Terminal device, information processing method, and information processing program

Abstract

To reduce the processing load of a device in a place where a service is provided to a user.SOLUTION: A terminal device includes a first information acquisition unit, a second information acquisition unit, and an information output unit. The first information acquisition unit acquires, from a device in a place where a service is provided, information on a learning model generated by machine learning that receives user information, as input, which is information on a user using the place and outputs index information which is information on an index value indicating a value of index on a service. The second information acquisition unit acquires index information to be output from the learning model by inputting the user information to the learning model on which the information has been acquired by the first information acquisition unit. The information output unit outputs the index information acquired by the second information acquisition unit to the device in the place.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] This invention relates to a terminal device, an information processing method, and an information processing program. [Background technology]

[0002] Conventionally, service provision devices that provide services to users based on user information are known in places that provide services to users, such as accommodations, restaurants, and sports facilities.

[0003] For example, Patent Document 1 proposes a service provider that uses a learning model, which has learned the relationship between the behavioral history of multiple users who have used the service in the past and the results of using the service included in that behavioral history, to predict how a user will use the service, and then provides the service to the user based on the predicted results. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2018-081584 [Overview of the project] [Problems that the invention aims to solve]

[0005] In the conventional technology described above, a service provider located at a specific location acquires user information from the user's terminal device and inputs this information into a learning model to predict the user's use of the service. However, this conventional technology has the drawback of a heavy processing load on the service provider located at the site.

[0006] This application has been made in view of the above, and aims to provide a terminal device, an information processing method, and an information processing program that can reduce the processing load on equipment at a location where a service is provided to a user. [Means for solving the problem]

[0007] The terminal device according to the present invention comprises a first information acquisition unit, a second information acquisition unit, and an information output unit. The first information acquisition unit acquires information from the location device that is generated by machine learning, which takes user information, which is information of users who use the location where the service is provided, as input and index information, which is information of index values ​​indicating the values ​​of indicators related to the service, as output. The second information acquisition unit takes user information as input to the learning model from which the information acquired by the first information acquisition unit has been obtained and acquires the index information output from the learning model. The information output unit outputs the index information acquired by the second information acquisition unit to the location device. [Effects of the Invention]

[0008] According to one embodiment, the processing load on the equipment at the location where the service is provided to the user can be reduced. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 shows an example of information processing according to the embodiment. [Figure 2] Figure 2 shows an example of the configuration of an information processing system according to the embodiment. [Figure 3] Figure 3 shows an example of the configuration of a site-installed device according to an embodiment. [Figure 4] Figure 4 shows an example of the configuration of a location control device according to an embodiment. [Figure 5] Figure 5 shows an example of the configuration of a terminal device according to this embodiment. [Figure 6] Figure 6 is a flowchart showing an example of information processing by the processing unit of the on-site installation device according to the embodiment. [Figure 7] Figure 7 is a flowchart showing an example of information processing by the processing unit of the location control device according to this embodiment. [Figure 8] Figure 8 is a flowchart showing an example of information processing by the processing unit of the terminal device according to this embodiment. [Figure 9] FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the functions of each of the location device and the terminal device according to the embodiment. Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments for carrying out the terminal device, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the terminal device, information processing method, and information processing program according to the present application are not limited by this embodiment. Also, the respective embodiments can be appropriately combined within a range that does not cause contradictions in the processing content. Also, in the following embodiments, the same parts are denoted by the same reference numerals, and duplicate explanations are omitted.

[0011] 〔1. Example of Information Processing〕 First, an example of information processing according to the embodiment will be described using FIG. 1. FIG. 1 is a diagram showing an example of information processing according to the embodiment.

[0012] The terminal device 2 shown in FIG. 1 acquires index-related information, which is information regarding the index of the service, from devices at service-providing locations AR1 to AR m m, and outputs index information, which is information of the index value indicating the value of the index regarding the service, based on the acquired index-related information. m is an integer of 2 or more. Hereinafter, the service-providing locations AR1 to AR m will be described as service-providing locations AR1 to AR m and, when indicating each of the plurality of service-providing locations AR1 to AR m without individually distinguishing them, may be described as service-providing location AR.

[0013] The service-providing location AR is, for example, a restaurant, a hotel, a retail store, a sports facility, an entertainment facility, a conference room, a library, a study room, a hospital, an osteopathic clinic, a massage parlour, a beauty salon, a barbershop, etc., but is not limited to these examples. The services provided by the service-providing location AR include the main service that is the main purpose at the service-providing location AR and the supplementary service at the service-providing location AR.

[0014] When the service-providing location AR is a restaurant, the main service is the provision of food and drink, etc., and the supplementary service is the provision of the location environment using facilities such as lighting, air conditioning, chairs, and tables in the store.

[0015] Also, when the service-providing location AR is a hotel, the main service is the provision of accommodation facilities including beds, chairs, desks, bathrooms, lighting fixtures, and air conditioning units, etc., and the supplementary service is, for example, the service of providing food and drink by vending machines, the service of providing conference rooms, etc.

[0016] The service-providing location AR is provided with location-installed devices 1A1 to 1An that are devices for providing services to the user U. n n is, for example, an integer of 2 or more. The location-installed devices 1A1 to 1An n are devices installed at the service-providing location AR and provided to provide services to the user U of the terminal device 2. The services provided at the service-providing location AR using the location-installed devices 1A1 to 1An are the main services described above or the supplementary services described above. In the following, when each of the location-installed devices 1A1 to 1An is shown without being individually distinguished, it may be described as the location-installed device 1A. n n n When the service-providing location AR is a restaurant, the location-installed devices 1A1 to 1An

[0017] are cooking devices and automatic food-dispensing devices for cooking the food and drink provided by the main service, order-receiving devices for the user U to order food and drink, and chairs, tables, lighting devices, air conditioning units, etc. provided by the supplementary service. n

[0018]

[0018] Furthermore, if the service provision location AR is an accommodation facility, then location installation device 1A1~1A n These include accommodation facilities provided as part of the main service (e.g., beds, bathrooms, lighting fixtures, air conditioning, television sets, etc.), vending machines provided as ancillary services, and meeting room facilities (e.g., lighting, air conditioning, chairs, and tables, etc.).

[0019] User U can receive services at the service location AR by visiting the service location AR. When User U visits the service location AR, the terminal device 2 carried by User U communicates with the equipment at the service location AR to send and receive information.

[0020] The location-based device 1A communicates with the terminal device 2 via short-range wireless communication or the like (step S1) and determines the information acquisition mode (step S2). Examples of short-range wireless communication include Bluetooth®, Felica, and ISO / IEC 14443 (MIFARE). Note that communication between the terminal device 2 and the location-based device 1A may be performed via a network such as the Internet or a LAN (Local Area Network) instead of short-range wireless communication. Furthermore, the process in step S2 is performed, for example, when the terminal device 2 is located within a predetermined range from the location-based device 1A, but is not limited to this example.

[0021] The information acquisition mode determined by the location-based device 1A is either the first information acquisition mode or the second information acquisition mode. The first information acquisition mode is an information acquisition mode in which information of the learning model is transmitted to the terminal device 2 as index-related information, and index information obtained by the terminal device 2 using the information of the learning model is acquired from the terminal device 2. The second information acquisition mode is an information acquisition mode in which index type information is transmitted to the terminal device 2 as index-related information, and index information corresponding to the index type information is acquired from the terminal device 2.

