JP7643966B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

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

Data on users' transfer information search history can be collected via a transfer information app on a smartphone or the like. Technology is known that predicts train congestion using a user's transfer information search history. For example, Patent Literature 1 discloses technology that predicts the congestion status of a route based on information on the search history of a transfer information app.

However, while the method disclosed in Patent Document 1 can predict the congestion status of a route, it cannot identify the car in which a user is riding. Advertisements promoting products and services are posted on trains according to the car. It is believed that businesses that post advertisements can increase the appeal of their advertised products and services to users if they can deliver content related to the advertisements posted in train cars to users.

JP 2015-26136 A

In view of the above problems, the present invention aims to provide an information processing device, an information processing method, and an information processing program that can identify the relative positional relationship of users.

In order to solve the above-mentioned problems and achieve the objective, the information processing device according to the present disclosure includes an acquisition unit that acquires sensor information measured by a sensor unit from a user terminal having a sensor unit that measures various types of sensor information, an identification unit that identifies the relative positional relationship of users based on time-series changes in the sensor information acquired by the acquisition unit from multiple user terminals, and a distribution unit that distributes content according to the identified positional relationship.

According to one aspect of the embodiment, it is possible to provide an information processing device, an information processing method, and an information processing program that can identify the relative positional relationship of users.

FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. FIG. 3 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. FIG. 4 is a diagram illustrating an example of information stored in the route information storage unit of the information processing device according to the embodiment. FIG. 5 is a diagram illustrating an example of information stored in the sensor information storage unit of the information processing device according to the embodiment. FIG. 6 is a diagram illustrating an example of information stored in the content storage unit of the information processing device according to the embodiment. FIG. 7 is a diagram illustrating an example of the configuration of a user terminal according to the embodiment. FIG. 8 is a diagram illustrating an example of the configuration of a carrier terminal according to the embodiment. FIG. 9 is a flowchart illustrating an example of information processing according to the embodiment. FIG. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device.

Below, the information processing device, information processing method, and information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, information processing method, and information processing program according to the present application are not limited to these embodiments.

(Embodiment)
1-1. Example of information processing according to the embodiment
First, an example of information processing according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment. Fig. 1 shows an example in which information processing according to the embodiment is executed by an information processing device 100.

Figure 1 shows an example in which an information processing device 100 acquires sensor information from multiple user terminals 200, identifies the relative positional relationship of users based on a comparison of time-series changes in the acquired sensor information, and delivers content according to the identified positional relationship. Below, an example of information processing according to an embodiment will be described step by step using Figure 1.

The information processing device 100 receives content submitted by an operator from the operator terminal 300 (step S1). For example, the information processing device 100 receives content submitted by an operator in association with a train car from the operator terminal 300.

The information processing device 100 receives the posted information from the user terminal 200B and acquires the sensor information (step S2). For example, the information processing device 100 receives the posted information about the vehicle in which the user U2 is riding that is posted by the user U2 from the user terminal 200B and acquires the sensor information measured by the user terminal 200B.

The information processing device 100 acquires sensor information from the user terminal 200A (step S3). For example, the information processing device 100 acquires sensor information from the user terminal 200A of a user U1 who has agreed to the provision of sensor information.

The information processing device 100 identifies the relative positional relationship of the users based on a comparison of the time-series changes in the sensor information (step S4). For example, the information processing device 100 may compare the time-series changes in the sensor information acquired from the user terminal 200A of the user U1 who has not posted the posted information with the time-series changes in the sensor information acquired from the user terminal 200B of the user U2 who has posted the posted information to calculate the similarity, and identify the relative positional relationship of the users based on the similarity. In addition, the timing at which a characteristic pattern of the time-series changes in the sensor information occurs may be detected, and the relative positional relationship of the users may be identified based on the difference in the timing at which the characteristic pattern occurs. Note that the relative positional relationship of the users here indicates the relative positions between the users, and may be, for example, that the user U1 is located 300 m away from the user U2 in the northwest direction. In other words, the relative positional relationship is not limited to the vehicle in which the user is riding, and may be, for example, that of a business establishment where a user identified by the relative positional relationship of the users came to work on the day in a company with multiple business establishments. As a result, for example, if the vehicle in which user U2 is riding is identified by the posted information, the vehicle in which user U1 is riding can be identified based on the relative positional relationship. In the example shown in FIG. 1, the information processing device 100 acquires the posted information posted by user U2 while riding in vehicle C4 and the sensor information measured at that time, and compares it with the sensor information measured by the user terminal 200A of user U1 who has not posted any posted information to identify the relative positional relationship between the users, and based on that, identifies that user U1 is riding in vehicle C1.

The information processing device 100 delivers content corresponding to the identified relative positional relationship to the user terminal 200 (step S5). For example, if the information processing device 100 determines that user U1 is in vehicle C1 as shown in the example of step S4, the information processing device 100 specifies vehicle C1 and delivers the content submitted by the business operator to the user terminal 200A of user U1.

This allows the information processing device 100 to identify the relative positional relationship of the user and deliver content according to the identified positional relationship to the user terminal 200. Therefore, it is possible to provide businesses with a variety of content delivery methods.

1-2. Another example 1 of information processing according to the embodiment (acceleration sensor)
The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user, based on the time-series change in acceleration measured by the acceleration sensor.

