JP2018098769A - Information processing method, information processing system and server - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing method, an information processing system and a server capable of efficiently providing a user with video content by extracting the video content corresponding to the user.SOLUTION: The information processing method receives an operation time 10002 showing a time to be taken in regulated operation of an IoT apparatus 1004 and a user ID from the IoT apparatus 1004, extracts user attribute data associated with the user ID received from the Lot apparatus 1004 from one or more user attribute data, extracts video content from a matching table on the basis of priority associated with a first set in the first set matching a purpose of operation included in the extracted user attribute data, adjusts a reproduction time of the extracted video content within the operation time, and distributes the adjusted video content to the IoT apparatus 1004 for performing the regulated operation.SELECTED DRAWING: Figure 14

Description

  The present disclosure relates to an information processing method, an information processing system, and a server that support a user's exercise.

  For example, Patent Document 1 discloses an information processing apparatus that presents an exercise that matches a user's preference to a user who uses a sports facility.

  Moreover, in patent document 2, using the waiting time during access with respect to the user who is operating the multimedia terminal device, it was accessed by the user's hobby, preference, family structure, and multimedia terminal device There has been disclosed a multimedia terminal device that displays a commercial video suitable for personal information such as usage history contents on a display screen.

Japanese Patent Laying-Open No. 2015-188893 JP 2003-67622 A

  However, in the above-described conventional configuration, even if a fitness menu according to the user's preference is provided to a user who does not have an exercise habit, the user actually moves the body and improves the user's exercise consciousness. It is difficult to exercise.

  In addition, even if a fitness menu according to the user's preference is provided to a user who has an exercise habit, the user may not be able to frequently go to a fitness club, and a user who has an exercise habit will be able to attend training video content. Even if acquired, this user does not always exercise while watching the video content of the training. For this reason, exercise habits may not be established for such users. Therefore, it cannot be said that video content can be efficiently provided to the user.

  Therefore, the present disclosure provides an information processing method, an information processing system, and a server that can efficiently provide video content to a user by extracting video content corresponding to the user.

  An information processing method according to an aspect of the present disclosure is an information processing method by a server that is connected to an IoT (Internet of Things) device that performs a specified driving operation by a user and distributes video content stored in a storage device. In the storage device, one or more user IDs that identify the user and the purpose of the exercise performed by the user are associated with user attribute data, the purpose of the exercise, the video content of the exercise, and the video content. A matching table including one or more first sets with the assigned priority order is stored, and the information processing method includes operation time information indicating an operation time required for the specified operation of the IoT device, and a user ID And the user attribute data associated with the user ID received from the IoT device is one or more Of the first set that matches the purpose of the exercise included in the extracted user attribute data, extracted from the user attribute data, based on the priority associated with the first set, The video content is extracted from the matching table, the playback time of the extracted video content is adjusted within the operation time, and the adjusted video content is distributed to the IoT device that performs the specified operation. .

  Note that these comprehensive or specific modes may be realized by a system, an apparatus, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM. Also, any combination of recording media may be realized.

  According to the present disclosure, it is possible to efficiently provide video content to the user by extracting video content corresponding to the user.

FIG. 1 is a diagram illustrating an information processing system according to the first embodiment. FIG. 2 is a block diagram illustrating an example of a cloud server according to the first embodiment. FIG. 3 is a diagram illustrating an example of user attribute data according to the first embodiment. FIG. 4 is a diagram illustrating an example of terminal attribute data of the wearable device according to the first embodiment. FIG. 5A is a diagram illustrating an example of video metadata according to the first embodiment. FIG. 5B is a diagram showing an example of the material video metadata in the first exemplary embodiment. FIG. 6 is a diagram showing an example of the matching table in the first embodiment. FIG. 7 is a diagram showing an example of reproduction history data in the first embodiment. FIG. 8 is a block diagram illustrating an example of the IoT device according to the first embodiment. FIG. 9 is a diagram illustrating an example of motion video content displayed on the display unit of the IoT device according to the first embodiment. FIG. 10 is a diagram illustrating an example of device attribute data according to the first embodiment. FIG. 11 is a block diagram illustrating an example of a video extraction unit according to the first embodiment. FIG. 12 is a diagram illustrating an example of motion video content output to the IoT device according to the first embodiment. FIG. 13 is a diagram illustrating another example of motion video content output to the IoT device according to the first embodiment. FIG. 14 is a flowchart illustrating an example of the information processing system according to the first embodiment. FIG. 15 is a flowchart illustrating an example of video content distribution in the first embodiment. FIG. 16 is a flowchart illustrating an example of processing for extracting “participatory” video content according to the first embodiment. FIG. 17 is a flowchart illustrating an example of processing for extracting “consciousness-type” video content according to the first embodiment. FIG. 18 is a flowchart illustrating an example of video content distribution according to the second embodiment.

  Hereinafter, the knowledge that is the basis of the present disclosure will be described.

  In recent years, methods for presenting a training menu according to the user's preference to the user have been studied. However, even if a fitness menu is provided to users who do not have exercise habits according to the user's preferences, the user can actually move and continuously exercise by improving the user's awareness of exercise. Is difficult.

  Even if a fitness menu according to the user's preference is provided to a user with exercise habits, the user may not be able to frequently go to a fitness club. Even if a user with exercise habits acquires training video content, this user does not always exercise while watching the training video content. For this reason, exercise habits may not be established for such users.

  Furthermore, even if the video content of one training is distributed to the IoT device during the processing time of the IoT (Internet of Things) device used by the user, the user only needs to view the video content of one training. It is difficult to establish exercise habits. This is because, in daily life, allowing the user to look back at the training video repeatedly and allowing the user to move the body even in a short time lead to the establishment of exercise habits. Therefore, it cannot be said that video content can be efficiently provided to the user.

  Up to now, no technical solution for providing training videos has been studied in order to improve awareness of exercise habits while users use IoT devices in daily life such as offices and residences.

  In order to solve the above-described problem, an information processing method according to an aspect of the present disclosure distributes video content stored in a storage device that is connected to an IoT (Internet of Things) device that performs a specified operation by a user operation. In the information processing method by the server, the user attribute data in which one or more user IDs for identifying the user and the purpose of the exercise performed by the user are associated with each other, the purpose of the exercise, and the exercise are stored in the storage device And a matching table including one or more first sets of video content and priority assigned to the video content, and the information processing method calculates an operation time required for the specified operation of the IoT device. The operation time information shown and the user ID are received from the IoT device, and the user ID associated with the user ID received from the IoT device is received. The user attribute data is extracted from the one or more user attribute data, and is linked to the first set among the first sets that match the purpose of the exercise included in the extracted user attribute data Based on the priority order, the video content is extracted from the matching table, the playback time of the extracted video content is adjusted within the operation time, and the adjusted video content is Distribute to the IoT device that is in operation.

  According to this, in the information processing method, at least the highest-priority user attribute data associated with the user ID received from the IoT device is extracted from the storage device. In the information processing method, the playback time of the extracted video content is adjusted within the operation time, and the server delivers the adjusted video content to the IoT device. By outputting the video content received from the server by the IoT device, even a user who does not have exercise habits can recognize the video content via the IoT device that the user uses on a daily basis.

  Therefore, in this information processing method, the video content can be efficiently provided to the user by extracting the video content corresponding to the user.

  In particular, in this information processing method, if the repeated video content is distributed, the video content of the repeated training can be viewed by the user. For this reason, since the video content suitable for the user's preference can be distributed to the IoT device that the user uses on a daily basis, the chance that the user touches the video content of the exercise can be increased.

  In addition, video content that meets the user's preference can be distributed according to the period during which the IoT device used by the user is stipulated, so that the gap time in daily life of the user can be used to improve exercise awareness. Can do.

  An information processing system according to an aspect of the present disclosure is an information processing system including an IoT device that performs a prescribed operation by a user operation, and a server that distributes video content stored in a storage device, In the storage device, one or more user IDs that identify the user and the purpose of the exercise performed by the user are linked to user attribute data, the purpose of the exercise, the video content of the exercise, and the video content. A matching table including one or more first sets of priorities, and the server stores operating time information indicating an operating time required for the specified operation of the IoT device, and a user ID, the IoT A communication unit received from a device and user attribute data associated with the user ID received from the IoT device are extracted from one or more user attribute data The video content based on the priority associated with the first set of the first set that matches the purpose of the exercise included in the extracted user attribute data. A video extraction unit that extracts from the matching table and adjusts the playback time of the extracted video content within the operation time, and the adjusted video content to the IoT device that performs the specified operation A video distribution unit that distributes, and the IoT device includes a display unit that acquires the video content distributed from the server and displays the video content.

  A server according to an aspect of the present disclosure is a server that is connected to an IoT device that performs a specified operation by a user operation and distributes video content stored in a storage device. The storage device includes 1 The first of the user attribute data, the purpose of the exercise, the video content of the exercise, and the priority assigned to the video content, associating the user ID for identifying the user with the purpose of the exercise performed by the user. A matching table including at least one set of the communication information, and the server receives from the IoT device, operation time information indicating an operation time required for the specified operation of the IoT device, and a user ID. A user management unit that extracts user attribute data associated with the user ID received from the IoT device from the one or more user attribute data; Of the first set that matches the purpose of the exercise included in the issued user attribute data, the video content is selected from the matching table based on the priority order associated with the first set. The IoT device that adjusts the playback time of the extracted video content within the operation time, and performs the specified operation on the adjusted video content Delivered to.

  Also in these cases, the same effects as described above are obtained.

  Further, in the information processing method according to an aspect of the present disclosure, the storage device further includes at least one IoT device ID and an installation location of the IoT device that are private to the user or a public location for the user. Device attribute data associated with location information indicating whether or not the device information is stored, and the information processing method extracts device attribute data associated with the IoT device ID from one or more device attribute data. Determining whether the installation location of the IoT device is the private location or the public location, and if the location information of the extracted device attribute data indicates the private location, Participatory video content that the user can exercise at the place is extracted.

  According to this, in the information processing method, when the location information of the extracted device attribute data indicates a private location, participatory video content is extracted. For this reason, the user can exercise at the place where the IoT device is installed in a private place that does not care about the human eye, in accordance with the video content of the exercise output from the IoT device. For this reason, in the information processing method, the exercise habit can be fixed to the user. In this information processing method, video content can be efficiently provided to the user.

  In addition, the information processing method according to an aspect of the present disclosure provides the conscious-type video content that increases consciousness of exercise by viewing the user when the location information of the extracted device attribute data indicates the public location. Extract.

  According to this, in the information processing method, when the location information of the extracted device attribute data indicates a public location, conscious video content is extracted. For this reason, the user can raise exercise consciousness by viewing the video content of the exercise output from the IoT device in a public place where the user is concerned. In this information processing method, video content can be efficiently provided to the user.

  In the information processing method according to an aspect of the present disclosure, the storage device further determines whether or not the storage device has a space where the user can exercise at the installation location of the IoT device ID and the IoT device. Device attribute data associated with the exercise availability information indicated is stored, and the information processing method extracts the device attribute data associated with the IoT device ID from one or more device attribute data, and the IoT device If it is determined based on the exercise availability information that the exercise availability information indicates that the user can exercise at the installation location of the IoT device, the installation of the IoT device is determined. Participatory video content that allows the user to exercise at the place is extracted.

  According to this, in the information processing method, when the exercise availability information indicates that the user can exercise at the installation location of the IoT device, the participation type video content that the user can exercise at the installation location of the IoT device is extracted. . For this reason, in the information processing method, the exercise habit can be fixed to the user. In this information processing method, video content can be efficiently provided to the user.