[0022] First, let's explain the first information acquisition mode. In the first information acquisition mode, the learning model information transmitted to terminal device 2 as metric-related information is model information that takes user information, which is information about user U, as input and metric information, which is information about metric values ​​that indicate the values ​​of metric indicators related to the service, as output.

[0023] The information about the learning model is, for example, information used to enable terminal device 2 to obtain metric information from user information. This includes, for example, information about a program (including parameters of the learning model) that causes terminal device 2 to execute processing by the learning model, or information that indicates the type and configuration of the learning model, or information about the parameters of the learning model, but is not limited to these examples.

[0024] The user information input into the learning model consists of at least one of the following: user U's attribute information, user U's behavioral history information, and user U's contextual information. User U's attribute information is information that indicates user U's attributes, such as user U's demographic attributes and user U's psychographic attributes.

[0025] User U's behavioral history information is a history of User U's past actions, including User U's past online or offline activities. For example, it includes one or more of the following: User U's past content browsing history, User U's past purchase history of items traded, and User U's past content search history. Content, for example, is web content.

[0026] User U context information is information that indicates the context of User U, and User U context is User U's situation, for example, User U's situation obtained from one or more sensors built into terminal device 2 (User U's position, User U's orientation, User U's movements, User U's body temperature, User U's heart rate, User U's pulse, etc.).

[0027] Service indicators are indicators that define the operation or processing of the location-installed device 1A. For example, if the location-installed device 1A is an electric chair in which the height of the armrests, the angle of the recline, the height of the seat, the softness of the seat, etc., can be electrically adjusted, the service provided by the location-installed device 1A is the use of the electric chair, and the service indicators are, for example, the height of the armrests, the angle of the recline, the height of the seat, the softness of the seat, etc.

[0028] Furthermore, if the on-site installation device 1A is an automatic food distribution device, the service provided by the on-site installation device 1A is the provision of food and beverages, and service indicators include, for example, the types of ingredients included in the food and beverages provided, the quantity of food and beverages, and the temperature of the food and beverages. For example, if the automatic food distribution device is a coffee maker, service indicators include, for example, the type of coffee beans, whether or not milk is included, the quantity of coffee, the amount of milk, and the temperature of the coffee. The automatic food distribution device is an example of an on-site installation device that manufactures the offerings provided to user U.

[0029] Furthermore, if the location-based device 1A is an order-taking device, the service provided by the location-based device 1A is an order-taking service for food and beverages, and indicators related to the service include, for example, the types of food and beverages in the menu provided to user U, the order of food and beverages in the menu, and the manner in which food and beverages are presented in the menu.

[0030] Furthermore, if the location-based device 1A is a music-providing device, the service provided by the location-based device 1A is a music-providing service, and indicators related to the service include, for example, the type of music provided, the volume of the music, and the sound quality of the music. The type of music is defined, for example, by the genre of music, the singer, the composer, the lyricist, etc.

[0031] The learning models described above are generated by machine learning using neural networks, such as convolutional neural networks. However, the examples are not limited to these; the learning models may also be generated using machine learning algorithms other than neural networks, such as linear regression, nonlinear regression, logistic regression, or support vector machines.

[0032] The metric information output from the learning model described above is, for example, information about metric values, which are values ​​of service-related metrics. If the service-related metric is the height of the armrest of an electric chair, the value of the service-related metric is the value indicating the height of the armrest of the electric chair. If the service-related metric is the type of coffee bean, the value of the service-related metric is the value indicating the type of coffee bean. If the service-related metric is the sound quality of music, the value of the service-related metric is the value indicating the sound quality of music.

[0033] The learning model can output metric information suitable for user U based on user information, and the on-site device 1A can provide services suitable for user U based on the metric information output from the learning model into which user information has been input.

[0034] The learning model is generated using training data that includes, for example, metric values ​​and user U information. For example, the learning model is generated using training data that includes metric values ​​set by user U as label data and also includes user U's attribute information.

[0035] Furthermore, the learning model is generated using training data that includes, for example, the values ​​of metrics set by user U as label data, and also includes information about user U before the metric values ​​were set (e.g., user UA's behavioral history information and user U's contextual information). The information about user U before the metric values ​​were set is, for example, information about user U from the time the metric values ​​were set by user U up to a predetermined period prior to that time. Note that the method of generating the learning model is not limited to the example described above.

[0036] Next, the second information acquisition mode will be described. As described above, the second information acquisition mode is an information acquisition mode in which indicator type information is transmitted to terminal device 2 as indicator-related information, and indicator information corresponding to the indicator type information is acquired from terminal device 2. The indicator information output from terminal device 2 in the second information acquisition mode is the same as the indicator information output from terminal device 2 in the first information acquisition mode.

[0037] The indicator type information transmitted to terminal device 2 includes information indicating the indicator type, which is the type of indicator related to the service provided by location-installed device 1A. For example, if location-installed device 1A is the electric chair described above, the indicator types may be, for example, the height of the armrests, the angle of the recline, the height of the seat, the softness of the seat, etc.

[0038] Furthermore, if the location-installed device 1A is an automatic food serving device, the indicator types are, for example, the type of coffee beans, whether or not milk is present, the amount of coffee, the amount of milk, and the temperature of the coffee. Also, if the location-installed device 1A is a music providing device, the indicator types are, for example, the type of music provided, the volume of the music, and the sound quality of the music.

[0039] Furthermore, the indicator type information may also include calculation information, which is information used to calculate the indicator value, which is the value of an indicator related to the service provided by the location-installed device 1A. The calculation information may include, for example, information on the formula for calculating the indicator value or information on the learning model. Such learning model information is, for example, the same as the learning model information in the first information acquisition mode.

[0040] In step S1, the location-based device 1A determines an information acquisition mode corresponding to the terminal device 2 based on terminal information output from the terminal device 2. The terminal information is, for example, information indicating the information acquisition modes that the terminal device 2 can support.

[0041] For example, if terminal information indicates that the location-installed device 1A is a terminal device 2 that can only support the first information acquisition mode, the first information acquisition mode is determined as the information acquisition mode. If terminal information indicates that the terminal device 2 can only support the second information acquisition mode, the second information acquisition mode is determined as the information acquisition mode.

[0042] Furthermore, if the terminal information indicates that the location-installed device 1A is a terminal device 2 that can support either the first information acquisition mode or the second information acquisition mode, the device will determine a predetermined information acquisition mode from among the first and second information acquisition modes.

[0043] Next, the location-based device 1A provides indicator-related information corresponding to the information acquisition mode determined in step S2 (step S3). In the process of step S3, the location-based device 1A transmits information about the learning model or indicator type information related to the service provided by the location-based device 1A to the terminal device 2 as indicator-related information.

[0044] For example, if the information acquisition mode determined in step S2 is the first information acquisition mode, the location-based device 1A transmits the learning model information to the terminal device 2 as index-related information, and if the information acquisition mode determined in step S2 is the second information acquisition mode, it transmits the index type information to the terminal device 2 as index-related information.

[0045] If there are multiple types of indicators related to the services provided by the on-site device 1A, the learning model information provided by the on-site device 1A is learning model information for each type. This learning model information for each type includes information on a learning model that takes user information as input and outputs information indicating the values ​​of various service-related indicators as indicator information.

[0046] Furthermore, if there are multiple types of indicators related to the services provided by the on-site installation device 1A, the indicator type information provided by the on-site installation device 1A includes multiple types of indicator type information related to the services provided by the on-site installation device 1A.