This information processing will be explained step by step. First, the information processing device 100 executes the same processing as steps S1 to S3 shown in FIG. 1. The processing from steps S1 to S3 is the same as the processing described above, so the explanation will be omitted. Note that in this information processing, the sensor information acquired by the information processing device 100 in steps S2 and S3 is the acceleration measured by the acceleration sensor.

The information processing device 100 may identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the acquired acceleration. For example, the information processing device 100 may compare the time-series change in acceleration acquired from the user terminal 200A of the user U1 who has not posted the posted information with the time-series change in acceleration acquired from the user terminal 200B of the user U2 who has posted the posted information, and calculate the similarity to identify the relative positional relationship of the user, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 may also detect the timing at which a characteristic pattern of the time-series change in acceleration (for example, a change in acceleration when a train approaches a curve) occurs, and identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern occurs in the acquired time-series change in acceleration, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 delivers content corresponding to the identified vehicle to the user terminal 200.

This allows the information processing device 100 to identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in acceleration. Furthermore, the information processing device 100 can distribute content associated with the vehicle to the user terminal 200. Therefore, it is possible to provide businesses with a variety of content distribution methods.

1-3. Another example 2 of information processing according to the embodiment (gyro sensor)
The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user, based on the time-series change in the angular velocity measured by the gyro sensor.

This information processing will be explained step by step. First, the information processing device 100 executes the same processing as steps S1 to S3 shown in FIG. 1. The processing from steps S1 to S3 is the same as the processing described above, so the explanation will be omitted. Note that in this information processing, the sensor information acquired by the information processing device 100 in steps S2 and S3 is the angular velocity measured by the gyro sensor.

The information processing device 100 may identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the acquired angular velocity. For example, the information processing device 100 may compare the time-series change in angular velocity acquired from the user terminal 200A of the user U1 who has not posted the posted information with the time-series change in angular velocity acquired from the user terminal 200B of the user U2 who has posted the posted information, and calculate the similarity to identify the relative positional relationship of the user, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 may also detect the timing at which a characteristic pattern of the time-series change in angular velocity (for example, fluctuations in angular velocity when a train approaches a curve) occurs, and identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern occurs in the acquired time-series change in angular velocity, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 delivers content corresponding to the identified vehicle to the user terminal 200.

This allows the information processing device 100 to identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in angular velocity. Furthermore, the information processing device 100 can distribute content associated with the vehicle to the user terminal 200. Therefore, it is possible to provide businesses with a variety of content distribution methods.

1-4. Another example 3 of information processing according to the embodiment (position information sensor)
The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user, based on a time-series change in the positional information measured by the positional information sensor.

This information processing will be explained step by step. First, the information processing device 100 executes the same processing as steps S1 to S3 shown in FIG. 1. The processing from steps S1 to S3 is the same as the processing described above, so the explanation will be omitted. Note that in this information processing, the sensor information acquired by the information processing device 100 in steps S2 and S3 is position information measured by a position information sensor.

The information processing device 100 may identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time series change of the acquired position information. For example, the information processing device 100 may compare the time series change of the position information acquired from the user terminal 200A of the user U1 who has not posted the posted information with the time series change of the position information acquired from the user terminal 200B of the user U2 who has posted the posted information, and calculate the similarity to identify the relative positional relationship of the user, and may identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 may also detect the timing at which a characteristic pattern of the time series change of the position information occurs (for example, the fluctuation of the position information when the train approaches a curve), and may identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern occurs in the time series change of the acquired position information, and may identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 delivers content corresponding to the identified vehicle to the user terminal 200. In addition, if the location information is obtained by a GPS (Global Positioning System) sensor, the accuracy of the location information is not high enough to directly identify the vehicle in which the user is riding from the location information, so the relative positional relationship between users is identified based on the time-series changes in the location information in this way.

This allows the information processing device 100 to identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series changes in the location information. Furthermore, the information processing device 100 can distribute content associated with the vehicle to the user terminal 200. Therefore, it is possible to provide businesses with a variety of content distribution methods.

1-5. Another example 4 of information processing according to the embodiment (magnetic sensor)
The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the magnetic information measured by the magnetic sensor.

This information processing will be explained step by step. First, the information processing device 100 executes the same processing as steps S1 to S3 shown in FIG. 1. The processing from steps S1 to S3 is the same as the processing described above, so the explanation will be omitted. Note that in this information processing, the sensor information acquired by the information processing device 100 in steps S2 and S3 is magnetic information measured by a magnetic sensor.

The information processing device 100 may identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change of the acquired magnetic information. For example, the information processing device 100 may compare the time-series change of the magnetic information acquired from the user terminal 200A of the user U1 who has not posted the posted information with the time-series change of the magnetic information acquired from the user terminal 200B of the user U2 who has posted the posted information, and calculate the similarity to identify the relative positional relationship of the user, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 may also detect the timing at which a characteristic pattern of the time-series change of the magnetic information (for example, fluctuations in the magnetic information when a train passes near a substation) occurs, and identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern occurs in the time-series change of the acquired magnetic information, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 delivers content corresponding to the identified vehicle to the user terminal 200.

This allows the information processing device 100 to identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series changes in the magnetic information. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

1-6. Another example 5 of information processing according to the embodiment (illuminance sensor)
The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user, based on a time-series change in the illuminance information measured by the illuminance sensor.

