JP7195077B2 - Information processing device, information providing method and program - Google Patents

Description

The present invention relates to an information processing device, an information providing method, and a program.

2. Description of the Related Art Conventionally, there is an information processing apparatus that realizes a navigation function that searches for a route to a set destination, guides a guide route, and provides traffic information on the guide route, information about shops in the vicinity, and the like. In such an information processing device, there is a technique for predicting the destination and future travel route from the travel route history when the user has not set the destination, and providing various information based on the prediction results. (For example, Patent Document 1).

In such technology, it is determined whether or not the user is within the daily living area based on the location information of the terminal device used by the user, and by switching the content of the information to be provided according to the determination result, more appropriate information is provided. can provide.

JP 2010-249642 A

However, if the reception of the signal used to acquire the location information is poor, or if the user intentionally turns off the location acquisition function of the terminal device, the location information of the terminal device cannot be acquired. Therefore, it becomes impossible to provide appropriate information according to the user's position.
In addition, even if the location information determines that the user is within the range of his or her daily life, the location information may be used in unusual circumstances such as when the user is out for leisure on a holiday, or when there is an emergency such as a disaster or accident. Under certain circumstances, the information provided may be inappropriate.
As described above, the above-described conventional technique has a problem that it is not easy to provide appropriate information according to the position of the user and the situation in which the user is placed.

An object of the present invention is to provide an information processing apparatus, an information providing method, and a program capable of providing more appropriate information.

In order to achieve the above object, the invention of the information processing device according to claim 1 ,
Whether the movement of the user moving with the terminal device is unusual movement or daily movement other than the extraordinary movement based on the feature information representing the characteristics of the object that the moving terminal device passes by a determination unit that determines
an information providing unit that provides information according to the determination result of the determining unit;
with
The characteristic information is characterized by including information relating to the characteristics of the moving object extracted from an image of the moving object passing by the terminal device.

The invention according to claim 2 is the information processing apparatus according to claim 1 ,
the moving body is a vehicle,
The characteristic information is characterized by including at least a part of information contained in the license plate of the vehicle passing by the terminal device.

The invention according to claim 3 is the information processing apparatus according to claim 1 or 2 ,
the moving body is a vehicle,
The feature information is characterized by including information related to the vehicle type of the vehicle passing by the terminal device.

In order to achieve the above object, the invention of the information processing device according to claim 4 ,
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination unit that determines whether to move;
an information providing unit that provides information according to the determination result of the determining unit;
with
The determination unit is configured to, when a degree of mismatch between the feature information acquired for the determination and the feature information acquired and accumulated during the past daily movement satisfies a predetermined condition, the extraordinary condition. It is characterized by judging that it is a natural movement.

The invention according to claim 5 is the information processing apparatus according to claim 4 ,
The determination unit is configured to perform the extraordinary movement when a ratio of the feature information that does not match the accumulated feature information among the plurality of feature information acquired for the determination is greater than a predetermined reference value. It is characterized by determining that there is

In order to achieve the above object, the invention of the information processing device according to claim 6 is:
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination unit that determines whether to move;
an information providing unit that provides information according to the determination result of the determining unit;
Predicting the user's destination based on predetermined first information when the determination unit determines that the movement is routine movement, and determining that the movement is extraordinary by the determination unit a prediction unit that predicts the destination of the user based on second information including information different from the first information when the
with
The information providing unit provides information according to the destination predicted by the prediction unit.

The invention according to claim 7 is the information processing apparatus according to claim 6 ,
The first information is information associated with the terminal device used by the user,
The second information is characterized by being information including information associated with one or more reference terminal devices used by users other than the user.

The invention according to claim 8 is the information processing apparatus according to claim 7 ,
The second information is characterized by including information associated with the reference terminal devices used by each of an unspecified number of users.

The invention according to claim 9 is the information processing apparatus according to claim 7 ,
The second information is characterized by being information associated with the reference terminal device used by a user who rides on the same means of transportation as the user.

The invention according to claim 10 is the information processing apparatus according to any one of claims 7 to 9 ,
The first information is information related to the usage history of the terminal device used by the user,
The second information is characterized by being information including information related to the usage history of the reference terminal device.

Further , in order to achieve the above object, the invention of the information providing method according to claim 11 is
A computer-implemented method of providing information, comprising:
Whether the movement of the user moving with the terminal device is unusual movement or daily movement other than the extraordinary movement based on the feature information representing the characteristics of the object that the moving terminal device passes by a determination step of determining
An information provision step of providing information according to the determination result in the determination step;
including
The characteristic information is characterized by including information relating to the characteristics of the moving object extracted from an image of the moving object passing by the terminal device.
Further, in order to achieve the above object, the invention of the information providing method according to claim 12 ,
A computer-implemented method of providing information, comprising:
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination step of determining whether to move;
An information provision step of providing information according to the determination result in the determination step;
including
In the determination step, when the degree of discrepancy between the feature information acquired for the determination and the feature information acquired and accumulated in the past routine movement satisfies a predetermined condition, the extraordinary condition is met. It is characterized by judging that it is a natural movement.
Further, in order to achieve the above object, the invention of the information providing method according to claim 13 ,
A computer-implemented method of providing information, comprising:
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination step of determining whether to move;
An information provision step of providing information according to the determination result in the determination step;
predicting the user's destination based on predetermined first information when the movement is determined to be the routine movement in the determination step, and determining that the movement is the extraordinary movement in the determination step; a prediction step of predicting the user's destination based on second information, including information different from the first information, if provided;
including
The information provision step is characterized by providing information corresponding to the destination predicted in the prediction step.

Further , in order to achieve the above object, the invention of the program according to claim 14 ,
a computer provided in an information processing device,
Whether the movement of the user moving with the terminal device is unusual movement or daily movement other than the extraordinary movement based on the feature information representing the characteristics of the object that the moving terminal device passes by determination means for determining
Information provision means for providing information according to the determination result by the determination means;
function as
The characteristic information is characterized by including information relating to the characteristics of the moving object extracted from an image of the moving object passing by the terminal device.
Further, in order to achieve the above object, the invention of the program according to claim 15 ,
a computer provided in an information processing device,
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. Determination means for determining movement,
Information provision means for providing information according to the determination result by the determination means;
function as
The determining means determines a degree of mismatch between the feature information acquired for the determination and the feature information acquired and accumulated during the past daily movement satisfies a predetermined condition when the extraordinary condition is met. It is characterized by judging that it is a natural movement.
Further, in order to achieve the above object, the invention of the program according to claim 16 ,
a computer provided in an information processing device,
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. Determination means for determining movement,
Information provision means for providing information according to the determination result by the determination means;
When the determination means determines that the movement is routine movement, predicting the user's destination based on predetermined first information, and determining that the movement is extraordinary by the determination means prediction means for predicting the user's destination based on second information including information different from the first information, if
function as
The information providing means provides information corresponding to the destination predicted by the prediction means.

ADVANTAGE OF THE INVENTION According to this invention, it is effective in being able to provide more appropriate information.

It is a figure explaining the information provision method which concerns on embodiment. It is a figure which shows the example of the information display screen in the display part of a terminal device. It is a figure which shows the structural example of a server apparatus and a terminal device. FIG. 5 is a diagram showing an example of contents of history information data; It is a figure which shows the example of the content of user information data. FIG. 4 is a diagram showing an example of content of position information data; FIG. 10 is a diagram showing an example of contents of accumulated feature information data; It is a flowchart which shows the control procedure by the control part of an information provision process. It is a figure explaining the information provision method when there is a fellow passenger in a car. It is a figure explaining the identification method of several terminal devices which a fellow passenger uses.

Embodiments of an information processing apparatus, an information providing method, and a program according to the present invention will be described below with reference to the drawings.

[1. Information provision method]
First, an information providing method according to the present embodiment will be described with reference to FIGS. 1 and 2. FIG.

[1-1. Overview of information provision method]
FIG. 1 is a diagram illustrating an information providing method according to an embodiment.
The information providing method of this embodiment is implemented using the server device 100 (information processing device) and the terminal device 10 . The server device 100 acquires information from the terminal device 10 (T1) used by the user U1 (passenger) riding in an automobile 200 (vehicle) as a means of transportation, so that the movement of the user U1 is similar to that of daily movement. or extraordinary movement. Moreover, the server device 100 predicts the destination of the user U1 (the automobile 200) by a method according to the determination result. In addition, the server device 100 causes the terminal device 10 (T1) to display information corresponding to the predicted destination (for example, traffic jam information to the predicted destination, etc.). to user U1 who uses

Here, "unusual movement" refers to at least one of movement outside the daily life area (daily life area) and movement under extraordinary circumstances.
Among these, the "daily living area" refers to the range of user U1's usual activities (typically, the area around the home or work place (for example, within a predetermined distance range from the home or work place), and the area around the commuting route. ), in other words, a familiar area for the user U1. Therefore, it can be said that "outside the daily living area" is an unfamiliar area (unfamiliar area) for the user U1.
In addition, the “unusual situation” refers to a case where the user U1 goes out for leisure on a holiday. It refers to a situation where there is a different situation, or a situation where an emergency situation such as a disaster, abnormal weather, incident, or accident occurs.
On the other hand, "routine movement" refers to movement other than the above-mentioned extraordinary movement. In other words, "routine movement" refers to movement in a familiar area (area of daily life) for user U1, and movement under circumstances that do not correspond to the above-described "extraordinary circumstances".