  In addition, the information processing method according to an aspect of the present disclosure provides an exercise by viewing the user when the exercise availability information of the extracted device attribute data indicates that the user cannot exercise at the installation location of the IoT device. Extract the video content of consciousness type that raises consciousness.

  According to this, in the information processing method, when the exercise availability information indicates that it is impossible for the user to exercise at the location where the IoT device is installed, the conscious video content that enhances the exercise awareness is extracted by viewing the user. For this reason, the user can raise exercise awareness by viewing the video content of exercise output from the IoT device. In this information processing method, video content can be efficiently provided to the user.

  In addition, in the information processing method according to an aspect of the present disclosure, when the video content is distributed to the IoT device, reproduction history data including the user ID, the IoT device ID, and the ID of the distributed video content is stored. The second set of priorities stored in the storage device and associated with the ID of the video content stored in the playback history data is updated to the priorities lowered from the current priorities.

  According to this, in the information processing method, the priority of the second set associated with the video content stored in the reproduction history data is updated to a priority lower than the current priority. For this reason, different video contents can be provided to the same user, that is, it is avoided to continuously deliver video content of the same exercise to the same user, thereby preventing a decrease in user's movement consciousness. it can.

  In addition, the information processing method according to an aspect of the present disclosure further receives physical activity information associated with the user ID and indicating the amount of activity due to exercise performed by the user from the wearable device worn by the user, and stores the memory The device includes the user attribute data in which the user ID and the physical activity information are linked, the matching table including one or more third sets of the physical activity information, the video content, and the priority order; Is stored, and the information processing method is linked to the third set of the third set that matches the purpose of the exercise or the physical activity information included in the user attribute data. The video content is extracted from the matching table based on the priority order.

  According to this, in the information processing method, the video content is extracted from the matching table based on the priority order associated with the third set including the user activity amount measured by the wearable device owned by the user. Extract. For this reason, since the video content of exercise is extracted based on the amount of activity, the video content can be provided to the user more efficiently.

  In addition, in the information processing method according to an aspect of the present disclosure, when the extracted video content is distributed to the IoT device, the user ID and the user ID are associated with the user ID and the ID of the reproduced video content from the IoT device. And the received user attribute data is extracted from the one or more user attribute data, and the extracted user attribute data is updated.

  According to this, in the information processing method, the video content that has been distributed is linked to the user attribute data, and the user attribute data is updated. For this reason, the video content of the exercise that the user has watched once can be viewed later. In this information processing method, video content can be efficiently provided to the user.

  Note that each of the embodiments described below shows a specific example of the present disclosure. Numerical values, shapes, components, steps, order of steps, and the like shown in the following embodiments are merely examples, and are not intended to limit the present disclosure. In addition, among the constituent elements in the following embodiments, constituent elements that are not described in the independent claims indicating the highest concept are described as optional constituent elements.

(Embodiment 1)
[Configuration of information processing system]
First, the information processing system 100 in the present embodiment will be described.

  FIG. 1 is a diagram showing an information processing system 100 in the present embodiment.

  The information processing system 100 is a system that supports the exercise of the user 1002, and is a system that can provide video content to the user via an IoT device. The information processing system 100 is a system that includes a cloud server 1001 that is connected to an IoT device 1004 that performs a prescribed operation by an operation of a user 1002 and distributes video content stored in a storage device. The information processing system 100 includes a cloud server 1001, one or more wearable devices 1003, and a device group 1005. For example, when the IoT device 1004 is a printer, the predetermined operation here means an operation such as printing or copying.

  The cloud server 1001 is a virtual server that can communicate with the wearable device 1003 and the IoT device 1004 of the device group 1005 via the Internet. The cloud server 1001 mainly manages huge big data that is difficult to handle with a normal database management tool or the like. The cloud server 1001 is an example of a server.

  Note that the cloud server 1001 is not limited to a virtual server. A computer that physically includes an external storage device such as a CPU (Central Processing Unit), memory, and HDD (Hard Disk Drive) may be used. A personal computer may also be used. Details of the cloud server 1001 will be described later.

  The wearable device 1003 is a device that can be connected to the Internet, and is, for example, a smartphone, a pedometer (registered trademark), a heart rate meter, or the like, measures the activity amount of the user 1002, and stores the measured numerical value. At least one wearable device 1003 is attached to the user 1002. Details of the wearable device 1003 will be described later.

  The IoT device 1004 has a display and is a device that can be connected to the Internet, for example, a device used in daily life, such as an office device or a home appliance. The office equipment is, for example, a multi-function machine for copying and printing, an elevator, and the like. Home appliances are a microwave oven, a television, a refrigerator, etc., for example. Note that the IoT device 1004 here does not include a smartphone or the like.

  The IoT device 1004 transmits device attribute data of the IoT device 1004 to the cloud server 1001. The cloud server 1001 registers the received device attribute data of the IoT device 1004. Details of the IoT device 1004 and device attribute data will be described later.

  The device group 1005 includes, for example, a group that belongs to the same LAN (Local Area Network) and includes one or more IoT devices 1004. The device group 1005 is a group that includes, for example, an IoT device 1004 installed in an office, a store, or a home, and may be of any size. In the present embodiment, the device group 1005 will be described as an office.

  In such an information processing system 100, the user 1002 inputs user attribute data of the user 1002 from a wearable device 1003 including an input unit such as a smartphone, for example. As a result, the wearable device 1003 transmits user attribute data to the cloud server 1001. The wearable device 1003 measures the amount of activity due to exercise performed by the user 1002 and transmits physical activity information indicating the amount of activity to the cloud server 1001 at a predetermined timing. Since the physical activity information is associated with the user ID, it is also associated with the user attribute data. The cloud server 1001 registers user attribute data of the user 1002 received from the wearable device 1003.

  For example, when the user 1002 uses the IoT device 1004, a waiting time of several seconds to several minutes is generated as a time during which the IoT device 1004 is operating. The cloud server 1001 waits for the video content of the exercise according to the user 1002 to the IoT device 1004 being used based on the user attribute data of the user 1002 and the device attribute data of the IoT device 1004 being used. To deliver. The IoT device 1004 displays the received video content of the exercise on the display. The motion picture content here is a motion video such as stretching, strength training, yoga, or a combination of these motions.

  When using the IoT device 1004, the user 1002 first performs user recognition for identifying the user 1002 and then uses the IoT device 1004. The IoT device 1004 transmits the user attribute data of the user 1002 being used and the device attribute data of the IoT device 1004 to the cloud server 1001, and further requests video content of the exercise to be played back.

  The cloud server 1001 extracts video content of exercise based on the user attribute data and the device attribute data received from the IoT device 1004 used by the user 1002, and the IoT that the user 1002 uses the extracted video content. Deliver to the device 1004.

  The IoT device 1004 receives the video content from the cloud server 1001 and displays the motion video content on the display on the IoT device 1004.

[Cloud server configuration]
Next, the configuration of the cloud server 1001 will be described with reference to FIG.

  FIG. 2 is a block diagram illustrating an example of the cloud server 1001 in the present embodiment.

  As shown in FIG. 2, the cloud server 1001 includes a communication unit 201, a video distribution unit 202, a video content storage unit 203, a user management unit 204, a device management unit 205, a video extraction unit 206, a video meta unit. A data storage unit 207, a user attribute storage unit 208, a device attribute storage unit 209, a matching table 210, and a reproduction history storage unit 211 are provided.

  The communication unit 201 receives, from the IoT device 1004, an operation time 10002 indicating the time taken for the prescribed operation of the IoT device 1004 and a user ID. The communication unit 201 is connected to a network and communicates with the IoT device 1004 and the wearable device 1003 via the network. The communication interface of the communication unit 201 is, for example, a wired LAN or a wireless LAN. The operation time 10002 is an example of the operation time indicated by the operation time information.

  The video distribution unit 202 distributes the video content to the IoT device 1004 that performs the prescribed operation via the communication unit 201. The motion picture content is composed of a motion video such as stretching, strength training, and yoga, or a video combining these motions. Note that the video distribution unit 202 may distribute video content to the IoT device 1004 in accordance with a playback instruction from the IoT device 1004.

  The user management unit 204 manages user attribute data, which is information indicating user attributes received from the wearable device 1003 by the communication unit 201. The user management unit 204 extracts user attribute data associated with the user ID received from the IoT device 1004 from one or more user attribute data. The user management unit 204 registers user attribute data in the user attribute storage unit 208.

  Also, the user management unit 204 receives physical activity information associated with the user ID and indicating the amount of activity due to exercise performed by the user 1002 from the wearable device 1003 worn by the user 1002 via the communication unit 201. The user management unit 204 includes, in the user attribute storage unit 208, a matching table 210 that includes one or more third sets of user attribute data in which a user ID and physical activity information are associated, an activity amount, video content, and a priority order. And memorize. Details of the physical activity information indicating the amount of activity will be described later.

  The user attribute storage unit 208 stores user attribute data in which one or more user IDs that specify the user 1002 and the purpose of exercise performed by the user 1002 are linked. The user attribute storage unit 208 is an example of a storage device.

[User attribute data]
Here, the user attribute data will be described.

  FIG. 3 is a diagram showing an example of user attribute data in the present embodiment.

  The user attribute data includes items of user ID, sex, age, wearable device ID, question, answer, and favorite.

  The user ID is an ID that uniquely identifies the user 1002 who uses the IoT device 1004, and indicates the user who owns the wearable device 1003. Note that the wearable device 1003 owned by the user 1002 may be plural. In this case, the wearable device ID includes the ID of the number of wearable devices 1003 held by the user 1002.

  The gender indicates the gender of the user 1002. The age indicates the age of the user 1002. The wearable device ID indicates an ID that uniquely identifies the wearable device 1003 owned by the user 1002. The question indicates one or more question contents such as user's preference and exercise purpose. The answer indicates the content of the answer to the question. Note that the answer content to the question may be changed by the user 1002 using the wearable device 1003. In that case, both the response content and the user ID input from the wearable device 1003 are transmitted to the cloud server 1001, and the user management unit 204 receives them via the communication unit 201. The user management unit 204 updates the received response content with respect to the response content associated with the same user ID among the user attribute data registered in the user attribute storage unit 208 and updates the user attribute storage unit Store in 208.

  For the favorite, when the video content extracted by the cloud server 1001 is distributed to the IoT device 1004, the user management unit 204 associates the user ID and the user ID from the IoT device 1004 with the ID of the reproduced video content. User attribute data including the received user attribute data is received via the communication unit 201. That is, when the user 1002 plays the motion video content on the IoT device 1004 and registers the played motion video content as a favorite, the ID of the motion video content played from the IoT device 1004 is transmitted together with the user ID. Received by the communication unit 201. The user management unit 204 updates the user attribute data in association with the user attribute data from which the video content has been extracted. The user management unit 204 extracts user attribute data that matches the received user attribute data from one or more user attribute data registered in the user attribute storage unit 208. The user management unit 204 updates the user attribute data including the received user ID and the ID of the received motion video content in the favorite of the same user attribute data, that is, stores new user attribute data in the user attribute storage unit 208. .

  For example, in FIG. 3, two pieces of user attribute data are stored in the user attribute storage unit 208. The first user attribute data is that the user ID is “12345”, the gender is “male”, the age is “40”, the wearable device ID is “P011234”, and the question is “1. "Improved, 2. What is the person?" And the answer to this question is "1. Stiff shoulders, 2. Don't mind". Also, “0123450101” is registered as favorite information. The questions “1. Function improvement, 2. What is your eye?” Are “1. What are the symptoms you want to improve?” And “2. Do you care about your eye when exercising?” The contents are omitted.

