Information provision device, information provision method, information provision program and provision system

Abstract

To give a user a sufficient feeling of satisfaction.SOLUTION: An information provision device 10 according to an embodiment detects an action of a user and determines characteristics that can be sensed by human senses based on the detected action. The information provision device 10 also provides information (recipe data) indicating a procedure for manufacturing a product having the determined characteristics. The product manufactured according to the recipe data is provided to the user.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information providing device, an information providing method, an information providing program, and an information providing system. [Background technology]

[0002] 2. Description of the Related Art Conventionally, there is known a system that estimates emotion information based on a user's biometric information and context information relating to the user's posture and the like, and presents content such as images and music according to the estimated emotion information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2021 / 261123 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional techniques have a problem in that they may not provide a sufficient sense of satisfaction to the user.

[0005] For example, images and music stimulate the user's visual and auditory senses. On the other hand, images and music do not stimulate the user's tactile senses, etc. For this reason, in conventional technology, the user may only be stimulated by some of the five senses, and may not feel a sufficient sense of satisfaction.

[0006] One aspect is to provide a user with a satisfactory feeling of satisfaction. [Means for solving the problem]

[0007] In one aspect, the information providing device is characterized by having a detection unit that detects a user's actions, a determination unit that determines characteristics that can be detected by human senses based on the actions detected by the detection unit, and a providing unit that provides information indicating a procedure for manufacturing a product having the characteristics determined by the determination unit. Effect of the Invention

[0008] According to one embodiment, a sufficient sense of satisfaction can be given to the user. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a provision system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of an information providing device according to the embodiment. [Diagram 3] FIG. 3 is a diagram for explaining a recipe generation model. [Figure 4] FIG. 4 is a diagram illustrating the taste determination model. [Diagram 5] FIG. 5 is a flowchart showing a flow of processing performed by the information providing device according to the embodiment. [Figure 6] FIG. 6 is a flowchart showing a flow of processing performed by the information providing device according to the embodiment. [Figure 7] FIG. 7 is a flowchart showing a flow of processing performed by the information providing device according to the embodiment. [Figure 8] FIG. 8 is a flowchart showing a flow of processing performed by the information providing device according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a hardware configuration of a server according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an information providing device, an information providing method, an information providing program, and a providing system according to the present disclosure (hereinafter, referred to as "embodiments") will be described in detail with reference to the drawings. Note that the present disclosure is not limited to the embodiments.

[0011] One of the objectives of this embodiment is to give the user a satisfactory feeling of satisfaction.

[0012] [Configuration of the embodiment] The provision system will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of the provision system according to the embodiment.

[0013] The provision system 1 collects biometric information, motion information, and the like of a user, and provides products based on the collected information. The products include food, footwear, clothing, plastic products, metal products, and the like.

[0014] For example, the providing system 1 is used in a service that allows a user to have a specific experience. The experience may involve a user's action. For example, the experience in the service may be exercising using equipment, playing a musical instrument, cooking, watching a video, etc. Furthermore, the experience may be appropriately rephrased as entertainment, activity, hands-on, workshop, etc.

[0015] For example, assume that the service allows the user to experience running on a treadmill (running machine). In this case, the user runs on the treadmill. Then, the providing system 1 provides the product to the user who has finished running.

[0016] As shown in FIG. 1, the providing system 1 includes an information providing device 10, a manufacturing device 20, a terminal 30, a camera 40, a camera 50, and an experience device 60.

[0017] The information providing device 10 is, for example, a server, and is connected to a manufacturing device 20, a terminal 30, a camera 40, a camera 50, and an experience device 60 via a network.

[0018] The information providing device 10 collects information from external devices including a terminal 30, a camera 40, a camera 50, and an experience device 60. The information providing device 10 generates information indicating a procedure for manufacturing a product based on the collected information. The information indicating the procedure for manufacturing a product is called recipe data. The information providing device 10 provides the recipe data to a manufacturing device 20. Note that providing here means transmitting data to another device.