This information processing will be explained step by step. First, the information processing device 100 executes the same processing as steps S1 to S3 shown in FIG. 1. The processing from steps S1 to S3 is the same as the processing described above, so the explanation will be omitted. Note that in this information processing, the sensor information acquired by the information processing device 100 in steps S2 and S3 is illuminance information measured by an illuminance sensor.

The information processing device 100 may identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the acquired illuminance information. For example, the information processing device 100 may compare the time-series change in illuminance information acquired from the user terminal 200A of the user U1 who has not posted the posted information with the time-series change in illuminance information acquired from the user terminal 200B of the user U2 who has posted the posted information, and calculate the similarity to identify the relative positional relationship of the user, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 may also detect the timing at which a characteristic pattern of the time-series change in the illuminance information occurs (for example, fluctuations in the illuminance information when a train passes through a tunnel), and identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern occurs in the time-series change in the acquired illuminance information, and identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 delivers content corresponding to the identified vehicle to the user terminal 200.

This allows the information processing device 100 to identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series changes in the illuminance information. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

1-7. Another example 6 of information processing according to the embodiment (beacon receiver)
The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the beacon information received by the beacon receiver.

This information processing will be explained step by step. First, the information processing device 100 executes the same processing as steps S1 to S3 shown in FIG. 1. The processing from steps S1 to S3 is the same as the processing described above, so the explanation will be omitted. Note that in this information processing, the sensor information acquired by the information processing device 100 in steps S2 and S3 is beacon information received by the beacon receiver.

The information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time series changes in the acquired beacon information. For example, the information processing device 100 may identify the relative positional relationship of the user by comparing the beacon signal reception time included in the beacon information acquired from the user terminal 200A of user U1 who has not posted any posted information with the beacon signal reception time included in the beacon information acquired from the user terminal 200B of user U2 who has posted any posted information, and may identify the vehicle in which the user is riding based on the relative positional relationship. The information processing device 100 delivers content corresponding to the vehicle identified by the user to the user terminal 200.

2. Configuration of Information Processing System
Next, the configuration of the information processing system 1 according to the embodiment will be described with reference to FIG. 2. FIG. 2 is a diagram showing an example of the configuration of the information processing system according to the embodiment. As shown in FIG. 2, the information processing system 1 includes an information processing device 100, a user terminal 200, and a business terminal 300. Note that the information processing system 1 shown in FIG. 2 may include a plurality of information processing devices 100, a plurality of user terminals 200, and a plurality of business terminals 300. The information processing device 100, the user terminal 200, and the business terminal 300 are connected to each other via a predetermined communication network (network N) so as to be communicable by wire or wirelessly.

The information processing device 100 may be, for example, a personal computer (PC), a work station (WS), or a computer with server functions. The information processing device 100 performs processing based on information transmitted from the user terminal 200 and the operator terminal 300 via the network N.

The user terminal 200 is an information processing device used by a user. The user terminal 200 may be, for example, an information processing device such as a smartphone, a tablet terminal, a desktop PC, a notebook PC, a mobile phone, or a PDA (Personal Digital Assistant). In the example shown in FIG. 1, the user terminal 200 is a smartphone.

The operator terminal 300 is an information processing device used by an operator. The operator terminal 300 may be, for example, an information processing device such as a smartphone, a tablet terminal, a desktop PC, a notebook PC, a mobile phone, or a PDA. Note that in the example shown in FIG. 1, the operator terminal 300 is a notebook PC.

3. Configuration of information processing device
Next, the configuration of the information processing device 100 according to the embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration of the information processing device according to the embodiment. As shown in Fig. 3, the information processing device 100 has a communication unit 110, a storage unit 120, and a control unit 130. Although not shown in Fig. 3, the information processing device 100 may have an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100, and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

(Regarding communication unit 110)
The communication unit 110 is realized by, for example, a network interface card (NIC) etc. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information between the user terminal 200 and the operator terminal 300.

(Regarding the storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk, a solid state drive (SSD), an optical disk, etc. As shown in FIG. 3 , the storage unit 120 has a post information storage unit 121, a sensor information storage unit 122, and a content storage unit 123.

(Regarding the posted information storage unit 121)
The posted information storage unit 121 stores information posted by a user using a transfer guide app. Fig. 4 is a diagram illustrating an example of information stored in the posted information storage unit of the information processing device according to the embodiment.

In the example shown in FIG. 4, the post information storage unit 121 stores information related to the following items in association with each other: "User ID," "Departure station ID," "Arrival station ID," "Departure and arrival time," "Line ID," "Train ID," and "Vehicle number."

"User ID" is a character string or number that identifies the user who posted the posted information. "Departure station ID" is a character string or number that identifies the departure station of the train that the poster boarded. "Arrival station ID" is a character string or number that identifies the arrival station of the train that the poster boarded. "Departure/arrival time" is information that indicates the departure and arrival times of the train that the poster boarded. "Route ID" is a character string or number that identifies the route on which the train that the poster boarded operates. "Train ID" is a character string or number that identifies the train that the poster boarded. "Car number" is a number that identifies the car in which the poster boards a train with multiple cars.

In other words, Figure 4 shows that a user identified by user ID "U1" has posted that he or she is riding in a car with the car number indicated by car number "C1" of a train identified by train ID "TR#1" that is running on a route identified by route ID "RT#1" from a departure station identified by departure station ID "ST#1" to an arrival station identified by arrival station ID "ST#2" at the departure and arrival time indicated by arrival time "TM#1".

