display screen) 70. Note that the information terminal 5 may be provided with a contact detection mechanism for the display unit 70 and also use the display unit 70 as an operation unit.

  Here, a person having the information terminal 5 or a vehicle including the information terminal 5 may be the moving body 7. At this time, the information terminal 5 and the mobile terminal 6 may be integrated, and may have the appearance shown in FIGS. 2 (A) to 2 (C). In the following description, it is assumed that the information terminal 5 and the mobile terminal 6 are not integrated.

  Moreover, when the mobile body 7 is an animal, the mobile terminal 6 may have the appearance of a collar (not shown). When the store requires movement prediction information, the information terminal 5 may have an appearance such as a cash register (not shown) or a large display (not shown) in the store.

1-2. Configuration of movement prediction system [Overall configuration]
FIG. 3 is a diagram illustrating a configuration example of the movement prediction system according to the first embodiment. The movement prediction system of the present embodiment may omit or change some of the components (each unit) in FIG. 3 or may have a configuration in which other components are added.

  As illustrated in FIG. 3, the movement prediction system 1 according to the first embodiment includes a plurality of mobile terminals 6 that move together with a plurality of environment measurement apparatuses 2 and a moving body 7 and transmit position information, and information that displays movement prediction information. A terminal 5 and a server 4 are included. In addition, although the several information terminal 5 is shown in FIG. 3, the information terminal 5 may be one.

  The environment measuring device 2 is distributed in an area including a region, measures the environment such as weather in each point of the area in real time, and transmits the measured environment data (environment information) to the communication network 3 (Internet or LAN). Etc.) to the server 4.

  The mobile terminal 6 generates position information of the mobile object 7 and transmits it to the server 4 via the communication network 3. The position information may be, for example, the position of the moving body 7 expressed in coordinates, but is not limited to this. The mobile terminal 6 may transmit a unique ID to each mobile terminal 6 together with the position information. In addition, when the vehicle provided with the information terminal 5 or the person carrying the information terminal 5 is the moving body 7 at the same time, a part or all of the mobile terminal 6 may be integrated with the information terminal 5.

  The server 4 (an example of an information processing device) receives environment data from the environment measurement device 2 and receives position information of the moving body 7 from the mobile terminal 6 via the communication network 3. Then, the server 4 analyzes the received information to generate movement prediction information and transmits it to the information terminal 5.

  The information terminal 5 receives the movement prediction information and notifies the owner or viewer (for example, the owner) of the information terminal 5 by display or sound.

[Configuration of environmental measurement equipment]
FIG. 4 is a diagram illustrating a configuration example of the environment measuring device 2 in the present embodiment. As shown in FIG. 4, in this embodiment, the environmental measurement device 2 includes an atmospheric pressure sensor 10, a temperature sensor 11, a humidity sensor 12, a wind direction / wind speed sensor 13, a rainfall sensor 14, an air quality sensor 15, and a transmission unit 16. Prepare. However, the environment measuring device 2 may not include a part of the various sensors described above, and conversely, may include another sensor (such as a radiation sensor).

  The atmospheric pressure sensor 10 is a sensor that measures ambient atmospheric pressure. For example, the lower the atmospheric pressure, the lower the oxygen absorption rate of the moving body 7 (here, a person or an animal), and thus the moving body 7 is easily fatigued. At this time, from the corresponding data described later, there is a possibility that the moving distance and moving speed of the moving body 7 tend to decrease when the atmospheric pressure decreases.

  The temperature sensor 11 is a sensor that measures the ambient temperature (air temperature). For example, as the temperature (air temperature) is higher, the amount of sweat of the moving body (here, a person or an animal) is increased, so that the moving body 7 is easily fatigued. At this time, from the correspondence data described later, there is a possibility that the moving distance and moving speed of the moving body 7 tend to decrease as the temperature increases.

  The humidity sensor 12 is a sensor that measures ambient humidity. For example, the sweating amount of the moving body (here, a person or an animal) increases as the humidity increases, so that the moving body 7 is easily fatigued. At this time, from the correspondence data described later, there is a possibility that the moving distance and moving speed of the moving body 7 tend to decrease as the humidity increases.

  The wind direction / wind speed sensor 13 is a sensor that measures the wind direction and wind speed in the vicinity. For example, the stronger the wind, the more difficult the moving body 7 moves. At this time, from the corresponding data described later, when the wind becomes strong, there is a possibility that the moving distance and moving speed of the moving body 7 tend to decrease.

  The rainfall sensor 14 is a sensor that measures the rainfall per unit time in the surrounding area. For example, if the amount of rainfall is large, the moving body 7 becomes difficult to move. At this time, from the correspondence data described later, when the amount of rainfall increases, there is a possibility that the moving distance and moving speed of the moving body 7 tend to decrease.

The air quality sensor 15 is a sensor that measures the concentration of fine particles (smoke, sand, pollen, etc.) and nitrogen oxides (NO _x ) in the surrounding air. For example, since the oxygen concentration decreases as the concentration of fine particles or the like present in the air increases, the mobile body 7 (here, a person or an animal) is likely to get tired. At this time, from the correspondence data described later, when the concentration of fine particles in the air increases, the moving distance and moving speed of the moving body 7 may tend to decrease.

