System

Abstract

An object of a system according to an embodiment is to understand needs of an elderly person, propose an appropriate product, and support a purchase procedure.SOLUTION: A system according to an embodiment includes a need understanding unit, a product proposal unit, and a purchase support unit. The needs understanding unit understands needs of an elderly person. The product proposal unit proposes a product based on the needs of the elderly person understood by the needs understanding unit. The purchase support unit supports a purchase procedure of the product proposed by the product proposal unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technologies have had the problem of not being able to accurately understand the needs of elderly people, suggest appropriate products, and provide sufficient support for the purchasing process.

[0005] The system according to the embodiment aims to understand the needs of elderly people, suggest appropriate products, and assist them in the purchasing process. [Means for solving the problem]

[0006] The system according to the embodiment includes a needs understanding unit, a product proposal unit, and a purchase support unit. The needs understanding unit understands the needs of elderly people. The product proposal unit proposes products based on the needs of elderly people understood by the needs understanding unit. The purchase support unit supports the purchase procedure for the products proposed by the product proposal unit. [Effects of the Invention]

[0007] The system according to the embodiment can understand the needs of the elderly, suggest appropriate products, and assist in the purchasing process. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The online purchasing service according to an embodiment of the present invention is a system that utilizes generative AI to help elderly people who lack transportation purchase groceries and daily necessities. This system understands the needs of elderly people, suggests optimal products, and assists in the purchasing process. As a result, the online purchasing service allows elderly people to purchase groceries and daily necessities easily and safely.

[0029] An online purchasing service according to an embodiment includes a needs understanding unit, a product proposal unit, and a purchase support unit. The needs understanding unit understands the needs of elderly people. For example, the needs understanding unit analyzes data such as the elderly person's past purchase history, preferences, and health status to understand their individual needs. The needs understanding unit can also use a generation AI to estimate the elderly person's emotions and adjust the products to be proposed based on those emotions. For example, the generation AI can estimate the elderly person's emotions and propose products with a relaxing effect when they are under high stress. The product proposal unit proposes products based on the elderly person's needs understood by the needs understanding unit. For example, the product proposal unit can analyze the elderly person's lifestyle patterns using the generation AI to propose products that are optimal for specific time periods. The product proposal unit can also propose health-conscious products based on the elderly person's health status. The purchase support unit supports the purchase process for the products proposed by the product proposal unit. For example, the purchase support unit uses the generation AI to support elderly people in smoothly completing online purchase processes. The purchase support unit can also estimate the elderly person's emotions and propose ways to simplify the process if the elderly person is feeling stressed. As a result, the online purchasing service according to the embodiment can understand the needs of elderly people, suggest optimal products, and assist with the purchasing process.

[0030] The needs understanding unit can analyze the lifestyle patterns of elderly people and suggest products that are optimal for specific time periods. For example, the needs understanding unit analyzes the lifestyle patterns of elderly people and suggests breakfast products during breakfast time. For example, it suggests cereal, yogurt, fruit, etc. The needs understanding unit also suggests ingredients for easy-to-prepare lunch sets and sandwiches during lunch time. For example, it suggests bread and toppings for salads and sandwiches. The needs understanding unit also suggests nutritionally balanced frozen foods and pre-cooked meals during dinner time. For example, it suggests frozen fish dishes and soups with lots of vegetables. This makes it possible to make more appropriate product suggestions by making product suggestions based on the lifestyle patterns of elderly people.

[0031] The needs understanding unit can collect feedback from the elderly person's family and caregivers and customize product suggestions based on that. For example, the needs understanding unit collects feedback from the elderly person's family and caregivers and adjusts the suggestions to avoid specific ingredients and products. For example, it can suggest products that do not contain ingredients that the elderly person is allergic to. The needs understanding unit also suggests products that suit the elderly person's preferences and health condition based on the opinions of the family and caregivers. For example, it can suggest low-sugar foods and low-salt seasonings. The needs understanding unit also allows family and caregivers to share the elderly person's lifestyle rhythms and dietary preferences, allowing the generation AI to make more personalized product suggestions. For example, it can suggest specific ingredients on specific days of the week. This makes it possible to customize product suggestions based on feedback from family and caregivers, thereby making it possible to make more appropriate product suggestions.

[0032] The needs understanding unit can suggest related products and services based on the hobbies and interests of elderly people. For example, if an elderly person's hobby is gardening, the needs understanding unit will suggest gardening supplies, plant seeds, fertilizer, etc. For example, it will suggest flower seeds and gardening tools that are appropriate for the season. Furthermore, if an elderly person's hobby is reading, the needs understanding unit will suggest the latest bestsellers and recommended books by genre. For example, it will suggest mystery novels and history books. Furthermore, if an elderly person's hobby is cooking, the needs understanding unit will suggest cooking recipe books, cooking utensils, and special ingredients. For example, it will suggest Japanese cuisine recipe books and high-quality knives. This makes it possible to make more appropriate product suggestions by making product suggestions based on the hobbies and interests of elderly people.

[0033] The needs understanding unit can suggest regional products based on the living environment of the elderly. For example, the needs understanding unit suggests convenient delivery services and products suited to urban life to elderly people living in urban areas. For example, it suggests home delivery lunches and small urban home appliances. The needs understanding unit also suggests products that can make use of gardens and large spaces to elderly people living in suburban areas. For example, it suggests kits for home vegetable gardening and outdoor equipment. The needs understanding unit also suggests local specialties and products useful for farm work to elderly people living in rural areas. For example, it suggests fresh local vegetables and gloves for farm work. In this way, more appropriate product suggestions can be made by making product suggestions based on the living environment of the elderly.