The server device 100 and the plurality of terminal devices 10 are communicably connected via a communication network (not shown). The server device 100 and the plurality of terminal devices 10 constitute an information providing system 1 (see FIG. 3) for providing the above information.

The terminal device 10 is, for example, a smart phone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. FIG. 1 illustrates an example in which the terminal device 10 is a smart phone. Note that the terminal device 10 is not limited to the devices described above as long as it can move with the user and can communicate with the server device 100 . For example, it may be a wearable device worn on the user's body, such as a watch, or an in-vehicle terminal device (such as a car navigation device) attached to the automobile 200 .

The terminal device 10 is configured to acquire position information and transmit it to the server device 100 . The method of acquiring the position information of the terminal device 10 is not particularly limited, but for example, a GPS (Global Positioning System) method of receiving transmission radio waves from a positioning satellite and measuring the position, a wireless LAN (Local Area Network) method, and the like. ), a method of specifying a position from information related to communication such as a third generation mobile communication system and a fourth generation mobile communication system, or the like can be used. The terminal device 10 of this embodiment acquires position information by GPS.
Acquisition of this location information usually consumes a lot of power, so the terminal device 10 can be set not to acquire location information by a user's input operation.

In FIG. 1 , a terminal ID for identifying the terminal device 10 is described in parentheses following the code “10” attached to each terminal device 10 . Specifically, it is assumed that the terminal ID of the terminal device 10 used by user U1 is "T1". It is also assumed that the terminal ID of the terminal device 10 used by a user other than the user U1 (for example, a user riding in the oncoming vehicle 300 of the automobile 200 in FIG. 1) is "Tn" ("n" is , a natural number equal to or greater than 2). . . , 10(Tn) are simply referred to as “terminal device 10” without a terminal ID when they are not distinguished from each other.

Also, in the server device 100, a plurality of users are identified by their respective user IDs. In the following, the user IDs of users U1, U2, .

User U1 is the driver of automobile 200 . An application program (hereinafter referred to as "navi app") that implements a navigation function is installed in the terminal device 10 (T1) used by the user U1. This navigation application searches for a route to a destination set by the user, provides guidance on a route (in other words, provides guidance), and provides traffic information on the route and information on nearby stores. or When the navigation application is running, information such as the location information of the terminal device 10 and the destination set by the user is transmitted from the terminal device 10 to the server device 100 . The server device 100 generates navigation information including a route to the destination based on these pieces of information, and transmits the navigation information to the terminal device 10 . In the terminal device 10 that has received the navigation information, a display for guiding the route to the destination is performed on the screen of the navigation application.

This navigation application operates in a "destination prediction mode" when no destination is set by the user, that is, when guidance to the destination is not performed. In the destination prediction mode, the destination and the future travel route are predicted from the travel route history and the like, and various types of information are provided (displayed) based on the prediction results. The information provided in the destination prediction mode includes the predicted destination (hereinafter also referred to as the "predicted destination"), traffic jams, accidents, automatic speed control devices (Orbis) on the route to the predicted destination, This information includes traffic information on places where temporary stops are required, and information on shops (eg, restaurants, gas stations, etc.) and facilities (eg, parking lots, etc.) along the route. Advertisements such as products related to the predicted destination may also be displayed.

In the conventional destination prediction mode, the destination is predicted from the past action history (behavior pattern) of the user U1 who is the driver. Specifically, based on past location information (for example, latitude and longitude information) of the terminal device 10 (T1) of the user U1 and the history of the movement route based on the time information (time stamp) when the location information was recorded Destination is predicted.

According to such a method, it is possible to predict the destination with a certain degree of accuracy, especially when the movement of the user U1 is the daily movement described above. This is because when the user U1 moves on a daily basis, there is a high probability that the destination will be a place that the user U1 visits repeatedly on a daily basis, such as the place of work or school, and the destination can be accurately determined from the past action history. This is because it is predictable.

On the other hand, if the movement of user U1 is the above-mentioned non-routine movement, usually the place of work that user U1 visits on a daily basis is not the destination. Therefore, if the destination is predicted from the past action history of the user U1, there is a problem that the prediction accuracy is lowered.

Therefore, the server device 100 of the present embodiment acquires the reference information acquired by the terminal device 10 (T1) from the terminal device 10 (T1) used by the user U1, and based on the reference information, the user It is determined whether the movement of U1 is routine movement or extraordinary movement. Here, the reference information is information relating to at least one of the position of the terminal device 10 (T1) and the situation in which the terminal device 10 (T1) is placed, and the details thereof will be described later.
Then, the server device 100 switches the method of destination prediction according to the determination result as to whether the movement is routine or extraordinary.

That is, when it is determined that the movement is daily, the server device 100 stores the terminal information (hereinafter also referred to as “user terminal information”) associated with the terminal device 10 (T1) of the user U1. Based on this, the destination of user U1 (automobile 200) is predicted. Here, the user terminal information includes the usage history of the terminal device 10 (T1) by the user U1, the history of the position information of the terminal device 10 (T1), and the like, and information reflecting the past action history of the user U1. is. Therefore, it can be said that the method of predicting the destination in daily movement predicts the destination based on the user U1's past action history (that is, based on the user U1's usual history).
The above user terminal information corresponds to the first information.

On the other hand, when it is determined that the movement is unusual, the server device 100 is associated with the terminal device 10 (hereinafter also referred to as "reference terminal device") used by the user other than the user U1. Based on information including terminal information (hereinafter also referred to as “general terminal information”), the destination of user U1 (car 200) is predicted. The general terminal information of this embodiment shall include terminal information associated with each of a plurality of terminal devices 10 used by each of an unspecified number of users. Such a destination prediction method based on general terminal information can be said to predict a destination based on the action history of an unspecified number of users (that is, based on the history of an unspecified number of users). In extraordinary movements, the destination is often a point that has little (or no relation) to the user's daily action history. The destination can be predicted more appropriately than the local prediction.
The above general terminal information corresponds to the second information. Note that the general terminal information may further include user terminal information. In this case, in order to sufficiently reduce the influence of the user terminal information on the general terminal information, the general terminal information includes terminal information related to a large number (for example, several tens to several hundred or more) of reference terminal devices. should be included.

A method of determining whether the movement is routine or extraordinary by the server device 100 and a method of predicting the destination according to the result of the determination will be described below.

[1-2. Method for Determining Regular Movement/Extraordinary Movement]
When the operation of the navigation application in the destination prediction mode is started in the terminal device 10 (T1) of the user U1, the server device 100 acquires current location information as reference information from the terminal device 10 (T1). try.
Location information can be acquired from the terminal device 10 (T1), and the location indicated by the acquired location information is outside the preset daily life area of the user U1 (outside the daily life area). In this case, server device 100 determines that user U1's movement is unusual.

On the other hand, when the reception condition of the signal used to acquire the position information is poor, or when the setting is such that the position information is not acquired, the position information may not be acquired from the terminal device (T1). In such a case, the server device 100 acquires from the terminal device 10 (T1) information reflecting the surrounding environment and situation of the terminal device 10 (T1) as reference information, and based on the reference information, Determine whether the movement is routine or extraordinary.
Further, even if the location information can be acquired from the terminal device 10 (T1) and the location indicated by the acquired location information is within the daily life range of the user U1, it is not necessarily a daily movement. Instead, it can be an extraordinary move, such as going out for leisure or an emergency situation. Therefore, in this case as well, the server device 100 acquires information reflecting the surrounding environment and situation from the terminal device 10 (T1) as reference information, and based on the reference information, moves whether it is normal or extraordinary. determine whether the movement is intentional.

In the example of FIG. 1, the terminal device 10 (T1) acquires feature information representing features of objects that the terminal device 10 (T1) passes by as reference information reflecting the environment and situation around the terminal device 10 (T1). do.
In daily movement, the terminal device 10 (T1) (user U1) often passes (comes and goes) a specific object each time. For example, during daily movement toward a destination (for example, commuting), objects (oncoming vehicles (other vehicles), communication devices such as terminal devices used by occupants of oncoming vehicles, stores, etc.) that pass by the automobile 200 of the user U1 buildings, and communication equipment within those buildings, etc.) are typically nearly identical. Therefore, when the feature information of the object that the terminal device 10 (T1) passes by is frequently the same as the feature information of a specific object that the terminal device 10 (T1) passes by on a daily basis, it can be determined that the movement is a daily movement. .
On the other hand, in non-daily movement, many things that pass by the terminal device 10 (T1) (user U1) are different from those in daily movement. Therefore, when the feature information of the object that the terminal device 10 (T1) passes by frequently differs from the feature information of a specific object that the terminal device 10 (T1) passes by on a daily basis, it can be determined that the movement is unusual.