[0047] Next, terminal device 2 receives indicator-related information, which is information corresponding to the information acquisition mode provided by location-installed device 1A, and transmits indicator information corresponding to the received indicator-related information to location-installed device 1A (step S4).

[0048] For example, if the received metric-related information is information about a learning model, terminal device 2 inputs user information into the learning model indicated by the learning model information and transmits the metric information output from the learning model to location-based device 1A.

[0049] Furthermore, if the received indicator-related information is indicator type information, terminal device 2 calculates an indicator value, which is the value of the indicator of the type indicated by such indicator type information, based on user information. Then, terminal device 2 transmits indicator information, including the calculated indicator value, to location-installed device 1A.

[0050] Next, the location installation device 1A operates based on the indicator information transmitted from the terminal device 2 (step S5). For example, if the location installation device 1A is the electric chair described above, in step S5, the location installation device 1A performs, for example, adjusting the height of the armrests, adjusting the reclining angle, adjusting the height of the seat, adjusting the softness of the seat, etc., based on the indicator information transmitted from the terminal device 2.

[0051] Furthermore, if the location-based device 1A is an automatic food distribution device, the location-based device 1A performs tasks such as selecting ingredients to be included in the food and beverages to be distributed, adjusting the quantity of food and beverages, and adjusting the temperature of food and beverages based on indicator information transmitted from the terminal device 2, and then distributes the food and beverages.

[0052] The AR equipment at the service provision location includes the aforementioned location installation devices 1A1 to 1A. n The terminal device 2 includes a location control device 1B which is a device capable of controlling the location installation devices 1A1 to 1A via the location control device 1B. n It can also be controlled.

[0053] In this case, the location control device 1B communicates with the terminal device 2 and transmits to the terminal device 2 indicator-related information of the location installation device 1A located within a predetermined range from the location of user U, based on the location information indicating the location of user U transmitted from the terminal device 2. The terminal device 2 generates indicator information based on the indicator-related information from the location control device 1B and transmits the generated indicator information to the location control device 1B.

[0054] The location control device 1B transmits indicator information from the terminal device 2 to the location installation device 1A, which is located within a predetermined range from the user U's location. As a result, the location installation device 1A, located within a predetermined range from the user U's location, receives the indicator information from the terminal device 2 via the location control device 1B and operates based on the acquired indicator information.

[0055] In this way, in the first information acquisition mode, terminal device 2 acquires information from the location installation device 1A or location control device 1B about a learning model generated by machine learning, which takes user information, which is information about users who use the location where the service is provided, as input and indicator information, which is information about indicator values ​​that show the values ​​of indicators related to the service, as output. Terminal device 2 then inputs user information into the learning model and outputs the indicator information output from the learning model to the location installation device 1A or location control device 1B. As a result, terminal device 2 can reduce the processing load on the AR device for the service provision location.

[0056] Furthermore, in the second information acquisition mode, terminal device 2 acquires indicator type information indicating the type of indicator related to the service from location installation device 1A or location control device 1B, calculates an indicator value which is the value of the indicator of the type indicated by such indicator type information, and outputs indicator information which is the calculated indicator value to location installation device 1A or location control device 1B. This also allows terminal device 2 to reduce the processing load on the device of the service provision location AR.

[0057] The configuration of the information processing system, including the terminal device 2, location installation device 1A, and location control device 1B that perform such processing, will be described in detail below.

[0058] [2. Configuration of the Information Processing System] Figure 2 is a diagram showing an example of the configuration of an information processing system according to an embodiment. As shown in Figure 2, the information processing system 100 according to the embodiment includes a plurality of location-based devices 1A, a location control device 1B, and a plurality of terminal devices 2. The plurality of location-based devices 1A and location control device 1B are provided for each service provision location AR. In the following, when location-based devices 1A and location control device 1B are not individually distinguished, they may be referred to as location device 1. Note that the location control device 1B may be provided, for example, outside the service provision location AR.

[0059] Each of the multiple location devices 1 and each of the multiple terminal devices 2 can communicate with each other by short-range wireless communication. Examples of short-range wireless communication include Bluetooth, Felica, ISO / IEC 14443, etc.

[0060] Furthermore, each of the multiple location devices 1 and each of the multiple terminal devices 2 are connected to each other via a network N, either by wire or wireless, enabling communication. Network N is, for example, a LAN or a WAN (Wide Area Network) such as the Internet. WANs include, for example, LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation: 5th Generation Mobile Communication System).

[0061] Each terminal device 2 may be, for example, a desktop PC (Personal Computer), a notebook PC, a tablet device, a smartphone, a mobile phone, or a PDA (Personal Digital Assistant). Each terminal device 2 is operated by user U. Note that each terminal device 2 is not limited to the examples described above; for example, it may be a smartwatch or a wearable device.

[0062] [3. Configuration of the site-installed device 1A] Figure 3 shows an example of the configuration of the location-based device 1A according to the embodiment. As shown in Figure 3, the location-based device 1A according to the embodiment includes a communication unit 10A, a storage unit 11A, and function execution units 121-12 k It comprises a processing unit 13A. k is an integer of 2 or more. In the following, the function execution units 121 to 12 k When referring to each of these components without distinguishing them individually, they may be referred to as the function execution unit 12.

[0063] [3.1. Communications Section 10A] The communication unit 10A is implemented, for example, by a NIC (Network Interface Card). The communication unit 10A transmits and receives information between the location control device 1B and the terminal device 2 via short-range wireless communication.

[0064] The communication unit 10A is connected to the network N by wire or wireless connection and can also send and receive information to and from the location control device 1B and the terminal device 2 via the network N.

[0065] [3.2. Storage section 11A] The memory unit 11A is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or by storage devices such as hard disks and optical discs.

[0066] The memory unit 11A stores, for example, the learning model information and metric type information described above for each metric. The learning model information is model information that takes user information, which is information about the user U, as input and metric information, which is information about metric values ​​that indicate the values ​​of metrics related to the service, as output.

[0067] The user information input into the learning model consists of at least one of the following: user U's attribute information, user U's behavioral history information, and user U's contextual information. User U's attribute information is information that indicates user U's attributes, such as user U's demographic attributes and user U's psychographic attributes.

[0068] User U's behavioral history information is a history of User U's past actions, including User U's past online or offline activities. For example, it includes one or more of the following: User U's past content browsing history, User U's past purchase history of items traded, and User U's past content search history. Content, for example, is web content.

[0069] User U context information is information that indicates the context of User U, and User U context is User U's situation, for example, User U's situation obtained from one or more sensors built into terminal device 2 (User U's position, User U's orientation, User U's movements, User U's body temperature, User U's heart rate, User U's pulse, etc.).

[0070] Service indicators are indicators that define the operation or processing of the location-installed device 1A. For example, if the location-installed device 1A is an electric chair in which the height of the armrests, the angle of the recline, the height of the seat, the softness of the seat, etc., can be electrically adjusted, the service provided by the location-installed device 1A is the use of the electric chair, and the service indicators are, for example, the height of the armrests, the angle of the recline, the height of the seat, the softness of the seat, etc.

[0071] Furthermore, if the location-based device 1A is an automatic food distribution device, the service provided by the location-based device 1A is the provision of food and beverages, and service indicators include, for example, the types of ingredients included in the food and beverages provided, the quantity of food and beverages, and the temperature of the food and beverages. For example, if the automatic food distribution device is a coffee maker, service indicators include, for example, the type of coffee beans, whether or not milk is included, the quantity of coffee, the amount of milk, and the temperature of the coffee.