[0034] The purchase support unit can analyze the operation history of an elderly person and suggest frequently used operations as shortcuts. The purchase support unit, for example, analyzes the operation history of an elderly person and suggests frequently used operations as shortcuts. For example, it displays a button that allows frequently purchased items to be added to a cart with one click. The purchase support unit also provides functions and settings that are frequently used by elderly people as shortcuts based on the operation history. For example, it presents options to automatically select frequently used payment methods and delivery addresses. The purchase support unit also analyzes the operation patterns of elderly people and suggests shortcuts to efficiently proceed with the purchase process. For example, it displays a list of products that have been purchased in the past, making it easy to repurchase them. In this way, by suggesting shortcuts based on the elderly person's operation history, the purchase process can be carried out efficiently.

[0035] The purchase support unit can customize the font size of the interface and the voice guidance according to the visual and hearing conditions of the elderly person. For example, the purchase support unit automatically adjusts the font size of the interface according to the visual condition of the elderly person. For example, if the elderly person's eyesight is impaired, a larger font size is used. The purchase support unit also customizes the volume and speed of the voice guidance according to the hearing condition. For example, if the elderly person's hearing is impaired, the volume is increased and the guidance is given at a slower speed. The purchase support unit also adjusts the color and contrast of the interface based on the visual and hearing conditions of the elderly person. For example, if the elderly person has color vision deficiency, an easy-to-see color is used. In this way, customizing the interface according to the visual and hearing conditions of the elderly person makes the purchase process go more smoothly.

[0036] The purchase support department can propose interface themes that match the preferences of elderly people. The purchase support department, for example, proposes interface themes that match the preferences of elderly people. For example, it provides themes with simple, easy-to-read designs and favorite colors. The purchase support department also automatically proposes themes that match the preferences of elderly people based on interface themes previously selected by the elderly people. For example, it presents designs similar to themes previously selected. The purchase support department also proposes customized interface themes based on the hobbies and interests of elderly people. For example, it provides a theme with a plant motif to an elderly person who enjoys gardening. In this way, by proposing interface themes that match the preferences of elderly people, the purchase process can be carried out more smoothly.

[0037] In the purchasing support department, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing any questions to be resolved immediately. In the purchasing support department, for example, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing any questions to be resolved immediately. For example, they can ask questions about problems that arise during the purchasing process through chat and receive an immediate answer. The purchasing support department also uses the support chat to resolve any questions or concerns seniors may have regarding the purchasing process. For example, it provides real-time answers to questions about changing payment methods or shipping addresses. In addition, the purchasing support department uses the generation AI to predict questions that will arise during the purchasing process and provides guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows real-time support to be provided when seniors go through the purchasing process, allowing any questions to be resolved immediately.

[0038] The product proposal unit can monitor the health data of elderly people in real time and update product proposals according to changes in their health condition. For example, the product proposal unit monitors the health data of elderly people in real time and updates product proposals according to fluctuations in blood pressure and blood sugar levels. For example, if blood pressure is high, low-salt foods are proposed. The product proposal unit also makes product proposals according to changes in season and weather based on the health data. For example, supplements containing vitamin D are proposed in winter. The product proposal unit also monitors the exercise data of elderly people and proposes nutritional supplements according to the amount of exercise. For example, a protein shake is proposed after exercise. In this way, by monitoring the health data of elderly people in real time and updating product proposals according to changes in their health condition, more appropriate product proposals are possible.

[0039] The product proposal unit can collect feedback from doctors and nutritionists for elderly people and customize product proposals based on that. For example, the product proposal unit collects feedback from doctors for elderly people and proposes products suitable for specific health conditions. For example, it proposes low-calorie foods recommended by doctors. The product proposal unit also makes product proposals that take into account the dietary balance of elderly people based on feedback from nutritionists. For example, it proposes foods containing vitamins and minerals recommended by nutritionists. The product proposal unit also reflects the opinions of doctors and nutritionists and makes product proposals tailored to specific health goals of elderly people. For example, it proposes low-calorie snacks for elderly people who are aiming to manage their weight. In this way, by customizing product proposals based on feedback from doctors and nutritionists, more appropriate product proposals can be made.

[0040] The product proposal department can also suggest exercise equipment and fitness programs based on the health condition of the elderly person. For example, the product proposal department considers the health condition of the elderly person and suggests appropriate exercise equipment. For example, it suggests an exercise bike that is gentle on the joints or a stretching mat. The product proposal department also suggests individually customized fitness programs based on the health condition. For example, it suggests low-impact exercise or yoga programs. The product proposal department also suggests equipment and programs to maximize the effects of exercise based on the exercise data of the elderly person. For example, it suggests a walking program while monitoring the heart rate. This makes it possible to suggest more appropriate products by suggesting exercise equipment and fitness programs based on the health condition of the elderly person.

[0041] The product proposal unit can propose recipes and meal plans that suit the health condition of the elderly person and provide ingredients based on them. For example, the product proposal unit proposes recipes that take into account the health condition of the elderly person and provides ingredients based on them. For example, it proposes low-salt meal plans or carbohydrate-restricted recipes. The product proposal unit also customizes meal plans that suit the health condition and provides the necessary ingredients all at once. For example, it proposes ingredient sets based on weekly meal plans. The product proposal unit also proposes recipes that take into account the nutritional balance of the elderly person and provides ingredients based on them. For example, it proposes recipes that include ingredients rich in vitamins and minerals. This makes it possible to propose more appropriate products by proposing recipes and meal plans that suit the health condition of the elderly person and providing ingredients based on them.