  The second user attribute data is that the user ID is “33445”, the gender is “female”, the age is “50”, the wearable device ID is “S012345”, and the question is “1. “Improved, 2. What is the first person?”, And the answer to this question is “1. Diet, 2. Care”. Also, no favorite information is registered with “−”. The questions "1. Constitution improvement, 2. What is the person?" Ask "1. What is the purpose of the exercise you do?" And "2. Do you care about the eye when you exercise?" The contents are omitted.

  Next, terminal attribute data of the wearable device 1003 will be described.

  FIG. 4 is a diagram illustrating an example of terminal attribute data of the wearable device 1003 according to the present embodiment.

  As illustrated in FIG. 4, the terminal attribute data of the wearable device 1003 includes items of a user ID, a wearable device ID, a wearable device name, a measurement target, a measurement value, and a measurement date and time. The terminal attribute data of the wearable device 1003 is registered in the user attribute storage unit 208 and is included in the user attribute data.

  The wearable device name indicates the name of the wearable device 1003. The measurement target indicates the amount of activity due to exercise performed by the user 1002 measured by the wearable device 1003. The measured value indicates a measured value of the amount of activity due to exercise performed by the user 1002 measured by the wearable device 1003. The measurement date and time indicates the date and time when the wearable device 1003 measured the measured amount of activity. That is, the physical activity information includes information on each of the measurement target, the measurement value, and the measurement date / time.

  In FIG. 4, two pieces of terminal attribute data of wearable device IDs are registered. The first terminal attribute data of the wearable device ID is that the user ID of the user 1002 is “12345”, the wearable device ID is “P011234”, and the wearable device name is “smartphone”. The amount of activity measured by the wearable device 1003 with the wearable device ID “P011234” is “the number of floors climbed” as the measurement target, “3rd floor” as the measurement value, and “2016/10/26 12” as the measurement date and time. : 0 ".

  The second terminal attribute data of the wearable device ID is that the user ID of the user 1002 is “33445”, the wearable device ID is “S012345”, and the wearable device name is “pedometer”. The amount of activity measured by the wearable device whose wearable device ID is “S012345” is the number of steps to be measured, the measurement value is “4000 steps”, and the measurement date is “2016/10/26 19:00”. Indicates that The activity amount may be updated regularly at a predetermined timing, for example, in units of minutes, seconds, or days, or may be performed at an arbitrary timing.

  Returning to the description of the cloud server 1001 in FIG.

  The device management unit 205 manages the IoT device 1004 connected to the cloud server 1001. For example, when a new IoT device 1004 is introduced into the office, the device management unit 205 registers device attribute data of the introduced new IoT device 1004. That is, the device management unit 205 stores the device attribute data received from the IoT device 1004 by the communication unit 201 in the device attribute storage unit 209.

  The device attribute storage unit 209 indicates one or more IoT device IDs acquired from the IoT device 1004 and a location indicating whether the installation location of the IoT device 1004 is a private location for the user 1002 or a public location for the user 1002 Device attribute data associated with information is stored. The device attribute storage unit 209 is an example of a storage device. Details of the device attribute data will be described later.

  The video content storage unit 203 stores motion video content to be distributed. The video content storage unit 203 is an example of a storage device.

  In the present embodiment, motion video content to be distributed is roughly divided into two. One is “participatory” video content in which the user 1002 exercises while watching the video content of the exercise. The other is video content in which a plurality of exercise videos are listed, and “conscious” video content that the user 1002 confirms the video content later. The “participation-type” video content and the “consciousness-type” video content can be viewed by the user 1002 by viewing the video content of a plurality of exercises to the user 1002 later.

  The “participatory” video content is video content that the user 1002 can exercise at the place where the IoT device 1004 is installed. The “participatory type” video content is, for example, a commentary video showing exercise, a commentary video showing what physical effect is obtained by exercising, and the like.

  “Conscious type” video content is video content that enhances exercise awareness through viewing by the user 1002. “Conscious type” video content is, for example, a commentary video showing exercise, a video showing a trainee exercise for the user 1002 to exercise with the trainee, and the like.

  The video metadata storage unit 207 stores video metadata assigned to each video content. The video metadata storage unit 207 is an example of a storage device. The video metadata includes main video metadata indicating an outline of a video content title and the like, and material video metadata constituting the video content. The video content distributed from the cloud server 1001 to the IoT device 1004 specifies the video content with video metadata, and specifies the video of the material constituting the video content with the material video metadata.

  Next, video metadata will be described.

  FIG. 5A is a diagram illustrating an example of video metadata according to the present embodiment.

  As shown in FIG. 5A, the video metadata includes a main video ID, a type, a title, an exercise effect, a strengthened part, a sex, and an implementation posture.

  The main video ID is an ID that uniquely identifies the video content of the exercise. The type is a type of motion video content. The title is the title of the video content of the exercise. The exercise effect indicates the exercise effect of the motion picture content. The strengthening part indicates a part of the body that is strengthened by the video content of the exercise. The gender indicates which gender of the motion video content is suitable for male, female, male / female. The implementation posture indicates the posture of the user 1002 when performing exercise.

  For example, in the first video metadata, the main video ID is “0001”, the type is “main”, the title is “shoulder rotation”, the exercise effect is “stiff shoulder”, and the strengthening part is “ “Shoulder”, the target gender is both “male and female”, and the posture for performing exercise is “standing”.

  FIG. 5B is a diagram showing an example of the material video metadata in the present embodiment.

  As shown in FIG. 5B, the material video metadata is associated with the main video ID in order to specify the video of the material constituting the video content specified by the video metadata.

  The material video metadata includes a material video ID, a main video ID, a configuration type, and a playback time.

  The material video ID is an ID that uniquely indicates the video of the material. The main video ID is video content specified by the video metadata. The configuration type indicates the video type of the material. The playback time indicates the length of the material video.

  For example, when the cloud server 1001 delivers “participatory” video content whose title is “shoulder” to the IoT device 1004, the video metadata whose main video ID is “0001” is shown in FIG. 5A. Identified. Further, as shown in FIG. 5B, the material video metadata whose main video ID is “0001”, the material video ID is “0001-01”, and the configuration type is “title call”, and the main video ID is “0001”. ”, The material video ID is“ 0001-02 ”and the composition type is“ commentary ”, and the main video ID is“ 0001 ”, the material video ID is“ 0001-03 ”, and the composition type. The material video metadata whose is “1 count” is identified. The 1 count here is, for example, an image of turning the shoulder once when the title is “shoulder turning”.

  In the present embodiment, for example, MPEG-DASH (MOVING PICTURE EXPPERTS GROUP-DYNAMIC ADAPTIVE STREAMING OVER HTTP) is used as a method for seamlessly distributing video content including videos of a plurality of materials as one video content.

  Returning to the description of the matching table 210 in FIG. The matching table 210 associates user attribute data and video metadata with the user 1002 specified by the user attribute data in order to determine the video content of the exercise to be reproduced. The matching table 210 is an example of a storage device.

  FIG. 6 is a diagram illustrating an example of the matching table 210 in the present embodiment.

  As shown in FIG. 6, the matching table 210 includes a matching ID, item 1, item 2, a candidate exercise title, a main video ID, and a score.

  The matching ID is an ID that uniquely identifies the content of matching. Item 1 is an item corresponding to “question” of user attribute data or “measurement target” of terminal attribute data of wearable device ID. Item 2 is an item corresponding to “answer” of user attribute data or “measurement value” of terminal attribute data of wearable device ID. The candidate exercise title is the “title” of the video metadata. The main video ID is the “main video ID” of the video metadata. The score is a score for the content of matching, and is used for extracting video content of exercise to be distributed. For example, the higher the score, the closer to the user's preference.

  For example, when extracting video content based on exercise information, the matching IDs “0001”, “0002”, and “0003” in the matching table 210 have item 1 “function improvement” and item 2 “stiff shoulder”. It is. The matching ID “0001” has the main video ID “0001” and the candidate exercise title “shoulder turn”. For the matching ID “0002”, the main video ID is “0002” and the candidate exercise title is “Bent Over Y”. For the matching ID “0003”, the main video ID is “0003”, and the candidate exercise title is “90/90 stretch”. The score of the matching ID “0001” is “10”, the score of the matching ID “0002” is “8”, and the score of the matching ID “0003” is “7”. When the “question” in the user attribute data is “function improvement” and the “answer” in the user attribute data is “stiff shoulder”, the score “10” is the highest among these three scores. The video content of the exercise to be distributed is the video content with the matching ID “0001”, that is, the video content with the main video ID “0001” and the candidate exercise title “shoulder”. “Function improvement”, “improvement of constitution”, and “part to be strengthened” in the matching table 210 are also examples of the purpose of exercise.

  For example, when extracting video content based on physical activity information, the matching ID “0006” has a main video ID “0004” and a candidate exercise title “Squat”. For the matching ID “0007”, the main video ID is “0004” and the candidate exercise title is “Squat”. The score of the matching ID “0006” is “8”, and the score of the matching ID “0007” is “5”. When the “question” of the user attribute data is “the number of floors climbed” and the “answer” of the user attribute data is “<10”, the score “8” is the highest of these two scores. The motion video content to be distributed is the video content having the matching ID “0006”, that is, the video content having the main video ID “0004” and the candidate motion title “Squat”.

  Note that the matching table 210 may update the score at an arbitrary timing, or may add a new matching ID.

  Thus, the matching table 210 is a table including one or more first sets of the purpose of exercise performed by the user, the video content of the exercise, and the priority assigned to the video content. The purpose of the exercise is to answer the question in FIG. The priority order is an example of the score of FIG.

  Also, the matching ID “0008” in the matching table 210 is that the item 1 is “steps”, the item 2 is “<5000” meaning less than 5000 steps, the main video ID is “0006”, and the candidate exercise title is “pelvic rotation”. It is tied to each of.

  Returning to the description of FIG. The playback history storage unit 211 stores playback history data that is a history of video content being played back by the IoT device 1004 when the cloud server 1001 distributes the video content to the IoT device 1004. The reproduction history storage unit 211 is an example of a storage device.

  Next, the reproduction history data will be described.

  FIG. 7 is a diagram showing an example of reproduction history data in the present embodiment.

  As shown in FIG. 7, the playback history data includes a playback history ID, a date and time, a user ID, an IoT device ID, a type, a main video ID, a material video ID, and a playback time.

  The playback history ID is an ID that uniquely indicates video metadata that identifies the played video content. The date / time indicates the date / time when the cloud server 1001 distributed video content to the IoT device 1004. The user ID indicates the ID of the user 1002 using the IoT device 1004. The IoT device ID indicates the ID of the IoT device 1004 that reproduced the video content. The type indicates whether the type of the video content of the reproduced exercise is “participation type” or “consciousness type”. The main video ID indicates a main video ID of video metadata of video content reproduced by the IoT device 1004. The material video ID indicates the ID of the material video metadata of the video content reproduced by the IoT device 1004. The material video ID stores material video IDs of a plurality of material video metadata separated by commas. The playback time indicates the total playback time of video content played back by the IoT device 1004.

  Specifically, the playback history data with the playback history ID “0123450101” has the date and time “2006-10-29 20:00”, the user ID “12345”, and the IoT device ID “A012345”. The type is “participating type”, the main video ID is “0001”, the material video ID is “0001-01, 0001-02, 0001-03, 0001-03, 0001-03”, The playback time is “30 seconds”.