[0019] The manufacturing apparatus 20 manufactures products according to the recipe data. The manufacturing apparatus 20 is a 3D printer, a machine tool, a food manufacturing machine, or the like. The manufacturing apparatus 20 may also be a facility that produces products by line production. The manufacturing apparatus 20 may also be replaced by a manufacturer that produces products. In this case, the manufacturer manufactures the products by referring to the recipe data.

[0020] The terminal 30 is an information processing device such as a personal computer or a smartphone owned by a user. The user can provide information to the information providing device 10 via the terminal 30.

[0021] The camera 40 captures an image of the user before the experience and transmits the captured image to the information providing device 10. The camera 50 captures an image of the user during the experience and transmits the captured image to the information providing device 10. The image may be a still image or a moving image.

[0022] The number of cameras that capture the user before and during the experience may be one or more. Furthermore, the cameras 40 and 50 may be replaced with other sensors. That is, the provision system 1 only needs to include a sensor that acquires information about the user before or during the experience.

[0023] Here, a user receiving the service visits a specified location (facility, venue, etc.), and then actually starts the experience after waiting time, etc. The state or time before the user starts the experience is called "pre-experience." The state or time from when the user actually starts the experience until it ends is called "during experience." The state or time after the experience ends is called "post-experience."

[0024] The experience device 60 is a device for allowing the user to experience something. For example, the experience device 60 is a treadmill (running machine). The experience device 60 transmits information acquired by a built-in sensor or information related to settings (for example, the speed of the treadmill) to the information providing device 10.

[0025] Here, the configuration of the information providing device 10 will be described in detail, and the overall processing flow of the information providing system 1 will be described.

[0026] 2 is a diagram showing an example of the configuration of an information providing device according to an embodiment. As shown in FIG. 2, the information providing device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0027] The communication unit 11 is a communication module for communicating data with other devices, and is, for example, a network interface controller (NIC).

[0028] The storage unit 12 is a storage device such as a flash memory, a non-volatile static random access memory (NVSRAM), etc. The storage unit 12 stores recipe generation model information 121 and collected data 122.

[0029] The recipe generation model information 121 is information about a model for determining the characteristics of a product. For example, the recipe generation model information 121 includes functions and parameters for determining the characteristics. The collected data 122 is data collected from each device.

[0030] Fig. 3 is a diagram for explaining a recipe generation model. As shown in Fig. 3, a recipe generation model group 1211 is constructed based on recipe generation model information 121. In addition, collected data 122 includes questionnaire data 1221, pre-experience measurement data 1222, and during-experience measurement data 1223. The recipe generation model group 1211 accepts input of the collected data 122 and outputs recipe data 150.

[0031] The control unit 13 controls the entire information providing device 10. The control unit 13 is, for example, a central processing unit (CPU), a micro processing unit (MPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or the like.

[0032] The control unit 13 executes each process by referring to the programs and data stored in the storage unit 12. In addition, the control unit 13 functions as various processing units by the operation of various programs. The control unit 13 has a detection unit 131, a collection unit 132, a determination unit 133, and a provision unit 134.

[0033] The detection unit 131 detects the user's actions. The detection unit 131 can detect the user's actions based on information provided by the camera 40, the camera 50, and the experience device 60. For example, the detection unit 131 detects the walking or running speed, the amount of smiling, the level of awakening, etc. as the user's actions. In addition to these, the detected actions may include the stride, pitch, and foot contact angle when walking or running.

[0034] The collection unit 132 collects information. The information collected by the collection unit 132 is stored in the storage unit 12 as collected data 122. The collected data 122 includes information on the user's actions detected by the detection unit 131.

[0035] The collection unit 132 collects, as the collected data 122, questionnaire data 1221, pre-experience measurement data 1222, and during-experience measurement data 1223 shown in FIG.

[0036] The collection unit 132 collects the questionnaire data 1221 in advance. "In advance" refers to, for example, the time from when the user visits a venue where the experience device 60 is installed until the user starts the experience. The collection unit 132 may also collect the questionnaire data 1221 before the user visits the venue. The collection unit 132 collects the questionnaire data 1221 via the terminal 30. For example, the information providing device 10 causes the terminal 30 to display a questionnaire. Then, the terminal 30 transmits the answers to the questionnaire entered by the user to the information providing device 10 as the questionnaire data 1221.