[0072] Furthermore, if the location-based device 1A is an order-taking device, the service provided by the location-based device 1A is an order-taking service for food and beverages, and indicators related to the service include, for example, the types of food and beverages in the menu provided to user U, the order of food and beverages in the menu, and the manner in which the menu is presented.

[0073] Furthermore, if the location-based device 1A is a music-providing device, the service provided by the location-based device 1A is a music-providing service, and indicators related to the service include, for example, the type of music provided, the volume of the music, and the sound quality of the music. The type of music is defined, for example, by the genre of music, the singer, the composer, the lyricist, etc.

[0074] The learning models described above are generated by machine learning using neural networks, such as convolutional neural networks. However, the examples are not limited to these; the learning models may also be generated using machine learning algorithms other than neural networks, such as linear regression, nonlinear regression, logistic regression, or support vector machines.

[0075] The metric information output from the learning model described above is, for example, information about metric values, which are values ​​of service-related metrics. If the service-related metric is the height of the armrest of an electric chair, the value of the service-related metric is the value indicating the height of the armrest of the electric chair. If the service-related metric is the type of coffee bean, the value of the service-related metric is the value indicating the type of coffee bean. If the service-related metric is the sound quality of music, the value of the service-related metric is the value indicating the sound quality of music.

[0076] The learning model can output metric information suitable for user U based on user information, and the on-site device 1A can provide services suitable for user U based on the metric information output from the learning model into which user information has been input.

[0077] The learning model is generated using training data that includes, for example, metric values ​​and user U information. For example, the learning model is generated using training data that includes metric values ​​set by user U as label data and also includes user U's attribute information.

[0078] Furthermore, the learning model is generated using training data that includes, for example, the values ​​of metrics set by user U as label data, and also includes information about user U before the metric values ​​were set (e.g., user UA's behavioral history information and user U's contextual information). The information about user U before the metric values ​​were set is, for example, information about user U from the time the metric values ​​were set by user U up to a predetermined period prior to that time. Note that the method of generating the learning model is not limited to the example described above.

[0079] Furthermore, the learning model may be a learning model specific to each user U, or it may be a learning model common to multiple users U. A learning model specific to each user U is generated, for example, using training data specific to each user U that includes metric values ​​and user U information, while a learning model common to multiple users U is generated, for example, using training data specific to each user U that includes metric values ​​and user U information.

[0080] [3.3. Function Execution Unit 12] Each function execution unit 12 performs a corresponding function from among the multiple functions of the location-installed device 1A. For example, if the location-installed device 1A is an electric chair, the function execution unit 12 may be, for example, a drive mechanism for changing the height of the armrests, a drive mechanism for changing the reclining angle, a drive mechanism for changing the height of the seat, or a drive mechanism for changing the softness of the seat.

[0081] Furthermore, if the location-installed device 1A is an automatic food serving device, the function execution unit 12 may include, for example, a selection mechanism for selecting ingredients to be included in the food and beverages to be served, a quantity adjustment mechanism for adjusting the amount of food and beverages, and a temperature adjustment mechanism for adjusting the temperature of the food and beverages.

[0082] Furthermore, if the installation device 1A is a coffee maker, the function execution unit 12 may include, for example, a selection mechanism for selecting the type of coffee beans, a quantity adjustment mechanism for adjusting the amount of coffee, a quantity adjustment mechanism for adjusting the amount of milk, and a temperature adjustment mechanism for adjusting the temperature of the coffee.

[0083] Furthermore, if the location-based device 1A is an order-receiving device, the function execution unit 12 may include, for example, a type-changing unit that changes the types of food and beverages on the menu, an order-changing unit that changes the order of food and beverages on the menu, or a presentation-style-changing unit that changes the way food and beverages are presented on the menu. The presentation style of food and beverages on the menu may include, for example, the size, design, and arrangement of food and beverages on the menu.

[0084] Furthermore, if the location-installed device 1A is a music-providing device, the function execution unit 12 may include, for example, a type determination unit that determines the type of music to be provided, a volume determination unit that determines the volume of the music, and a sound quality determination unit that determines the sound quality of the music. The type of music may be defined by, for example, the genre of music, the singer, the composer, the lyricist, etc.

[0085] [3.4. Processing Unit 13A] The processing unit 13A is a controller, which is realized by executing various programs stored in the memory device inside the on-site device 1A using RAM as the working area, for example, by a CPU (Central Processing Unit) or MPU (Micro Processing Unit).

[0086] The processing unit 13A may be partially or entirely implemented by an integrated circuit, such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The processing unit 13A comprises an information acquisition unit 14A, a determination unit 15A, a function control unit 16, and an information output unit 17A.

[0087] [3.4.1. Information Acquisition Unit 14A] The information acquisition unit 14A acquires information from an external device. For example, the information acquisition unit 14A acquires indicator information transmitted from the terminal device 2 or the location control device 1B and received by the communication unit 10A.

[0088] Furthermore, the information acquisition unit 14A acquires terminal information transmitted from the terminal device 2 and received by the communication unit 10A. Terminal information is, for example, information necessary for the determination unit 15A to determine the information acquisition mode, and includes information indicating the OS (Operating System) of the terminal device 2, the type and version of the application, or information indicating the model or model number of the terminal device 2.

[0089] [3.4.2.Decision section 15A] The determination unit 15A determines the information acquisition mode corresponding to the terminal device 2. This is either the information acquisition mode or the second information acquisition mode.

[0090] The first information acquisition mode is an information acquisition mode in which information about the learning model is transmitted to terminal device 2 as metric-related information, and metric information obtained by terminal device 2 using the learning model information is acquired from terminal device 2. The second information acquisition mode is an information acquisition mode in which metric type information is transmitted to terminal device 2 as metric-related information, and metric information corresponding to the metric type information is acquired from terminal device 2.

[0091] For example, the determination unit 15A determines the first information acquisition mode as the information acquisition mode if the terminal information indicates that the terminal device 2 is capable of supporting only the first information acquisition mode, and determines the second information acquisition mode as the information acquisition mode if the terminal information indicates that the terminal device 2 is capable of supporting only the second information acquisition mode.

[0092] Furthermore, if the terminal information indicates that the terminal device 2 is capable of supporting either the first information acquisition mode or the second information acquisition mode, the determination unit 15A determines a predetermined information acquisition mode from among the first and second information acquisition modes.

[0093] Furthermore, the terminal information may include information specifying the type of indicator-related information. In this case, the determination unit 15A determines the information acquisition mode from among the first information acquisition mode and the second information acquisition mode that corresponds to the type of indicator-related information indicated in the terminal information.

[0094] [3.4.3. Function Control Unit 16] The function control unit 16 causes each function execution unit 12 to execute a function based on the indicator information for each indicator acquired by the information acquisition unit 14A. The indicator information includes information indicating the indicator value, and such indicator value is a setting value indicating the operation setting of the location installation device 1A or a value corresponding to the setting value. If the indicator value is a value corresponding to the setting value, the function control unit 16 converts the indicator value to the setting value and causes the function execution unit 12 to execute the function.

[0095] For example, if the location-based device 1A is an electric chair, the indicator information for each indicator includes information such as an indicator value indicating the height of the armrests, an indicator value indicating the reclining angle, an indicator value indicating the height of the seat, and an indicator value indicating the softness of the seat. Based on this indicator information for each indicator, the function control unit 16 causes multiple function execution units 12 to perform adjustments such as adjusting the height of the armrests, adjusting the reclining angle, adjusting the height of the seat, and adjusting the softness of the seat.