The characteristic information is, for example, communication identification information of a communication device passing by the terminal device 10 (T1). Here, the communication device is a device (wireless master device, wireless slave device, etc.) capable of performing wireless communication, and the terminal device 10 of the present embodiment is also included in the communication device.

The above identification information is not particularly limited as long as the communication devices can be mutually identified, but typically, it can be a MAC (Media Access Control) address unique to the communication device. In addition, SSID (Service Set Identifier) used for identifying wireless LAN access points, ID for identifying communication devices in short-range wireless communication such as Bluetooth (registered trademark), and reading by wireless communication The user ID of the user of the terminal device 10, which is open to the public in a possible manner, may be used as the identification information.

2. Description of the Related Art A communication device that performs wireless communication such as a wireless LAN or Bluetooth periodically transmits data (packets) called a beacon for searching for a connection destination access point (for example, at intervals of 100 msec). This beacon contains identification information (such as the MAC address described above) for identifying the communication device that transmits the beacon. The terminal device 10 (T1) acquires the identification information included in the beacon, for example, by receiving this beacon.

In the example of FIG. 1, the terminal device 10 (T1) of the user U1 has the MAC address "XX-XX-XX-XX-XX-XX" of the terminal device 10 (T11) used by the user of the oncoming vehicle 300, The MAC address "YY-YY-YY-YY-YY-YY" of the wireless LAN access point 40 in the store 400 along the road is acquired as feature information.

Another example of feature information is information relating to features of a moving object extracted from an image of a moving object passing by the terminal device 10 (T1). Here, the moving object is typically an automobile (vehicle), and at least part of the information included in the license plate (automobile registration number) of the automobile or the type of automobile can be used as feature information.
A license plate includes a place name, a two-digit or three-digit classification number, one hiragana character (or alphabet), and a four-digit vehicle number. All of these may be used as feature information, or part of them (usually part including the vehicle number) may be used as feature information.
In addition, the vehicle type used as the feature information may be the "type" of the vehicle such as a passenger car, a small truck, a large truck, a bus, and a motorcycle, or may be a "car name" that is the individual name of the vehicle. It can be.
The information on the license plate and the information on the vehicle type of the oncoming vehicle may be used together, or only one of them may be used.

The method of capturing images of moving objects passing by is not particularly limited, but a method of using an image from a drive recorder installed in the automobile 200, or an image of the front direction of the terminal device 10 (T1) from the windshield of the automobile 200 can be captured. A method of mounting the terminal device 10 (T1) at a suitable position and capturing an image with a camera mounted on the terminal device 10 (T1) may be used.
As a method for extracting feature information from a captured image, various known optical character recognition (OCR) or the like can be used.

In the example of FIG. 1, the terminal device 10 (T1) converts license plate information "YY 300 Ah 12-34" and "ZZ 300 Ah 13-57" obtained from the image of the oncoming vehicle 300 into feature information. to get as

The server device 100 acquires a plurality of feature information acquired by the terminal device 10 (T1) along with the movement of the user U1 via a communication network, and stores each of the feature information in advance in the storage unit 120 (Fig. 3) is checked to see if it matches the characteristic information accumulated in the above (hereinafter referred to as accumulated characteristic information).
Here, the accumulated feature information is the feature information acquired in the past daily movement of the user U1 (the terminal device 10 (T1), the car 200) (that is, the information of a plurality of cars (group of cars) that pass each other on a daily basis). and information on a plurality of communication devices (a group of communication devices) that we pass each other on a daily basis), and in FIG. exemplified.

As a result of collating (matching) the acquired feature information with the accumulated feature information, if the feature information matches any of the accumulated feature information, it means that the feature information is the feature information that can be acquired in daily movement. can. Also, if the acquired feature information does not match any of the stored feature information, it can be said that the feature information may be feature information that cannot be acquired in daily movement. Therefore, the greater the degree of mismatch between the acquired feature information and the accumulated feature information (the smaller the degree of It can be estimated that the greater the degree, the more likely it is a daily movement.

When the degree of mismatch between the feature information acquired from the terminal device 10 (T1) and the accumulated feature information satisfies a predetermined condition, the server apparatus 100 determines that the movement of the user U1 is unusual. . More specifically, the server device 100 detects that the ratio of the feature information that does not match the accumulated feature information among the plurality of feature information acquired from the terminal device 10 (T1) is greater than a predetermined reference value (threshold). It is determined that the movement is extraordinary. That is, it is determined whether the movement is regular or extraordinary by outlier determination for the accumulated feature information.

The reference value used for this determination can be determined according to the type and number of accumulated feature information, the user U1's behavior pattern in daily movement, and the like. Specifically, when the accumulated characteristic information is still small (for example, when the number of days of use of the navigation application in the terminal device 10 (T1) is still small), even the characteristic information acquired during daily movement is accumulated. Since there is a high possibility that it will not match the feature information, the reference value may be set high, and the reference value may be lowered as the accumulated feature information increases (as the number of days the navigation application is used increases).
In addition, among the accumulated feature information, the weight of specific feature information that can be strongly estimated as daily movement is increased, and the reference value is increased when the specific feature information is acquired (i.e., extraordinary so that it is less likely to be determined to be a random movement). Examples of the above specific feature information include feature information that can be obtained only when the user U1 is in the area of daily life, such as the MAC address of a wireless LAN access point installed at a store near his or her home or place of work. .

It should be noted that instead of the ratio of mismatches with the accumulated feature information, it may be determined that the movement is unusual when the number of feature information that does not match the accumulated feature information is greater than a predetermined number.

Also, if the number of feature information used for determination is too small, the result of determining whether the movement is routine or unusual may be inappropriate. For example, even if the movement is routine, if new feature information that is not included in the accumulated characteristic information is acquired by chance immediately after the start of the movement, there is a high possibility that the movement will be erroneously determined to be an extraordinary movement. Become. For this reason, it is desirable to start determining whether the movement is regular or extraordinary when the number of pieces of characteristic information equal to or greater than the predetermined lower limit is acquired.

In the example of FIG. 1, it is assumed that the reference value is 0.5 (50%). On the other hand, among the four pieces of feature information acquired in FIG. The information does not match the stored feature information. Therefore, the ratio of feature information that does not match the accumulated feature information is 0.75, which is greater than the reference value (0.5), so server device 100 determines that user U1's movement is unusual. do.

Further, although not illustrated in FIG. 1, if the ratio of feature information that does not match the accumulated feature information among the acquired feature information is equal to or less than a reference value, the server device 100 determines that the movement of the user U1 is It is determined that it is daily movement.
In this case, the server device 100 adds the acquired feature information to the accumulated feature information and updates the content of the accumulated feature information.

[1-3. Destination prediction method and example of information provision mode]
When it is determined that the movement of user U1 is daily movement, server device 100 predicts the destination based on the user terminal information associated with terminal device 10 (T1) of user U1. In FIG. 1, history information related to the usage history of the terminal device 10 (T1) is used as the user terminal information. More specifically, the information of the "navigation application destination history" representing the points designated as destinations in the past in the navigation application of the terminal device 10 (T1) and the points actually moved to is used. In the "navigation app destination history", multiple destinations are ranked and arranged according to the number of times they have been designated as destinations, the number of times they have actually visited, and so on. In the example of FIG. 1, "BCD Trading", "Super S", and "Z Elementary School" are arranged in descending order. Among these, "BCD Trading" is the workplace of user U1.
Also, when predicting the destination, the server device 100 acquires the latest user terminal information from the terminal device 10 (T1). Alternatively, user terminal information stored in the server device 100 in advance may be used.

In the example of FIG. 1, the server apparatus 100 predicts "BCD Trading", which has the highest ranking, as the destination based on this user terminal information when it is determined that the movement is daily. Note that the destination prediction algorithm is not limited to the above, and the distance from the current position, the time period, and the like may be further taken into consideration.

On the other hand, when it is determined that the movement of user U1 is an extraordinary movement, server device 100 selects reference terminal devices used by users other than user U1 (in FIG. 1, terminal device 10 (T11) to 10 (T14), etc.). In FIG. 1, the general terminal information includes history information related to the usage history of the reference terminal device, more specifically, "navigation application destination history". In this "navigation application destination history", the ranking is made and arranged in the same way as the destination history of the user terminal information.
Further, when predicting the destination, the server device 100 acquires the latest terminal information from each reference terminal device and updates the general terminal information. Instead of this, general terminal information stored in the server device 100 in advance may be used.