[0037] In this embodiment, it is assumed that the serving system 1 serves ice cream. Therefore, the contents of the questionnaire data 1221 relate to the ice cream to be served.

[0038] As shown in FIG. 3, the questionnaire data 1221 includes the "size", "quantity", and "type" of ice cream desired by the user, the user's "consciousness towards beauty" and "taste preference".

[0039] Furthermore, the collection unit 132 collects pre-experience measurement data 1222. The pre-experience measurement data 1222 includes information on the actions detected by the detection unit 131. As shown in Fig. 3, the pre-experience measurement data 1222 includes "alertness", "amount of smile", and "temperature". For example, the detection unit 131 can detect "alertness" and "amount of smile" from an image of the user's face.

[0040] For example, the detection unit 131 uses a machine learning model for image recognition to determine whether or not the user is smiling from an image. Then, the detection unit 131 detects the proportion of the time period during which the user is smiling in a certain period as the "amount of smiling face."

[0041] In addition, the detection unit 131 counts the number of times the user blinks from the image using a machine learning model for image recognition. Then, the detection unit 131 detects the user's wakefulness level based on the number of times the user blinks in a certain period of time. The fewer the number of times the user blinks, the greater the wakefulness level.

[0042] The collection unit 132 collects "temperature" from an external server, a terminal 30, an experience device 60, or other sensors.

[0043] Furthermore, the collection unit 132 collects during-experiencing measurement data 1223. The during-experiencing measurement data 1223 includes information on the movement detected by the detection unit 131. As shown in Fig. 3, the during-experiencing measurement data 1223 includes "awakening level", "amount of smile", "speed", and "center of gravity position".

[0044] The collection unit 132 collects the pre-experience measurement data 1222 and the in-experience measurement data during the experience. The experience period is the time from immediately before the user starts the experience to the end of the experience. The collection unit 132 may collect the pre-experience measurement data 1222 in advance, similar to the questionnaire data 1221.

[0045] The collection unit 132 collects the speed set on the treadmill (the experience device 60) as the “speed.” The user is considered to walk or run at the speed set on the treadmill.

[0046] The detection unit 131 can detect the movement trajectory of each part of the user's body during movement by motion capture using one or more cameras. The detection unit 131 may use an existing motion capture system such as Kinect (registered trademark) (https: / / ja.wikipedia.org / wiki / Kinect) or VICON (http: / / www.vicon.jp / ).

[0047] The detection unit 131 detects the position of a specific part of the user's body at each time as a trajectory 1223a of the center of gravity position. The trajectory 1223a shown in Fig. 3 is the trajectory of the center position of the pelvis. The detection unit 131 may detect the position and trajectory of other parts of the user's body as a movement, not limited to the center of gravity.

[0048] For example, the detection unit 131 can detect the swing width of the upper arm relative to the center position of the shoulder joint, or a change in the position of the center of the palm, a change in the bending angle of the elbow, etc., as the trajectory of the arm swing. The detection unit 131 may also detect the trajectory of a straight line connecting both shoulders as the degree of shoulder shaking. The detection unit 131 may also detect changes in the bending angles of the knee joint, hip joint, and ankle joint in the sagittal plane and the difference between the left and right. The detection unit 131 may also detect the trajectory of the center position of the head, the trajectory of the degree of lifting of the toes, etc.

[0049] The collected data 122 collected by the collecting unit 132 may include data other than those shown in Fig. 3. For example, the collected data 122 may include biometric information of the user. The collecting unit 132 collects biometric information such as the user's body temperature, heart rate, and blood pressure from a wearable terminal (e.g., a smart watch) worn by the user.

[0050] The determining unit 133 determines a feature that can be sensed by a human sense based on the collected data 122. The collected data 122 includes information on the motion detected by the detecting unit 131.