[0042] The regular purchase suggestion unit can analyze the consumption patterns of elderly people and suggest the optimal regular purchase frequency. The regular purchase suggestion unit, for example, analyzes the consumption patterns of elderly people and suggests the optimal regular purchase frequency. For example, for products that are purchased weekly, it suggests weekly regular purchases. The regular purchase suggestion unit also predicts the timing of replenishment of products needed by elderly people based on the consumption patterns and suggests the optimal regular purchase frequency. For example, for products that are purchased once a month, it suggests monthly regular purchases. The regular purchase suggestion unit also analyzes the consumption patterns of elderly people and suggests regular purchase frequencies that match seasons and events. For example, it suggests products that are needed for each season. This makes it possible to make more appropriate suggestions by suggesting the optimal regular purchase frequency based on the consumption patterns of elderly people.

[0043] The regular purchase suggestion unit can customize the timing of regular purchases to suit the lifestyle rhythm of the elderly. The regular purchase suggestion unit, for example, analyzes the lifestyle rhythm of the elderly and customizes the optimal timing of regular purchases. For example, for an elderly person who cannot live without coffee every morning, the regular purchase suggestion unit may suggest a monthly regular purchase of coffee beans. The regular purchase suggestion unit may also adjust the timing of regular purchases based on the lifestyle rhythm so that products are delivered on a specific day of the week or time of day. For example, for an elderly person who does all their shopping on the weekend, the regular purchase suggestion unit may suggest that products be delivered on the weekend. The regular purchase suggestion unit may also take into account the lifestyle rhythm of the elderly and suggest the timing of regular purchases to coincide with specific events or occasions. For example, regular purchases of food ingredients may be made to coincide with monthly family gatherings. In this way, more appropriate suggestions can be made by customizing the timing of regular purchases based on the lifestyle rhythm of the elderly.

[0044] The subscription suggestion unit can suggest benefits and discounts that match the preferences of seniors. For example, the subscription suggestion unit suggests benefits and discounts that match the preferences of seniors. For example, by setting up a subscription, discounts or points can be provided for specific products. The subscription suggestion unit also customizes benefits and discounts based on products and services that seniors have purchased in the past. For example, it can suggest discounts for frequently purchased products. Furthermore, when a subscription is made, the generation AI suggests benefits and discounts that match the preferences of seniors. For example, it can offer discounts for products of specific brands or categories. This makes it possible to make more appropriate suggestions by suggesting benefits and discounts that match the preferences of seniors.

[0045] The subscription suggestion unit uses the generation AI to provide real-time support chat when seniors are setting up a subscription, allowing them to immediately resolve any questions they may have. For example, when seniors are setting up a subscription, the generation AI provides real-time support chat to immediately resolve any questions they may have. For example, they can ask questions about problems that arise during the subscription process through chat and receive an immediate answer. The subscription suggestion unit also uses the support chat to resolve seniors' questions and concerns about subscriptions. For example, it provides real-time answers to questions about how to cancel a subscription or how to make changes. The subscription suggestion unit also predicts questions that seniors may have while setting up a subscription and provides guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows seniors to immediately resolve their questions by providing real-time support when setting up a subscription.

[0046] The delivery notification unit can analyze the elderly person's past delivery history and suggest the optimal notification timing. The delivery notification unit, for example, analyzes the elderly person's past delivery history and suggests the optimal notification timing. For example, the optimal notification timing is set based on the time period in which delivery notifications were received in the past. The delivery notification unit also suggests the notification timing that will give the elderly person the most peace of mind based on the delivery history. For example, it may notify the elderly person when delivery is approaching and notify them of the estimated arrival time. The delivery notification unit also customizes the optimal notification timing taking into account the elderly person's lifestyle rhythm. For example, it may notify them based on their daytime activity times. This makes it possible to provide more appropriate notifications by suggesting the optimal notification timing based on the elderly person's past delivery history.

[0047] The delivery notification unit can customize the notification format and voice guidance according to the visual and hearing conditions of the elderly person. For example, the delivery notification unit automatically adjusts the notification format according to the visual condition of the elderly person. For example, if the elderly person's eyesight is impaired, a larger font size is used. The delivery notification unit also customizes the volume and speed of the voice guidance according to the hearing condition. For example, if the elderly person's hearing is impaired, the volume is increased and the guidance is given at a slower speed. The delivery notification unit also adjusts the color and contrast of the notification based on the visual and hearing conditions of the elderly person. For example, if the elderly person has color vision deficiency, a color that is easy to see is used. This allows for more appropriate notifications to be provided by customizing the notification according to the visual and hearing conditions of the elderly person.

[0048] The delivery notification unit can suggest notification themes that match the preferences of elderly people. The delivery notification unit, for example, suggests notification themes that match the preferences of elderly people. For example, it provides themes with simple, easy-to-read designs and favorite colors. The delivery notification unit also automatically suggests themes that match the preferences of elderly people based on notification themes previously selected by the elderly people. For example, it presents designs similar to themes previously selected. The delivery notification unit also suggests customized notification themes based on the hobbies and interests of elderly people. For example, it provides a theme with a plant motif to an elderly person who enjoys gardening. This allows for more appropriate notifications by suggesting notification themes that match the preferences of elderly people.

[0049] In the delivery notification unit, when elderly people check their delivery status, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. In the delivery notification unit, for example, when elderly people check their delivery status, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. For example, they can ask questions about the delivery status through chat and receive an immediate answer. The delivery notification unit also resolves elderly people's questions and concerns about the delivery status through the support chat. For example, it provides real-time answers to questions about delivery delays or changes. In addition, the delivery notification unit predicts questions that may arise when elderly people check their delivery status and provides guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows elderly people to receive real-time support when checking their delivery status, allowing them to immediately resolve any questions they may have.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The needs understanding department can suggest related products and services based on the hobbies and interests of elderly people. For example, if an elderly person's hobby is gardening, gardening supplies, plant seeds, fertilizer, etc. will be suggested. For example, seasonal flower seeds and gardening tools will be suggested. Furthermore, if an elderly person's hobby is reading, the needs understanding department will suggest the latest bestsellers and recommended books by genre. For example, mystery novels and history books will be suggested. Furthermore, if an elderly person's hobby is cooking, the needs understanding department will suggest cooking recipe books, cooking utensils, and special ingredients. For example, Japanese cuisine recipe books and high-quality kitchen knives will be suggested. This makes it possible to make more appropriate product suggestions by making product suggestions based on the hobbies and interests of elderly people.