In the example of FIG. 1, when it is determined that the movement is unusual, the server device 100 selects "shopping mall X" acquired from the most reference terminal devices based on this general terminal information. Predict as a destination. Note that the destination prediction algorithm is not limited to being based solely on the number of terminal devices from which keywords representing the destination have been acquired, but rather the order in the destination history of each reference terminal device, the distance from the current location, and the time period. etc. may be further considered.

Alternatively, only part of the general terminal information may be selected and used for destination prediction.
In this case, the terminal information selected from the general terminal information can be, for example, the terminal information of the reference terminal device pre-associated with the terminal device 10 (T1) of the user U1. Examples of the reference terminal device associated with the terminal device 10 (T1) in advance include, for example, a reference terminal device of a user whose address is close to that of the user U1 (a reference terminal device of a user whose address is within the daily living area of the user U1, etc.), and a reference terminal device of a user having common attributes (sex, age, preferences, etc.).
Alternatively, when the current location of the terminal device 10 (T1) can be acquired, terminal information that takes into account the current location of the terminal device 10 (T1) may be selected from the general terminal information. For example, among the terminal information of the reference terminal device, the terminal information including the past destination history searched with the range near the current position of the terminal device 10 (T1) as the departure point may be extracted from the general terminal information.

The server device 100 provides information corresponding to the destination thus predicted to the terminal device 10 (T1) in which the navigation application is operating in the destination prediction mode. Here, providing information means transmitting necessary data to the terminal device 10 (T1) and displaying various information on the screen of the navigation app in the display unit 14 of the terminal device 10 (T1). say.

FIG. 2 is a diagram showing an example of an information display screen on the display unit 14 of the terminal device 10 (T1). In FIG. 2, an example will be described in which the movement is determined to be daily movement by the above method.
As shown in FIG. 2, in the terminal device 10 (T1) that has received the information about the predicted destination, the information about "BCD Trading" is displayed as the predicted destination in the upper part of the display section 14. 14, the route to "BCD Trading", traffic information such as congestion on the route, and information on shops (here, restaurants) around the route are displayed.

[2. Configuration of Information Providing System]
Next, configurations of the server device 100 and the terminal device 10 forming the information providing system 1 will be described.
FIG. 3 is a diagram showing a configuration example of the server device 100 and the terminal device 10. As shown in FIG.

[2-1. Configuration of Server Device]
The server device 100 includes a control unit 110, a storage unit 120, a communication unit 130, and the like. In addition, the server device 100 further includes an input unit (keyboard, mouse, etc.) for receiving input operations from the operator of the server device 100, a display unit (liquid crystal display device, etc.) for displaying various information, and the like. It's okay to be there.

The control unit 110 (computer) includes an arithmetic device such as a CPU (Central Processing Unit), and a storage device such as a RAM (Random Access Memory), a ROM (Read Only Memory), and a flash memory. By executing the program 123 stored in the storage unit 120, the operation of each unit of the server device 100 is controlled. By executing the program 123, the control unit 110 functions as a determining unit 111 (determining means), a predicting unit 112 (predicting means), and an information providing unit 113 (information providing means).

The determination unit 111 obtains reference information such as position information and the above-described feature information from the terminal device 10 (T1), and uses the above-described method to determine whether the movement of the user U1 moving with the terminal device 10 (T1) is Determine whether the movement is extraordinary or routine. Specifically, when the location information can be acquired from the terminal device 10 (T1), the determining unit 111 identifies the current location of the terminal device 10 (T1) based on the location information, If it is out of range, it is determined that the movement is extraordinary. Further, the determination unit 111 acquires feature information from the terminal device 10 (T1) and determines whether or not the feature information matches any of the accumulated feature information in the accumulated feature information data 122 of the storage unit 120. do. Further, the determination unit 111 determines that the movement is unusual when the ratio of the feature information that does not match the accumulated feature information among the plurality of feature information acquired from the terminal device 10 (T1) is greater than a predetermined reference value. If the value is equal to or less than the reference value, it is determined to be daily movement. In addition, the determination unit 111 stores the acquired feature information in the accumulated feature information data 122 when determining that the movement is a daily movement.

The prediction unit 112 predicts the destination of the user U1 (terminal device 10 (T1)) using a method based on the determination result of the determination unit 111 . That is, the prediction unit 112 predicts the destination based on the user terminal information in the terminal information data 121 of the storage unit 12 when the determination unit 111 determines that the movement is a daily movement. When it is determined that the movement is a moderate movement, the destination is predicted based on the general terminal information in the terminal information data 121 . In addition, the prediction unit 112 acquires terminal information from the terminal device 10 as necessary when predicting the destination.

The information providing unit 113 provides information according to the destination predicted by the prediction unit 112 . The information to be provided and the method of providing the information are as described above.

The storage unit 120 is implemented by a storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The storage unit 120 stores terminal information data 121 in which the user terminal information and general terminal information described above are stored, accumulated feature information data 122 in which accumulated feature information is stored, programs 123, and the like. Among them, the terminal information data 121 includes history information data 121a storing history information of the terminal device 10, user information data 121b storing information related to the user of the terminal device 10, and position information storing position information of the terminal device 10. It includes information data 121c and the like.

FIG. 4 is a diagram showing an example of contents of the history information data 121a.
The history information data 121a includes information on items such as "terminal ID", "user ID", "search word", "navigation application destination history", "purchase history", and "installed application" for each terminal device 10. is the associated data.
“Terminal ID” is an ID set to identify the terminal device 10 .
“User ID” is an ID set to identify a user using the terminal device 10 . The user ID is, for example, an ID associated with an account used by the user to log in to the server device 100 on an application program (hereinafter referred to as “app”) installed in the terminal device 10 .
A “search word” is a search word used for searching information in the terminal device 10 . Specifically, it is a search word used in a search for displaying desired information in a browser application installed in the terminal device 10, a search word used in a destination search in a navigation application, or the like. The search words are ranked according to predetermined criteria for each terminal device 10 . Methods for ranking search words include a method in which the more frequently used search words are ranked higher, and a method in which words used more recently in searches are ranked higher. Alternatively, ranking may be determined by weighting according to a plurality of factors such as the number of times of use and search time.
The contents of the "navigation application destination history" are as described above.
“Purchase history” is information on products purchased in the past on the application of the terminal device 10 . Information on these products is ranked and arranged according to the number of purchases, the number of days since the last purchase, and the like.
The “installed application” is information related to the type of application installed in the terminal device 10 (for example, the name and genre of the application). These apps are ranked and arranged according to usage frequency and the like.

Thus, the history information data 121a includes various information other than the navigation application destination history. Therefore, the prediction unit 112 may use other information included in the history information data 121a in addition to the navigation application destination history or instead of the navigation application destination history when predicting the destination.
For example, the prediction unit 112, based on the information of the search word, the user of the terminal device (user U1 in case of daily movement, other unspecified number of users in case of non-daily movement) has searched in the past. You may predict the destination related to the matter which was carried out as a destination.
In addition, the prediction unit 112 predicts, based on the purchase history information, the user of the terminal device (user U1 for daily movement, other unspecified number of users for non-daily movement). It is also possible to specify the products that are sold, and predict the destination as a commercial facility that has stores that sell these products in common.
In addition, the prediction unit 112 predicts that the user of the terminal device (user U1 in case of daily movement, other unspecified number of users in case of non-daily movement) is interested based on the information of the installed application. It is also possible to specify a field that the user has and predict a point highly related to the field as the destination. For example, when a fishing information application is installed in the terminal device, a point where fishing can be performed (river, fishing pond, etc.) may be predicted as the destination.
Also, the prediction unit 112 may predict the destination by using these pieces of information in combination.

FIG. 5 is a diagram showing an example of contents of the user information data 121b.
The user information data 121b is data in which information items such as “terminal ID”, “user ID”, “sex”, “age”, and “family” are associated with each terminal device 10 .
“Gender” is the gender of the user.
“Age” is the age of the user. Age information may be used instead of age.
"Family" is information indicating the user's family. For example, when the user's family has a user ID, the family structure is specified by the user ID. Instead of this, the family members may be identified by other methods such as a method of identifying users with the same registered address as family members.
The user information data 121b may also include information such as name, place of residence (address), interest, income, and lifestyle.
The prediction unit 112 may predict the destination in consideration of the user information included in the user information data 121b in addition to the history information included in the history information data 121a. For example, when it is determined that the movement is unusual, the destination is predicted based on the history information associated with the reference terminal device of the user having the same attributes (gender, age, etc.) as the user U1. can be

FIG. 6 is a diagram showing an example of the contents of the position information data 121c.
The location information data 121c is data in which the history of the location information of the terminal device 10 corresponding to the terminal ID is stored in chronological order for each terminal ID. In the positional information data 121c, the positional information representing the position of each terminal device 10 is arranged in chronological order in association with the time when the positional information was obtained.