[0096] Furthermore, if the location-based device 1A is an automatic food delivery device, the indicator information for each indicator includes information such as an indicator value indicating the type of ingredients to be included in the food and beverages to be delivered, an indicator value indicating the quantity of food and beverages, and an indicator value indicating the temperature of the food and beverages. Based on this indicator information for each indicator, the function control unit 16 causes multiple function execution units 12 to perform tasks such as selecting the ingredients to be included in the food and beverages to be delivered, adjusting the quantity of food and beverages, and adjusting the temperature of the food and beverages.

[0097] Furthermore, if the on-site installation device 1A is a coffee maker, the indicator information for each indicator includes information such as an indicator value indicating the type of coffee beans, an indicator value indicating the amount of coffee, an indicator value indicating whether or not milk is present, an indicator value indicating the amount of milk, and an indicator value indicating the temperature of the coffee. Based on this indicator information for each indicator, the function control unit 16 causes multiple function execution units 12 to perform actions such as selecting coffee beans, adjusting the amount of coffee, adjusting the amount of milk, and adjusting the temperature of the coffee.

[0098] Furthermore, if the location-based device 1A is an order-receiving device, the indicator information for each indicator includes information such as an indicator value indicating the type of food and beverage on the menu, an indicator value indicating the order of food and beverages on the menu, and an indicator value indicating the presentation method of food and beverages on the menu. Based on this indicator information for each indicator, the function control unit 16 causes multiple function execution units 12 to perform tasks such as selecting food and beverages to include in the menu, adjusting the order of food and beverages on the menu, and adjusting the presentation method of food and beverages on the menu.

[0099] Furthermore, if the location-based device 1A is a music provider, the indicator information for each indicator includes information such as an indicator value indicating the type of music, an indicator value indicating the volume of the music, and an indicator value indicating the sound quality of the music. Based on this indicator information for each indicator, the function control unit 16 causes multiple function execution units 12 to perform tasks such as selecting the music to be provided, adjusting the volume of the music, and adjusting the sound quality of the music.

[0100] Furthermore, if the location-based device 1A is a device used simultaneously by multiple users U, the function control unit 16 will cause multiple function execution units 11 to execute functions using setting values ​​corresponding to the same set of multiple indicator information output from multiple terminal devices 2.

[0101] A location-based device 1A is a device used simultaneously by multiple users U, for example, when the location-based device 1A is a lighting device, an air conditioning device, a music provider, or an order-taking device.

[0102] The setting value corresponding to the same set of multiple metrics is, for example, a value obtained by substituting the multiple metrics indicated by the same set of metrics into a predetermined calculation formula (e.g., mean, median, or weighted sum). The weighted sum is, for example, a value obtained by adding the metrics with a weight for each user U.

[0103] The weight of user U may be set higher, for example, the more frequently the location-installed device 1A has been used in the past, but it may also be set higher the longer the location-installed device 1A has been used in the past. The predetermined calculation formula described above may be different for each indicator, or it may be a calculation formula common to two or more indicators.

[0104] The function control unit 16 can, for example, set the indicator value of user U with the highest priority among multiple indicator values ​​indicated by the same set of indicator information as the set value. User U's priority is set, for example, for each location-based device 1A or for each service provision location AR. For example, the longer the past usage frequency and past usage time of the location-based device 1A, the higher the priority of user U will be set. Also, the higher the amount of money spent at the service provision location AR, the higher the priority of user U will be set.

[0105] Furthermore, if the location-based device 1A is, for example, a music provider, multiple indicator values ​​indicated by the same set of multiple indicator information can be sequentially set as the set value. In this case, the longer the past usage frequency and past usage time of the location-based device 1A, the longer the time that user U's indicator value is adopted as the set value, or the longer the time that user U's indicator value is adopted as the set value, the higher the priority of user U's indicator value. In this way, the function control unit 16 can cause the location-based device 1A to execute based on user U's indicator value in separate periods.

[0106] [3.4.4. Information Output Unit 17A] The information output unit 17A transmits indicator-related information corresponding to the information acquisition mode determined by the determination unit 15A to the terminal device 2 or the location control device 1B via the communication unit 10A.

[0107] For example, if the information acquisition mode determined by the determination unit 15A is the first information acquisition mode, the information output unit 17A transmits information about the learning model for each indicator to the terminal device 2 or the location control device 1B.

[0108] Furthermore, if the information acquisition mode determined by the determination unit 15A is the second information acquisition mode, the information output unit 17A transmits indicator type information for each indicator to the terminal device 2 or the location control device 1B. The indicator type information includes information indicating the indicator type, which is the type of indicator related to the service provided by the location installation device 1A. For example, if the location installation device 1A is the electric chair described above, the indicator types are, for example, the height of the armrests, the angle of the recline, the height of the seat, the softness of the seat, etc.

[0109] Furthermore, if the location-installed device 1A is an automatic food serving device, the indicator types are, for example, the type of coffee beans, whether or not milk is present, the amount of coffee, the amount of milk, and the temperature of the coffee. Also, if the location-installed device 1A is a music providing device, the indicator types are, for example, the type of music provided, the volume of the music, and the sound quality of the music.

[0110] Furthermore, the indicator type information may also include calculation information, which is information used to calculate the indicator value, which is the value of an indicator related to the service provided by the location-installed device 1A. The calculation information may include, for example, information on the formula for calculating the indicator value or information on the learning model. Such learning model information is, for example, the same as the learning model information in the first information acquisition mode.

[0111] The information output unit 17A transmits indicator-related information corresponding to the information acquisition mode determined by the determination unit 15A to the terminal device 2, for example, when the terminal device 2 is located within a predetermined range from the location installation device 1A. The information output unit 17A determines whether or not the terminal device is within a predetermined range from the location installation device 1A based on the signal strength transmitted from the terminal device 2 via short-range wireless communication or location information transmitted from the terminal device 2.

[0112] Furthermore, the information output unit 17A can also transmit indicator-related information corresponding to the information acquisition mode determined by the determination unit 15A to the terminal device 2, for example, when requested by the location control device 1B.

[0113] [4. Configuration of the location control device 1B] Figure 4 shows an example of the configuration of a location control device 1B according to the embodiment. As shown in Figure 4, the location control device 1B according to the embodiment comprises a communication unit 10B, a storage unit 11B, and a processing unit 13B. The communication unit 10B is the same as the communication unit 10A, so its description is omitted.

[0114] [4.1. Storage section 11B] The memory unit 11B is implemented by, for example, semiconductor memory elements such as RAM and flash memory, or storage devices such as hard disks and optical discs.

[0115] The memory unit 11B stores, for example, information on the learning model for each indicator and information on the indicator type for each indicator, for each location-based device 1A.

[0116] [4.2. Processing Unit 13B] The processing unit 13B is a controller, which is realized by executing various programs stored in the memory device inside the location control device 1B using RAM as the working area, for example, by a CPU or MPU.

[0117] The processing unit 13B may be partially or entirely implemented by an integrated circuit such as an ASIC or FPGA. The processing unit 13B includes an information acquisition unit 14B, a determination unit 15B, and an information output unit 17B.

[0118] [4.2.1. Information acquisition unit 14B] The information acquisition unit 14B acquires information from an external device. For example, similar to the information acquisition unit 14A, the information acquisition unit 14B acquires indicator information transmitted from the terminal device 2 and received by the communication unit 10B.

[0119] [4.2.2.Decision section 15B] The determination unit 15B, similar to the determination unit 15A, determines the information acquisition mode corresponding to the terminal device 2.