[0052] The needs understanding department can suggest regional products based on the living environment of the elderly. For example, for elderly people living in urban areas, it can suggest convenient delivery services and products suitable for urban life. For example, it can suggest delivery lunch boxes and small urban home appliances. For elderly people living in suburban areas, it can suggest products that can make use of gardens and large spaces. For example, it can suggest kits for home gardening and outdoor equipment. For elderly people living in rural areas, it can suggest local specialties and products useful for farm work. For example, it can suggest fresh local vegetables and gloves for farm work. This makes it possible to suggest more appropriate products by making product suggestions based on the living environment of the elderly.

[0053] The purchase support unit can analyze the operation history of elderly people and suggest frequently used operations as shortcuts. For example, it can analyze the operation history of elderly people and suggest frequently used operations as shortcuts. For example, it can display a button that allows frequently purchased items to be added to a cart with one click. The purchase support unit can also provide functions and settings that elderly people often use as shortcuts based on the operation history. For example, it can present options to automatically select frequently used payment methods and delivery addresses. The purchase support unit can also analyze the operation patterns of elderly people and suggest shortcuts to efficiently proceed with the purchase process. For example, it can display a list of products that have been purchased in the past, making it easy to repurchase them. In this way, by suggesting shortcuts based on the elderly people's operation history, the purchase process can be carried out efficiently.

[0054] The purchasing support department can customize the font size of the interface and the voice guidance according to the visual and hearing conditions of the elderly person. For example, the font size of the interface can be automatically adjusted according to the visual condition of the elderly person. For example, if the elderly person's eyesight is impaired, a larger font size can be used. The purchasing support department also customizes the volume and speed of the voice guidance according to the hearing condition. For example, if the elderly person's hearing is impaired, the volume can be increased and the guidance can be given at a slower speed. The purchasing support department also adjusts the color and contrast of the interface based on the visual and hearing conditions of the elderly person. For example, if the elderly person has color vision deficiency, a color that is easy to see can be used. In this way, customizing the interface according to the visual and hearing conditions of the elderly person makes the purchasing process go more smoothly.

[0055] In the purchasing support department, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. For example, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. For example, they can ask about problems that arise during the purchasing process through chat and receive an immediate answer. The purchasing support department also uses the support chat to resolve any questions or concerns seniors may have regarding the purchasing process. For example, it provides real-time answers to questions about changing payment methods or shipping addresses. The purchasing support department also uses the generation AI to predict questions that seniors may have during the purchasing process and provide guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows seniors to receive real-time support as they go through the purchasing process, allowing them to immediately resolve any questions they may have.

[0056] The product proposal department can also suggest exercise equipment and fitness programs based on the health condition of the elderly person. For example, it proposes appropriate exercise equipment taking into consideration the health condition of the elderly person. For example, it proposes an exercise bike that is gentle on the joints or a stretching mat. The product proposal department also proposes individually customized fitness programs based on the health condition. For example, it proposes low-impact exercise or yoga programs. The product proposal department also proposes equipment and programs to maximize the effects of exercise based on the exercise data of the elderly person. For example, it proposes a walking program while monitoring the heart rate. This makes it possible to suggest more appropriate products by suggesting exercise equipment and fitness programs based on the health condition of the elderly person.

[0057] The product proposal department can propose recipes and meal plans that take into account the health condition of the elderly person and provide ingredients based on them. For example, it proposes recipes that take into account the health condition of the elderly person and provides ingredients based on them. For example, it proposes low-salt meal plans or carbohydrate-restricted recipes. The product proposal department also customizes meal plans that take into account the health condition and provides the necessary ingredients all at once. For example, it proposes ingredient sets based on weekly meal plans. The product proposal department also proposes recipes that take into account the nutritional balance of the elderly person and provides ingredients based on them. For example, it proposes recipes that include ingredients rich in vitamins and minerals. This makes it possible to propose more appropriate products by proposing recipes and meal plans that take into account the health condition of the elderly person and providing ingredients based on them.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The needs understanding unit understands the needs of seniors. For example, the needs understanding unit analyzes data such as seniors' past purchase history, preferences, and health status to understand their individual needs. It can also use the generation AI to estimate the emotions of seniors and adjust the products it recommends based on those emotions. For example, the generation AI can estimate the emotions of seniors and suggest products that have a relaxing effect when they are under a lot of stress. Step 2: The product proposal department proposes products based on the needs of seniors as understood by the needs understanding department. For example, the product proposal department can use generative AI to analyze the lifestyle patterns of seniors and propose products that are optimal for specific time periods. It can also propose health-conscious products based on the seniors' health conditions. Step 3: The purchasing support department assists with the purchase process for the product suggested by the product proposal department. For example, the purchasing support department uses generative AI to help seniors smoothly complete online purchase procedures. It can also estimate the emotions of seniors and make suggestions to simplify the process if they are feeling stressed.

[0060] (Example 2) The online purchasing service according to an embodiment of the present invention is a system that utilizes generative AI to help elderly people who lack transportation purchase groceries and daily necessities. This system understands the needs of elderly people, suggests optimal products, and assists in the purchasing process. As a result, the online purchasing service allows elderly people to purchase groceries and daily necessities easily and safely.