  The playback history ID is used when the user 1002 performs favorite registration via the input unit of the IoT device 1004 during or after playback of video content.

  The reproduction history data can be confirmed by the wearable device 1003 owned by the user 1002 at an arbitrary timing.

  Returning to the description of FIG. The video extraction unit 206 includes user attribute data stored in the user attribute storage unit 208, device attribute data stored in the device attribute storage unit 209, and playback history data stored in the playback history storage unit 211. And the video metadata stored in the video metadata storage unit 207 and the matching table 210 are referenced to extract video content that matches the user attribute data.

  The video extraction unit 206 also selects video content based on the priority associated with the third set of the third set that matches the purpose of exercise or physical activity information included in the user attribute data. Are extracted from the matching table 210.

  In addition, the video extraction unit 206 creates video content to be distributed to the IoT device 1004 used by the user 1002. Details of the video extraction unit 206 will be described later.

[IoT equipment]
Next, the configuration of the IoT device 1004 will be described.

  FIG. 8 is a block diagram showing an example of the IoT device 1004 in the present embodiment.

  As illustrated in FIG. 8, the IoT device 1004 includes a communication unit 301, a display unit 302, an input unit 305, a control unit 303, a user identification unit 304, and a device attribute storage unit 306.

  In this embodiment, the IoT device 1004 is a device installed in an office, for example, a multifunction device installed at the end of an office office work area or a microwave oven installed in a cafeteria in the office. .

  The communication unit 301 is connected to the network and communicates with the cloud server 1001 via the network. The communication unit 301 is, for example, a wired LAN or wireless LAN communication interface.

  A display unit 302 is a display on which motion video content distributed from the cloud server 1001 is displayed.

  FIG. 9 is a diagram illustrating an example of motion video content displayed on the display unit 302 of the IoT device 1004 according to the present embodiment.

  As shown in FIG. 9, the display unit 302 has an exercise video content 10001, an operation time 10002 indicating a time required for a predetermined operation of the IoT device 1004, and a user 1002 who likes the video content to be played back. A favorite registration button 10003 for executing registration is displayed. In other words, the operation time is the remaining processing time from the present time when the IoT device 1004 is performing the specified operation to the end of the operation, and is an example of the operation time.

  As illustrated in FIG. 8, the input unit 305 receives an input from the user 1002 for operating the IoT device 1004.

  In the present embodiment, when the IoT device 1004 is a multifunction device, the input unit 305 is, for example, a card reader that reads an employee card held by the user 1002. The input unit 305 may be a touch panel of the IoT device 1004.

  The control unit 303 controls the original function of the IoT device 1004 to cause the main body of the IoT device 1004 to perform a predetermined operation. When the user 1002 uses the IoT device 1004, the control unit 303 calculates the operation time of the IoT device 1004 and transmits it as device attribute data to the cloud server 1001 via the communication unit 301.

  In the present embodiment, for example, if the IoT device 1004 is a multifunction device, the control unit 303 controls the copying, printing, scanning, and the like, which are the original operations of the multifunction device, and performs operations such as copying, printing, and scanning. Calculate the required operation time.

  The user identification unit 304 identifies the user 1002 who uses the IoT device 1004 input by the input unit 305. In the present embodiment, for example, when the IoT device 1004 is a multifunction device, information for identifying the user 1002 by the input unit 305 that is a card reader, that is, a user ID is read, and the user identification unit 304 is based on the read user ID. User identification. The user identification unit 304 transmits the user ID to the cloud server 1001 via the communication unit 301.

  In the present embodiment, for example, when the IoT device 1004 is a microwave oven, the user 1002 to be used may be uniquely specified by face recognition or the like using a camera provided in the microwave oven. The user 1002 may be uniquely identified by operating a microwave oven using a smartphone that is a wearable device 1003 owned by.

  Furthermore, when the user 1002 cannot be uniquely specified by the camera provided in the microwave oven, or when the user 1002 cannot be uniquely specified, the gender and age of the user 1002 can be identified by facial recognition or the like using the camera provided in the microwave oven. May be used instead of the user ID.

  The device attribute storage unit 306 is a storage device that stores device attribute data related to the IoT device 1004.

  FIG. 10 is a diagram illustrating an example of device attribute data in the present embodiment.

  As illustrated in FIG. 10, the device attribute data includes an IoT device ID, a name, an installation location, a location, and an operation time.

  The IoT device ID indicates an ID that uniquely identifies the IoT device 1004. The name indicates the name of the device of the IoT device 1004. The installation location indicates an address where the IoT device 1004 is installed and a position in the building. The location indicates whether the location where the IoT device 1004 is set is a public location that is touched by an unspecified number of people or a private location. The operation time indicates a time for executing the function of the IoT device 1004. The operation time is calculated by the control unit 303 when the user 1002 uses the IoT device 1004.

  When the user 1002 uses the IoT device 1004, the operation time calculated by the control unit 303 is added to the device attribute data, and the device attribute data is transmitted to the cloud server 1001.

  For example, an IoT device 1004 with an IoT device ID “A012345” has a name “MFP”, an installation location “Osaka Prefecture XXXX, X Building Y Floor North Area”, and a location “Private”. The operation time is “30” seconds. The definition of whether the place where the IoT device 1004 is installed is “private” or “public” can be freely set.

[Configuration of video extractor]
Next, a detailed configuration of the video extraction unit 206 of the cloud server 1001 will be described with reference to FIG.

  FIG. 11 is a block diagram illustrating an example of the video extraction unit 206 in the present embodiment. FIG. 11 shows a communication unit 201, a reproduction history storage unit 211, a user attribute storage unit 208, a device attribute storage unit 209, a matching table 210, and a video metadata storage unit 207 related to the video extraction unit 206.

  As shown in FIG. 11, the video extraction unit 206 includes a user attribute control unit 402, a device attribute control unit 404, a video metadata matching unit 406, a video scale adjustment unit 401, a playback history control unit 403, and a video. And a metadata acquisition unit 405.

  The user attribute control unit 402 uses the user ID transmitted from the IoT device 1004 to acquire user attribute data that matches the user ID from the user attribute storage unit 208.

  In the present embodiment, for example, as shown in FIG. 3, when the user ID transmitted from the IoT device 1004 is “12345”, the user attribute control unit 402 sets the user ID from “12345” in the user attribute data. As the user attribute data matching "", the gender is "male", the age is "40", the wearable device ID is "P011234", and the question is "1. Function improvement, 2. What is the person?" Yes, user attribute data whose answer is “1. Stiff shoulder, 2. Don't care” and favorite is “0123450101” is acquired from the user attribute storage unit 208.

  As illustrated in FIG. 11, the device attribute control unit 404 acquires device attribute data of the IoT device 1004 used by the user 1002 from the device attribute storage unit 209.

  For example, as illustrated in FIG. 10, the device attribute control unit 404 has an IoT device ID “A012345” in the device attribute data if the IoT device 1004 has an IoT device ID “A012345”. , Device attribute data whose name is “MFP”, installation address is “Osaka Prefecture XXXX, X Building Y Floor North Area”, location is “Private”, and operation time is “30” seconds, Obtained from the device attribute storage unit 209.

  As shown in FIG. 11, the video metadata acquisition unit 405 acquires metadata of a candidate video content from the video metadata storage unit 207. Specifically, the main video ID of the matching ID “0001” is “0001”, the main video ID of the matching ID “0002” is “0002”, and the main video ID of the matching ID “0003” is “0003”. Therefore, the video metadata acquisition unit 405 acquires, from the matching table 210, metadata with main video IDs “0001”, “0002”, and “0003” from the video metadata and the material video metadata.

  The video metadata matching unit 406 extracts video content candidates suitable for the user 1002 from the user attribute data and the matching table 210.

  As shown in FIGS. 3 and 6, for example, when the user ID is “12345”, the question is “1. Function improvement, 2. What is the person?” And the answer is “1. If the matching table 210 is used, the item 1 is “function improvement”, the item 2 is “stiff shoulder”, the matching ID “0001”, the candidate exercise title “shouldering”, and the matching ID “0002” ”And the candidate exercise title“ Bent Over Y ”, the matching ID“ 0003 ”, and the candidate exercise title“ 90/90 stretch ”are extracted as video content candidates suitable for the user 1002. At this time, the score of the matching ID “0001” is “10”, the score of the matching ID “0002” is “8”, and the score of the matching ID “0003” is “7”.

  As shown in FIGS. 10 and 11, the video metadata matching unit 406 refers to the video metadata acquired by the video metadata acquisition unit 405 and extracts video content according to the device attribute data of the IoT device 1004. .

  For example, in the case of a multifunction peripheral whose IoT device ID of the IoT device 1004 is “A012345”, the location of the device attribute data is “private”. In this case, the user 1002 can exercise while watching the video content of the exercise in the vicinity of the multifunction peripheral having the IoT device ID “A012345”. As a result, the cloud server 1001 generates “participatory” video content.

  As shown in FIGS. 6 and 11, the video metadata matching unit 406 has the candidate exercise titles “shoulder rotation”, “bent over Y”, and “90/90 stretch” extracted as video content candidates suitable for the user 1002. The candidate exercise titles “shoulder turn” and “bent over Y” that can be exercised around the multi-function peripheral having the IoT device ID “A012345” are extracted.

  At this time, since the score “10” of the candidate exercise title “shouldering” is higher than the score “8” of the candidate exercise title “Bent over Y”, the video metadata matching unit 406 selects the video content to be distributed as candidates. The exercise title is “Shoulder Rotation”.

  As shown in FIGS. 10 and 11, as another example, if the IoT device 1004 has a microwave oven whose IoT device ID is “R010210”, the device attribute control unit 404 includes the IoT device ID in the device attribute data. Is "R010210", the name is "microwave oven", the installation address is "Osaka Prefecture XXXX, Z ridge X floor cafeteria", the location is "public", and the operation time is "40" seconds Get device attribute data.

  Since the location of the device attribute data is public, the user 1002 cannot exercise while watching the video content of the exercise around the microwave oven whose IoT device ID of the IoT device 1004 is “R010210”. Thereby, “consciousness-type” video content including a plurality of video content is generated.

  As shown in FIGS. 6 and 11, specifically, the video metadata matching unit 406 extracts the candidate exercise titles “shoulder”, “bent over Y”, “betover Y” extracted as video content candidates suitable for the user 1002. Video content is extracted using all of “90/90 stretch”.

  As shown in FIGS. 10 and 11, the video extraction unit 206 adjusts the playback time of the extracted video content within the operation time. More specifically, the video scale adjustment unit 401 of the video extraction unit 206 uses the operation time of the device attribute data to adjust the playback time of the video content extracted from the matching table 210 provided to the user 1002 within the operation time. Then, motion video content to be provided to the IoT device 1004 is created, and the generated video content is distributed to the communication unit 201.

  For example, since the IoT device ID of the IoT device 1004 of the device attribute data is “A012345” and the operation time of the multifunction device is 30 seconds, the video scale adjustment unit 401 displays the video content of the candidate exercise title “shoulder”. , “Participatory” video content with a playback time of 30 seconds or less is generated.

  As described above, the video extraction unit 206 matches the video content based on the score associated with the first set out of the first set that matches the purpose of the exercise included in the extracted user attribute data. Extract from 210.

  As shown in FIGS. 5A, 5B, and 11, the video scale adjustment unit 401 includes the material video metadata of the main video ID “0001” that is the title “shouldering” acquired by the video metadata acquisition unit 405. The video content is generated while calculating the reproduction time of the material video IDs “0001-01”, “0001-02”, and “0001-03”.