The posted information storage unit 121 is not limited to information related to the items "User ID", "Departure station ID", "Arrival station ID", "Departure and arrival time", "Line ID", "Train ID", and "Vehicle number", and may store other posted information posted by any user.

(Regarding the sensor information storage unit 122)
The sensor information storage unit 122 stores the sensor information acquired from the user terminal 200. Fig. 5 is a diagram showing an example of information stored in the sensor information storage unit of the information processing device according to the embodiment.

In the example shown in FIG. 5, the sensor information storage unit 122 stores information related to the items "user ID," "user terminal ID," "sensor type," and "sensor information" in association with each other.

"User ID" is a character string or number that identifies a user. "User terminal ID" is a character string or number that identifies a user terminal. "Sensor type" is information that indicates the type of sensor of the sensor unit 250 provided in the user terminal 200, which will be described later. "Sensor information" is data that indicates sensor information acquired from the user terminal 200. Note that the sensor information is time-series data, and the sensor information is stored in association with the time at which the sensor information was measured.

In other words, FIG. 5 shows that the sensor information indicated by the sensor information "SD#1" of the sensor type indicated by the sensor type "ST#1" is acquired from the user terminal indicated by the user terminal ID "200A" owned by the user indicated by the user ID "U1" by the acquisition unit 131 of the information processing device 100 and then stored in the sensor information storage unit 122.

The sensor information storage unit 122 is not limited to information related to the items "user ID," "user terminal ID," "sensor type," and "sensor information," and may store information related to any other sensor.

(Regarding the content storage unit 123)
The content storage unit 123 stores the content received from the operator terminal 300. Fig. 6 is a diagram showing an example of information stored in the content storage unit of the information processing device according to the embodiment.

In the example shown in FIG. 6, the content storage unit 123 stores information related to the items "operator ID," "content ID," "content data," "route ID," "train ID," and "vehicle number" in association with each other.

"Operator ID" is a character string or number that identifies the operator. "Content ID" is a character string or number that identifies the content received from the operator. "Content data" is data of the content that the operator wishes to distribute. "Route ID" is a character string or number that identifies the route on which the train to which the operator wishes to distribute content runs. "Train ID" is a character string or number that identifies the train to which the operator wishes to distribute content. "Car number" is information that indicates the car number of one of the multiple cars of the train to which the operator wishes to distribute content, which has been designated as the distribution destination of the content.

In other words, FIG. 6 shows that the content data indicated by the content data "CD#1" has been submitted as content identified by the content ID "CT#1" by the operator indicated by the operator ID "M1", specifying the vehicle with the vehicle number indicated by the vehicle number "C1" of the train indicated by the train ID "TR#1" that runs on the line indicated by the line ID "RT#1", and then stored in the content storage unit 123.

The content storage unit 123 is not limited to information related to the items "operator ID," "content ID," "content data," "route ID," "train ID," and "vehicle number," and may store information related to any other content.

(Regarding the control unit 130)
Next, returning to Fig. 3, the control unit 130 will be described. The control unit 130 is realized by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like executing various programs stored in the storage device of the information processing device 100 using a RAM as a working area. The control unit 130 may also be realized by an integrated circuit such as an ASIC (Application Specific Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 3, the control unit 130 has an acquisition unit 131, a reception unit 132, a determination unit 133, and a distribution unit 134.

(Regarding the Acquisition Unit 131)
The acquisition unit 131 acquires sensor information measured by the sensor unit 250 from the user terminal 200 equipped with a sensor unit 250 that measures various sensor information. For example, when the sensor unit 250 equipped in the user terminal 200 is an acceleration sensor, the acceleration measured by the acceleration sensor is acquired from the user terminal 200. The acquisition unit 131 stores the sensor information acquired from the user terminal 200 in the sensor information storage unit 122. The acquisition unit 131 may acquire sensor information using geofencing, which acquires sensor information measured by the sensor unit 250 when the user terminal 200 enters a specific area. Geofencing is a method of setting a virtual boundary in a specific area or its periphery using GPS information or Wi-fi (Wireless Fidelity) (registered trademark), and executing a specific action by software when an object enters the boundary. That is, a train may be set as a specific area, and sensor information may be acquired when the user gets on the train.

(Regarding the Reception Unit 132)
The reception unit 132 receives content that the business operator wishes to distribute from the business operator terminal 300. That is, the reception unit 132 receives content submitted by the business operator from the business operator terminal 300 and stores the received content in the content storage unit 123.

The reception unit 132 also receives posted information from the user terminal 200. That is, the reception unit 132 receives posted information posted by a user from the user terminal 200, and stores the received posted information in the posted information storage unit 121.

(Regarding the identification unit 133)
The identifying unit 133 identifies the relative positional relationship of users based on the time-series change of the sensor information acquired by the acquiring unit 131 from the multiple user terminals 200. For example, the identifying unit 133 compares the time-series change of the acquired sensor information to calculate a similarity, and identifies the relative positional relationship of users based on the calculated similarity. The identifying unit 133 may also detect the timing at which a characteristic pattern of the time-series change of the sensor information occurs, and identify the relative positional relationship of users based on the difference in the timing at which the characteristic pattern is detected.