  Each environment measuring device 2 measures the environment such as weather in real time with a period of, for example, a second order, and the atmospheric pressure sensor 10, the temperature sensor 11, the humidity sensor 12, the wind direction / wind speed sensor 13, the rainfall sensor 14, and the air quality sensor 15 The environmental data (atmospheric pressure data, temperature data, humidity data, wind direction / wind speed data, rainfall amount data, air quality data) measured by the above is transmitted to the server 4 by the transmission unit 16.

  Even if the environmental measuring device 2 is not equipped with a wind direction / velocity sensor, the atmospheric pressure gradient between two arbitrary points (between the two environmental measuring devices 2) (= pressure difference between two points / 2 points) Distance), and the current wind direction and speed can be estimated from the distribution of the atmospheric pressure gradient.

[Configuration of mobile terminal]
FIG. 5 is a diagram illustrating a configuration example of the mobile terminal 6 in the present embodiment. As shown in FIG. 5, in the present embodiment, the mobile terminal 6 includes a processing unit (CPU) 150, a GPS data receiving unit 162, a storage unit 166, a recording medium 168, and a communication unit 174. The mobile terminal 6 of this embodiment may omit or change some of the components (each unit) in FIG. 5 or may have a configuration with other components added.

  The GPS data receiving unit 162 receives a radio signal transmitted from a GPS satellite and demodulates a navigation message including orbit information and time information of the GPS satellite superimposed on the radio signal.

  The storage unit 166 stores programs, data, and the like for the processing unit (CPU) 150 to perform calculation processing and control processing. The storage unit 166 is used as a work area of the processing unit (CPU) 150, and programs and data read from the recording medium 168, data received from the server via the communication unit 174, and the processing unit (CPU) 150. Is also used for temporarily storing calculation results and the like executed according to various programs. Moreover, you may memorize | store the map data used in order to produce | generate the positional information on a moving body.

  The processing unit (CPU) 150 performs calculation processing and control processing according to programs stored in the storage unit 166 and the recording medium 168. Specifically, the processing unit (CPU) 150 receives data from the GPS data receiving unit 162 and performs a calculation process of position information. The processing unit (CPU) 150 performs processing for controlling data communication with the server via the communication unit 174.

  In the present embodiment, the processing unit (CPU) 150 includes a position information generation unit 151 and a communication control unit 152. However, the processing unit (CPU) 150 of the present embodiment may omit or change some of these configurations (elements), or may have a configuration in which other configurations (elements) are added.

  The position information generation unit 151 performs positioning calculation using the trajectory information and time information included in the navigation message demodulated by the GPS data reception unit 162, and obtains the position information of the mobile terminal 6 (that is, the position information of the moving body 7). Generate the process. In the present embodiment, the position information generation unit 151 generates the position information of the mobile object 7 using the navigation message demodulated by the GPS data reception unit 162, but the mobile object is acquired using other means. 7 position information may be generated. In that case, the GPS data receiving unit 162 may be omitted.

  For example, the position information generation unit 151 receives radio waves from a plurality of base stations (base stations such as mobile phones and wireless LANs), and performs triangulation using the received radio wave intensity and the position information of each base station. The position information of the moving body 7 may be generated by this method.

  The communication control unit 152 performs processing for controlling data communication performed with the server via the communication unit 174. In particular, in the present embodiment, the communication control unit 152 performs a process of transmitting the position information generated by the position information generation unit 151 to the server 4 via the communication unit 174. Further, the communication control unit 152 may perform a process of receiving necessary information (for example, map information, program) from the server via the communication unit 174.

  The recording medium 168 is a computer-readable recording medium. In particular, in the present embodiment, a program for causing the computer to function as each of the above-described units is stored. The processing unit (CPU) 150 of this embodiment functions as the position information generation unit 151 and the communication control unit 152 by executing a program stored in the recording medium 168. Alternatively, the program is received from a server connected to a wired or wireless communication network via the communication unit 174 or the like, the received program is stored in the storage unit 166 or the recording medium 168, and the program is executed. Also good.

  Note that at least a part of the position information generation unit 151 and the communication control unit 152 may be realized by hardware (dedicated circuit).

  The recording medium 168 can be realized by, for example, an optical disk (CD, DVD), a magneto-optical disk (MO), a magnetic disk, a hard disk, a magnetic tape, or a memory (ROM, flash memory, etc.).

  Here, the mobile terminal 6 may generate the position information at a predetermined time interval (for example, every minute), or generate the position information irregularly or in conjunction with the action of the mobile body 7 (for example, the start of movement). May be. In addition, the mobile terminal 6 according to the present embodiment is always operating like the environment measurement device 2 and continues to transmit position information to the server 4. However, the mobile terminal 6 may include an operation unit, for example, and may be turned on or off by an operation of the mobile body 7 (here, a person). The mobile terminal 6 includes an atmospheric pressure sensor (not shown), and the number of floors of a building where the mobile body 7 (here, a person or an animal) is present may be generated as position information.

[Configuration of information terminal]
FIG. 6 is a diagram illustrating a configuration example of the information terminal 5 in the present embodiment. As shown in FIG. 6, in this embodiment, the information terminal 5 includes an operation unit 40, a processing unit (CPU) 50, a GPS data receiving unit 62, a storage unit 66, a recording medium 68, a display unit 70, and a sound output unit 72. The communication unit 74 is included. The information terminal 5 of the present embodiment may omit or change some of the components (each unit) in FIG. 6 or may have a configuration in which other components are added.

  The operation unit 40 is an input device configured by operation keys, button switches, and the like, and outputs an operation signal corresponding to an operation by a moving body to a processing unit (CPU) 50. For example, the moving body may switch the on state and the off state of the information terminal 5 depending on whether or not it is desired to acquire the movement prediction information by operating the operation unit 40.