  Specifically, the video scale adjustment unit 401, at the beginning of the generated video content, has a material video ID “0001-01” (reproduction time “2”) whose material video metadata configuration type is “title call”. Place. Next, the video scale adjustment unit 401 arranges a material video ID “0001-02” (reproduction time “12”) whose configuration type is “commentary”. Next, the video scale adjustment unit 401 arranges a material video ID “0001-03” (reproduction time “5”) whose configuration type is “1 count”. Since the total playback time so far is “19” and the remaining time for the operation time of 30 seconds is “11”, the video scale adjustment unit 401 further has a material video ID whose configuration type is “1 count”. “0001-03” (reproduction time “5”) is repeatedly arranged twice. The total playback time so far is “29”, which is within the operation time “30”. In this way, the video scale adjustment unit 401 generates video content in the order of the material video metadata of the material video ID.

  Next, the playback time of video content will be described.

  FIG. 12 is a diagram showing an example of motion video content output to the IoT device in the present embodiment. FIG. 12 shows the video content generated by the video scale adjustment unit 401 as described above. In FIG. 12, the material video IDs are in the order of “0001-01”, “0001-02”, “0001-03”, “0001-03”, “0001-03” so that the operation time is 30 seconds. The video content whose playback time is within 29 seconds is shown.

  In this way, the user 1002 can exercise while watching the video content while waiting for the processing of the IoT device 1004.

  FIG. 13 is a diagram illustrating another example of motion video content output to the IoT device 1004 according to the present embodiment. FIG. 13 shows the video content generated by the video scale adjustment unit 401 as described above.

  As another example, as shown in FIGS. 5A, 5B, 7 and 13, the video scale adjustment unit 401 has an IoT device ID “R010210” of the IoT device 1004 in the device attribute data, and the operation of the microwave oven. Since the time is 40 seconds, the video content of the “conscious type” motion that has a playback time within 40 seconds is generated.

  Specifically, the video scale adjustment unit 401 uses all of the candidate exercise titles “shoulder rotation”, “bent over Y”, and “90/90 stretch” extracted by the video metadata matching unit 406 for 40 seconds. Video content of “conscious” movement is generated to match the playback time.

  The video scale adjustment unit 401 has a main video ID “0001” whose candidate exercise title is “shoulder rotation”, a main video ID “0002” whose candidate exercise title is “Bent over Y”, and a candidate exercise title “90/90”. Video content is generated from each material metadata of the main video ID “0003” which is “stretch”.

  Specifically, the material video ID “0001-01” (reproduction time “2”) having the composition type of the material video metadata “title call” is arranged at the beginning of the generated video content. Next, a material video ID “0002-01” with a playback time “2” having a configuration type of the material video metadata of “title call” is arranged. Next, a material video ID “0003-01” with a playback time “2” whose material video metadata configuration type is “title call” is arranged. Since the total playback time is “6” so far, the material video ID “0001-02” of the playback time “12” whose configuration type of the material video metadata is “commentary” is arranged next. Furthermore, a material video ID “0002-02” having a playback time “10” having a material video metadata configuration type “commentary” is arranged, and a playback time “10” having a material video metadata configuration type “commentary”. The material video ID “0003-02” is arranged. Up to this point, the total playback time is “39”, which falls within the operation time “40”. The video scale adjustment unit 401 is arranged in the order of the material video IDs “0001-01”, “0001-02”, “0002-01”, “0002-02”, “0003-01”, “0003-02”. Generate video content.

  The IoT device 1004 receives and reproduces video content generated from the cloud server 1001.

  When the video content is distributed to the IoT device 1004, the playback history control unit 403 provides the main video ID, the material video ID, and the user that are added to the video content created by the video scale adjustment unit 401 and distributed to the IoT device 1004. The reproduction history storage unit 211 stores the reproduction history data including the ID and the IoT device ID. The main video ID and the material video ID are examples of video content IDs. Specifically, when the user 1002 with the user ID “12345” uses a multifunction device with the IoT device ID “A012345”, the playback history control unit 403 has the type “participatory” and the title “shoulder” ”Rotation”, main video ID “0001”, and material video ID “0001-01, 0001-02, 0001-03, 0001-03, 0001-03” to which the movement history is given That the video content has been distributed is linked to the playback history ID “0123450101” and stored in the playback history storage unit 211 as playback history data.

  The video metadata matching unit 406 updates the priority of the second set associated with the main video ID and the material video ID stored in the reproduction history data to a priority lower than the current priority. For example, when the user 1002 with the user ID “12345” uses the multifunction device with the IoT device ID “A012345” for the second time, the video metadata matching unit 406 refers to the reproduction history data and extracts the extracted candidates. It can be seen that “shoulder rotation” of the main video ID “0001” has already been provided. Therefore, the video metadata matching unit 406 subtracts “5” from the score “10” of the main video ID “0001” in the matching table 210. Then, the video score having the highest score is “8” and the candidate exercise title is “Bent Over Y”. Thus, in this information processing system 100, different video contents can be provided to the same user.

[Operation of information processing system]
Next, the operation of the information processing system 100 will be specifically described.

  FIG. 14 is a flowchart illustrating an example of the information processing system 100 according to the present embodiment.

  As illustrated in FIGS. 3 and 14, the user 1002 operates the wearable device 1003 owned by the user 1002 to access the cloud server 1001 and performs user registration with the cloud server 1001. Upon receiving the user registration instruction, the user management unit 204 of the cloud server 1001 assigns the user ID “12345” to the user 1002, for example, and registers it in the user attribute storage unit 208 as user attribute data including the user ID (S1301). Specifically, the user management unit 204 registers “12345” indicating the user ID in the “user ID” of the user attribute data.

  Next, after the user registration is completed, the user 1002 inputs the sex, the age, and the answer to the question in the form of answering the inquiry displayed on the wearable device 1003 owned, and registers these inputs as user attribute data. (S1302). Specifically, “male” and “40” are registered for “gender” and “age” of the user attribute data, respectively, according to the answer of the user 1002. In addition, as an answer to the question, “1. Function improvement” is registered as “1. Stiff shoulder”, and “2.

  In addition, the wearable device 1003 owned by the user 1002 is also registered with the cloud server 1001. Specifically, the wearable device ID “P011234” used by the user 1002 is registered in the cloud server 1001 as the wearable device ID of the user attribute data.

  Although the user attribute data is registered by the user 1002, the present invention is not limited to this. For example, the administrator of the cloud server 1001 may perform proxy registration with the contents applied for by the user 1002.

  Next, the user 1002 registers the device attribute data of the IoT device 1004 in the cloud server 1001 (S1303). The device attribute data is registered in order for the cloud server 1001 to distribute video content to the IoT device 1004 installed in the office or home.

  Specifically, the user 1002 registers the “installation location” of the IoT device 1004 as shown in the device attribute data of FIG. Also, the user 1002 registers whether the installed location is a public location that can be seen by many people or a private location that cannot be seen by people. Further, the user 1002 registers whether or not the user 1002 using the IoT device 1004 can exercise while looking at the display of the IoT device 1004 at a place where the IoT device 1004 is set.

  For example, in the MFP having the IoT device ID “A012345” in FIG. 10, the device attribute is set as the device attribute data having the installation location “Osaka Prefecture XXXX, X Building Y Floor North Area” and the location “Private”. Registered in the storage unit 306.

  The device attribute data registered in the IoT device 1004 is transmitted to the cloud server 1001 and is also recorded in the device attribute storage unit 209.

  Registration of device attribute data may be performed by a wearable device 1003 owned by a trader or user 1002 who installs the IoT device 1004. Moreover, an administrator may implement it.

  Note that the order of the registration of the user ID / registration of user attribute data described in S1301 to S1302 and the registration of the IoT device described in S1303 may be reversed.

  Next, processing when the user 1002 uses the IoT device 1004 will be described.

  The IoT device 1004 authenticates the user 1002 who uses the IoT device 1004 (S1304). Specifically, the user identification unit 304 of the IoT device 1004 identifies the user ID read by the input unit 305 and authenticates the user 1002. For example, the user 1002 has a user ID “12345”. In addition, when the user 1002 using the IoT device 1004 cannot be identified, for example, the gender and age of the user 1002 may be estimated by face recognition using a camera provided in a microwave oven. If the user ID cannot be specified, the user identification unit 304 treats the user ID as “NULL”.

  Next, for example, when the IoT device 1004 is a multifunction peripheral, the control unit 303 calculates an operation time necessary for operations such as copying, printing, and scanning of the IoT device 1004 (S1305), and stores the operation time in the device attribute storage unit 306. Is stored. This operation time is a waiting time while the user 1002 uses the IoT device 1004.

  Next, the IoT device 1004 transmits the identified user ID and device attribute data stored in the device attribute storage unit 306 to the cloud server 1001 (S1306).

  If the IoT device 1004 cannot identify the user ID, it transmits the estimated gender and age and the device attribute data stored in the device attribute storage unit 306 to the cloud server 1001 in addition to the user ID “NULL”.

  Next, the cloud server 1001 extracts the video content of the exercise to be distributed to the user specified by the user ID from the user ID and device attribute data transmitted from the IoT device 1004, and for the IoT device 1004, The extracted motion picture content is distributed (S1307). In this way, the IoT device 1004 acquires the motion picture content from the cloud server 1001. As a result, the IoT device 1004 performs processing different from the specified operation during the gap time during the specified operation. That is, the display unit 302 of the IoT device 1004 displays the video content of this exercise.

  Details of FIG. 14 will be described with reference to FIG.

  FIG. 15 is a flowchart illustrating an example of video content distribution according to the present embodiment.

  As illustrated in FIGS. 3 and 15, the communication unit 201 receives a user ID and device attribute data from the IoT device 1004. The user attribute control unit 402 acquires user attribute data that matches the received user ID from the user attribute storage unit 208 (S1401).

  For example, when extracting video content based on exercise information, if the received user ID is “12345”, the user attribute data is that the user ID is “12345”, the gender is “male”, the age Is “40”, the wearable device ID is “P011234”, the question is “1. Function improvement, 2. What is the person?”, And the answer is “1. Stiff shoulder, 2. Don't mind” The favorite is “0123450101”.

  When the user ID is “33445”, the user attribute data indicates that the gender is “female”, the age is “50”, the wearable device ID is “S012345”, and the question is “1. "What is your eye?", The answer is "1. Diet, 2. Don't care", and the favorite is "-".

  If the received user ID is “NULL”, the user attribute data cannot be acquired, so the received sex and age are used.

  Next, the device attribute control unit 404 confirms that the received device attribute data is registered in the device attribute storage unit 209 of the cloud server 1001. If the registration of the device attribute storage unit 209 is confirmed, the device attribute control unit 404 confirms the “location” of the device attribute data (S1402). That is, the device attribute control unit 404 determines whether the installation location of the IoT device 1004 is a private location or a public location.

  If the location of the device attribute data is “private” (YES in S1402), the process proceeds to S1405. Specifically, when the IoT device ID of the device attribute data is “A012345”, the location in FIG. 10 is “private”.

  If the location of the device attribute data is “public” (NO in S1402), the process proceeds to S1403. Specifically, when the IoT device ID of the device attribute data is “R010210”, the location in FIG. 10 is “public”.

  Next, the user attribute control unit 402 confirms whether or not the user cares about the eye based on the answer to the question “What is the eye?” In the user attribute data (S1403).