The identification unit 133 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in acceleration measured by the acceleration sensor. For example, the identification unit 133 may compare the time-series change in acceleration acquired from the user terminal 200 of a user who has not posted posted information with the time-series change in acceleration acquired from the user terminal 200 of a user who has posted posted information and calculate the similarity to identify the relative positional relationship and identify the vehicle in which the user is riding based on the relative positional relationship. The identification unit 133 may also detect the timing at which a characteristic pattern of the time-series change in acceleration (for example, a change in acceleration when a train approaches a curve) occurs, identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern was detected, and identify the vehicle in which the user is riding based on the relative positional relationship.

The identification unit 133 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the angular velocity measured by the gyro sensor. For example, the identification unit 133 may compare the time-series change in the angular velocity acquired from the user terminal 200 of the user who has not posted the posted information with the time-series change in the angular velocity acquired from the user terminal 200 of the user who has posted the posted information, and calculate the similarity to identify the relative positional relationship, and identify the vehicle in which the user is riding based on the relative positional relationship. The identification unit 133 may also detect the timing at which a characteristic pattern of the time-series change in the angular velocity (for example, fluctuations in the angular velocity when the train approaches a curve) occurs, identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern was detected, and identify the vehicle in which the user is riding based on the relative positional relationship.

The identification unit 133 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the position information measured by the position information sensor. For example, the identification unit 133 may compare the time-series change in the position information acquired from the user terminal 200 of the user who has not posted the posted information with the time-series change in the position information acquired from the user terminal 200 of the user who has posted the posted information, and calculate the similarity to identify the relative positional relationship, and identify the vehicle in which the user is riding based on the relative positional relationship. The identification unit 133 may also detect the timing at which a characteristic pattern of the time-series change in the position information occurs (for example, a change in the position information when the train approaches a curve), identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern was detected, and identify the vehicle in which the user is riding based on the relative positional relationship.

The identification unit 133 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the magnetic information measured by the magnetic sensor. For example, the identification unit 133 may compare the time-series change in the magnetic information acquired from the user terminal 200 of the user who has not posted the posted information with the time-series change in the magnetic information acquired from the user terminal 200 of the user who has posted the posted information, and calculate the similarity to identify the relative positional relationship, and identify the vehicle in which the user is riding based on the relative positional relationship. The identification unit 133 may also detect the timing at which a characteristic pattern of the time-series change in the magnetic information (for example, fluctuations in the magnetic information when a train passes near a substation) occurs, identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern was detected, and identify the vehicle in which the user is riding based on the relative positional relationship.

The identification unit 133 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the illuminance information measured by the illuminance sensor. For example, the identification unit 133 may compare the time-series change in illuminance information acquired from the user terminal 200 of the user who has not posted the posted information with the time-series change in illuminance information acquired from the user terminal 200 of the user who has posted the posted information, and calculate the similarity to identify the relative positional relationship, and identify the vehicle in which the user is riding based on the relative positional relationship. The identification unit 133 may also detect the timing at which a characteristic pattern of the time-series change in the illuminance information (for example, a change in the illuminance information when a train passes through a tunnel) occurs, identify the relative positional relationship of the user based on the difference in the timing at which the characteristic pattern was detected, and identify the vehicle in which the user is riding based on the relative positional relationship.

The identification unit 133 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time series change of the beacon information received by the beacon receiver. For example, the identification unit 133 may identify the relative positional relationship of the user by comparing the beacon signal reception time included in the beacon information acquired from the user terminal 200A of user U1 who has not posted any posted information with the beacon signal reception time included in the beacon information acquired from the user terminal 200B of user U2 who has posted any posted information, and may identify the vehicle in which the user is riding based on the relative positional relationship.

(Regarding the distribution unit 134)
The distribution unit 134 distributes content according to the identified positional relationship. For example, when the identification unit 133 identifies that the vehicle in which the user U1 is riding is the vehicle C1, the distribution unit 134 reads out content submitted by the business operator in association with the vehicle C1 from the content storage unit 123 and distributes the content to the user terminal 200A of the user U1 via the communication unit 110.

[4. Configuration of user terminal]
Next, the configuration of the user terminal 200 according to the embodiment will be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of the configuration of the user terminal according to the embodiment. As shown in Fig. 7, the user terminal 200 has a communication unit 210, an input unit 220, an output unit 230, a control unit 240, a sensor unit 250, and a storage unit 260.

The communication unit 210 is realized, for example, by a NIC. The communication unit 210 is connected to the network N by wire or wirelessly, and transmits and receives various information to and from the information processing device 100 via the network N.

The input unit 220 receives various types of operation information input from the user. For example, the input unit 220 may receive various types of operations from the user via a display surface (e.g., the output unit 230) using a touch panel. The input unit 220 may also receive various types of operations from buttons provided on the user terminal 200, or a keyboard or mouse connected to the user terminal 200.

The output unit 230 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various information. In other words, when the input unit 220 of the user terminal 200 is a touch panel, the display screen which is the output unit 230 accepts input from the user and also outputs to the user. The output unit 230 is also a speaker, and may output sound from the speaker.

The control unit 240 is realized, for example, by a CPU, an MPU, or the like, executing various programs stored in the user terminal 200 using the RAM as a working area. The control unit 240 may also be realized, for example, by an integrated circuit such as an ASIC or an FPGA.

As shown in FIG. 7, the control unit 240 has a reception unit 241 and a provision unit 242.