  The display unit 70 is a display device configured by an LCD (Liquid Crystal Display) or the like, and displays various types of information based on display signals input from the processing unit (CPU) 50.

  The sound output unit 72 is a device that outputs sound such as a speaker, and outputs various sounds (including sound) based on a signal input from the processing unit (CPU) 50.

  The GPS data receiving unit 62, the storage unit 66, and the recording medium 68 are the same as the GPS data receiving unit 162, the storage unit 166, and the recording medium 168 of the mobile terminal 6, and detailed description thereof is omitted. The storage unit 66 may be used for storing data input from the operation unit 40.

  The processing unit (CPU) 50 performs various types of calculation processing and control processing according to programs stored in the storage unit 66 and the recording medium 68. Specifically, the processing unit (CPU) 50 receives data from the GPS data receiving unit 62 and performs various calculation processes. In addition, the processing unit (CPU) 50 performs various processes in accordance with operation signals from the operation unit 40, processes for displaying various types of information on the display unit 70, processes for outputting various types of sounds to the sound output unit 72, and communication. Processing for controlling data communication with the server via the unit 74 is performed.

  In particular, in the present embodiment, the processing unit (CPU) 50 includes a position information generation unit 51, a communication control unit 52, a display control unit 53, and a sound output control unit 54. However, the processing unit (CPU) 50 of the present embodiment may omit or change some of these configurations (elements), or may have a configuration in which other configurations (elements) are added.

  The processing unit (CPU) 50 of this embodiment functions as a position information generation unit 51, a communication control unit 52, a display control unit 53, and a sound output control unit 54 by executing a program stored in the recording medium 68. To do. Note that at least a part of the position information generation unit 51, the communication control unit 52, the display control unit 53, and the sound output control unit 54 may be realized by hardware (a dedicated circuit).

  The position information generation unit 51 performs a positioning calculation using the trajectory information and time information included in the navigation message demodulated by the GPS data reception unit 62, and performs a process of generating the position information of the information terminal 5. By transmitting the position information of the information terminal 5 to the server via the communication unit 74, the movement prediction information about the area around the information terminal 5 can be received from the server.

  In the present embodiment, the position information generation unit 51 generates the position information of the information terminal 5 using the navigation message demodulated by the GPS data reception unit 62, but the information terminal uses other means. 5 pieces of position information may be generated. In that case, the GPS data receiving unit 62 may be omitted.

  Further, when the information terminal 5 receives all of the movement prediction information from the server regardless of the position of the information terminal 5, the GPS data receiving unit 62 and the position information generating unit 51 may not be provided.

  The communication control unit 52 performs processing for controlling data communication performed with the server via the communication unit 74. In the present embodiment, the communication control unit 52 performs processing for transmitting the position information generated by the position information generating unit 51 to the server 4 via the communication unit 74. Further, the communication control unit 52 performs processing for receiving movement prediction information from the server via the communication unit 74.

  The display control unit 53 performs processing for controlling display on the display unit 70. In particular, in the present embodiment, the display control unit 53 performs a process of causing the display unit 70 to display the movement prediction information received from the server.

  The sound output control unit 54 performs processing for causing the sound output unit 72 to output various sounds. For example, the sound output control unit 54 may cause the sound output unit 72 to output a voice that reads out a warning included in the movement prediction information.

  When the information terminal 5 and the mobile terminal 6 are integrated, the processing unit (CPU) 150, the GPS data receiving unit 162, the storage unit 166, the recording medium 168, and the communication unit 174 of the mobile terminal 6 are respectively connected to the information terminal 5 The processing unit (CPU) 50, the GPS data receiving unit 62, the storage unit 66, the recording medium 68, and the communication unit 74 are integrated.

Server configuration
FIG. 7 is a diagram illustrating a configuration example of the server 4 in the present embodiment. As shown in FIG. 7, in the present embodiment, the server 4 includes a processing unit (CPU) 20, a storage unit 30, a recording medium 32, a communication unit 34, an operation unit 36, a display unit 38, and a sound output unit 39. It is configured. The server 4 of this embodiment may omit or change some of the components (each unit) in FIG. 7, or may have a configuration with other components added.

  The operation unit 36 is an input device configured by operation keys, button switches, and the like, and outputs an operation signal according to an operation by a user (for example, a system administrator) to the processing unit (CPU) 20.

  The display unit 38 is a display device configured by an LCD or the like, and displays various types of information based on a display signal input from the processing unit (CPU) 20.

  The sound output unit 39 is a device that outputs sound, such as a speaker, and outputs various sounds (including sound) based on signals input from the processing unit (CPU) 20.

  The storage unit 30 stores programs, data, and the like for the processing unit (CPU) 20 to perform various calculation processes and control processes. The storage unit 30 is used as a work area of the processing unit (CPU) 20, and programs and data read from the recording medium 32, information received via the communication unit 34, and various types of processing unit (CPU) 20 are used. It is also used for temporarily storing calculation results executed according to a program.

  The data stored in the storage unit 30 includes map data (map information). Furthermore, terrain data (terrain information) may be included. The map data includes at least information on roads and buildings on which the moving body can move, and the terrain data includes inclination of the roads.