  If the answer is “I don't care” (NO in S1403), the process proceeds to S1405. If the answer is “care” (YES in S1403), the process advances to S1406.

  When the IoT device ID of the device attribute data is “R010210”, the location is “public”. When the user ID of the user attribute data is “12345”, the answer “2. What is the person?” Of the question is “2. Don't care”.

  When the received user ID is “NULL”, there is no user attribute data, and for example, it is assumed that the user does not care.

  Next, the device attribute control unit 404 performs a process of extracting content of participatory video that allows the user 1002 to exercise on the spot while viewing the video content of exercise (S1405).

  If the location information of the extracted device attribute data indicates a private location (YES in S1402), in step S1405, participation-type video content that the user 1002 can exercise at the installation location of the IoT device 1004 is extracted. Specifically, in the case of a multifunction peripheral whose IoT device ID of the device attribute data is “A012345”, video content of “participatory” exercise is distributed from the cloud server 1001 to the display unit 302 of the IoT device 1004. .

  On the other hand, when the location information of the extracted device attribute data indicates a public location, the device attribute control unit 404 performs processing for extracting video content of “consciousness” exercise that increases exercise awareness by viewing the user 1002. (S1406).

  In the case of a microwave oven in which the IoT device ID of the device attribute data is “R010210” in FIG. 10, video content of “consciousness” exercise is distributed to the display of the microwave oven.

  That is, from steps S1402, S1403, S1405, and S1406, even if the user 1002 does not care about the eye even in a public place, the video content of “participatory” exercise is distributed to the IoT device 1004. When the user 1002 cares about the eye, the video content of the “conscious” exercise is distributed to the IoT device 1004.

  After step S1405 or step S1406, the video metadata of the extracted motion video content is distributed to the IoT device 1004 via the communication unit 201 (S1407). That is, the device attribute control unit 404 distributes the extracted motion video content to the IoT device 1004 via the communication unit 201.

  The IoT device 1004 acquires the video content stored in the video content storage unit 203 on the cloud server 1001 from the acquired video metadata, and reproduces this video content.

  Next, the playback history control unit 403 records the video metadata constituting the motion video content distributed to the IoT device 1004 in the playback history storage unit 211 together with the user ID and the IoT device ID, thereby playing the playback history data. Is updated (S1408).

  As the playback history data, the main video content is “participatory” exercise content for the IoT device ID “A012345” used by the user ID “12345” at the date “2016-10-29 20:00” in FIG. Video ID “0001” and material video IDs “0001-01, 0001-02, 0001-03, 0001-03, 0001-03” are recorded. As a result, the user 1002 can exercise while watching the video content of the “participatory type” exercise, or can raise awareness by watching the video content of the “conscious type” exercise.

  Next, step S1405 in FIG. 15 will be described with reference to FIG.

  FIG. 16 is a flowchart illustrating an example of processing for extracting video content of “participatory” exercise in the present embodiment.

  As shown in FIG. 16, first, the video metadata matching unit 406 extracts video content candidates suitable for the user 1002 from the user attribute data and the matching table 210. First, the video metadata matching unit 406 specifies a candidate exercise title corresponding to the question and answer of the user attribute data using the matching table 210 based on the pair of the question and answer of the user attribute data, and obtains a score. Extract (S1501).

  Specifically, as shown in FIGS. 3 and 6, the answer to the question “function improvement” of the user attribute data of the user 1002 of the user ID “12345” is “stiff shoulder”, so the video metadata matching unit 406 , Candidate exercise title “shoulder turn” (score “10”) matching the item 1 “function improvement”, item 2 “stiff shoulder” of the matching table 210, candidate exercise title “bent over Y” (score “8”), and The candidate exercise title “90/90 stretch” (score “7”) is extracted, and each main video ID is specified.

  The video metadata matching unit 406 also uses terminal attribute data of the wearable device 1003 owned by another user 1002 to extract video content. When the number of steps measured by the pedometer of the wearable device ID “S012345” owned by the user 1002 of the user ID “33445” is 4000 steps, the video metadata matching unit 406 matches the item 1 “ The number of steps ”, item 2“ <5000 ”, extraction candidate exercise title“ pelvic rotation ”, and score“ 6 ”are extracted, and the main video ID is specified.

  Next, the video metadata matching unit 406 confirms the reproduction history data of the IoT device 1004 (S1502). That is, the video metadata matching unit 406 determines whether there is a matching user ID in the reproduction history data.

  If there is no matching user ID in the reproduction history data stored in the reproduction history storage unit 211 (NO in S1502), the process proceeds to step S1504.

  If there is a matching user ID in the reproduction history data stored in the reproduction history storage unit 211 (YES in S1502), the process proceeds to step S1503.

  Next, the video metadata matching unit 406 updates the score of the main video ID included in the reproduction history data in the extracted candidate exercise title (S1503).

  Specifically, in the case of the user 1002 whose user ID is “12345” in FIGS. 6 and 7, there is reproduction history data that matches this user ID, and the main video ID is “0001”. The matching unit 406 subtracts, for example, “5” from the shoulder rotation score “10” having the main video ID “0001” in the extracted video content, thereby obtaining the score “5” of the extracted video content. To do. Thus, the score of the extracted video content is updated. Then, the score of the candidate exercise title “Bent Over Y” is “8”, the score of the candidate exercise title “90/90 Stretch” is “7”, and the score of the candidate exercise title “Shoulder” is “5”. .

  By updating the score in this way, it is possible to provide video content with different exercises every time the user 1002 uses the same IoT device 1004.

  Next, the video metadata matching unit 406 selects the candidate exercise title with the highest score from the video content of the candidate exercise title with the “implementation status” of the video metadata being “standing”, The motion picture content is narrowed down to one (S1504).

  Specifically, as shown in FIG. 5A and FIG. 6, among the extracted candidate exercise titles “shoulder rotation”, “bent over Y”, and “90/90 stretch”, the “implementation posture” of the video metadata is “ "Standing" and "Bent over Y" which are standing positions are candidates. Of the candidate exercise titles “shoulder turning” and “bent over”, “shoulder turning” has the highest score, so “shoulder turning” is determined as the video content to be distributed. In addition, when a candidate exercise title cannot be narrowed down to one, a preset candidate exercise title may be used as the video content.

  The video metadata acquisition unit 405 refers to the video metadata and acquires material video metadata related to the main video ID from the main video ID of the video content extracted by the video metadata matching unit 406.

  The video metadata acquisition unit 405 acquires material video metadata of the main video ID “0001” of the material video metadata from the main video ID “0001” of the candidate exercise content “shoulder rotation”.

  Next, as shown in FIG. 16, the video scale adjustment unit 401 adjusts the reproduction time “m” of the video content of the exercise to be distributed based on the operation time “L” of the device attribute data. The video scale adjustment unit 401 sets the arrangement of the material video for adjusting the reproduction time in this order of the configuration type of title call, explanation, and 1 count. The video scale adjustment unit 401 sets the reproduction time of the configuration type “title call” to m (S1505).

  Next, the video scale adjustment unit 401 determines whether or not the reproduction time m is less than the operation time L (S1506).

  If m <L (YES at S1506), the process proceeds to step S1507. If m ≧ L (NO at S1506), the process proceeds to step S1511.

  Next, the video scale adjustment unit 401 adds the video of the material whose configuration type is “commentary” to the video content of the motion with the reproduction time m in step S1505 (S1507). That is, the playback time of the video of the material of the configuration type “commentary” is added to the playback time m of the motion video content in step S1505.

  It is determined whether the reproduction time m is less than the operation time L (S1508).

  If m <L (YES in step S1508), the process advances to step S1509. If m ≧ L (NO in step S1508), the process advances to step S1511.

  Next, the video scale adjustment unit 401 adds the video of the material whose configuration type is “1 count” to the video content of the motion with the reproduction time m in step S1507 (S1509). That is, the playback time of the video of the material of the configuration type “1 count” is added to the playback time m of the motion picture content.

  Next, the video scale adjustment unit 401 determines whether or not the playback time m of the motion video content in step S1509 is less than the operation time L (S1510).

  If m <L (YES in step S1510), the video scale adjustment unit 401 further adds a video of the material having the configuration type “1 count” to the video content of the motion with the playback time m in step S1509. However, it is determined whether m <L or not (S1512).

  If the video content of the motion with the playback time m in step S1509 is further added with the video of the material having the configuration type “1 count”, if m <L (YES in S1512), the video scale adjustment unit 401 returns the processing to S1509.

  On the other hand, if a video of the material having the configuration type “1 count” is further added to the video content of the motion with the playback time m in step S1509, if m ≧ L (NO in S1512), the video scale adjustment unit 401 advances the processing to S1511.

  If m ≧ L (NO in S1510), the process proceeds to S1511.

  Next, the video scale adjustment unit 401 creates motion video content with material video metadata having a playback time m equal to or longer than the operation time L (S1511).

  Note that the video scale adjusting unit 401 performs, for example, cutting motion video content that exceeds the operation time L, or deleting the video of the material of the configuration type “1 count” added last in step S1509, Motion video content may be created with material video metadata having a playback time m equal to or longer than the operation time L.

  As shown in FIG. 5B and FIG. 16, specifically, the video scale adjustment unit 401 includes the material video ID “0001−” among the material video metadata of the main video ID “0001” whose title is “shouldering”. The motion picture content is generated while calculating the playback time of “01”, “0001-02”, and “0001-03”. The video scale adjustment unit 401 first arranges the material video metadata of the material of the material video ID “0001-01” (reproduction time “2”) whose composition type is “title call”. Next, the video scale adjustment unit 401 further adds a video of the material with the material video ID “0001-02” (reproduction time “12”) whose configuration type is “commentary”. Next, the video scale adjustment unit 401 further adds a video of the material with the material video ID “0001-03” (reproduction time “5”) whose configuration type is “1 count”. Since the total playback time so far is “19” and the remaining playback time is “11”, the video scale adjustment unit 401 further includes the material video ID “0001-” whose configuration type is “1 count”. The video of the material “03” (reproduction time “5”) is repeatedly added twice. The video content of the exercise has a total playback time of “29” and falls within the operation time of “30”. In this way, the video scale adjustment unit 401 generates video content in the order of the material video metadata of the material video ID.

  FIG. 17 is a flowchart showing an example of processing for extracting video content of “consciousness-type” exercise in the present embodiment. In FIG. 17, steps S1501 to S1503 are the same as the flowchart for extracting the video content of the “participatory type” exercise in FIG.

  As shown in FIGS. 3 and 6, since the answer to the question “functional improvement” of the user attribute data of the user 1002 whose user ID is “12345” is “shoulder”, the video metadata matching unit 406 includes a matching table. 210, candidate exercise title “shoulder turn” (score “10”), candidate exercise title “bent over Y” (score “8”), and candidate exercise that match item 1 “function improvement”, item 2 “stiff shoulder” The title “90/90 stretch” (score “7”) is extracted, and the main video ID is specified.

  The video metadata acquisition unit 405 refers to the video metadata and acquires material video metadata related to the main video ID from the main video ID of the video content extracted by the video metadata matching unit 406.

  The video metadata acquisition unit 405 stores the main material video metadata from the main video IDs “0001”, “0002”, and “0003” of the candidate motion contents “shoulder rotation”, “bent over Y”, and “90/90 stretch”. The material video metadata of the video IDs “0001”, “0002”, and “0003” is acquired. In this way, the processing from step S1501 to step S1503 is performed.