[0061] An online purchasing service according to an embodiment includes a needs understanding unit, a product proposal unit, and a purchase support unit. The needs understanding unit understands the needs of elderly people. For example, the needs understanding unit analyzes data such as the elderly person's past purchase history, preferences, and health status to understand their individual needs. The needs understanding unit can also use a generation AI to estimate the elderly person's emotions and adjust the products to be proposed based on those emotions. For example, the generation AI can estimate the elderly person's emotions and propose products with a relaxing effect when they are under high stress. The product proposal unit proposes products based on the elderly person's needs understood by the needs understanding unit. For example, the product proposal unit can analyze the elderly person's lifestyle patterns using the generation AI to propose products that are optimal for specific time periods. The product proposal unit can also propose health-conscious products based on the elderly person's health status. The purchase support unit supports the purchase process for the products proposed by the product proposal unit. For example, the purchase support unit uses the generation AI to support elderly people in smoothly completing online purchase processes. The purchase support unit can also estimate the elderly person's emotions and propose ways to simplify the process if the elderly person is feeling stressed. As a result, the online purchasing service according to the embodiment can understand the needs of elderly people, suggest optimal products, and assist with the purchasing process.

[0062] The needs understanding unit can estimate the emotions of elderly people and adjust the products it recommends based on those emotions. For example, the needs understanding unit uses a generative AI to estimate the emotions of elderly people and suggest products with a relaxing effect when they are under high stress. For example, it can suggest herbal tea or aroma oils with a relaxing effect. Furthermore, if an elderly person is feeling happy or excited, the needs understanding unit can suggest high-quality sweets or gift sets as a special reward. For example, it can suggest high-quality chocolates or fruit baskets for special occasions. Furthermore, if an elderly person is feeling sad or lonely, the needs understanding unit can suggest entertainment products or hobby-related products to brighten their mood. For example, it can suggest movie DVDs or craft kits. This makes it possible to adjust product suggestions based on the emotions of elderly people, thereby making it possible to make more appropriate product suggestions.

[0063] The needs understanding unit can analyze the lifestyle patterns of elderly people and suggest products that are optimal for specific time periods. For example, the needs understanding unit analyzes the lifestyle patterns of elderly people and suggests breakfast products during breakfast time. For example, it suggests cereal, yogurt, fruit, etc. The needs understanding unit also suggests ingredients for easy-to-prepare lunch sets and sandwiches during lunch time. For example, it suggests bread and toppings for salads and sandwiches. The needs understanding unit also suggests nutritionally balanced frozen foods and pre-cooked meals during dinner time. For example, it suggests frozen fish dishes and soups with lots of vegetables. This makes it possible to make more appropriate product suggestions by making product suggestions based on the lifestyle patterns of elderly people.

[0064] The needs understanding unit can collect feedback from the elderly person's family and caregivers and customize product suggestions based on that. For example, the needs understanding unit collects feedback from the elderly person's family and caregivers and adjusts the suggestions to avoid specific ingredients and products. For example, it can suggest products that do not contain ingredients that the elderly person is allergic to. The needs understanding unit also suggests products that suit the elderly person's preferences and health condition based on the opinions of the family and caregivers. For example, it can suggest low-sugar foods and low-salt seasonings. The needs understanding unit also allows family and caregivers to share the elderly person's lifestyle rhythms and dietary preferences, allowing the generation AI to make more personalized product suggestions. For example, it can suggest specific ingredients on specific days of the week. This makes it possible to customize product suggestions based on feedback from family and caregivers, thereby making it possible to make more appropriate product suggestions.

[0065] The needs understanding unit can suggest related products and services based on the hobbies and interests of elderly people. For example, if an elderly person's hobby is gardening, the needs understanding unit will suggest gardening supplies, plant seeds, fertilizer, etc. For example, it will suggest flower seeds and gardening tools that are appropriate for the season. Furthermore, if an elderly person's hobby is reading, the needs understanding unit will suggest the latest bestsellers and recommended books by genre. For example, it will suggest mystery novels and history books. Furthermore, if an elderly person's hobby is cooking, the needs understanding unit will suggest cooking recipe books, cooking utensils, and special ingredients. For example, it will suggest Japanese cuisine recipe books and high-quality knives. This makes it possible to make more appropriate product suggestions by making product suggestions based on the hobbies and interests of elderly people.

[0066] The needs understanding unit can suggest regional products based on the living environment of the elderly. For example, the needs understanding unit suggests convenient delivery services and products suited to urban life to elderly people living in urban areas. For example, it suggests home delivery lunches and small urban home appliances. The needs understanding unit also suggests products that can make use of gardens and large spaces to elderly people living in suburban areas. For example, it suggests kits for home vegetable gardening and outdoor equipment. The needs understanding unit also suggests local specialties and products useful for farm work to elderly people living in rural areas. For example, it suggests fresh local vegetables and gloves for farm work. In this way, more appropriate product suggestions can be made by making product suggestions based on the living environment of the elderly.

[0067] The needs understanding unit uses the emotion estimation function to analyze in real time how seniors feel about product proposals and adjust the content of the proposals. For example, the generation AI in the needs understanding unit analyzes the seniors' facial expressions and voices to analyze their emotions toward the product proposals in real time. For example, if the seniors show a happy expression toward the proposed product, the generation AI will prioritize the proposal. Furthermore, if the seniors are dissatisfied or have doubts about the proposed product, the generation AI will detect that emotion and suggest a different product. For example, if the seniors have a negative reaction to the proposed product, an alternative product will be suggested. Furthermore, the needs understanding unit uses the emotion estimation function to analyze whether seniors have positive emotions toward the proposed product and adjust the content of the proposals. For example, if the seniors show interest in the proposed product, other products related to that product will also be suggested. This enables more appropriate product proposals to be made by adjusting product proposals in real time based on the seniors' emotions.