  The processing unit (CPU) 20 performs various calculation processes and control processes according to programs stored in the storage unit 30 and the recording medium 32. Specifically, the processing unit (CPU) 20 receives data from the environment measurement device 2, the mobile terminal 6, and the information terminal 5 via the communication unit 34 and performs various calculation processes. In addition, the processing unit (CPU) 20 performs various processes in accordance with operation signals from the operation unit 36, processes for displaying various types of information on the display unit 38, processes for outputting various types of sound on the sound output unit 39, and communication Processing for controlling data communication with the environmental measurement device 2, the mobile terminal 6, the information terminal 5, and the like via the unit 34 is performed.

  In particular, in this embodiment, the processing unit (CPU) 20 includes an environment data acquisition unit 21, an environment prediction unit 22, a movement prediction information generation unit 23, a communication control unit 24, a display control unit 25, a sound output control unit 26, and a terminal. A data acquisition unit 27 and a corresponding data generation unit 28 are included. However, the processing unit (CPU) 20 of the present embodiment may omit or change some of these configurations (elements), or may have a configuration in which other configurations (elements) are added.

  The environmental data acquisition unit 21 continuously acquires environmental data together with the identification ID from the environmental measurement device 2 via the communication unit 34, and sequentially stores the storage unit 30 in association with the identification ID assigned to each environmental measurement device 2. Save the file.

  The environment prediction unit 22 performs processing for predicting the environment of the target region from the time series of the environment data acquired by the environment data acquisition unit 21. The environment prediction unit 22 comprehensively analyzes changes in the environment at the measurement point of the environment measurement device from a predetermined time to the present, and after a predetermined time (for example, 10 minutes) at a predetermined time interval. Predict until 1 hour later).

  For example, if the temperature distribution in the region is 30 minutes before, the distribution is as shown in FIG. 8A, and the current distribution is as shown in FIG. 8B. Although the temperatures of A, B, and D have not changed, the temperatures of areas C, E, F, and G have decreased. In such a case, for example, after 30 minutes, the environment predicting unit 22 does not change the temperatures of the areas A, B, and D as shown in FIG. As shown in FIG. 8 (D), the temperature in Areas A, B, and D does not change and the temperatures in Areas C, E, F, and G further decrease after one hour. It may be predicted.

  The terminal data acquisition unit 27 acquires the location information of the mobile unit 7 and the information terminal 5 together with the identification ID (terminal ID) from the mobile terminal 6 and the information terminal 5 via the communication unit 34, and assigns them to each terminal. A process of storing in the storage unit 30 in association with the identified ID is performed. Of these, the position information of the moving body 7 from the mobile terminal 6 is used for generating the movement prediction information. The position information of the information terminal 5 is used for selecting movement prediction information to be transmitted to the information terminal 5. For example, if the position information of the information terminal 5 is X town Y chome, it is used to select and transmit only movement prediction information about X town Y chome and its surroundings.

  The correspondence data generation unit 28 generates correspondence data in which environment data (environment information) is associated with the position of the moving body 7. The correspondence data is stored in the storage unit 30 and used when the movement prediction information generation unit 23 generates movement prediction information. The correspondence data is used to predict a movement tendency due to an environmental change of the moving body 7. Therefore, it is not necessary to identify each moving body 7 as correspondence data. In addition, in order to reduce the burden of calculation processing of the movement prediction information generation unit 23 and to make it easy to grasp the movement tendency from the viewpoint of personal information protection, the mobile body 7 is divided into categories and group management is performed. It is preferable to do.

  FIG. 9A shows an example of a table 200 indicating the correspondence between the mobile terminal ID 210 (that is, each mobile object 7) and its group 220. For example, a certain mobile unit 7 carries a mobile terminal 6 having a mobile terminal ID 210 of XXX. At this time, the correspondence data generation unit 28 determines that the object 230 of the moving body 7 is a person based on the moving speed of the moving body 7. And the area 240 on a map is determined by comparing the position of the mobile body 7 and map data.

  For example, the area 240 on the map may be a combination of symbols representing large areas, small areas, and building types. At this time, by including the types of buildings, it is possible to distinguish whether the moving body 7 which is a person is a person working in the area, a shopper, or a resident. In addition, the area 240 on the map may be further classified, or conversely, a large classification.

  FIG. 9A also shows an example of the moving body 7 that is a vehicle. At this time, it is possible to know from the type of building in the area 240 on the map whether the vehicle is for commuting or is a transportation means for shopping. It is possible to divide the moving body 7 into the group 220 including the object 230 and the area 240 on the map by observing the position of the moving body 7 for a while. If the correspondence data is created using the group 220, personal information can be protected without specifying an individual.

  FIG. 9B is an example of correspondence data 300. The correspondence data 300 is a table in which the group 220 is associated with environmental data and the like, and is stored in the storage unit 30. Here, the uppermost data in FIG. 9B will be described. The weather 320 on March 15 at 14:03 (date 330) is clear. The atmospheric pressure 340 is 1018 hPa, the temperature 350 is 25 degrees, and the humidity 360 is 63%. In addition, a southwest wind (wind direction 370) is blowing.

  At this time, it can be seen that there are 53 (several 310) moving bodies 7 that are people (target 230) in a place where the area 240 on the map is A-5-12. This is current or past performance data, and is used for data mining when the movement prediction information generation unit 23 generates movement prediction information. Note that other weather information (for example, wind speed, rainfall) may be associated.