  As shown in FIG. 17, the video scale adjustment unit 401 adjusts the reproduction time “m” of the video content of the exercise to be distributed based on the operation time “L” of the device attribute data. The video scale adjustment unit 401 sets the arrangement of the video of the material for adjusting the reproduction time in this order of the title type and explanation. The video scale adjustment unit 401 sets m as the reproduction time of each “title call” of the candidate exercise titles extracted by the video metadata matching unit 406 (S1604).

  Next, the video scale adjustment unit 401 determines whether or not the reproduction time m is less than the operation time L (S1605).

  If m <L (YES in step S1605), the process proceeds to step S1606. If m ≧ L (NO in step S1605), the process proceeds to step S1607.

  Next, the video scale adjustment unit 401 adds the video of each “explanation” material of the candidate exercise title extracted by the video metadata matching unit 406 to the video content of the exercise with the playback time m in step S1507 ( S1606). That is, the playback time of the video of the material that is the “explanation” of the candidate motion title is added to the playback time m of the motion picture content.

  Next, the video scale adjustment unit 401 generates motion video content using material video metadata whose playback time m is equal to or shorter than the operation time L (S1607).

  As shown in FIG. 7, for example, since the operation time of the microwave oven whose IoT device ID of the IoT device 1004 of the device attribute data is “R010210” is 40 seconds, the video content of the “conscious” exercise in 40 seconds. Is generated.

  As shown in FIG. 6, the video scale adjustment unit 401 includes a main video ID “0001” whose candidate exercise title is “shoulder rotation”, a main video ID “0002” whose candidate exercise title is “bent over Y”, and The video content is generated from the respective material metadata of the main video ID “0003” which is the candidate exercise title “90/90 stretch”.

  As shown in FIG. 5B, specifically, at the beginning of the generated video content, the material video ID “0001-01” (reproduction time “2”) whose composition type of the material video metadata is “title call”. Place video of the material. Next, the video scale adjustment unit 401 further adds a video of the material with the material video ID “0002-01” (reproduction time “2”) whose configuration type of the material video metadata is “title call”. Next, the video scale adjustment unit 401 further adds the video of the material having the material video ID “0003-01” (reproduction time “2”) whose material video metadata has the configuration type “title call”. Since the total playback time so far is “6”, the video of the material with the material video ID “0001-02” (playback time “12”) whose composition type of the material video metadata is “commentary” is further displayed. Append. The video scale adjustment unit 401 further adds a video of the material having the material video ID “0002-02” (reproduction time “10”) whose composition type of the material video metadata is “commentary”. An image of a material having a material image ID “0003-02” (reproduction time “10”) having a configuration type of “commentary” is added. The video content of the exercise has a total playback time of “39” and falls within the operation time of “40”. As described above, the video scale adjustment unit 401 has the material video IDs “0001-01”, “0001-02”, “0002-01”, “0002-02”, “0003-01”, and “0003-02”. Video content is generated in order.

[Function and effect]
Next, the effects of the information processing method, the information processing system, and the cloud server 1001 according to the present embodiment will be described.

  As described above, in the information processing method according to the present embodiment, at least the user attribute data with the highest score associated with the user ID received from the IoT device 1004 is extracted from the storage device. In the information processing method, the playback time of the extracted video content is adjusted within the operation time, and the cloud server 1001 distributes the adjusted video content to the IoT device 1004. By outputting the video content received from the cloud server 1001 by the IoT device 1004, even if the user 1002 has no exercise habits, the user 1002 can recognize the video content via the IoT device 1004 that is routinely used. it can.

  Therefore, in this information processing method, the video content can be efficiently provided to the user 1002 by extracting the video content corresponding to the user 1002.

  In particular, in this information processing method, if video content is distributed repeatedly, the user 1002 can be shown video content for repeated training. For this reason, since the video content suitable for the user 1002 can be distributed to the IoT device 1004 that the user 1002 uses on a daily basis, the opportunity for the user 1002 to touch the motion video content can be increased.

  In addition, since the video content suitable for the user's 1002 preference can be distributed in accordance with the prescribed operation of the IoT device 1004 used by the user 1002, the gap time in the daily life of the user 1002 can be reduced. It can be used for improvement.

  The information processing system and the cloud server 1001 also have the same effects as described above.

  In addition, in the information processing method according to the present embodiment, when the location information of the extracted device attribute data indicates a private location, participatory video content is extracted. For this reason, the user 1002 can exercise at a place where the IoT device 1004 is installed in a private place where the IoT device 1004 is output in a private place where the user does not care. For this reason, in the information processing method, exercise habits can be fixed for the user 1002. In this information processing method, video content can be efficiently provided to the user 1002.

  In the information processing method according to the present embodiment, when the location information of the extracted device attribute data indicates a public location, conscious video content is extracted. For this reason, the user 1002 can raise exercise consciousness by viewing the video content of exercise output from the IoT device 1004 in a public place where attention is paid to the eyes. In this information processing method, video content can be efficiently provided to the user 1002.

  In the information processing method according to the present embodiment, the second set of scores associated with the video content stored in the reproduction history data is updated to a score lower than the current score. For this reason, different video contents can be provided to the same user, that is, it is avoided to continuously deliver video content of the same exercise to the same user 1002, thus preventing a decrease in the exercise awareness of the user 1002. be able to.

  In the information processing method according to the present embodiment, the video content is obtained based on the score associated with the third set including the activity amount of the user 1002 measured by the wearable device 1003 owned by the user 1002. Extract from the matching table 210. For this reason, since motion video content is extracted based on the amount of activity, more effective video content can be provided.

  Further, in the information processing method according to the present embodiment, the video content that has been distributed is linked to the user attribute data, and the user attribute data is updated. For this reason, it is possible to look back on the motion picture content that the user 1002 has watched once. In this information processing method, video content can be efficiently provided to the user 1002.

(Embodiment 2)
An information processing method according to Embodiment 2 will be described.

  The information processing method of this embodiment is different from that of Embodiment 1 in that it is determined whether or not there is a space where the user 1002 can exercise near the place where the IoT device 1004 is installed. For this reason, in the information processing method of Embodiment 2, the same code | symbol as Embodiment 1 is attached | subjected about the structure which is common in the information processing method of Embodiment 1. FIG. Hereinafter, only the configuration different from the first embodiment will be described, and the description of the configuration common to the first embodiment will be omitted.

  The device attribute storage unit 209 stores one or more device attribute data in which an IoT device ID and exercise availability information indicating whether or not there is a space in which the user 1002 can exercise at the installation location of the IoT device 1004 are linked. Is done. The exercise availability information indicates the availability of exercise in FIG.

  In addition to the IoT device ID, name, installation location, location, and operation time, the device attribute data includes the availability of exercise. The availability of exercise indicates whether or not the user 1002 can exercise at the place where the IoT device 1004 is installed.

  The device attribute control unit 404 determines whether there is a space in which the user 1002 can exercise at the installation location of the IoT device ID and the IoT device 1004 based on exercise availability information stored in the device attribute storage unit 209 in advance. Do. Specifically, the device attribute control unit 404 extracts device attribute data associated with the IoT device ID from one or more device attribute data, and determines whether or not exercise is possible at the place where the IoT device 1004 is installed. Is determined based on exercise availability information. When the exercise availability information indicates that the user 1002 can exercise at the installation location of the IoT device 1004, the device attribute control unit 404 extracts participation-type video content that the user 1002 can exercise at the installation location of the IoT device 1004. To do. When the exercise availability information in the extracted device attribute data indicates that the user 1002 cannot exercise at the location where the IoT device 1004 is installed, the device attribute control unit 404 is configured to increase the awareness of exercise by viewing the user 1002. Type video content.

  FIG. 18 is a flowchart illustrating an example of video content distribution according to the present embodiment.

  As illustrated in FIGS. 3 and 18, the communication unit 201 receives a user ID and device attribute data from the IoT device 1004. The user attribute control unit 402 acquires user attribute data that matches the received user ID from the user attribute storage unit 208 (S1401).

  When the received user ID is “12345”, the user attribute data includes the user ID “12345”, the gender “male”, the age “40”, and the wearable device ID “P011234”. Yes, the question is “1. Function improvement, 2. What is the person?”, The answer is “1. Stiff shoulder, 2. Don't care”, and the favorite is “0123450101”. If the received user ID is “NULL”, the user attribute data cannot be acquired, so the received sex and age are used.

  Next, the device attribute control unit 404 confirms that the received device attribute data is registered in the device attribute storage unit 209 of the cloud server 1001. If the registration of the device attribute storage unit 209 is confirmed, the device attribute control unit 404 confirms the “location” of the device attribute data (S1402).

  If the location of the device attribute data is “private” (YES in S1402), the process proceeds to S1404. Specifically, when the IoT device ID of the device attribute data is “A012345”, the location in FIG. 10 is “private”.

  If the location of the device attribute data is “public” (NO in S1402), the process proceeds to S1403. Specifically, when the IoT device ID of the device attribute data is “R010210”, the location in FIG. 10 is “public”.

  Next, the user attribute control unit 402 confirms whether or not the user cares about the eye based on the answer to the question “What is the eye?” In the user attribute data (S1403).

  If the answer is “don't care” (NO in S1403), the process proceeds to S1404. If the answer is “care” (YES in S1403), the process advances to S1406.

  When the IoT device ID of the device attribute data is “R010210”, the location is “public”. When the user ID of the user attribute data is “12345”, the answer “2. What is the person?” Of the question is “2. Don't care”.

  When the received user ID is “NULL”, there is no user attribute data, and for example, it is assumed that the user does not care.

  Next, the device attribute control unit 404 confirms whether or not exercise of the device attribute data is possible based on the exercise availability information (S1404). The device attribute control unit 404 extracts device attribute data associated with the IoT device ID from one or more device attribute data, and determines whether or not there is a space that can be exercised at the installation location of the IoT device 1004. Judgment based on information.

  The device attribute control unit 404, when the device attribute data exercise is “possible” (YES in S1404), the user 1002 can participate in the exercise while watching the exercise video content. The content is extracted (S1405). As an example of the device attribute data, as shown in FIG. 10, the device attribute control unit 404 is a multifunction device whose IoT device ID of the IoT device 1004 is “A012345”. “MFP”, installation address “Osaka Prefecture XXX, X Building Y Floor North Area”, location “Private”, exercise availability “Yes”, and operation time “30” seconds Is obtained from the device attribute storage unit 209. Then, the video content of the “participatory” exercise is displayed from the cloud server 1001 on the display of the multifunction peripheral.

  On the other hand, when the device attribute data 404 indicates that the exercise of the device attribute data is “impossible” (NO in S1404), the device attribute control unit 404 displays an image of “consciousness-type” exercise for improving the exercise awareness of the user 1002. Processing for extracting content is performed (S1406). As an example of the device attribute data, as shown in FIG. 10, the device attribute control unit 404 has the name of the device attribute data as long as it is a microwave oven whose IoT device ID of the IoT device 1004 is “R010210”. "Microwave", installation address is "Osaka Prefecture XXXX, Z Building X Floor Cafeteria", location is "Public", exercise availability is "impossible", operation time is "40" seconds Certain device attribute data is acquired from the device attribute storage unit 209. The video content of the “conscious” exercise is displayed on the display of the microwave oven.

  After step S1405 or step S1406, the video metadata of the extracted motion video content is transmitted to the IoT device 1004 via the communication unit 201 (S1407). That is, the device attribute control unit 404 distributes the extracted motion video content to the IoT device 1004 via the communication unit 201.

  The IoT device 1004 acquires the video content stored in the video content storage unit 203 on the cloud server 1001 from the acquired video metadata, and reproduces this video content.