[0051] The determination unit 133 determines the features by using the recipe generation model group 1211 constructed from the recipe generation model information 121. The features determined by the determination unit 133 are reflected in the recipe data 150. Each item of the recipe data 150 shown in FIG. 3 corresponds to a feature.

[0052] First, the determining unit 133 determines the value of the item "size" of the questionnaire data 1221 as the value of the item "disher" of the recipe data 150. The item "disher" is the size of a disher for scooping ice cream.

[0053] The determining unit 133 determines the value of the item "number of scoops" of the questionnaire data 1221 as the value of the item "number of scoops" of the recipe data 150. The item "number of scoops" is the number of times ice cream is scooped with a scooper.

[0054] The determining unit 133 determines the value of the item "type" of the questionnaire data 1221 as the value of the item "type" of the recipe data 150. The item "type" is a feature related to a container (cone or cup) for holding the ice cream.

[0055] The determination unit 133 determines a part of the value of the item "sauce" of the recipe data 150 based on the value of the item "beauty awareness" of the questionnaire data 1221. The item "sauce" is data in the format of (type, amount), and the value of the first element, "type," is "caramel," "chocolate," "fruit," etc.

[0056] When "beauty consciousness" is "high", the determination unit 133 determines the type value to be "fruit". When "beauty consciousness" is "medium", the determination unit 133 determines the type value to be "chocolate". When "beauty consciousness" is "low", the determination unit 133 determines the type value to be "caramel". Note that, in this case, it is assumed that "fruit", "chocolate", and "caramel" are considered to have the least adverse effects on beauty in that order.

[0057] The determination unit 133 determines the item “taste” of the recipe data 150 using the taste determination model 1211a based on the item “taste preference” of the recipe data 150, the items “alertness” and “amount of smiles” of the pre-experience measurement data 1222, and the items “alertness” and “amount of smiles” of the during-experience measurement data 1223.

[0058] The taste determination model 1211a will be described with reference to Fig. 4. Fig. 4 is a diagram for explaining the taste determination model. The determination unit 133 functions as an identification unit that identifies the user's emotion.

[0059] 4, first, the determination unit 133 identifies the user's emotion using the Russell ring model (left side of FIG. 4) based on the user's biological information and the movement detected by the detection unit 131. The determination unit 133 plots the awakening level and the amount of smiling detected by the detection unit 131 on the Russell ring model.

[0060] The determination unit 133 plots the level of arousal and the amount of smiles before the experience, and the level of arousal and the amount of smiles during the experience, on the Russell circumplex model.

[0061] As a result, the determination unit 133 classifies the user's behavior (arousal level and amount of smiling) into any one of the first, second, third, and fourth quadrants in the Russell Circumplex Model. The determination unit 133 can quantitatively identify emotions by using the Russell Circumplex Model.

[0062] Here, the determination unit 133 identifies four flavors corresponding to the four quadrants based on the item "flavor preference" of the questionnaire data 1221. When the item "flavor preference" is "sweet tooth", the determination unit 133 identifies "strawberry, banana, melon, and milk" as the four flavors. Note that "strawberry", "banana", "melon", and "milk" correspond to the first quadrant, second quadrant, third quadrant, and fourth quadrant, respectively.

[0063] For example, if the item "flavor preference" is "non-sweet tooth," the four flavors are identified as "mint, matcha, coffee, and nuts." Note that "mint," "matcha," "coffee," and "nuts" correspond to the first, second, third, and fourth quadrants, respectively.

[0064] The determination unit 133 determines, as the feature, the type of feature corresponding to the quadrant into which the emotion is classified. For example, in the example of Fig. 4, the arousal level and the amount of smiles before the experience are plotted in the third quadrant, and the emotion of "lethargy / depression" is specified. Also, the arousal level and the amount of smiles during the experience are plotted in the third quadrant, and the emotion of "elation / excitement" is specified.

[0065] The determination unit 133 determines the characteristic based on the emotion identified by. The determination unit 133 determines the flavor corresponding to the quadrant that identifies the emotion as the characteristic. In the example of Fig. 4, the determination unit 133 determines the value of the item "flavor" of the recipe data 150 to be "melon, strawberry".