  The movement prediction information generation unit 23 generates movement prediction information including at least the predicted position information of the moving body from the prediction result of the environment prediction unit 22 and the correspondence data 300 generated by the correspondence data generation unit 28. Examples of the movement prediction information other than the predicted position information of the moving body include, for example, a warning that a person moves and concentrates.

  The movement prediction information generation unit 23 searches the correspondence data 300 having the same environment data as the prediction result of the environment prediction unit 22. Based on the retrieved correspondence data 300 and the correspondence data 300 before and after the date and time 330, the movement tendency of the mobile object 7 is grasped. Then, the movement prediction information is generated by applying the movement tendency to the current moving body 7. Among them, the predicted position information of the moving body 7 may be such that the distribution of the moving body can be visually recognized using the map information.

  Here, the movement prediction information generation unit 23 may filter the group 220 to grasp the movement tendency of the moving body 7. For example, the vehicle may be excluded from the moving body 7 and the movement tendency of only people may be grasped. Further, the filtering may be executed based not only on the group 220 but also on another element of the correspondence data 300. For example, the number 310 of less than 10 may be excluded from the correspondence data 300 used for grasping the movement tendency. The movement tendency may be acquired by a method similar to that of the environment prediction unit 22 (see FIGS. 8A to 8D), or may be acquired by a method such as frequent pattern extraction or regression analysis. .

  The communication control unit 24 performs processing for controlling data communication with the environment measurement device 2, the mobile terminal 6, and the information terminal 5 performed via the communication unit 34.

  The display control unit 25 performs processing for controlling display on the display unit 38. In particular, in the present embodiment, the display control unit 25 performs a process of causing the display unit 38 to display the movement prediction information generated by the movement prediction information generation unit 23.

  The sound output control unit 26 performs processing for causing the sound output unit 39 to output various sounds. For example, the sound output control unit 26 may perform a process of causing the sound output unit 39 to output an alarm sound or a sound when the movement prediction information has changed.

  The recording medium 32 is a computer-readable recording medium. In particular, in the present embodiment, a program for causing the computer to function as each of the above-described units is stored. Then, the processing unit (CPU) 20 of the present embodiment executes a program stored in the recording medium 32, thereby causing the environment data acquisition unit 21, the environment prediction unit 22, the movement prediction information generation unit 23, and the communication control unit. 24, a display control unit 25, a sound output control unit 26, a terminal data acquisition unit 27, and a corresponding data generation unit 28. Alternatively, the program is received from another server connected to a wired or wireless communication network via the communication unit 34 or the like, the received program is stored in the storage unit 30 or the recording medium 32, and the program is executed. It may be. However, at least one of the environment data acquisition unit 21, the environment prediction unit 22, the movement prediction information generation unit 23, the communication control unit 24, the display control unit 25, the sound output control unit 26, the terminal data acquisition unit 27, and the corresponding data generation unit 28. The unit may be realized by hardware (dedicated circuit).

  The recording medium 32 can be realized by, for example, an optical disk (CD, DVD), a magneto-optical disk (MO), a magnetic disk, a hard disk, a magnetic tape, or a memory (ROM, flash memory, etc.).

1-3. Process of Movement Prediction System FIGS. 10 and 11 are diagrams illustrating an example of a flowchart of the process of the movement prediction system 1 of the present embodiment. FIG. 10 is a diagram illustrating an example of a flowchart of processing by the processing unit (CPU) 20 of the server 4, and FIG. 11 is a diagram illustrating an example of a flowchart of processing by the processing unit (CPU) 50 of the information terminal 5. .

  The processing unit (CPU) 20 of the server 4 receives the environmental data from the environmental measurement device 2 and stores it in the storage unit 30 (S14).

  The processing unit (CPU) 20 of the server 4 receives the terminal ID and the position information of the moving body from the mobile terminal 6 and stores them in the storage unit 30 (S16).

  The processing unit (CPU) 20 of the server 4 reads the map data (map information), associates the environmental data with the position information, generates the correspondence data 300, and stores it in the storage unit 30 (S20).

  The processing unit (CPU) 20 of the server 4 predicts environmental changes in the region from the time series of environmental data up to the present (environment data stored in order in step S14) (S24).

  The processing unit (CPU) 20 of the server 4 reads correspondence data 300 that is the same as or similar to the predicted environmental data from the storage unit 30. At this time, the corresponding data 300 that changes in time is also read out, and filtering is performed on the group of moving bodies 7 that need to be predicted (S30).

  Then, the processing unit (CPU) 20 of the server 4 grasps the movement tendency of the group from the correspondence data 300. And it applies to the present moving body 7, and the future change of the moving position of the moving body 7 is predicted (S34).

  The processing unit (CPU) 20 of the server 4 processes the predicted position information of the moving body into a distribution on the map, and generates movement prediction information together with necessary warnings. Then, the movement prediction information is transmitted to the information terminal 5 (S36).

  The processing unit (CPU) 50 of the information terminal 5 receives the movement prediction information from the server 4 (S60). The processing unit (CPU) 50 of the information terminal 5 may display a screen 100 as shown in FIG. In the screen 100 of FIG. 12, as a prediction after 40 minutes, the moving object 7 (here, a person) is represented by black dots on the map around the information terminal 5, and the distribution of the moving object 7 is visually recognized. I understand.

  In the screen 100 of FIG. 12, the arrow 8 indicates the tendency (movement tendency) of the moving body to move along with a message that heavy rain is expected after about 30 minutes. At this time, it turns out that the mobile body 7 is concentrating on the building shown with a dotted line.