[0120] [4.2.3. Information Output Unit 17B] Similar to the information output unit 17A, the information output unit 17B transmits indicator-related information corresponding to the information acquisition mode determined by the determination unit 15B to the terminal device 2 via the communication unit 10B.

[0121] For example, the information output unit 17B transmits indicator-related information to the terminal device 2 via the communication unit 10B when the terminal device 2 is located within a predetermined range from the location installation device 1A. The predetermined range is set for each location installation device 1A, and the information output unit 17B transmits indicator-related information to the terminal device 2 via the communication unit 10B corresponding to the location installation device 1A in which the terminal device 2 is located within the predetermined range.

[0122] The information output unit 17B determines whether the location is within a predetermined range from the location installation device 1A, based on the signal strength transmitted from the terminal device 2 via short-range wireless communication or location information transmitted from the terminal device 2.

[0123] Furthermore, the information output unit 17B transmits the indicator information acquired by the information acquisition unit 14B to the location installation device 1A corresponding to the indicator information via the communication unit 10B.

[0124] [5. Terminal device 2] Figure 5 shows an example of the configuration of the terminal device 2 according to the embodiment. As shown in Figure 5, the terminal device 2 according to the embodiment includes a communication unit 20, a display unit 21, an operation unit 22, a sensor group 23, a storage unit 24, and a processing unit 25.

[0125] [5.1. Communications Section 20] The communication unit 20 is implemented by, for example, a NIC. The communication unit 20 transmits and receives information between the location installation device 1A and the location control device 1B, respectively, via short-range wireless communication.

[0126] The communication unit 20 is connected to the network N by wire or wireless connection and can also send and receive information to and from the location installation device 1A and the location control device 1B via the network N.

[0127] [5.2.Display section 21] The display unit 21 is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display.

[0128] [5.3. Operation unit 22] The operation unit 22 includes, for example, a keyboard with keys for entering letters, numbers, and spaces, an enter key and arrow keys, a mouse, and a power button. If the display unit 21 is a touch panel compatible display, the operation unit 22 includes a touch panel.

[0129] [5.4. Sensor Group 23] Sensor group 23 includes various sensors. Sensor group 23 includes, for example, a positioning sensor, an accelerometer, a gyroscope, a geomagnetic sensor, a voice sensor (microphone), an illuminance sensor, a temperature sensor, a humidity sensor, a pressure sensor, a proximity sensor, sensors for acquiring biometric information such as odor, sweat, heart rate, pulse, and brain waves, and an image sensor. The positioning sensor is a sensor that detects the position of terminal device 2 and outputs position information.

[0130] [5.5. Storage section 24] The memory unit 24 is implemented by, for example, semiconductor memory elements such as RAM and flash memory, or storage devices such as hard disks and optical discs.

[0131] The storage unit 24 stores, for example, information transmitted from the location installation device 1A or location control device 1B and acquired by the processing unit 25 via the communication unit 20, as well as detection information, which is information detected by the sensor group 23. The storage unit 24 also stores the terminal information mentioned above.

[0132] Furthermore, the memory unit 24 stores information about user U. This information about user U includes, for example, user U's attribute information, user U's behavioral history information, and user U's context information.

[0133] User U's attribute information is information that indicates User U's attributes, such as User U's demographic attributes and User U's psychographic attributes. Demographic attributes are demographic attributes such as age, gender, occupation, place of residence, annual income, and family structure. Psychographic attributes are psychological attributes such as lifestyle, values, and interests.

[0134] User U's behavioral history information includes, for example, historical information such as User U's service usage history, and also includes, for example, User U's payment history information, User U's search history information, User U's browsing history information, and User U's contextual history information.

[0135] User U's payment history information includes purchase history information for goods purchased by User U online, in physical stores, or at physical facilities using payment services, and service usage history information for services used by User U for a fee online, in physical stores, or at physical facilities using payment services.

[0136] Purchase history information includes information about the products purchased by user U, purchase costs, purchase date and time, and store of purchase. Service usage history information includes information about the services used by user U, usage costs, usage date and time, and store of use.

[0137] User U's search history information includes, for example, information about web content searches on search engines and search history on various websites. User U's browsing history information is information about web content that User U has viewed.

[0138] The context history information for user U is the user U context detected by the sensor group 23 and the user U context history information determined by the processing unit 25 based on the detected information. The context of user U is the status of user U.

[0139] User U's status includes, for example, User U's position, User U's orientation, User U's movements, User U's body temperature, User U's heart rate, and User U's pulse, and is stored in the storage unit 24 by the processing unit 25.

[0140] The status of user U may also include, for example, user U traveling by train, user U taking a walk, user U taking a bath, or user U sleeping.

[0141] Furthermore, the storage unit 24 may, for example, have calculation information for each indicator type pre-stored in it, or it may store calculation information for each indicator type that is transmitted from the location installation device 1A or location control device 1B and acquired by the processing unit 25 via the communication unit 20.

[0142] [5.6. Processing Unit 25] The processing unit 25 is a controller, which is realized, for example, by a CPU or MPU executing various programs stored in the memory device inside the terminal device 2 using RAM as the working area.

[0143] The processing unit 25 may be partially or entirely implemented by an integrated circuit such as an ASIC or FPGA. The processing unit 25 includes an information acquisition unit 30, a determination unit 31, a calculation unit 32, a display processing unit 33, an information output unit 34, and a deletion unit 35.

[0144] [5.6.1. Information acquisition unit 30] The information acquisition unit 30 acquires various types of information from external devices. For example, the information acquisition unit 30 acquires indicator-related information transmitted from the location installation device 1A or location control device 1B and received by the communication unit 20 via short-range wireless communication or network N.

[0145] Furthermore, the information acquisition unit 30 acquires various types of content from external information processing devices. This content may include, for example, web content such as news articles, weather reports, and shopping information.

[0146] The information acquisition unit 30 includes a first information acquisition unit 40 and a second information acquisition unit 41. The first information acquisition unit 40 acquires indicator-related information from the location setting device 1A or the location control device 1B. The indicator-related information is either learning model information or indicator type information.

[0147] The learning model information is information about a learning model generated by machine learning, which takes user information (user U) as input and metric information as output. The metric type information includes information indicating the metric type, which is the type of metric related to the service provided by the on-site device 1A.

[0148] Furthermore, the indicator type information may also include calculation information, which is information used to calculate the indicator value, which is the value of an indicator related to the service provided by the on-site device 1A. The calculation information may include, for example, information on the formula for calculating the indicator value or information on the learning model.

[0149] Furthermore, the second information acquisition unit 41 inputs user information into the learning model from which information has been acquired by the first information acquisition unit 40 and acquires metric information output from the learning model for each metric. Alternatively, instead of inputting user information and acquiring metric information output from the learning model for each metric through calculation using the learning model, the second information acquisition unit 41 can also input user information into the learning model used by the calculation unit 32 and acquire metric information for each metric from the calculation unit 32.

[0150] [5.6.2. Judgment unit 31] The determination unit 31 determines the context of user U based on the detection information output from the sensor group 23. The determination unit 31 stores the determined context information of user U in the storage unit 24.

[0151] The determination unit 31 determines the position of user U, the orientation of user U, the movement of user U, etc., based on information detected by positioning sensors, acceleration sensors, gyro sensors, geomagnetic sensors, etc.