The reception unit 241 receives posted information from users. The posted information is information posted by users via the transfer information app, and indicates information about the vehicle the user is riding in. For example, the reception unit 132 receives the "user ID", "departure station ID", "arrival station ID", "departure and arrival time", "line ID", "train ID", and "vehicle number" from users as posted information. Note that for the "user ID", "departure station ID", "arrival station ID", "departure and arrival time", "line ID", and "train ID", if the user inputs the departure station, arrival station, departure time, and arrival time, the transfer information app searches for transfer route candidates and displays them on the output unit 230. Therefore, if the user selects a displayed candidate, the user can post the posted information by inputting only the "vehicle number" into the user terminal 200 without inputting the information into the user terminal 200.

The providing unit 242 provides the content distributed from the information processing device 100 to the user. For example, if the content distributed from the information processing device 100 is a video, the providing unit 242 provides the content to the user by having the output unit 230 output the video. Also, for example, if the content distributed from the information processing device 100 is audio, the providing unit 242 may provide the content to the user by having the output unit 230 output the audio of the content. Also, for example, if the content distributed from the information processing device 100 is text data, the providing unit 242 may provide the content to the user by having the output unit 230 display the text.

The sensor unit 250 is a measuring device that measures various sensor information. The sensor unit 250 may be an acceleration sensor. The acceleration sensor measures the acceleration of the user terminal 200. The acceleration sensor may be, for example, a capacitance-type acceleration sensor that uses a movable electrode and a fixed electrode created by MEMS (Micro Electro Mechanical Systems) and measures acceleration using the relationship between the change in capacitance caused by the movement of the movable power and the acceleration.

The sensor unit 250 may also be a gyro sensor. The gyro sensor measures the angular velocity of the user terminal 200. The gyro sensor generates a primary vibration that vibrates in one direction in the movable electrode, and when rotation is applied to the movable electrode, a secondary vibration occurs due to the Coriolis force acting in a direction 90° from the vibration direction, causing a change in capacitance, and the gyro sensor may be a capacitance-type MEMS gyro sensor that detects this change. The angular velocity can be determined from the change in capacitance and the vibration phase of the movable electrode.

The sensor unit 250 may also be a location information sensor. The location information sensor measures location information of the user terminal 200. The location information sensor may be, for example, a GPS sensor. The GPS sensor includes a receiver that receives radio waves transmitted from a GPS satellite. The GPS sensor receives radio waves transmitted from multiple GPS satellites, and measures the current location (e.g., latitude and longitude) of the user terminal 200 by calculating the distance from the GPS satellite to the user terminal 200 using the difference between the time the radio waves were received and the time the GPS satellite transmitted the radio waves.

The sensor unit 250 may also be a magnetic sensor. The magnetic sensor measures the magnitude and direction of a magnetic field. The magnetic sensor may be a Hall element sensor that uses the Hall effect of a Hall element in which a Lorentz force is applied to a current due to the interaction between a magnetic field and a current, generating an electromotive force. The magnetic sensor may also be a magnetic resistance sensor that configures a Wheatstone bridge using magnetic resistance elements whose electrical resistance value changes depending on the magnitude of the magnetic field.

The sensor unit 250 may also be an illuminance sensor. The illuminance sensor may be a phototransistor, a photodiode, or a photodiode with an amplifier circuit added. A photodiode has a structure in which an electrode is attached to a PN junction semiconductor, and an internal electric field is generated in the depletion layer near the PN junction, so that an output current flows when light hits it. The illuminance is measured by detecting this output current. A phototransistor has a structure in which a photodiode and a transistor are integrated, and the output current of the photodiode is amplified by the transistor before being output. The phototransistor can increase sensitivity because it amplifies the minute current of the photodiode before being output.

The sensor unit 250 may be a beacon receiver. The beacon receiver may be a beacon receiver for a directional beacon transmitter of Wi-Fi (registered trademark) or UWB (Ultra Wide Band). For example, a directional beacon transmitter may be installed on a railroad track, and when a train passes over it, a beacon receiver equipped in the user terminal 200 of a user riding the train may receive beacon information transmitted by the directional beacon transmitter. Note that the beacon information is information transmitted from the directional beacon transmitter, and includes a beacon signal and the time when the beacon signal was received.

The storage unit 260 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk, an SSD, or an optical disk. As shown in FIG. 7, the storage unit 260 has a sensor information storage unit 261. Although not shown, the storage unit 260 also stores a program for the control unit 240 to execute the transfer information app.

The sensor information storage unit 261 stores the sensor information measured by the sensor unit 250. The information stored in the sensor information storage unit 261 stores the "sensor type" and "sensor information" from the information stored in the sensor information storage unit 122 of the information processing device 100. The "sensor type" and "sensor information" stored in the sensor information storage unit 261 are the same as the "sensor type" and "sensor information" stored in the sensor information storage unit 122 of the information processing device 100, so a description thereof will be omitted.

5. Configuration of carrier terminal
Next, the configuration of the operator terminal 300 according to the embodiment will be described with reference to Fig. 8. Fig. 8 is a diagram showing an example of the configuration of the operator terminal according to the embodiment. As shown in Fig. 8, the operator terminal 300 has a communication unit 310, an input unit 320, an output unit 330, and a control unit 340.