[0066] In this way, the detection unit 131 detects, as the user's movements, a first movement of the user at a first time (before the experience) and a second movement of the user at a second time (during the experience) after the first time. The determination unit 133 identifies the user's first emotion at the first time based on the first movement, and identifies the user's second emotion at the second time based on the second movement. For example, the first movement is the amount of smiling and the alertness before the experience. Also, for example, the second movement is the amount of smiling and the alertness during the experience.

[0067] This allows the product to reflect not only the emotion at one time point, but also the change in emotion between two or more points in time, which makes the user more interested in the provided product.

[0068] The method by which the determination unit 133 identifies emotions from biological information and movements is not limited to the method using Russell's ring model. The determination unit 133 may use any method that can plot points based on collected information in a two- or more-dimensional space (including a plane) and quantify emotions based on the positions. For example, the determination unit 133 may use a method based on Schlossberg's cone model and the three-way theory of emotions.

[0069] The amount of smile and the level of arousal are examples of information used by the determination unit 133 to identify the emotion. The determination unit 133 may identify the emotion using other information related to biometric information and movements. For example, the determination unit 133 may identify the emotion from the user's facial expression (including facial expressions other than a smile) recognized from an image, or the tone of the user's voice recognized from a voice recorded by a microphone. The determination unit 133 may also identify the emotion from biometric information such as body temperature, heart rate, and blood pressure.

[0070] Furthermore, the determination unit 133 may calculate the degree of emotions, such as the degree of depression, sadness, anger, and relaxation, from the collected information using a predetermined formula, and identify the emotion by plotting points indicating the calculated degrees of two or more emotions in space, instead of the amount of smiles and the degree of arousal.

[0071] The determination unit 133 determines the feature based on the identified change from the first emotion to the second emotion. For example, the information providing device 10 can express the feature based on the change by a combination of two ice creams as described herein.

[0072] Furthermore, the determination unit 133 may determine characteristics such as aroma, type and amount of toppings, and not just taste, based on the emotion.

[0073] Returning to Fig. 3, the determination unit 133 determines the item "degree of mixing" of the recipe data 150 using the texture determination model 1211b based on the item "temperature" of the pre-experience measurement data 1222. "Degree of mixing" is a feature that suggests whether the texture of the ice cream is closer to a smooth texture like gelato or closer to an unsmooth texture like sorbet, depending on the way it is mixed. For example, the texture determination model 1211b outputs a mixing method that makes the texture closer to sorbet the higher the input temperature.

[0074] The determination unit 133 uses the sauce determination model 1211c to determine the second element "amount" of the item "sauce" of the recipe data 150, based on the item "speed" of the experience measurement data 1223. For example, the sauce determination model 1211c increases the amount of sauce to be output as the input speed increases.

[0075] Furthermore, the determination unit 133 determines, as a feature, a trajectory 1223a of the center of gravity position of the user detected by the detection unit 131. The item "toppings" of the recipe data 150 indicates the position in space of the center of gravity for each time (e.g., a spatial vector). According to the item "toppings" of the recipe data 150, the manufacturing device 2 can form a three-dimensional shape along the trajectory 1223a. The three-dimensional shape is formed, for example, by chocolate work.

[0076] Furthermore, the determining unit 133 may determine the trajectory 1223a as a feature of a pattern drawn on the paper or cone container, or on a cookie topping, or the like.

[0077] In this way, the determination unit 133 determines at least one of the appearance, taste, aroma, and feel of the food as a feature based on the action detected by the detection unit 131. The feel of food is sensed by organs in the mouth such as the tongue, and may be rephrased as texture. Generally, when the taste (flavor) of ice cream changes, not only the taste itself but also the color (appearance), aroma, etc. change. For this reason, the "taste" of the recipe data 150 is a feature of the appearance, taste, and aroma. Also, the "mixing level" is a feature of the feel felt in the mouth.