  In addition, in the screen 100 of FIG. 12, as other warnings, attention should be paid to the increase of rivers in the 53rd area, and more than twice as many people may flow into the A commercial facility as compared to the present in order to avoid rain. It has been shown that there is sex.

  The owner of the information terminal 5 can receive the movement prediction information and take the following actions. For example, if the owner of the information terminal 5 is a department store or a restaurant person, it can be used for customer collection prediction or prediction of crowded time. In addition, a person in charge of safety measures can predict dangers due to excessive concentration of people and vehicles and take measures such as guidance to other places and traffic control.

  The process of the movement prediction system 1 will be described with reference to FIGS. 10 and 11 again. The processing unit (CPU) 20 of the server 4 performs steps S14 to S36 every time a predetermined time Δt (for example, 1 minute) elapses (Y in S40) until the user finishes the process (N in S38). The process is repeated, and when the end operation is performed, the process ends (Y in S38).

  On the other hand, the processing unit (CPU) 50 of the information terminal 5 receives a termination instruction from the owner of the information terminal 5 (N in S62) every time a predetermined time Δt (for example, 1 minute) elapses (S64). Y) The movement prediction information is updated (step S60), and upon receiving an end instruction, the process ends (Y in S62).

  According to the movement prediction system of the first embodiment described above, the server 4 analyzes the environmental conditions in real time using the environmental data measured by each of the plurality of environmental measurement devices 2 distributed in the region. Therefore, it is possible to accurately grasp environmental changes around the area.

  Then, the server 4 generates movement prediction information including at least the predicted position information of the moving body from the prediction result of the environment prediction unit 22 and the correspondence data 300 generated by the correspondence data generation unit 28. At this time, the correspondence data 300 is, for example, a table in which the group 220 is associated with past environmental data, and the accuracy of prediction can be improved.

  That is, it is possible to generate a movement prediction information that predicts a local weather change and accurately predicts the movement and distribution of the moving body due to the weather change.

  Further, according to the movement prediction system of the present embodiment, the server 4 having a high processing capability directly transmits the environment data measured by the large number of environment measuring apparatuses 2 and the position information from the mobile terminal 6 without using the information terminal 5. By receiving and centrally processing the generation of movement prediction information, the processing load on the information terminal 5 can be greatly reduced.

2. Second Embodiment 2-1. Overview of Movement Prediction System In the movement prediction system of the second embodiment, the information terminal 5 performs the processing performed by the server 4 in the first embodiment. That is, the information terminal 5 generates the movement prediction information similar to that of the first embodiment using the environment data and the position information of the moving body.

  Here, the information terminal 5 transmits the movement prediction information to the server 4, and the server 4 can collect and display all the movement prediction information.

2-2. Configuration of movement prediction system [Overall configuration]
Since the overall configuration diagram of the movement prediction system of the second embodiment is the same as that of FIG. 3, the illustration thereof is omitted.

  In the movement prediction system 1 of the second embodiment, the information terminal 5 (an example of an information processing apparatus) receives environment data from the environment measurement apparatus 2 and position information from the mobile terminal 6 via the communication network 3. Alternatively, the information terminal 5 may receive environment data and position information by directly performing data communication with each environment measurement device 2 and the mobile terminal 6. And the information terminal 5 analyzes environmental data, the positional information on the moving body 7, etc., and produces | generates movement prediction information.

  The server 4 can collect the movement prediction information generated by the information terminal 5 via the communication network 3, and can collect and display all the movement prediction information on the display unit 38, for example. A user (for example, a system administrator) of the server 4 can take an early response such as an evacuation instruction or guidance by, for example, collecting and displaying only warnings.

  Since the configuration diagrams of the environment measurement device 2 and the mobile terminal 6 in the second embodiment are the same as those in FIGS. 4 and 5, illustration and description thereof are omitted.

[Configuration of information terminal]
FIG. 13 is a diagram illustrating a configuration example of the information terminal 5 in the second embodiment. As shown in FIG. 13, in this embodiment, the information terminal 5 includes an operation unit 40, a processing unit (CPU) 50, a GPS data receiving unit 62, a storage unit 66, a recording medium 68, a display unit 70, and a sound output unit 72. The communication unit 74 is included. The information terminal 5 of the present embodiment may omit or change some of the components (each unit) in FIG. 13 or may have a configuration in which other components are added. Since the functions of the operation unit 40, the GPS data receiving unit 62, the storage unit 66, the recording medium 68, the display unit 70, the sound output unit 72, and the communication unit 74 are the same as those in the first embodiment, description thereof is omitted. .

  The processing unit (CPU) 50 performs various types of calculation processing and control processing according to programs stored in the storage unit 66 and the recording medium 68. In particular, in this embodiment, the processing unit (CPU) 50 includes a position information generation unit 51, a communication control unit 52, a display control unit 53, a sound output control unit 54, an environment data acquisition unit 80, an environment prediction unit 81, and a movement prediction. An information generation unit 82, a correspondence data generation unit 83, and a mobile terminal data acquisition unit 84 are included. However, the processing unit (CPU) 50 of the present embodiment may omit or change some of these configurations (elements), or may have a configuration in which other configurations (elements) are added.

  Since the functions of the position information generation unit 51, the communication control unit 52, the display control unit 53, and the sound output control unit 54 are the same as those in the first embodiment, description thereof is omitted.