The communication unit 310 is realized, for example, by a NIC. The communication unit 310 is connected to the network N by wire or wirelessly, and transmits and receives various information to and from the information processing device 100 via the network N.

The input unit 320 receives various types of operation information from the business operator. For example, the input unit 320 may receive various operations from the business operator from a keyboard or mouse connected to the business operator terminal 300. The input unit 320 may also receive various operations from the business operator via a display surface (e.g., the output unit 330) using a touch panel.

The output unit 330 is a display screen realized by, for example, a liquid crystal display or an organic EL display, and is a display device for displaying various information. When the input unit 320 of the business operator terminal 300 accepts various operations from the business operator via a touch panel, the display screen of the output unit 330 accepts input from the user and also outputs the information to the user.

The control unit 340 is realized, for example, by a CPU, an MPU, or the like, executing various programs stored in the operator terminal 300 using the RAM as a working area. The control unit 340 may also be realized, for example, by an integrated circuit such as an ASIC or an FPGA.

As shown in FIG. 8, the control unit 340 has a reception unit 341.

The reception unit 341 receives content from the operator. The content may be data including text, audio, still images, and moving images related to advertisements posted on the vehicle. For example, the reception unit 341 receives content from the operator in association with the vehicle. That is, the reception unit 341 receives an "operator ID", "content data", a "route ID", a "train ID", and a "vehicle number" from the operator.

[6. Information processing flow]
Next, a procedure of information processing by the information processing device 100 according to the embodiment will be described with reference to FIG. 9. FIG. 9 is a flowchart showing an example of information processing according to the embodiment. For example, the information processing device 100 receives content from the operator terminal 300 (step S101). Then, the information processing device 100 acquires sensor information measured by the sensor unit 250 of the user terminal 200 (step S102). Then, the information processing device 100 identifies the relative positional relationship of the user based on the time-series change in the sensor information (step S103). Then, the information processing device 100 delivers content according to the identified positional relationship (step S104).

7. Hardware Configuration
The information processing device 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in Fig. 10, for example. Fig. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected by a bus 1090.

The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The primary storage device 1040 is a memory device, such as a RAM, that primarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device that stores data used by the arithmetic device 1030 for various calculations and various databases, and is realized by a ROM (Read Only Memory), HDD (Hard Disk Drive), flash memory, etc.

The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and is realized, for example, by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (registered trademark) (High Definition Multimedia Interface). The input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, and scanner, and is realized, for example, by a USB.

The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be an external storage medium such as a USB memory.

The network IF 1080 receives data from other devices via the network N and sends it to the computing device 1030, and also transmits data generated by the computing device 1030 to other devices via the network N.

The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

For example, when the computer 1000 functions as the information processing device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 of the information processing device 100 by executing a program loaded onto the primary storage device 1040.

[8. Composition and Effects]
The information processing device 100 according to the present disclosure includes an acquisition unit 131 that acquires sensor information measured by a sensor unit 250 from a user terminal 200 equipped with a sensor unit 250 that measures various types of sensor information, an identification unit 133 that identifies the relative positional relationship of users based on time-series changes in the sensor information acquired by the acquisition unit 131 from multiple user terminals 200, and a distribution unit 134 that distributes content according to the identified positional relationship.

With this configuration, the information processing device 100 can identify the relative positional relationship of the user and deliver content according to the identified positional relationship to the user terminal 200. Therefore, it is possible to provide businesses with a variety of content delivery methods.

The sensor unit 250 provided in the user terminal 200 is an acceleration sensor, and the identification unit 133 provided in the information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in acceleration measured by the acceleration sensor.

With this configuration, the information processing device 100 can identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in acceleration. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

The sensor unit 250 provided in the user terminal 200 is a gyro sensor, and the identification unit 133 provided in the information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the angular velocity measured by the gyro sensor.

According to this configuration, the information processing device 100 can identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the angular velocity. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

The sensor unit 250 provided in the user terminal 200 is a position information sensor, and the identification unit 133 provided in the information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the positional information measured by the positional information sensor.

According to this configuration, the information processing device 100 can identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the position information. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

The sensor unit 250 provided in the user terminal 200 is a magnetic sensor, and the identification unit 133 provided in the information processing device 100 identifies the vehicle in which the user is riding as the relative position of the user based on the time-series changes in the magnetic information measured by the magnetic sensor.

With this configuration, the information processing device 100 can identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series changes in the magnetic information. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

The sensor unit 250 provided in the user terminal 200 is an illuminance sensor, and the identification unit 133 provided in the information processing device 100 identifies the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the illuminance information measured by the illuminance sensor.

According to this configuration, the information processing device 100 can identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time-series change in the illuminance information. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

The sensor unit 250 provided in the user terminal 200 is a beacon receiver, and the identification unit identifies the vehicle in which the user is riding as the relative position of the user based on the time series changes in the beacon information received by the beacon receiver.

According to this configuration, the information processing device 100 can identify the vehicle in which the user is riding as the relative positional relationship of the user based on the time series data of the beacon information. In addition, the information processing device 100 can deliver content associated with the vehicle to the user terminal 200.

The information processing method according to the present disclosure is an information processing method executed by the information processing device 100, and includes the steps of acquiring information measured by the sensor unit 250 from a user terminal 200 having a sensor unit 250 that measures various information, identifying the relative positional relationship of users based on time-series changes in the sensor information acquired from the multiple user terminals 200, and delivering content according to the identified positional relationship.