[0078] Furthermore, the determination unit 133 determines the characteristics of the container and tableware for serving the food. For example, the "type" of the recipe data 150 is information for identifying the container. In addition, the determination unit 133 may determine the color and shape of the spoon, which is the tableware provided to the user together with the ice cream.

[0079] The providing unit 134 provides information indicating a procedure for manufacturing a product having the characteristics determined by the determining unit 133, i.e., recipe data 150. The information provided by the providing unit 134 also includes information indicating a procedure for manufacturing a product having at least a part of a three-dimensional shape along the trajectory 1223a.

[0080] In this embodiment, the providing unit 134 provides information indicating a procedure for producing ice cream (an example of a food product) having the characteristics determined by the determining unit 133. The providing unit 134 also provides information for identifying containers and tableware having the characteristics determined by the determining unit 133.

[0081] Unlike content such as images and music, food stimulates multiple human senses. By reflecting the user's actions and emotions in food and related items, the user's senses can be stimulated more and a sense of satisfaction can be given.

[0082] Furthermore, the provision system 1 does not consider the superiority or inferiority of a user's actions or emotions as product features. In other words, the quality of a product is not superior or inferior when the user's emotions are negative (the negative side of each axis in Russell's circular model) versus positive, but the difference in emotions appears as a difference in the direction of the taste. For example, strawberry flavor is not objectively superior to melon flavor.

[0083] Therefore, the user can enjoy a product that reflects his or her own actions and emotions, without feeling that the product is pointing out that his or her own actions or emotions are inferior.

[0084] The providing unit 134 provides the recipe data 150 to the manufacturing apparatus 20. The manufacturing apparatus 20 manufactures ice cream according to the recipe data 150.

[0085] Furthermore, the providing unit 134 provides the terminal 30 with information on the recipe data 150 or a product manufactured using the recipe data 150. For example, the providing unit 134 transmits to the terminal 30 a QR code (registered trademark) that allows the recipe data 150 to be downloaded, an image of the product, and the like.

[0086] For example, the user can publish the images and the like provided by the providing unit 134 on a social networking service (SNS). This makes the content of the service widely known, and can have an effect of attracting customers.

[0087] [Processing flow of the embodiment] The flow of processing performed by the information providing device 10 before the experience will be described with reference to Fig. 5. Fig. 5 is a flowchart showing the flow of processing performed by the information providing device according to the embodiment.

[0088] 5, first, the information providing device 10 collects questionnaire data (step S101). Next, the information providing device 10 detects the user's movements and biological information before the experience (step S102).

[0089] Here, the information providing device 10 collects the detected data (step S103). Until the experience starts (step S104, No), the information providing device 10 repeats the processes of steps S102 and S103.

[0090] When the experience starts (step S104, Yes), the information providing device 10 holds the collected data and proceeds to processing during the experience (step S105).

[0091] The flow of processing of the information providing device 10 during an experience will be described with reference to Fig. 6. Fig. 6 is a flowchart showing the flow of processing of the information providing device according to the embodiment.

[0092] 6, first, the information providing device 10 detects the user's movements and biological information during the experience (step S201), and then collects the detected data (step S202).

[0093] The information providing device 10 repeats the processes of steps S201 and S202 until the experience ends (step S203, No).

[0094] When the experience ends (Yes in step S203), the information providing device 10 stores the collected data and proceeds to post-experience processing (step S204).

[0095] The flow of processing by the information providing device 10 after the experience will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the flow of processing by the information providing device according to the embodiment.

[0096] 7, first, the information providing device 10 determines the characteristics of the product from the data held therein (step S301), then generates recipe data 150 based on the determined characteristics (step S302) and outputs it (step S303).

[0097] The flow of processing for determining a feature based on an emotion will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the flow of processing in the information providing device according to the embodiment.

[0098] The process of Fig. 8 is performed, for example, in step S301 of Fig. 7. As shown in Fig. 8, first, the information providing device 10 identifies four options corresponding to each quadrant of the coordinate plane based on the user's preferences indicated in the questionnaire (step S401). For example, the four options are "strawberry, banana, melon, milk" in Fig. 4.