FIG. 7 is a diagram showing an example of the contents of the accumulated characteristic information data 122. As shown in FIG.
In FIG. 7, in addition to the characteristic information "MAC address" and "license plate" illustrated in FIG. remembered. Such feature information may be further used in determining whether the movement is routine or extraordinary. Further, feature information other than the feature information illustrated in FIG. 7 may be further stored in the accumulated feature information data 122 and used for the determination.

The communication unit 130 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 130 is connected to the communication network N by wire or wirelessly, and transmits and receives information to and from the communication unit 13 of the terminal device 10 .

[2-2. Configuration of terminal device]
As shown in FIG. 3, the terminal device 10 includes a control unit 11, a storage unit 12, a communication unit 13, a display unit 14, a position information acquisition unit 15, and the like.

The control unit 11 includes an arithmetic unit such as a CPU (Central Processing Unit) and a storage device such as a RAM (Random Access Memory), a ROM (Read Only Memory), and a flash memory. The operation of each part of the terminal device 10 is controlled by executing stored system programs and various application programs (for example, the navigation application 12a, etc.).
Specifically, the control unit 11 causes the position information acquisition unit 15 to acquire position information at a predetermined timing, and causes the communication unit 13 to transmit the result to the server device 100 .
Further, when the user performs an input operation instructing execution of the navigation application 12a, the control unit 11 executes the navigation application 12a and causes the display unit 14 to display information corresponding to the processing content. For example, when information corresponding to the predicted destination is acquired from the server device 100, the control unit 11 causes the display unit 14 to display route information, peripheral information, etc. according to the acquired information.

The storage unit 12 is implemented by a storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The storage unit 12 stores the system program described above and various applications such as the navigation application 12a.

The communication unit 13 is realized by various communication modules for performing communication by the 3rd generation mobile communication system, 4th generation mobile communication system, etc., wireless LAN communication, and short-range wireless communication such as Bluetooth (registered trademark) and infrared communication. be done. The communication unit 13 transmits and receives information to and from the communication unit 130 of the server device 100 via the communication network N. FIG. Further, the communication unit 13 transmits and receives information to and from the communication unit 13 of another terminal device 10 by near field communication or the like.

The display unit 14 is implemented by a liquid crystal display device, an organic EL (Electro Luminescence) display device, or the like, and displays various information under the control of the control unit 11 . The display screen of the display unit 14 may be provided with a touch panel that receives an input operation from the user.

The position information acquisition unit 15 is a GPS module that receives radio waves transmitted from positioning satellites, demodulates and decodes them, and calculates the current position of the terminal device 10 based on the obtained information. The content of the calculated current position is output to the control section 11 as position information in a predetermined format, and transmitted to the server device 100 via the communication section 13 .

[3. Information provision processing flow]
Next, information providing processing executed by the control unit 110 of the server device 100 to provide the information described above will be described.

FIG. 8 is a flow chart showing a control procedure by the control unit 110 for information provision processing.
This information providing process is started when the navigation application is executed in the terminal device 10 (T1) of the user U1 and the destination is not set (when the destination prediction mode is in operation). be.

When the information providing process is started, the control unit 110 (determining unit 111) determines whether or not position information can be acquired from the terminal device 10 (T1) used by the user U1 (step S101). If it is determined that the position information can be acquired ("YES" in step S101), the control unit 110 (determination unit 111) acquires the position information, and the terminal device 10 ( It is determined whether or not the current position of T1) is within the preset daily life range of user U1 (step S102).

If it is determined in the process of step S101 that the position information cannot be acquired ("NO" in step S101), or if it is determined in the process of step S102 that the current position is within the daily life area ("YES" in step S102) ), the control unit 110 (determination unit 111) acquires characteristic information from the terminal device 10 (T1) (step S103).

The control unit 110 (determining unit 111) determines whether or not a predetermined lower limit number or more of feature information has been acquired (step S104). (“NO” in step S104), the process returns to step S103. If it is determined that the feature information equal to or greater than the lower limit has been acquired ("YES" in step S104), the control unit 110 (determining unit 111) determines whether the acquired feature information matches the accumulated feature information. It is determined whether or not the ratio of feature information that is not used is greater than a reference value (step S105).

If it is determined that the ratio of feature information that does not match the accumulated feature information among the acquired feature information is equal to or less than the reference value ("NO" in step S105), the control unit 110 (determination unit 111) instructs the user It is determined that the movement of U1 is daily movement (step S106). In response to this, the control unit 110 (prediction unit 112) predicts the destination by the method described above based on the user terminal information in the terminal information data 121 (step S107: prediction step).

If it is determined in the process of step S105 that the ratio of the feature information that does not match the accumulated feature information among the acquired feature information is greater than the reference value ("YES" in step S105), or if the process of step S102 causes the terminal When it is determined that the current position of the device 10 (T1) is outside the daily living area of the user U1 ("NO" in step S102), the control unit 110 (determining unit 111) determines that the movement of the user U1 is It is determined that the movement is extraordinary (step S108). In response to this, the control unit 110 (prediction unit 112) predicts the destination by the method described above based on the general terminal information in the terminal information data 121 (step S109: prediction step).
Among the above steps, the processing from step S101 to step S106 or step S108 corresponds to the determination step.

When the destination is predicted in the process of step S107 or step S109, the control unit 110 (information providing unit 113) transmits information corresponding to the predicted destination to the terminal device 10 (T1), and the terminal device 10 It is displayed on the display unit 14 of (T1) (step S105: information providing step).

The control unit 110 determines whether or not the user U1 (the terminal device 10 (T1)) has arrived at the predicted destination based on the position information of the terminal device 10 (T1) (step S111). If it is determined that user U1 has not arrived at the predicted destination ("NO" in step S111), control unit 110 executes the process of step S111 again, and user U1 has arrived at the predicted destination. ("YES" in step S111), the control unit 110 terminates the information providing process.

Note that the information providing process may be modified as follows.
That is, when it is determined in step S102 that it is within the range of daily life ("YES" in step S102), it is once determined that it is a daily movement (step S106), and the destination is predicted based on the user history information ( After starting step S107) and information provision according to the predicted destination (step S110), in parallel with this, it is additionally determined whether or not the movement is extraordinary based on the feature information ( Steps S103 to S105) may be performed. That is, when the determination result of step S105 based on the acquired feature information is "YES", it is determined that the movement is unusual (step S108), and the destination is predicted based on the general history information (step S109). ) to update the predicted destination, and provide information according to the updated predicted destination (step S110). According to this, information provision can be started at an earlier stage, and user convenience can be improved.

[4. Other aspects of information provision method]
Next, the above [1. Information providing method] will be described.

Among extraordinary movements, in the case where there is a fellow passenger other than the user U1 in the automobile 200, the prediction accuracy is improved by predicting the destination in consideration of the fellow passenger's attributes, tastes, behavior patterns, etc. can be done. This is because in such cases, the purpose of travel is often leisure or shopping, and the attributes and tastes of fellow passengers are likely to be reflected in the destination.
Therefore, when it is determined that the movement is unusual, the destination can be predicted based on the terminal information associated with the reference terminal device of the user riding in the vehicle 200 among the general terminal information. , a more appropriate destination prediction can be performed. Also, in this case, the terminal information corresponding to the terminal device 10 (T1) of the user U1 may be used together with the prediction of the destination.

FIG. 9 is a diagram for explaining an information providing method when there is a fellow passenger in automobile 200. As shown in FIG.
In the example of FIG. 9, users U2 to U4 are riding in an automobile 200 in addition to user U1. It is assumed that users U2 to U4 use terminal devices 10(T2) to 10(T4) (reference terminal devices), respectively. The terminal devices 10(T2) to 10(T4) are all communicably connected to the server device 100 via a communication network.

In the example of FIG. 9, when it is determined that the movement of user U1 is an extraordinary movement, server device 100 is first used by a plurality of users U1 to U4 riding together in automobile 200. A plurality of terminal devices 10(T1) to 10(T4) are specified. The method for specifying the terminal device 10 is not particularly limited, but a method using the position information of the terminal device 10 can be used.

FIG. 10 is a diagram illustrating a method of identifying a plurality of terminal devices 10 used by fellow passengers.
FIG. 10(a) depicts terminal devices 10(T1) to 10(T6) around the terminal device 10(T1) of user U1 at time t1 and position LC1.
The server device 100 calculates the distance from the terminal device 10 (T1) of the user U1 to each terminal device 10 based on the position information acquired from each of these terminal devices 10 (T1) to 10 (T6). A terminal device 10 within a range of a predetermined distance r (usually several meters) from the terminal device 10 (T1) is used by a passenger of the vehicle 200 (inside the vehicle 200). It is specified (estimated) as 10. Here, since the five terminals 10(T1) to 10(T5) are within the range of the distance r from the terminal 10(T1), they are identified as the terminal 10 used by the passenger of the vehicle 200. .