[0152] Furthermore, the determination unit 31 determines the emotions of user U based on information detected by sensors for acquiring biometric information such as odor, sweat, heart rate, pulse, and brain waves. The determination unit 31 can also detect whether user U is traveling by train, taking a walk, bathing, or sleeping, based on the results detected by one or more sensors included in the sensor group 23.

[0153] [5.6.3. Calculation Unit 32] The calculation unit 32 calculates the index value for each index type indicated by the index type information obtained by the first information acquisition unit 40, based on the user information, which is information of user U.

[0154] If the indicator type information includes calculation information, the calculation unit 32 calculates the indicator value for each indicator using the calculation information from the user information acquired by the information acquisition unit 30, which is the user information used to calculate the indicator value using the calculation information.

[0155] For example, if the calculation information is information for the calculation formula of the index value, the calculation unit 32 calculates the index value by substituting user information, which is user information acquired by the information acquisition unit 30, into the calculation formula and performing the calculation on the formula.

[0156] Furthermore, if the calculation information is information from the learning model, the calculation unit 32 inputs user information acquired by the information acquisition unit 30 into the learning model, calculates an index value using the learning model, and obtains the index value which is the output of the learning model.

[0157] Furthermore, if the indicator type information does not include calculation information, and the calculation information is stored in the storage unit 24, the calculation unit 32 retrieves the calculation information corresponding to the indicator type indicated in the indicator type information from the storage unit 24, and calculates the indicator value using the calculation information retrieved from the storage unit 24.

[0158] [5.6.4. Display Processing Unit 33] The display processing unit 33 displays the information acquired by the information acquisition unit 30 on the display unit 21. For example, the display processing unit 33 displays information such as content acquired by the information acquisition unit 30 on the display unit 21.

[0159] [5.6.5. Information Output Unit 34] The information output unit 34 transmits various types of information to an external device via the communication unit 20. For example, it transmits operation information, which is information corresponding to operations performed by user U on the operation unit 22, to an external information processing device via the communication unit 20.

[0160] Furthermore, the information output unit 34 transmits, for example, terminal information stored in the storage unit 24 to the location setting device 1A or location control device 1B via the communication unit 20.

[0161] Furthermore, the information output unit 34 transmits the indicator information acquired by the second information acquisition unit 41 or the indicator information calculated by the calculation unit 32 to the location setting device 1A or the location control device 1B via the communication unit 20.

[0162] [5.6.6. Deleted section 35] The deletion unit 35 deletes the learning model information acquired from the location device 1 by the information acquisition unit 30 and stored in the storage unit 24 from the storage unit 24 after the index information output from the learning model has been output from the information output unit 34.

[0163] [6. Processing Procedure] Next, the procedure for information processing by the processing unit 13A of the site-mounted device 1A according to this embodiment will be described. Figure 6 is a flowchart showing an example of information processing by the processing unit 13A of the site-mounted device 1A according to this embodiment.

[0164] As shown in Figure 6, the processing unit 13A of the location-installed device 1A determines whether or not there is terminal information acquired from the terminal device 2 (step S10). If the processing unit 13A determines that there is terminal information (step S10: Yes), it determines the information acquisition mode based on the terminal information (step S11). Then, the processing unit 13A transmits the indicator-related information corresponding to the determined information acquisition mode to the terminal device 2 (step S12).

[0165] If the processing in step S12 is completed, or if it is determined that there is no terminal information (step S10: No), the processing unit 13A determines whether or not there is indicator information acquired from the terminal device 2 (step S13). If the processing unit 13A determines that there is indicator information (step S13: Yes), it controls the function execution unit 12 based on the acquired indicator information (step S14).

[0166] When the processing in step S14 is completed, or when it is determined that there is no indicator information (step S13: No), the processing unit 13A determines whether or not it is time to terminate the operation (step S15). For example, the processing unit 13A determines that it is time to terminate the operation when the power to the on-site device 1A is turned off, or when it is determined that a termination operation has been performed by operating on an unillustrated control unit of the on-site device 1A.

[0167] If the processing unit 13A determines that it is not yet time to terminate the operation (step S15: No), it proceeds to step S10. If it determines that it is time to terminate the operation (step S15: Yes), it terminates the process shown in Figure 6.

[0168] Next, the information processing procedure by the processing unit 13B of the location control device 1B according to the embodiment will be described. Figure 7 is a flowchart showing an example of information processing by the processing unit 13B of the location control device 1B according to the embodiment. The processing in steps S20 to S23 and S25 shown in Figure 7 is the same as the processing in steps S10 to S13 and S15 in Figure 6, so the explanation will be omitted.

[0169] As shown in Figure 7, if the processing unit 13B of the location control device 1B determines that there is indicator information (step S23: Yes), it transmits the acquired indicator information to the location installation device 1A corresponding to that indicator information (step S24).

[0170] Next, the procedure for information processing by the processing unit 25 of the terminal device 2 according to this embodiment will be described. Figure 8 is a flowchart showing an example of information processing by the processing unit 25 of the terminal device 2 according to this embodiment.

[0171] As shown in Figure 8, the processing unit 25 of the terminal device 2 determines whether or not it has detected the location device 1 (step S30). If the processing unit 25 determines that it has detected the location device 1 (step S30: Yes), it transmits the terminal information stored in the storage unit 24 to the detected location device 1 (step S31).

[0172] If the processing in step S31 is completed, and the processing unit 25 determines that it has not detected the location device 1 (step S30: No), it determines whether there is any indicator-related information obtained from the location device 1 (step S32).

[0173] If the processing unit 25 determines that there is indicator-related information (step S32: Yes), it calculates the indicator value based on the indicator-related information (step S33). Then, the processing unit 25 transmits the indicator information, including the indicator value calculated in step S33, to the location device 1 (step S34).

[0174] When the processing in step S34 is completed, or when it is determined that there is no indicator-related information (step S32: No), the processing unit 25 determines whether or not it is time to terminate the operation (step S35).

[0175] The processing unit 25 determines that it is time to terminate operation, for example, when the power to terminal device 2 is turned off, or when it determines that a termination operation has been performed by an operation on the operation unit 22 of terminal device 2.

[0176] If the processing unit 25 determines that it is not yet time to terminate the operation (step S35: No), it proceeds to step S30. If it determines that it is time to terminate the operation (step S35: Yes), it terminates the process shown in Figure 8.

[0177] [7. Hardware Configuration] Each of the location device 1 and terminal device 2 according to the above embodiment is implemented by a computer 80 having a configuration such as that shown in Figure 9. Figure 9 is a hardware configuration diagram showing an example of a computer 80 that implements the functions of each of the location device 1 and terminal device 2 according to the embodiment. The computer 80 has a CPU 81, RAM 82, ROM (Read Only Memory) 83, HDD (Hard Disk Drive) 84, communication interface (I / F) 85, input / output interface (I / F) 86, and media interface (I / F) 87.

[0178] The CPU 81 operates based on programs stored in the ROM 83 or HDD 84, and controls various parts of the system. The ROM 83 stores boot programs executed by the CPU 81 when the computer 80 starts up, as well as programs that depend on the computer 80's hardware.

[0179] HDD84 stores programs executed by CPU81 and data used by such programs. The communication interface85 receives data from other devices via network N (see Figure 2) and sends it to CPU81, and transmits the data generated by CPU81 to other devices via network N.

[0180] The CPU 81 controls output devices such as displays and printers, and input devices such as keyboards and mice, via the input / output interface 86. The CPU 81 acquires data from input devices via the input / output interface 86. The CPU 81 also outputs data it has generated to output devices via the input / output interface 86.