[0099] Next, the information providing device 10 identifies the quadrant in the coordinate plane of the first point indicating the awakening level and comfort level before the experience (step S402). In the example of Fig. 4, the amount of smiling corresponds to the comfort level.

[0100] Then, the information providing device 10 identifies a quadrant in the coordinate plane of the second point indicating the awakening level and comfort level being experienced (step S403). Furthermore, the information providing device 10 determines options corresponding to the two identified quadrants as features (step S404).

[0101] [Other embodiments] So far, an example has been described in which food (ice cream) is provided as a product. However, the product provided by the provision system 1 is not limited to ice cream. For example, the determination unit 133 can determine at least one of the sole characteristics, size, shape, and appearance of the shoes as characteristics based on the motion detected by the detection unit 131. Then, the provision unit 134 provides information indicating a procedure for manufacturing shoes having the characteristics determined by the determination unit 133. The sole characteristics are cushioning and resilience of the sole, etc. In addition, the determination unit 133 may determine characteristics of shoe laces, shoe bags, boxes, etc. related to the shoes.

[0102] In this case, the manufacturing device 20 is composed of a 3D printer that creates shoe parts, a laser cutter that cuts out the parts, etc. In this way, by reflecting the user's actions and emotions in wearable articles such as shoes, it is possible to stimulate the user's senses more and provide a sense of satisfaction.

[0103] The information collected and the characteristics determined by the information providing device 10 are not limited to those described above. For example, the questionnaire data 1221 may include exercise habits (frequency of exercise in a certain period), fatigue level, satisfaction with sleep, and subjective feelings.

[0104] Furthermore, the pre-experience measurement data 1222 and the during-experience measurement data 1223 may include stride length (stride, pitch), posture (degree of hunched back, left / right difference, degree of straight neck), and the like.

[0105] Ice cream characteristics may also include vitamins, protein content, the presence or absence of toppings such as chocolate chips, flavor intensity, and pattern.

[0106] The provision system 1 may acquire the user's preference regarding the provision of the product in advance, and provide the product in a manner according to the preference. For example, the provision system 1 acquires the number of people who wish to receive the product, the method of providing information about the product (e.g., recipe data) (QR code), etc. as the preference.

[0107] Furthermore, the provision system 1 can provide projection mapping that projects images of the product, images that change depending on the number of times the product is provided, images that are provided to multiple users that are completed by combining all of them, etc. This encourages users to use the service again and spreads good word-of-mouth on SNS, etc.

[0108] Fig. 9 is a diagram showing an example of a hardware configuration of a server according to an embodiment. As shown in Fig. 9, the information providing device 10 includes a computer including a processor 1010, a memory 1020, an input / output IF 1030, and a bus 1040. The processor 1010, the memory 1020, and the input / output IF 1030 can transmit and receive information to and from each other via the bus 1040.

[0109] The processor 1010 executes each function by reading and executing a management program stored in the memory 1020. The processor 1010 is, for example, an example of a processing circuit, and includes one or more of a CPU, a DSP (Digital Signal Processor), and a system LSI (Large Scale Integration).

[0110] The memory 1020 includes one or more of a RAM, a ROM, a flash memory, an EPROM (Erasable Programmable Read Only Memory), and an EEPROM (Electrically Erasable Programmable Read Only Memory). The input / output IF 1030 includes, for example, an AD converter, a DA converter, and an input / output port.

[0111] The information providing device 10 may be configured to include a data reading unit that reads out a computer-readable management program from a recording medium on which the management program is recorded. The processor 1010 controls the data reading unit to obtain the management program recorded in the recording medium from the data reading unit, and can store the obtained management program in the memory 1020. The recording medium includes, for example, one or more of a non-volatile or volatile semiconductor memory, a magnetic disk, a flexible memory, an optical disk, a compact disk, and a DVD (Digital Versatile Disc).

[0112] Furthermore, information providing device 10 may include a communication unit that receives the management program from a server via a network. In this case, processor 1010 can obtain the management program from the server via the communication unit and store the obtained management program in memory 1020.