[0068] The purchasing support department can estimate the emotions of elderly people and make suggestions to simplify the process if they are feeling stressed. For example, the generation AI analyzes the facial expressions and voice of elderly people and makes suggestions to simplify the process if they are feeling stressed. For example, it presents options to complete the purchase process with one click. Furthermore, if an elderly person feels anxious or confused during the process, the generation AI detects that emotion and provides guidance to simplify the process. For example, it displays simple step-by-step instructions. Furthermore, the purchasing support department uses the emotion estimation function to analyze in real time whether an elderly person is feeling stressed during the process and makes suggestions to simplify the process. For example, it guides the elderly person to skip complicated procedures and enter only the minimum necessary information. This simplifies the process if the elderly person is feeling stressed, allowing the purchase process to go more smoothly.

[0069] The purchase support unit can analyze the operation history of an elderly person and suggest frequently used operations as shortcuts. The purchase support unit, for example, analyzes the operation history of an elderly person and suggests frequently used operations as shortcuts. For example, it displays a button that allows frequently purchased items to be added to a cart with one click. The purchase support unit also provides functions and settings that are frequently used by elderly people as shortcuts based on the operation history. For example, it presents options to automatically select frequently used payment methods and delivery addresses. The purchase support unit also analyzes the operation patterns of elderly people and suggests shortcuts to efficiently proceed with the purchase process. For example, it displays a list of products that have been purchased in the past, making it easy to repurchase them. In this way, by suggesting shortcuts based on the elderly person's operation history, the purchase process can be carried out efficiently.

[0070] The purchase support unit can customize the font size of the interface and the voice guidance according to the visual and hearing conditions of the elderly person. For example, the purchase support unit automatically adjusts the font size of the interface according to the visual condition of the elderly person. For example, if the elderly person's eyesight is impaired, a larger font size is used. The purchase support unit also customizes the volume and speed of the voice guidance according to the hearing condition. For example, if the elderly person's hearing is impaired, the volume is increased and the guidance is given at a slower speed. The purchase support unit also adjusts the color and contrast of the interface based on the visual and hearing conditions of the elderly person. For example, if the elderly person has color vision deficiency, an easy-to-see color is used. In this way, customizing the interface according to the visual and hearing conditions of the elderly person makes the purchase process go more smoothly.

[0071] The purchase support department can propose interface themes that match the preferences of elderly people. The purchase support department, for example, proposes interface themes that match the preferences of elderly people. For example, it provides themes with simple, easy-to-read designs and favorite colors. The purchase support department also automatically proposes themes that match the preferences of elderly people based on interface themes previously selected by the elderly people. For example, it presents designs similar to themes previously selected. The purchase support department also proposes customized interface themes based on the hobbies and interests of elderly people. For example, it provides a theme with a plant motif to an elderly person who enjoys gardening. In this way, by proposing interface themes that match the preferences of elderly people, the purchase process can be carried out more smoothly.

[0072] In the purchasing support department, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing any questions to be resolved immediately. In the purchasing support department, for example, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing any questions to be resolved immediately. For example, they can ask questions about problems that arise during the purchasing process through chat and receive an immediate answer. The purchasing support department also uses the support chat to resolve any questions or concerns seniors may have regarding the purchasing process. For example, it provides real-time answers to questions about changing payment methods or shipping addresses. In addition, the purchasing support department uses the generation AI to predict questions that will arise during the purchasing process and provides guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows real-time support to be provided when seniors go through the purchasing process, allowing any questions to be resolved immediately.

[0073] The purchasing support department can use the emotion estimation function to detect in real time any anxieties or questions that seniors may have during the process and provide appropriate support. For example, the purchasing support department can use the emotion estimation function to detect in real time any anxieties or questions that seniors may have during the process and provide appropriate support. For example, if they are feeling anxious, detailed explanations or guides can be displayed. Furthermore, if a senior has a question during the process, the purchasing support department's generation AI detects that emotion and immediately provides an answer through a support chat. For example, questions about payment methods can be answered in real time. Furthermore, the purchasing support department can use the emotion estimation function to provide support to reduce the stress that seniors feel during the process. For example, if the process is complicated, it can guide them through a simplified procedure. In this way, the purchasing process can be carried out smoothly by detecting in real time any anxieties or questions that seniors may have during the process and providing appropriate support.

[0074] The product proposal department can suggest health-conscious products based on the health condition of the elderly. For example, the generation AI estimates the emotions of the elderly and suggests health foods and supplements according to their emotional state. For example, the generation AI estimates the emotions of the elderly and suggests health foods and supplements that have a relaxing effect when stress levels are high. For example, it suggests chamomile tea or magnesium supplements. Furthermore, if the elderly person is feeling tired, the product proposal department suggests health foods and supplements that help replenish energy. For example, it suggests vitamin B supplements or protein bars. Furthermore, if the elderly person is feeling depressed, the product proposal department suggests health foods and supplements that have a mood-boosting effect. For example, it suggests supplements containing omega-3 fatty acids or dark chocolate. This enables more appropriate product suggestions by suggesting health-conscious products based on the elderly person's health condition.