[0181] The media interface 87 reads a program or data stored in the recording medium 88 and provides it to the CPU 81 via the RAM 82. The CPU 81 loads the program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 can be, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0182] For example, when the computer 80 functions as a location device 1 and a terminal device 2 according to the embodiment, the CPU 81 of the computer 80 realizes the functions of the processing units 13A, 13B and 25 by executing programs loaded on the RAM 82. In addition, data from the storage units 11A, 11B or storage unit 24 is stored in the HDD 84. The CPU 81 of the computer 80 reads and executes these programs from the recording medium 88, but as another example, these programs may be obtained from other devices via the network N.

[0183] [8. Other] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and various data and parameters shown in the above document and drawings can be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0184] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0185] For example, the location control device 1B described above may be implemented using multiple server computers, and depending on the function, it may be implemented by calling external platforms via APIs or network computing, allowing for flexible configuration changes.

[0186] Furthermore, the embodiments and modifications described above can be combined as appropriate, provided that the processing content is not inconsistent.

[0187] [9. Effects] As described above, the terminal device 2 according to this embodiment comprises a first information acquisition unit 40, a second information acquisition unit 41, and an information output unit 34. The first information acquisition unit 40 acquires information from the location device 1 about a learning model generated by machine learning, which takes user information, which is information about the user U using the service provision location AR, as input and indicator information, which is information about indicator values ​​indicating the values ​​of indicators related to the service, as output. The second information acquisition unit 41 inputs user information into the learning model from which the information acquired by the first information acquisition unit 40 has been obtained and acquires the indicator information output from the learning model. The information output unit 34 outputs the indicator information acquired by the second information acquisition unit 41 to the location device 1. As a result, the terminal device 2 can reduce the processing load on the location device that provides the service to user U.

[0188] Furthermore, the first information acquisition unit 40 acquires information from the learning model for each service-related indicator, the second information acquisition unit 41 acquires indicator information for each indicator using the learning model information for each indicator, and the information output unit 34 outputs indicator information for each indicator. As a result, the terminal device 2 can reduce the processing load on the device at the location where the service is provided to user U.

[0189] Furthermore, the indicator information is information about setting values ​​or values ​​corresponding to setting values ​​that indicate the operating settings of location device 1. This allows terminal device 2 to reduce the processing load on the location device that provides the service to user U.

[0190] Furthermore, location device 1 is a location-based device 1A that is installed at a location and provides services to user U. This allows terminal device 2 to reduce the processing load on the location device that provides services to user U.

[0191] Furthermore, when multiple users U use the location device 1 simultaneously, it operates with settings corresponding to multiple indicator information output from multiple terminal devices 2. This allows terminal devices 2 to reduce the processing load on the location device that provides the service to user U.

[0192] Furthermore, location device 1 is a location installation device 1A that is installed at the service provision location AR and manufactures the items that are provided to user U as a service. This allows terminal device 2 to reduce the processing load on the device at the location where the service is provided to user U.

[0193] Furthermore, user information includes at least one of the following: user U's attribute information, user U's behavioral history information, and user U's contextual information. This allows terminal device 2 to reduce the processing load on the device at the location where it provides the service to user U.

[0194] Furthermore, the terminal device 2 includes a storage unit 24 that stores information of the learning model acquired by the first information acquisition unit 40, and a deletion unit 35 that deletes the learning model information from the storage unit 24 after the index information has been output by the information output unit 34. As a result, the terminal device 2 can reduce the processing load on the device at the location where the service is provided to user U.

[0195] Although embodiments of the present application have been described in detail based on the drawings, these are illustrative examples, and the present invention can be implemented in various other forms, including those described in the disclosure section of the invention, based on the knowledge of those skilled in the art.

[0196] Furthermore, the terms "section, module, unit" mentioned above can be replaced with "means" or "circuit," etc. For example, the acquisition unit can be replaced with acquisition means or acquisition circuit. [Explanation of symbols]

[0197] 1. Place device 1A, 1A1~1A n Location-based installation device 1B Location control device 2 Terminal devices 10A,10B,20 Communication department 12,121~12 k Function execution unit 11A,11B,24 Storage section 13A, 13B, 25 Processing Unit 14A,14B,30 Information acquisition section 15A,15B Decision section 16. Functional Control Unit 17A,17B,34 Information output section 21 Display section 22 Control section 23 Sensor Groups 31 Judgment section 32 Calculation Section 33 Display Processing Unit 40 1st Information Acquisition Department 41 2nd Information Acquisition Department 100 Information Processing Systems

Claims

1. A first information acquisition unit acquires information of a learning model generated by machine learning from the equipment at the location, which takes user information, which is information of users who use the location where the service is provided, as input and indicator information, which is information of indicator values ​​that show the values ​​of indicators related to the said service, as output. A second information acquisition unit inputs the user information into the learning model from which information has been acquired by the first information acquisition unit and acquires the index information output from the learning model, The system includes an information output unit that outputs the indicator information acquired by the second information acquisition unit to the device at the location. A terminal device characterized by the following features.

2. The first information acquisition unit is, As information for the aforementioned learning model, information for the learning model for each of the aforementioned indicators is obtained. The aforementioned second information acquisition unit is: Using the information of the learning model for each of the aforementioned indicators, the indicator information is obtained for each of the aforementioned indicators. The aforementioned information output unit is Output the indicator information for each of the aforementioned indicators. The terminal device according to feature 1.

3. The aforementioned indicator information is, This information is a setting value indicating the operating setting of the device at the aforementioned location, or a value corresponding to the aforementioned setting value. The terminal device according to claim 1 or 2.

4. The apparatus at the aforementioned location is A device installed at the aforementioned location and providing the aforementioned service to the aforementioned user. The terminal device according to feature 3.

5. The apparatus at the aforementioned location is When multiple users use the device simultaneously, it operates with settings corresponding to the multiple indicator information output from the multiple terminal devices. The terminal device according to feature 4.

6. The apparatus at the aforementioned location is A device installed at the aforementioned location that manufactures products provided to the user as a service. The terminal device according to feature 4.

7. The aforementioned user information is At least one of the user's attribute information, the user's behavioral history information, and the user's contextual information. The terminal device according to claim 1 or 2.

8. A storage unit that stores the information of the learning model acquired by the first information acquisition unit, The system includes a deletion unit that deletes the learning model information from the storage unit after the index information has been output by the information output unit. The terminal device according to claim 1 or 2.

9. An information processing method performed by a terminal device, A first information acquisition step involves acquiring information from a device at a location that generates a learning model, which takes user information, which is information about users who use the location where the service is provided, as input, and indicator information, which is information about indicator values ​​that show the values ​​of indicators related to the service, as output. A second information acquisition step involves inputting the user information into the learning model from which information has been acquired by the first information acquisition step and acquiring the index information output from the learning model, The information output step includes outputting the indicator information obtained by the second information acquisition step to the device at the location. An information processing method characterized by the following:

10. A first information acquisition procedure involves acquiring information from a device at a location that generates a learning model, which takes user information, which is information about users who use the location where the service is provided, as input, and indicator information, which is information about indicator values ​​that show the values ​​of indicators related to the service, as output. A second information acquisition procedure involves inputting the user information into the learning model from which information has been acquired by the first information acquisition procedure and acquiring the index information output from the learning model, The terminal device is instructed to execute an information output procedure that outputs the indicator information obtained by the second information acquisition procedure to the device at the location. An information processing program characterized by the following features.

Images