Next, as shown in FIG. 10(b), the server device 100 periodically acquires location information from the specified terminal devices 10 (T1) to (T5), and determines the moving route of each terminal device 10. Identify. Then, among the terminal devices 10 (T1) to (T5) identified as being in the car 200 at time t1, the fellow passenger uses the terminal device 10 whose moving route is the same as that of the terminal device 10 (T1). The terminal device 10 is re-identified, and the identification result of the terminal device 10 is updated. In the example of FIG. 10(b), the positions of the terminal devices 10 (T1) to (T4) coincide at positions LC1, LC2, and LC3 at each of the times t1 to t3, whereas the terminal device 10 (T5 ) are positions LC1, LC4, and LC5 at times t1 to t3, respectively, and are different from the moving routes of the terminal devices 10(T1) to 10(T4). Therefore, the server device 100 presumes that the terminal device 10 (T5) is outside the vehicle 200 at the timings of time t2 and time t3, and the remaining terminal devices 10 (T1) to 10 (T4) are It is re-identified as the terminal device 10 used by the fellow passenger.

As shown in FIG. 9, the server device 100 acquires terminal information from each of the four terminal devices 10(T1) to 10(T4) thus identified. In FIG. 9, history information related to the usage history of the terminal device 10 is extracted from the terminal information. More specifically, search words are extracted from the history information included in the history information data 121a of FIG.
In the example of FIG. 9, in the terminal device 10 (T1) of the user U1, the search words "book A", "sweetfish fishing", and "skiing" are extracted in descending order of rank. In the terminal device 10 (T2) of the user U2, the search words "zoo B", "shop C", and "book A" are extracted in descending order of rank. Further, in the terminal device 10 (T3) of the user U3, the search words "toy D", "zoo B", and "aquarium E" are extracted in descending order of rank. Further, in the terminal device 10 (T4) of the user U4, the search words "picture book F", "zoo B", and "toy G" are extracted in descending order of rank.

The server device 100 identifies and extracts the search words included in the history information (general terminal information) of the most terminal devices 10 among the extracted search words, and extracts the extracted search words. Predict 200 destinations. Here, since the search word "B zoo" is included in the history information of the most terminal devices 10 (three terminal devices 10 (T2) to 10 (T4)), the search for "B zoo" Words are extracted and used to predict the destination. Note that if there are a plurality of search words included in the history information of the same number of terminal devices 10, the search words used for destination prediction are determined based on the ranking of the search words described above.
Here, "the most searched word (keyword) included in the history information of the terminal device 10" is, in other words, the "greatest common divisor of keywords".

A method of predicting a destination based on an extracted search word is not particularly limited. Considering the degree of relevance and distance from the current location, the candidate locations are ranked, and the candidate location with the highest ranking is specified as the predicted destination. Any search algorithm can be used as long as it searches for a candidate site that satisfies a predetermined condition regarding the degree of relevance to the search word.
In the example of FIG. 9, as a result of a search using "B zoo" as a search word, "B zoo", "H zoo and botanical garden", . ” is identified as the predicted destination.

When the predicted destination is identified, the server device 100 provides information according to the predicted destination to the terminal device 10 (T1) in which the navigation application is operating in the destination prediction mode. As a result, the display unit 14 of the terminal device 10 (T1) displays information about "Zoo B", a route to "Zoo B", traffic information on the route, information about shops in the vicinity, and the like.
It should be noted that the navigation app is also installed on the terminal devices 10 (T2) to 10 (T4), and when the navigation app is being executed on these terminal devices 10, the terminal device 10 is also installed on the terminal device 10 (T1 ) may be displayed.

According to such an information providing method, a facility ("B zoo") highly relevant to matters in which a plurality of fellow passengers (here, users U2 to U4) are interested is specified as a predicted destination. Therefore, it is possible to increase the probability of accurately predicting the destination of the user U1 during extraordinary travel. In addition, even if the predicted destination is different from the actual destination, recommending facilities that many passengers are interested in as destinations or providing information about such facilities Therefore, it is possible to provide services with high user satisfaction and convenience.

In the above description, the operation in the case where the terminal information is acquired from the four terminal devices 10(T1) to 10(T4) identified at time t2 in FIG. However, similar operations are also performed at time t1 and time t3 in FIG. 10(a). That is, first, at time t1 (when users U1 to U4 get into automobile 200), terminal devices 10 used by fellow passengers are identified, terminal information is obtained, destinations are predicted, and destinations are predicted and information will be provided. At time t1, it is determined that the terminal device 10 (T5) actually outside the vehicle 200 is also inside the vehicle 200, and the terminal information acquired from the terminal device 10 (T5) is also used to predict the destination. used for

After that, at time t2 after the automobile 200 starts to move, the terminal devices 10(T1) to 10(T4) inside the automobile 200 are accurately identified, and these terminal devices 10(T1) to 10(T4) are The destination is predicted again based on the terminal information from 10(T4) and updated. The prediction accuracy of the destination at time t2 is higher than the prediction accuracy at time t1 because the prediction is made based only on the terminal information from the terminal devices 10(T1) to 10(T4) in the vehicle. .
Thereafter, at predetermined timings (times t3, t4, . . . ), the terminal device 10 used by the fellow passenger is identified, terminal information is obtained, the destination is predicted, and information is provided according to the predicted destination. .

In this way, by first predicting the destination based on the combination (cluster) of users at the moment they get into the automobile 200, the conventional destination prediction using only the terminal information of the terminal device 10 (T1) of the user U1 can be performed. The prediction accuracy can be improved with respect to the prediction method. In addition, by predicting the destination based on the latest terminal information and updating the destination every time the terminal device 10 is re-specified, it is possible to further improve the prediction accuracy of the destination.

Note that the terminal information is acquired only at the first time t1, and at subsequent times t2, t3, . You can try to do it again. Thereby, the amount of communication data can be suppressed.

Also, the predicted destination may be updated according to the moving route of the vehicle 200 . For example, when it is determined from the moving route of the vehicle 200 that the first predicted destination is opposite to the moving direction of the vehicle 200, the vehicle A candidate location beyond 200 travel directions may be updated as the new predicted destination.

In the example of FIG. 9, the destination is predicted based on the history information acquired from the terminal devices 10 (T1) to 10 (T4) of the fellow passengers. You can For example, facilities that cannot be used during the current time period (for example, outside business hours) may not be adopted as predicted destinations.

Also, the destination may be predicted based on the context of fellow passengers (users U1 to U4). Here, context is arbitrary information that can be used to identify a user's relationship with a specific object, the user's state, and the like. For example, from the viewpoint of relationships between a user and other users, information such as sex, age, place of residence, interests, family relationships, income, and lifestyle can serve as context. As for the user's condition, information such as the facility where the user is staying, surrounding conditions, physical condition, exercise condition, etc. can serve as a context.
As a method of destination prediction based on the user's context, for example, when the fellow passengers have a specific relationship such as family, prediction is made based on past movement histories of these fellow passengers. There is a method of preferentially adopting destinations that are expected to be predictive destinations. Alternatively, the history information may be weighted according to the context, and the destination may be predicted based on the weighted history information. For example, a mode may be adopted in which the history information acquired from the terminal device 10 of the user who is a child is weighted less.

Further, the method of specifying the terminal device 10 used by the passenger of the automobile 200 is not limited to the method using the position information described above. For example, the terminal device 10 (T1) of the user U1 and the terminal device 10 connected by short-range wireless communication may be identified as the terminal device 10 of the fellow passenger. Further, the passenger's terminal device 10 may be specified according to a predetermined input operation on the terminal device 10 by the user.

[5. effect]
As described above, the server device 100 as the information processing device according to the above-described embodiment includes the control unit 110, and the control unit 110 controls the moving terminal device 10 (T1) to determines whether the movement of the user U1 who is moving with the terminal device 10 (T1) is an extraordinary movement or an everyday movement other than the extraordinary movement (decision unit 111). 111 provides information according to the determination result (information providing unit 113).
Accordingly, it is possible to determine whether the movement of the user U1 is routine movement or extraordinary movement, based on the circumstances of the environment around the terminal device 10 (T1). Therefore, even if the position information cannot be acquired from the terminal device 10 (T1), it is possible to appropriately determine whether the movement is routine or extraordinary. Further, even if the terminal device 10 (T1) is determined to be within the daily life range of the user U1 based on the location information, the situation of the environment around the terminal device 10 (T1) may cause an unusual situation. It becomes possible to appropriately determine whether or not there is movement. Further, by providing information according to these determination results, it is possible to provide more appropriate information.