With this configuration, it is possible to identify the relative positional relationship of the user and deliver content according to the identified positional relationship to the user terminal 200.

The information processing program according to the present disclosure causes a computer to execute the steps of acquiring information measured by a sensor unit 250 from a user terminal 200 having a sensor unit 250 that measures various types of information, identifying the relative positional relationship of users based on time-series changes in the sensor information acquired from multiple user terminals 200, and delivering content according to the identified positional relationship.

With this configuration, it is possible to identify the relative positional relationship of the user and deliver content according to the identified positional relationship to the user terminal 200.

The above describes the embodiments of the present application in detail with reference to the drawings, but this is merely an example, and the present invention can be implemented in other forms with various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the disclosure section of the invention.

The above-mentioned "section, module, unit" can be read as "means" or "circuit." For example, the acquisition unit 131 can be read as an acquisition means or an acquisition circuit.

REFERENCE SIGNS LIST 100 Information processing device 110 Communication unit 120 Storage unit 121 Posted information storage unit 122 Sensor information storage unit 123 Content storage unit 130 Control unit 131 Acquisition unit 132 Acceptance unit 133 Identification unit 134 Distribution unit 200 User terminal 300 Business operator terminal N Network

Claims (9)

An acquisition unit that acquires sensor information measured by a sensor unit from a user terminal having the sensor unit that measures various types of sensor information;
an identification unit that identifies a relative positional relationship between a user who has not posted the posted information and a user who has posted the posted information by calculating a similarity based on a time series change in sensor information acquired from a user terminal of the user who has posted the posted information and a time series change in sensor information acquired from a user terminal of a user who has not posted the posted information, and identifies a vehicle in which the user who has not posted the posted information is riding as the relative positional relationship between the users based on the relative positional relationship and the vehicle in which the user who posted the posted information is riding that is identified by the posted information;
a distribution unit that reads out from the content storage unit content submitted by a business operator in association with a vehicle in which a user who has not posted posted information as the specified positional relationship is riding, and distributes the content to a user terminal of the user who has not posted posted information ,
the sensor unit is a magnetic sensor or an illuminance sensor,
the identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in magnetic information measured by a magnetic sensor or illuminance information measured by an illuminance sensor.
Information processing device. the sensor unit is an acceleration sensor,
the identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in acceleration measured by an acceleration sensor;
The information processing device according to claim 1 . the sensor unit is a gyro sensor,
the identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in the angular velocity measured by the gyro sensor.
The information processing device according to claim 1 . the sensor unit is a position information sensor,
the identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in the location information measured by a location information sensor.
The information processing device according to claim 1 . the sensor unit is a magnetic sensor,
the identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in the magnetic information measured by the magnetic sensor.
The information processing device according to claim 1 . the sensor unit is an illuminance sensor,
the identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in illuminance information measured by an illuminance sensor.
The information processing device according to claim 1 . the sensor unit is a beacon receiver,
The identification unit identifies a vehicle in which a user who has not posted any posted information is riding, as a relative positional relationship between the users, based on a time-series change in the beacon information received by the beacon receiver.
The information processing device according to claim 1 . An information processing method executed by an information processing device,
A step of acquiring sensor information measured by a sensor unit from a user terminal having a sensor unit that measures various types of sensor information;
a step of calculating a similarity based on time series changes in sensor information acquired from a user terminal of a user who posted the posted information and time series changes in sensor information acquired from a user terminal of a user who did not post the posted information, thereby identifying a relative positional relationship between the user who did not post the posted information and the user who posted the posted information, and identifying a vehicle in which the user who did not post the posted information is riding as the relative positional relationship between the users based on the relative positional relationship and the vehicle in which the user who posted the posted information is riding identified by the posted information;
reading out from the content storage unit content submitted by the business operator in association with a vehicle in which a user who has not posted posted information as the specified positional relationship is riding, and distributing the content to a user terminal of the user who has not posted posted information;
the sensor unit is a magnetic sensor or an illuminance sensor,
In the step of specifying, a vehicle in which a user who has not posted any posted information is riding is specified as a relative positional relationship between the users based on a time-series change in magnetic information measured by a magnetic sensor or illuminance information measured by an illuminance sensor.
Information processing methods. A step of acquiring sensor information measured by a sensor unit from a user terminal having a sensor unit that measures various types of sensor information;
a step of calculating a similarity based on time series changes in sensor information acquired from a user terminal of a user who posted the posted information and time series changes in sensor information acquired from a user terminal of a user who did not post the posted information, thereby identifying a relative positional relationship between the user who did not post the posted information and the user who posted the posted information, and identifying a vehicle in which the user who did not post the posted information is riding as the relative positional relationship between the users based on the relative positional relationship and the vehicle in which the user who posted the posted information is riding identified by the posted information;
reading out from the content storage unit content submitted by the business operator in association with a vehicle in which a user who has not posted posted information as the specified positional relationship is riding, and distributing the content to a user terminal of the user who has not posted posted information;
the sensor unit is a magnetic sensor or an illuminance sensor,
In the step of specifying, a vehicle in which a user who has not posted any posted information is riding is specified as a relative positional relationship between the users based on a time-series change in magnetic information measured by a magnetic sensor or illuminance information measured by an illuminance sensor;
An information processing program that causes a computer to execute the above.

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