  The environment data acquisition unit 80 continuously acquires the environment data measured by each environment measurement device 2 via the communication unit 74, and sequentially stores the data in association with the identification ID assigned to each environment measurement device 2. The process which preserve | saves to 66 is performed.

  The mobile terminal data acquisition unit 84 acquires the position information of the mobile body 7 from the mobile terminal 6. The position information acquired by the mobile terminal data acquisition unit 84 is used when the movement prediction information generation unit 82 generates movement prediction information.

  The processes of the environment prediction unit 81, the movement prediction information generation unit 82, and the correspondence data generation unit 83 are the same as those of the environment prediction unit 22, the movement prediction information generation unit 23, and the correspondence data generation unit 28 in the first embodiment. Therefore, the description is omitted.

Server configuration
FIG. 14 is a diagram illustrating a configuration example of the server 4 in the second embodiment. As shown in FIG. 14, in the present embodiment, the server 4 includes a processing unit (CPU) 20, a storage unit 30, a recording medium 32, a communication unit 34, an operation unit 36, a display unit 38, and a sound output unit 39. It is configured. The server 4 of this embodiment may omit or change some of the components (each unit) in FIG. 14, or may have a configuration with other components added. Since the functions of the storage unit 30, the recording medium 32, the communication unit 34, the operation unit 36, the display unit 38, and the sound output unit 39 are the same as those in the first embodiment, description thereof will be omitted.

  The processing unit (CPU) 20 performs various calculation processes and control processes according to programs stored in the storage unit 30 and the recording medium 32. In particular, in the present embodiment, the processing unit (CPU) 20 includes a communication control unit 24, a display control unit 25, a sound output control unit 26, and a terminal data acquisition unit 27. However, the processing unit (CPU) 20 of the present embodiment may omit or change some of these configurations (elements), or may have a configuration in which other configurations (elements) are added.

  The terminal data acquisition unit 27 performs processing for acquiring movement prediction information from the information terminal 5 via the communication unit 34.

  The communication control unit 24 performs processing for controlling data communication and the like with the information terminal 5 performed via the communication unit 34.

  The display control unit 25 performs a process of collecting the movement prediction information acquired by the terminal data acquisition unit 27 and displaying it on the display unit 38.

  Since the process of the sound output control unit 26 is the same as that of the first embodiment, the description thereof is omitted.

2-3. Process of Movement Prediction System FIGS. 15 and 16 are diagrams illustrating an example of a flowchart of the process of the movement prediction system 1 of the present embodiment.

  FIG. 15 is a diagram illustrating an example of a flowchart of processing by the processing unit (CPU) 50 of the information terminal 5.

  As shown in FIG. 15, the processing unit (CPU) 50 of the information terminal 5 waits until the owner of the information terminal 5 performs a start operation (N in S150), and when the start operation is performed (Y in S150) ), The operation after step S152 is performed.

  Here, steps S152 to S172 are executed by the processing unit (CPU) 50 of the information terminal 5 in place of the processing unit (CPU) 20 of the server 4, but are the same as steps S14 to S34 of the first embodiment. The description is omitted.

  After step S172, the processing unit (CPU) 50 of the information terminal 5 processes the predicted position information of the moving body into a distribution on the map, and generates and displays movement prediction information together with necessary warnings (S174). ). At this time, the processing unit (CPU) 50 of the information terminal 5 may display a screen 100 as shown in FIG.

  Then, the processing unit (CPU) 50 of the information terminal 5 transmits the generated movement prediction information to the server 4 (S176).

  The processing unit (CPU) 50 of the information terminal 5 every time a predetermined time Δt (for example, 1 minute) elapses (Y in S180) until the end operation by the owner of the information terminal 5 is performed (N in S178). Then, the processes in steps S152 to S176 are repeated, and the process ends when an end operation is performed (Y in S178).

  FIG. 16 is a diagram illustrating an example of a flowchart of processing by the processing unit (CPU) 20 of the server 4.

  As shown in FIG. 16, the processing unit (CPU) 20 of the server 4 receives the terminal ID and the movement prediction information from the information terminal 5 and stores them in the storage unit 30 (S112).

  Next, the processing unit (CPU) 20 of the server 4 aggregates the movement prediction information stored in the storage unit 30 in step S112 and displays the list on the display unit 38, for example (S114).

  Then, the processing unit (CPU) 20 of the server 4 repeats the processes of steps S112 and S114 until the end operation is performed by the user (for example, system administrator) (N in S116). The process is terminated (Y in S116).

  According to the movement prediction system of the second embodiment described above, the information terminal 5 analyzes the environmental conditions in real time using the environmental data measured by each of the plurality of environmental measurement devices 2 distributed in the area. By doing so, it is possible to accurately grasp environmental changes around the area.

  Then, the information terminal 5 generates movement prediction information including at least the predicted position information of the moving body from the prediction result of the environment prediction unit 81 and the corresponding data 300 generated by the corresponding data generation unit 83. At this time, the correspondence data 300 is, for example, a table in which the group 220 is associated with past environmental data, and the accuracy of prediction can be improved.

  That is, it is possible to generate a movement prediction information that predicts a local weather change and accurately predicts the movement and distribution of the moving body due to the weather change.

3. Modification [Modification 1]
In the first embodiment, the server 4 and the information terminal 5 in the second embodiment directly communicate with each environment measuring device 2 to acquire environment data. However, the environment measuring devices 2 communicate with each other ad hoc. The environmental data may be collected in one environmental measurement device 2 and the environmental measurement device 2 may transmit the environmental data to the server 4 or the information terminal 5 in a lump. In addition, for each mobile terminal 6, one mobile terminal 6 may transmit the location information in a lump by the same method.