In addition, by using the communication identification information of the communication device that the terminal device 10 (T1) passes by as the feature information, an object (communication device) that the terminal device 10 (T1) passes by is the same as an object that the terminal device 10 (T1) passes by on a daily basis. It can be determined whether there is Therefore, it is possible to easily determine whether the movement is routine movement or extraordinary movement.

Further, by using the unique MAC address of the communication device (T1) as the characteristic information, it is possible to individually identify the communication devices that pass each other. Therefore, it is possible to reliably determine whether or not the passing communication device is an object that the user passes by during daily movement, and easily and reliably determine whether it is a daily movement or an extraordinary movement. .

Further, by using, as feature information, information relating to the features of a moving object (such as a vehicle) that the terminal device 10 (T1) passes by, which is extracted from an image captured by the moving object, it is possible to determine whether or not the difference between the moving object and the moving object passing by the terminal device 10 (T1) is similar to that of the moving object on a daily basis. It is possible to determine whether the movement is casual or unusual. Therefore, even when there is no communication device passing each other or when identification information cannot be obtained from the communication device, it is possible to obtain the feature information and determine whether the movement is routine or extraordinary. .

In addition, by using at least a part of the information included in the license plate of the vehicle as the moving object that the terminal device 10 (T1) passes as the characteristic information, the vehicle that the terminal device 10 (T1) passes by can be reliably specified by a simple process.

Further, by using the information related to the vehicle type of the vehicle passing by the terminal device 10 (T1) as the feature information, it is possible to more reliably identify the vehicle that the terminal device 10 (T1) passes by.

Further, the control unit 110 controls the extraordinary when the degree of mismatch between the feature information acquired for the determination and the accumulated feature information acquired and accumulated during the past daily movements satisfies a predetermined condition. It is determined to be movement (determination unit 111). As a result, it is possible to determine whether the movement is regular or extraordinary by a simple process of collating the feature information with the accumulated feature information.

Further, the control unit 110 determines that the movement is unusual when the ratio of the feature information that does not match the accumulated feature information among the plurality of feature information acquired for the determination is greater than a predetermined reference value. (Determination unit 111). As a result, by adjusting the reference value, it is possible to easily and flexibly change the criteria for determining whether the movement is routine or extraordinary. Therefore, it is possible to make an appropriate determination according to the environment of the user U1.

Further, when it is determined that the movement is a daily movement, the control unit 110 predicts the destination of the user U1 based on the user terminal information as the first information, and determines that the movement is an extraordinary movement. predicts the destination of the user U1 based on general terminal information as second information including information different from the first information (prediction unit 112), and information corresponding to the predicted destination is provided (information providing unit 113). The destination of user U1's movement often differs depending on whether it is a routine movement or an extraordinary movement. Since the destination can be predicted using different information depending on the type of travel (that is, the destination prediction method can be switched), the probability of being able to predict an appropriate destination according to the mode of movement can be increased. . Therefore, it is possible to provide more accurate information based on a more appropriate destination prediction. Also, even if the predicted destination is different from the actual destination, it is possible to provide information about a point that is likely to be of interest to the user U1, thereby providing services with high user satisfaction and convenience. can do. By providing such a user experience, it is possible to encourage the user to actively use the service (start up the navigation app) even when guidance to the destination is not required (i.e., It is possible to increase or maximize user actions by providing situations by utilizing data, etc.).

Further, in the above embodiment, when it is determined that the movement is daily, the user terminal information associated with the terminal device 10 (T1) used by the user U1 is used as the first information to predict the destination. and if the movement is determined to be extraordinary, general terminal information including information associated with one or more reference terminal devices used by users other than user U1 is used as the second information. to predict the destination. In daily movement, the destination is often a point that can be inferred from the past behavior pattern of the user U1. Therefore, in daily movement, by using the user terminal information as the first information, it is possible to predict an appropriate destination in consideration of the behavior pattern of the user U1. Also, in the case of extraordinary travel, the destination is often a point that is unrelated (or irrelevant) to the past behavior pattern of the user U1. Therefore, by using the general terminal information as the second information, it is possible to increase the probability that the destination is predicted more appropriately. In other words, it is possible to suppress the occurrence of the problem that the predicted destination is biased toward the point that the user U1 visits on a daily basis, and the predicted result is irrelevant, even though the movement is unusual.

In addition, by using general terminal information including information associated with reference terminal devices used by each of an unspecified number of users as the second information, the past behavior of user U1 can be The influence of patterns can be effectively suppressed to predict the destination more appropriately.

Further, in the above "4. Other aspects of the information providing method", the second information is associated with the reference terminal device used by the user riding in the same car 200 as the user U1 among the general terminal information. Predict the destination using terminal information. According to this, it is possible to predict the destination in consideration of the attributes, tastes and behavior patterns of fellow passengers. Therefore, the destination can be predicted with a higher degree of accuracy when the travel is unusual and there is a fellow passenger. In addition, even if the predicted destination is different from the actual destination, it is possible to provide information about points that are likely to be of interest to many of the passengers. can be provided.

Also, as the first information, history information related to the usage history of the terminal device 10 (T1) used by the user U1 is used, and as the second information, information including history information related to the usage history of the reference terminal device is used. Thus, it is possible to predict a point of interest to the user of the terminal device 10 (T1) or the reference terminal device as the destination. That is, in daily movement, a point that the user U1 of the terminal device 10 (T1) is interested in on a daily basis can be predicted as the destination. A point of interest to a large number of users can be predicted as a destination.

Further, in the information providing method of the present embodiment, based on the characteristic information representing the characteristics of objects that the moving terminal device 10 (T1) passes by, the movement of the user U1 moving together with the terminal device 10 (T1) is It includes a determination step of determining whether the movement is a daily movement or a routine movement other than the extraordinary movement, and an information provision step of providing information according to the determination result in the determination step. According to such a method, even if the location information cannot be obtained from the terminal device 10 (T1), it is possible for the user U1 to move on a daily basis based on the environmental conditions around the terminal device 10 (T1). Since it is possible to determine whether the movement is normal or unusual, it is possible to provide more appropriate information.

Further, the program 123 of the present embodiment causes the control unit 110 as a computer provided in the server device 100 to control the terminal device 10 ( The determination unit 111 that determines whether the movement of the user U1 moving with T1) is an extraordinary movement or an everyday movement other than the extraordinary movement, and information according to the determination result by the determination unit 111 It functions as an information providing unit 113 that provides information. By operating the server device 100 with such a program, even if the position information cannot be obtained from the terminal device 10 (T1), the user U1 can Since it is possible to determine whether the movement of the person is a daily movement or an extraordinary movement, it is possible to provide more appropriate information.

[6. others]
The present invention is not limited to the above embodiments, and various modifications are possible.
For example, in the above-described embodiment, an example in which both position information (if obtainable) and feature information are used in determining whether the movement is routine or extraordinary has been described, but the present invention is not limited to this. , it may be determined whether the movement is ordinary or extraordinary based only on the feature information.

Further, the feature information of the moving body is not limited to the license plate and vehicle type information, and can be any information representing the feature of the moving body. Further, the feature information of a mobile object is not limited to the feature information of a vehicle, and may be the feature information of a bicycle, a pedestrian, or the like.
Other examples of characteristic information of moving objects include the state of oncoming vehicles (wet with rain, snow piled up, etc.), the number of oncoming vehicles that pass each other in a given time period, and the number of bicycles passed in a given time period. , the number of pedestrians walking on the sidewalk, and characteristics of the pedestrians (whether they are adults or children (and whether they are walking to and from school with school bags on their backs, etc.)). For example, when the oncoming vehicle is covered with snow, it can be estimated that the vehicle is headed for a snowy area such as a ski resort, so it can be determined that the movement is unusual. If there are few bicycles and pedestrians on weekdays and many bicycles and pedestrians on weekends and holidays, if the number of bicycles and pedestrians is more than the specified number, it is considered a holiday (unusual movement). It can be determined that there is Also, if the number of children carrying school bags on their way to and from school is greater than a predetermined number, it can be determined that it is a weekday (daily movement).

Further, it may be determined whether the movement is a daily movement or an extraordinary movement according to the number of each "type" of vehicles that pass each other. For example, if the percentage of oncoming traffic that is trucks is greater than a predetermined value, it is estimated to be on a weekday and is determined to be a daily move, and if the percentage of trucks is less than a predetermined value, it is estimated to be a holiday. Therefore, it may be determined that the movement is unusual.

Further, in the above embodiment, based on the number and ratio of the feature information that does not match the accumulated feature information among the feature information acquired from the terminal device 10 (T1) (that is, by outlier determination), daily movement However, the present invention is not limited to this, and based on the number and ratio of the feature information that matches the accumulated feature information among the acquired feature information, whether it is a daily move or not is determined. It may be determined whether the movement is extraordinary.