  Next, the playback history control unit 403 records the video metadata constituting the motion video content distributed to the IoT device 1004 in the playback history storage unit 211 together with the user ID and the IoT device ID, thereby playing the playback history data. Is updated (S1408).

  As the playback history data, the main video content is “participatory” exercise content for the IoT device ID “A012345” used by the user ID “12345” at the date “2016-10-29 20:00” in FIG. Video ID “0001” and material video IDs “0001-01, 0001-02, 0001-03, 0001-03, 0001-03” are recorded.

[Function and effect]
Next, the effect of the information processing method in this Embodiment is demonstrated.

  As described above, in the information processing method according to the present embodiment, when the exercise availability information indicates that the user 1002 can exercise at the installation location of the IoT device 1004, the user 1002 exercises at the installation location of the IoT device 1004. Extract possible participatory video content. For this reason, in the information processing method, exercise habits can be fixed for the user 1002. In this information processing method, video content can be efficiently provided to the user 1002.

  In addition, the information processing method according to the present embodiment is a conscious type that increases the consciousness of exercise by viewing the user 1002 when the exercise availability information indicates that the user 1002 cannot exercise at the installation location of the IoT device 1004. Extract video content. Therefore, the user 1002 can increase exercise awareness by viewing the exercise video content output from the IoT device 1004. In this information processing method, video content can be efficiently provided to the user 1002.

  The other operational effects in the present embodiment also have the same operational effects as in the first embodiment.

(Other variations)
The information processing method, the information processing system, and the server according to the first and second embodiments of the present disclosure have been described above, but the first and second embodiments of the present disclosure are limited to the first and second embodiments described above. is not.

  For example, in the first and second embodiments, in FIG. 15 and FIG. 18, the determination of whether or not the user in step S1403 cares about the eyes may be omitted. That is, in FIG. 15, the process may proceed to S1405 if YES in step S1402, and may proceed to S1406 if NO in step S1402. In FIG. 18, the process may proceed to S1404 if YES in step S1402, and may proceed to S1406 if NO in step S1402. For this reason, step S1403 is not an essential component.

  In the first and second embodiments, the update of the reproduction history data in step S1408 may be omitted in FIGS. For this reason, step S1408 is not an essential component.

  In the first and second embodiments, steps S1402 to S1406 may be omitted in FIG. In this case, video content may be created using the flow of FIG. 16 or FIG. For this reason, steps S1402 to S1406 in FIG. 15 are not essential constituent requirements.

  In the first and second embodiments, the score is updated in steps S1502 and S1503 in FIGS. 16 and 17, but these steps may be omitted and the process may proceed to step S1504 in FIG. In step 17, the process may proceed to step S1604. For this reason, step S1502 and step S1503 of FIG.16 and FIG.17 are not essential requirements.

  In the first and second embodiments, the example in which the user 1002 using the IoT device 1004 is single is shown, but this is not restrictive. For example, when the IoT device 1004 is an elevator, when a plurality of users 1002 use the elevator, motion video content may be distributed to the elevator and displayed on a display installed inside the elevator. At this time, a plurality of users 1002 who use the elevator cannot be identified. In that case, a plurality of users working on the same floor are treated as one group, and as the attribute data of the group, items to be improved in function are set in advance, and the group is specified based on the number of floors specified when the elevator is used, If it is a set item whose function is to be improved, for example, low back pain, video metadata may be extracted based on low back pain.

  In the present embodiment, the processing of the video metadata matching unit has been described for the case where there is one candidate to be matched with item 1 of the matching data, but there may be a plurality of processes. Specifically, when the user attribute data question is “function improvement”, the attribute measurement target of the wearable device is “number of climbs”, and “sex” is received from the IoT device 1004 instead of the user ID The video metadata matching unit 406 extracts a plurality of candidate exercise titles that match “function improvement”, “number of climbs”, and “sex” of item 1 of the matching table 210, and extracts each score.

  In this embodiment, the motion picture content is a motion video such as stretching, strength training, yoga, or a combination of these motions. However, a video for rehabilitation or for preventing aging is used. It may be a video of gymnastics or a video for specific health guidance focusing on built-in obesity.

  The information processing system is not limited to offices, stores, and residences, and may be a fitness club, a rehabilitation facility, a hospital, a medical center, or a sports facility such as a golf course, tennis court, soccer field, or baseball field. . Moreover, the car navigation system mounted in the vehicle may be sufficient.

  In addition, the technology described in the above aspect is, for example, a cloud service such as Iaas (infrastructure as a service), Paas (platform as a service), or Saas (software as a service). It can be realized in a type. However, the types of cloud services in which the technology described in the above aspect is realized are not limited to these.

  In each of the above embodiments, each component may be configured by dedicated hardware or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory. Here, the software that realizes the information processing system of each of the above embodiments is a program as follows.

  That is, this program is an information processing method for a system including an IoT device used by a user on a computer and a server that includes a storage device and distributes video content. The storage device includes at least one user. And a user attribute data that associates the user ID for identifying the user with the purpose of exercise of the user, and a matching table that includes at least one set of the purpose of exercise, the video content of the exercise, and a priority order, and the information is stored. The processing method receives the user ID and the IoT device ID that identifies the IoT device from the IoT device used by the user, and first matches the received user ID from the one or more user attribute data. The user attribute data is extracted, and matches the purpose of the exercise of the first user attribute data from the matching table. The extracts priority high the video content among the outputs of the video contents extracted to the IoT device, to execute the information processing method.

  As described above, the information processing system according to one or more aspects has been described based on the first and second embodiments, but the present disclosure is not limited to the first and second embodiments. Without departing from the gist of the present disclosure, one or a plurality of forms in which various modifications conceived by those skilled in the art have been made in the first and second embodiments and a combination of components in different embodiments are also possible. It may be included within the scope of the embodiments.

  The information processing system and the information processing method according to the present disclosure are useful in an office, a store, a residence, or the like in which an IoT device that a user uses on a daily basis is installed.

DESCRIPTION OF SYMBOLS 100 Information processing system 201 Communication part 202 Image | video delivery part 203 Image | video content memory | storage part (storage device)
204 User management unit 206 Video extraction unit 207 Video metadata storage unit (storage device)
208 User attribute storage unit (storage device)
209, 306 Device attribute storage unit (storage device)
210 Matching table (storage device)
211 Playback history storage unit (storage device)
302 Display unit 1001 Cloud server (server)
1002 User 1003 Wearable device 1004 IoT device 10001 Motion video content 10002 Operation time (driving time)

Claims (10)

An information processing method by a server that is connected to an IoT (Internet of Things) device that performs a prescribed operation by a user's operation and distributes video content stored in a storage device,
In the storage device,
One or more user ID data that associates a user ID that identifies the user with the purpose of the exercise performed by the user;
A matching table including at least one first set of exercise purpose, exercise video content and priority assigned to the video content is stored;
The information processing method is as follows:
Receiving operation time information indicating an operation time required for the specified operation of the IoT device and a user ID from the IoT device;
User attribute data associated with the user ID received from the IoT device is extracted from the one or more user attribute data;
Of the first set that matches the purpose of the exercise included in the extracted user attribute data, the video content is selected from the matching table based on the priority order associated with the first set. Extract and
Adjust the playback time of the extracted video content within the driving time,
An information processing method for delivering the adjusted video content to the IoT device that performs the specified operation. The storage device further includes one or more device attributes in which one or more IoT device IDs and location information indicating whether the installation location of the IoT device is a private location for the user or a public location for the user Data is stored,
The information processing method is as follows:
Device attribute data associated with the IoT device ID is extracted from one or more device attribute data;
It is determined whether the installation location of the IoT device is the private location or the public location, and when the location information of the extracted device attribute data indicates the private location, the installation location of the IoT device The information processing method according to claim 1, wherein participatory video content that the user can exercise is extracted. 3. The information processing method according to claim 2, wherein when the location information of the extracted device attribute data indicates the public location, the conscious-type video content that enhances exercise consciousness by viewing the user is extracted. The storage device further includes device attribute data that associates one or more IoT device IDs with exercise availability information indicating whether or not there is a space where the user can exercise at the installation location of the IoT device. Remembered,
The information processing method is as follows:
Extracting device attribute data associated with the IoT device ID from one or more device attribute data,
If it is determined based on the exercise availability information whether the IoT device can be exercised, and if the exercise availability information indicates that the user can exercise at the IoT device installation location, the IoT The information processing method according to any one of claims 1 to 3, wherein the participatory video content that allows a user to exercise at a device installation location is extracted. When the exercise availability information of the extracted device attribute data indicates that it is impossible for the user to exercise at the place where the IoT device is installed, the conscious-type video content that enhances exercise awareness by the user's viewing is extracted. Item 5. The information processing method according to Item 4. Further, when distributing the video content to the IoT device, reproduction history data including the user ID, the IoT device ID, and the ID of the distributed video content is stored in the storage device,
The second set of priorities associated with the ID of the video content stored in the playback history data is updated to the priorities lowered from the current priorities. The information processing method according to item 1. Furthermore, physical activity information indicating the amount of activity due to exercise performed by the user associated with the user ID is received from the wearable device worn by the user,
In the storage device,
The user attribute data associated with the user ID and the physical activity information;
The matching table including one or more third sets of the physical activity information, the video content, and the priority order;
The information processing method is based on the priority associated with the third group among the third group that matches the purpose of the exercise included in the user attribute data or the physical activity information. The information processing method according to any one of claims 1 to 6, wherein the video content is extracted from the matching table. When the extracted video content is distributed to the IoT device, user attribute data including the user ID and the ID of the reproduced video content associated with the user ID is received from the IoT device,
Extracting the received user attribute data from the one or more user attribute data;
The information processing method according to claim 1, wherein the extracted user attribute data is updated. An information processing system including an IoT device that performs a prescribed operation by a user operation, and a server that distributes video content stored in a storage device,
In the storage device, one or more user ID data that associates a user ID that identifies the user with the purpose of exercise performed by the user, and
A matching table including at least one first set of exercise purpose, exercise video content and priority assigned to the video content is stored;
The server
A communication unit that receives an operation time information indicating an operation time required for the specified operation of the IoT device and a user ID from the IoT device;
A user management unit that extracts the user attribute data associated with the user ID received from the IoT device from one or more user attribute data;
Of the first set that matches the purpose of the exercise included in the extracted user attribute data, the video content is selected from the matching table based on the priority order associated with the first set. A video extraction unit that extracts and adjusts the playback time of the extracted video content within the driving time;
A video distribution unit that distributes the adjusted video content to the IoT device that performs the specified operation,
The IoT device includes a display unit that acquires the video content distributed from the server and displays the video content. A server that is connected to an IoT device that performs a prescribed operation by a user operation and distributes video content stored in a storage device,
In the storage device,
One or more user ID data that associates a user ID that identifies the user with the purpose of the exercise performed by the user;
A matching table including at least one first set of exercise purpose, exercise video content and priority assigned to the video content is stored;
The server
A communication unit that receives an operation time information indicating an operation time required for the specified operation of the IoT device and a user ID from the IoT device;
A user management unit that extracts user attribute data associated with the user ID received from the IoT device from the one or more user attribute data;
Of the first set that matches the purpose of the exercise included in the extracted user attribute data, the video content is selected from the matching table based on the priority order associated with the first set. An image extracting unit for extracting,
The video extraction unit
Adjust the playback time of the extracted video content within the driving time,
A server that distributes the adjusted video content to the IoT device that performs the specified operation.

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