[0075] The product proposal unit can monitor the health data of elderly people in real time and update product proposals according to changes in their health condition. For example, the product proposal unit monitors the health data of elderly people in real time and updates product proposals according to fluctuations in blood pressure and blood sugar levels. For example, if blood pressure is high, low-salt foods are proposed. The product proposal unit also makes product proposals according to changes in season and weather based on the health data. For example, supplements containing vitamin D are proposed in winter. The product proposal unit also monitors the exercise data of elderly people and proposes nutritional supplements according to the amount of exercise. For example, a protein shake is proposed after exercise. In this way, by monitoring the health data of elderly people in real time and updating product proposals according to changes in their health condition, more appropriate product proposals are possible.

[0076] The product proposal unit can collect feedback from doctors and nutritionists for elderly people and customize product proposals based on that. For example, the product proposal unit collects feedback from doctors for elderly people and proposes products suitable for specific health conditions. For example, it proposes low-calorie foods recommended by doctors. The product proposal unit also makes product proposals that take into account the dietary balance of elderly people based on feedback from nutritionists. For example, it proposes foods containing vitamins and minerals recommended by nutritionists. The product proposal unit also reflects the opinions of doctors and nutritionists and makes product proposals tailored to specific health goals of elderly people. For example, it proposes low-calorie snacks for elderly people who are aiming to manage their weight. In this way, by customizing product proposals based on feedback from doctors and nutritionists, more appropriate product proposals can be made.

[0077] The product proposal department can also suggest exercise equipment and fitness programs based on the health condition of the elderly person. For example, the product proposal department considers the health condition of the elderly person and suggests appropriate exercise equipment. For example, it suggests an exercise bike that is gentle on the joints or a stretching mat. The product proposal department also suggests individually customized fitness programs based on the health condition. For example, it suggests low-impact exercise or yoga programs. The product proposal department also suggests equipment and programs to maximize the effects of exercise based on the exercise data of the elderly person. For example, it suggests a walking program while monitoring the heart rate. This makes it possible to suggest more appropriate products by suggesting exercise equipment and fitness programs based on the health condition of the elderly person.

[0078] The product proposal unit can propose recipes and meal plans that suit the health condition of the elderly person and provide ingredients based on them. For example, the product proposal unit proposes recipes that take into account the health condition of the elderly person and provides ingredients based on them. For example, it proposes low-salt meal plans or carbohydrate-restricted recipes. The product proposal unit also customizes meal plans that suit the health condition and provides the necessary ingredients all at once. For example, it proposes ingredient sets based on weekly meal plans. The product proposal unit also proposes recipes that take into account the nutritional balance of the elderly person and provides ingredients based on them. For example, it proposes recipes that include ingredients rich in vitamins and minerals. This makes it possible to propose more appropriate products by proposing recipes and meal plans that suit the health condition of the elderly person and providing ingredients based on them.

[0079] The product proposal unit can use the emotion estimation function to analyze how the elderly feel about health-related proposals and adjust the content of the proposals. For example, the product proposal unit uses the emotion estimation function to analyze in real time how the elderly feel about health-related proposals. For example, if the elderly express positive emotions toward a recommended health food, the product proposal unit prioritizes the recommendation of that product. Furthermore, if the elderly feel anxious or have doubts about a health-related proposal, the product proposal unit uses the generation AI to detect that emotion and make a different proposal. For example, if the elderly feel anxious about a recommended exercise program, the product proposal unit suggests a different program. Furthermore, the product proposal unit uses the emotion estimation function to analyze whether the elderly feel positive emotions about health-related proposals and adjust the content of the proposals. For example, if the elderly express interest in a recommended recipe, the product proposal unit also suggests other recipes related to that recipe. This allows for more appropriate product proposals to be made by adjusting the content of health-related proposals based on the elderly's emotions.

[0080] The subscription suggestion unit can estimate the emotions of older adults and take care to ensure that subscription suggestions do not cause stress. For example, the generation AI of the subscription suggestion unit estimates the emotions of older adults and takes care to ensure that subscription suggestions do not cause stress. For example, the frequency of suggestions can be adjusted and suggestions can be made only when necessary. Furthermore, if an older adult feels anxious or has doubts about a subscription suggestion, the generation AI can detect that emotion and provide detailed explanations and support. For example, it can explain the benefits of subscriptions and the ease of the process. Furthermore, the subscription suggestion unit uses its emotion estimation function to analyze whether an older adult has positive emotions toward the subscription suggestion and adjust the content of the suggestion. For example, if the older adult shows interest in a suggested product, it can also suggest other subscription options related to that product. This allows for subscription suggestions that take into consideration the emotions of older adults, reducing stress and enabling more appropriate suggestions.

[0081] The regular purchase suggestion unit can analyze the consumption patterns of elderly people and suggest the optimal regular purchase frequency. The regular purchase suggestion unit, for example, analyzes the consumption patterns of elderly people and suggests the optimal regular purchase frequency. For example, for products that are purchased weekly, it suggests weekly regular purchases. The regular purchase suggestion unit also predicts the timing of replenishment of products needed by elderly people based on the consumption patterns and suggests the optimal regular purchase frequency. For example, for products that are purchased once a month, it suggests monthly regular purchases. The regular purchase suggestion unit also analyzes the consumption patterns of elderly people and suggests regular purchase frequencies that match seasons and events. For example, it suggests products that are needed for each season. This makes it possible to make more appropriate suggestions by suggesting the optimal regular purchase frequency based on the consumption patterns of elderly people.

[0082] The regular purchase suggestion unit can customize the timing of regular purchases to suit the lifestyle rhythm of the elderly. The regular purchase suggestion unit, for example, analyzes the lifestyle rhythm of the elderly and customizes the optimal timing of regular purchases. For example, for an elderly person who cannot live without coffee every morning, the regular purchase suggestion unit may suggest a monthly regular purchase of coffee beans. The regular purchase suggestion unit may also adjust the timing of regular purchases based on the lifestyle rhythm so that products are delivered on a specific day of the week or time of day. For example, for an elderly person who does all their shopping on the weekend, the regular purchase suggestion unit may suggest that products be delivered on the weekend. The regular purchase suggestion unit may also take into account the lifestyle rhythm of the elderly and suggest the timing of regular purchases to coincide with specific events or occasions. For example, regular purchases of food ingredients may be made to coincide with monthly family gatherings. In this way, more appropriate suggestions can be made by customizing the timing of regular purchases based on the lifestyle rhythm of the elderly.