Further, in the above embodiment, the destination is predicted, and then information is provided (guidance guidance, road information, advertisement, etc.) according to the specified predicted destination. However, the purpose is not limited to this, and information may be provided without prediction of the destination. For example, information may be provided (for example, display of advertisements, news, etc.) according to the determined situation based on the result of determining whether the movement is regular or extraordinary. Specifically, the content and amount of advertisements to be displayed may be varied, or the genre of news to be displayed may be varied depending on whether the user is traveling on a daily basis or on an extraordinary basis. In addition, when it is determined that the movement of the terminal device 10 (T1) is unusual even though the terminal device 10 (T1) is within the range of daily life of the user U1, there is a possibility that an emergency such as a disaster or accident has occurred. It may be assumed that there is, and related news may be displayed.

Further, the processing executed by the server device 100 in the above embodiment may be executed by the terminal device 10 (T1). In this case, the terminal device 10 (T1) constitutes an information processing device.
With such a configuration, destination prediction and information provision can be performed by the method of the above embodiment without using the server device 100 .

Further, in the above "4. Other aspects of the information providing method", an example in which a plurality of terminal devices 10 (T1) to (T4) of users riding together in the automobile 200 each communicate with the server device 100 has been described. but not limited to this. For example, only the terminal device 10 (T1) communicates with the server device 100, and the terminal device 10 (T1) and the terminal devices 10 (T2) to (T4) communicate by short-range wireless communication or the like. Then, the terminal information transmitted from the terminal devices 10 (T2) to (T4) to the terminal device 10 (T1) may be transmitted to the server device 100 by the terminal device 10 (T1).
Further, the processing executed by the server device 100 in the above embodiment may be executed by one of the terminal devices 10 (T1) to (T4).

Further, the services provided by the server device 100 in the above embodiment may be provided by HaaS (Hardware as a Service). For example, in a service that provides a user with hardware resources such as a CPU, memory, and storage as a virtualized information processing device, destination prediction and information provision similar to those in the above embodiments may be performed.

Moreover, the terminal information is not limited to history information, user information, and location information, and can include any information that can be associated with the terminal device 10 . For example, as the terminal information, image data of a photograph taken by the terminal device 10, recorded voice data, or the like may be acquired and used for destination prediction.

Also, as the first information and the second information, terminal information (user terminal information, general terminal information) associated with the terminal device 10 has been described as an example. At least one of the first information and the second information may be information associated with the user of the terminal device 10 . For example, in a mode in which the navigation application usage history is managed for each user ID, the destination may be predicted based on the navigation application destination history or the like associated with the user ID.

In addition to terminal information and position information from the terminal device 10, travel data (probe information) may be acquired from the automobile 200 and used for destination prediction. The travel data in this case includes time stamps, position information, vehicle speed, engine speed, and the like.

In addition, although the automobile 200 has been exemplified as a means of transportation, the means of transportation is not limited to this, and any vehicle that allows a plurality of users to ride together (for example, a motorcycle, a bicycle, a horse-drawn carriage, rickshaw, etc.).

Further, in the above-described embodiment, the case where the user U1 travels in the automobile 200 as a means of transportation has been described as an example. You may apply said information provision method.

Although several embodiments of the present invention have been described, the scope of the present invention is not limited to the above-described embodiments, and includes the scope of the invention described in the claims and equivalent ranges thereof. .

1 information providing system 10 terminal device 11 control unit 12 storage unit 12a navigation application 13 communication unit 14 display unit 15 position information acquisition unit 40 wireless LAN access point (communication device)
100 server device (information processing device)
110 control unit 111 determination unit 112 prediction unit 113 information provision unit 120 storage unit 121 terminal information data 121a history information data 121b user information data 121c position information data 122 accumulated characteristic information data 123 program 130 communication unit 200 automobile (transport means)

Claims (16)

Whether the movement of the user moving with the terminal device is unusual movement or daily movement other than the extraordinary movement based on the feature information representing the characteristics of the object that the moving terminal device passes by a determination unit that determines
an information providing unit that provides information according to the determination result of the determining unit;
with
The information processing apparatus, wherein the characteristic information includes information relating to the characteristics of the moving object extracted from an image of the moving object passing by the terminal device. the moving body is a vehicle,
2. The information processing apparatus according to claim 1 , wherein the feature information includes at least a part of information included in a license plate of the vehicle passing by the terminal device. the moving body is a vehicle,
3. The information processing apparatus according to claim 1 , wherein the feature information includes information relating to the vehicle type of the vehicle passing by the terminal device. Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination unit that determines whether to move;
an information providing unit that provides information according to the determination result of the determining unit;
with
The determination unit is configured to, when a degree of mismatch between the feature information acquired for the determination and the feature information acquired and accumulated during the past daily movement satisfies a predetermined condition, the extraordinary condition. An information processing apparatus, characterized in that it determines that a movement is a natural movement. The determination unit is configured to perform the extraordinary movement when a ratio of the feature information that does not match the accumulated feature information among the plurality of feature information acquired for the determination is greater than a predetermined reference value. 5. The information processing apparatus according to claim 4 , wherein it is determined that there is. Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination unit that determines whether to move;
an information providing unit that provides information according to the determination result of the determining unit;
Predicting the user's destination based on predetermined first information when the determination unit determines that the movement is routine movement, and determining that the movement is extraordinary by the determination unit a prediction unit that predicts the destination of the user based on second information including information different from the first information when the
with
The information processing apparatus, wherein the information providing unit provides information corresponding to the destination predicted by the prediction unit. The first information is information associated with the terminal device used by the user,
7. The information processing apparatus according to claim 6 , wherein said second information is information including information associated with one or more reference terminal devices used by users other than said user. 8. The information processing apparatus according to claim 7 , wherein said second information includes information associated with said reference terminal devices used by each of an unspecified number of users. 8. The information processing apparatus according to claim 7 , wherein said second information is information associated with said reference terminal device used by a user who rides with said user on the same means of transportation. The first information is information related to the usage history of the terminal device used by the user,
10. The information processing apparatus according to any one of claims 7 to 9 , wherein the second information is information including information related to a usage history of the reference terminal device. A computer-implemented method of providing information, comprising:
Whether the movement of the user moving with the terminal device is unusual movement or daily movement other than the extraordinary movement based on the feature information representing the characteristics of the object that the moving terminal device passes by a determination step of determining
An information provision step of providing information according to the determination result in the determination step;
including
The information providing method, wherein the characteristic information includes information relating to the characteristics of the moving object extracted from an image of the moving object passing by the terminal device. A computer-implemented method of providing information, comprising:
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination step of determining whether to move;
An information provision step of providing information according to the determination result in the determination step;
including
In the determination step, when the degree of discrepancy between the feature information acquired for the determination and the feature information acquired and accumulated in the past routine movement satisfies a predetermined condition, the extraordinary condition is met. A method of providing information, characterized by determining that the movement is a natural movement. A computer-implemented method of providing information, comprising:
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. a determination step of determining whether to move;
An information provision step of providing information according to the determination result in the determination step;
predicting the user's destination based on predetermined first information when the movement is determined to be the routine movement in the determination step, and determining that the movement is the extraordinary movement in the determination step; a prediction step of predicting the user's destination based on second information, including information different from the first information, if provided;
including
An information providing method, wherein the information providing step provides information corresponding to the destination predicted in the predicting step. a computer provided in an information processing device,
Whether the movement of the user moving with the terminal device is unusual movement or daily movement other than the extraordinary movement based on the feature information representing the characteristics of the object that the moving terminal device passes by determination means for determining
Information provision means for providing information according to the determination result by the determination means;
function as
A program, wherein the feature information includes information relating to features of a moving object extracted from an image of a moving object passing by the terminal device. a computer provided in an information processing device,
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. Determination means for determining movement,
Information provision means for providing information according to the determination result by the determination means;
function as
The determining means determines a degree of mismatch between the feature information acquired for the determination and the feature information acquired and accumulated during the past daily movement satisfies a predetermined condition when the extraordinary condition is met. A program characterized by determining that it is a natural movement. a computer provided in an information processing device,
Based on the feature information representing the features of objects that pass by or pass by the moving terminal device, it is possible to determine whether the movement of the user who is moving with the terminal device is extraordinary or routine other than the extraordinary movement. Determination means for determining movement,
Information provision means for providing information according to the determination result by the determination means;
When the determination means determines that the movement is routine movement, predicting the user's destination based on predetermined first information, and determining that the movement is extraordinary by the determination means prediction means for predicting the user's destination based on second information including information different from the first information, if
function as
A program, wherein the information providing means provides information according to the destination predicted by the predicting means.

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