[0113] The disclosed embodiments should be considered to be illustrative and not restrictive in all respects. Indeed, the above-described embodiments may be embodied in various forms. Furthermore, the above-described embodiments may be omitted, substituted, or modified in various forms without departing from the scope and spirit of the appended claims. [Explanation of symbols]

[0114] 1. Provision system 10 Information provision device 11 Communications Department 12 Storage section 13 Control section 20 Manufacturing equipment 30 Terminals 40, 50 Camera 60 Experience Device 121 Recipe Generation Model Information 122 Collected Data 131 Detection unit 132 Collection Department 133 Decision Section 134 Provision Department 150 Recipe Data 1211 Recipe Generation Models 1211a Taste Decision Model 1211b Texture determination model 1211c Source Determination Model 1221 Survey Data 1222 Pre-experience measurement data 1223 Experience measurement data 1223a locus

Claims

1. A detection unit that detects a user's action; a determination unit that determines a characteristic that can be sensed by a human sense based on the motion detected by the detection unit; a providing unit that provides information indicating a procedure for manufacturing a product having the characteristics determined by the determining unit; An information providing device having the above configuration.

2. an identification unit that identifies an emotion of the user based on the action detected by the detection unit; and The determining unit determines the characteristic based on the emotion identified by the identifying unit.

2. The information providing device according to claim 1.

3. the detection unit detects, as the user's movements, a first movement of the user at a first time and a second movement of the user at a second time after the first time; the identification unit identifies a first emotion of the user at the first time based on the first action, and identifies a second emotion of the user at the second time based on the second action; The determining unit determines the characteristic based on a change from the first emotion to the second emotion identified by the identifying unit.

3. The information providing device according to claim 2.

4. The identification unit classifies the user's emotion into any one of a first quadrant, a second quadrant, a third quadrant, and a fourth quadrant in a Russell cycloid model, The determining unit determines, as the feature, a type of feature corresponding to a quadrant into which the emotion is classified.

3. The information providing device according to claim 2.

5. The detection unit detects a center of gravity position of the user as the movement, The determination unit determines a trajectory of a center of gravity position of the user detected by the detection unit as the feature; The providing unit provides information indicating a procedure for manufacturing a product having at least a part of a three-dimensional shape along the trajectory.

2. The information providing device according to claim 1.

6. The determination unit determines at least one of an appearance, a taste, an aroma, and a feel of the food as the characteristic based on the movement detected by the detection unit, The providing unit provides information indicating a procedure for producing a food product having the characteristics determined by the determining unit.

2. The information providing device according to claim 1.

7. The determining unit determines the characteristics of a container and a dish for serving food; The providing unit provides information for identifying containers and tableware having the characteristics determined by the determining unit.

7. The information providing device according to claim 6.

8. The determination unit determines at least one of a sole characteristic, a size, a shape, and an appearance of the shoe as the feature based on the movement detected by the detection unit, The providing unit provides information indicating a procedure for manufacturing a shoe having the characteristics determined by the determining unit.

2. The information providing device according to claim 1.

9. The detection unit detects biological information of the user, The identification unit identifies an emotion of the user based on the motion and the biological information detected by the detection unit.

3. The information providing device according to claim 2.

10. Detect user actions, determining a characteristic detectable by a human sense based on the detected motion; providing information indicative of a procedure for producing a product having said determined characteristics; A method of providing information in which processing is performed by a computer.

11. Detect user actions, determining a characteristic detectable by a human sense based on the detected motion; providing information indicative of a procedure for producing a product having said determined characteristics; An information providing program that causes a computer to execute processing.

12. A provision system having an information provision device, a camera, and exercise equipment equipped with a computer, The camera transmits a captured image to the information providing device, the exercise equipment transmits information regarding the operation of the exercise equipment to the information providing device; The information providing device includes: A detection unit that detects a user's movement based on information received from the camera and the exercise equipment; a determination unit that determines a characteristic that can be sensed by a human sense based on the motion detected by the detection unit; a providing unit that provides information indicating a procedure for manufacturing a product having the characteristics determined by the determining unit; A provision system having the above configuration.

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