  In this way, it is possible to reduce the overhead of the server 4 or the information terminal 5 due to the switching of the communication target and improve the communication speed of the environmental data.

[Modification 2]
In the second embodiment, the information terminal 5 communicates with each environmental measurement device 2 to acquire environmental data. However, as in the first embodiment, the server 4 acquires environmental data from each environmental measurement device 2. Then, the information terminal 5 may acquire environmental data from the server 4. Further, the information terminal 5 may acquire the position information from the server 4 in the same manner for each mobile terminal 6.

[Modification 3]
The moving body of the first and second embodiments may include an animal. The animal may be wild or kept, but for example, it is assumed that the mobile terminal 6 is equipped with a collar or an ankle. At this time, wild animals (for example, bears, monkeys, foxes, and frogs) fall from the mountains to the villages due to the effects of weather changes, causing crop damage, and village animals (for example, dogs and cats) are garbage. It is possible to take measures in anticipation of damage that will cause damage. Moreover, when the feeding ground of the livestock which is grazing changes with the weather, it is also possible to predict a feeding ground by the movement prediction system 1, and to ensure a sufficient amount of feeding.

  The above-described embodiments and modifications are merely examples, and the present invention is not limited to these. For example, it is possible to appropriately combine each embodiment and each modification.

  The present invention includes configurations that are substantially the same as the configurations described in the embodiments (for example, configurations that have the same functions, methods, and results, or configurations that have the same objects and effects). In addition, the invention includes a configuration in which a non-essential part of the configuration described in the embodiment is replaced. In addition, the present invention includes a configuration that exhibits the same operational effects as the configuration described in the embodiment or a configuration that can achieve the same object. Further, the invention includes a configuration in which a known technique is added to the configuration described in the embodiment.

DESCRIPTION OF SYMBOLS 1 Movement prediction system 2 Environment measuring device 3 Communication network 4 Server 5 Information terminal 6 Mobile terminal 7 Mobile body 10 Pressure sensor 11 Temperature sensor 12 Humidity sensor 13 Wind direction / wind speed sensor 14 Rainfall Sensor, 15 Air quality sensor, 16 Transmitter, 20 Processing unit (CPU), 21 Environmental data acquisition unit, 22 Environmental prediction unit, 23 Movement prediction information generation unit, 24 Communication control unit, 25 Display control unit, 26 Sound output control Unit, 27 terminal data acquisition unit, 28 corresponding data generation unit, 30 storage unit, 32 recording medium, 34 communication unit, 36 operation unit, 38 display unit, 39 sound output unit, 40 operation unit, 50 processing unit (CPU), 51 position information generation unit, 52 communication control unit, 53 display control unit, 54 sound output control unit, 62 GPS data reception unit, 66 Storage unit, 68 Recording medium, 70 Display unit, 72 Sound output unit, 74 Communication unit, 80 Environmental data acquisition unit, 81 Environmental prediction unit, 82 Movement prediction information generation unit, 83 Corresponding data generation unit, 84 Mobile terminal data acquisition unit 99 building, 100 screen, 150 processing unit (CPU), 151 position information generating unit, 152 communication control unit, 162 GPS data receiving unit, 166 storage unit, 168 recording medium, 174 communication unit, 200 table, 300 corresponding data

Claims (11)

An environment prediction unit that uses weather information to predict weather changes;
A terminal data acquisition unit for acquiring information on a location where the mobile body is generated generated by a mobile terminal carried by the mobile body;
A correspondence data generating unit that generates correspondence data in which the weather information and the location of the moving body are associated;
Using the prediction result of the environment prediction unit and the correspondence data, a movement prediction information generation unit that predicts a position where the moving body moves and generates movement prediction information including the predicted position information of the moving body When,
Including an information processing apparatus. In claim 1,
The correspondence data generation unit
An information processing apparatus that sets an area using map information and generates the correspondence data in which the moving body is classified into a group for each area. In claim 2,
The movement prediction information generation unit
An information processing apparatus that generates the movement prediction information for each group. In claim 2 or 3,
The movement prediction information generation unit
An information processing apparatus that generates a distribution of the moving object on a map as the position information using the map information. In any one of Claims 1 thru | or 4,
An information processing apparatus that targets at least one of a person, a vehicle, and an animal as the moving body. An information processing apparatus according to any one of claims 1 to 5,
An environmental measurement device arranged in an area where the moving body moves;
Including a movement prediction system. Predicting weather changes using weather information;
Obtaining information of a location where the mobile body is generated generated by a mobile terminal carried by the mobile body;
Generating correspondence data in which the weather information and the location of the moving body are associated with each other;
Using the predicted weather change and the corresponding data, predicting a position where the moving body moves, and generating movement prediction information including the predicted position information of the moving body;
Including a movement prediction method. In claim 7,
The step of generating the correspondence data includes:
A movement prediction method, wherein map data is used to generate the correspondence data in which the moving objects are classified into groups for each area. In claim 8,
The step of generating the movement prediction information includes:
A movement prediction method for generating the movement prediction information for each group. In claim 8 or 9,
The step of generating the movement prediction information includes:
A movement prediction method that uses the map information to generate a distribution of the moving object on a map as the position information. In any one of Claims 7 thru | or 10,
A movement prediction method for at least one of a person, a vehicle, and an animal as the moving body.

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