[0083] The subscription suggestion unit can suggest benefits and discounts that match the preferences of seniors. For example, the subscription suggestion unit suggests benefits and discounts that match the preferences of seniors. For example, by setting up a subscription, discounts or points can be provided for specific products. The subscription suggestion unit also customizes benefits and discounts based on products and services that seniors have purchased in the past. For example, it can suggest discounts for frequently purchased products. Furthermore, when a subscription is made, the generation AI suggests benefits and discounts that match the preferences of seniors. For example, it can offer discounts for products of specific brands or categories. This makes it possible to make more appropriate suggestions by suggesting benefits and discounts that match the preferences of seniors.

[0084] The subscription suggestion unit uses the generation AI to provide real-time support chat when seniors are setting up a subscription, allowing them to immediately resolve any questions they may have. For example, when seniors are setting up a subscription, the generation AI provides real-time support chat to immediately resolve any questions they may have. For example, they can ask questions about problems that arise during the subscription process through chat and receive an immediate answer. The subscription suggestion unit also uses the support chat to resolve seniors' questions and concerns about subscriptions. For example, it provides real-time answers to questions about how to cancel a subscription or how to make changes. The subscription suggestion unit also predicts questions that seniors may have while setting up a subscription and provides guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows seniors to immediately resolve their questions by providing real-time support when setting up a subscription.

[0085] The subscription suggestion unit can use the emotion estimation function to analyze how seniors feel about subscriptions and adjust the content of the suggestions. For example, the subscription suggestion unit uses the emotion estimation function to analyze in real time how seniors feel about subscriptions. For example, if a senior expresses positive feelings about a proposed subscription, the suggestion is prioritized. Furthermore, if a senior expresses anxiety or doubts about a subscription, the generation AI detects that emotion and provides detailed explanations and support. For example, it explains the benefits of subscriptions and the ease of the process. Furthermore, the subscription suggestion unit uses the emotion estimation function to analyze whether seniors feel positive feelings about subscriptions and adjust the content of the suggestions. For example, if a senior expresses interest in a suggested product, it also suggests other subscription options related to that product. This allows for more appropriate suggestions to be made by adjusting the content of subscription suggestions based on the senior's emotions.

[0086] The delivery notification unit can estimate the emotions of elderly people and take care to ensure that delivery status notifications reduce anxiety. For example, the generation AI in the delivery notification unit estimates the emotions of elderly people and takes care to ensure that delivery status notifications reduce anxiety. For example, it provides detailed explanations of the delivery status and clearly communicates the estimated arrival time. Furthermore, if an elderly person feels anxious or has questions about the delivery status notification, the generation AI detects that emotion and provides detailed explanations and support. For example, if a delivery delay occurs, it notifies the elderly person of the reason and the new estimated arrival time. Furthermore, the delivery notification unit uses its emotion estimation function to analyze whether the elderly person has positive emotions toward the delivery status notification and adjusts the content of the notification. For example, if the delivery is progressing smoothly, it sends a message that provides a sense of reassurance. In this way, delivery status notifications are provided with consideration for the emotions of elderly people, reducing anxiety and enabling more appropriate notifications.

[0087] The delivery notification unit can analyze the elderly person's past delivery history and suggest the optimal notification timing. The delivery notification unit, for example, analyzes the elderly person's past delivery history and suggests the optimal notification timing. For example, the optimal notification timing is set based on the time period in which delivery notifications were received in the past. The delivery notification unit also suggests the notification timing that will give the elderly person the most peace of mind based on the delivery history. For example, it may notify the elderly person when delivery is approaching and notify them of the estimated arrival time. The delivery notification unit also customizes the optimal notification timing taking into account the elderly person's lifestyle rhythm. For example, it may notify them based on their daytime activity times. This makes it possible to provide more appropriate notifications by suggesting the optimal notification timing based on the elderly person's past delivery history.

[0088] The delivery notification unit can customize the notification format and voice guidance according to the visual and hearing conditions of the elderly person. For example, the delivery notification unit automatically adjusts the notification format according to the visual condition of the elderly person. For example, if the elderly person's eyesight is impaired, a larger font size is used. The delivery notification unit also customizes the volume and speed of the voice guidance according to the hearing condition. For example, if the elderly person's hearing is impaired, the volume is increased and the guidance is given at a slower speed. The delivery notification unit also adjusts the color and contrast of the notification based on the visual and hearing conditions of the elderly person. For example, if the elderly person has color vision deficiency, a color that is easy to see is used. This allows for more appropriate notifications to be provided by customizing the notification according to the visual and hearing conditions of the elderly person.

[0089] The delivery notification unit can suggest notification themes that match the preferences of elderly people. The delivery notification unit, for example, suggests notification themes that match the preferences of elderly people. For example, it provides themes with simple, easy-to-read designs and favorite colors. The delivery notification unit also automatically suggests themes that match the preferences of elderly people based on notification themes previously selected by the elderly people. For example, it presents designs similar to themes previously selected. The delivery notification unit also suggests customized notification themes based on the hobbies and interests of elderly people. For example, it provides a theme with a plant motif to an elderly person who enjoys gardening. This allows for more appropriate notifications by suggesting notification themes that match the preferences of elderly people.

[0090] In the delivery notification unit, when elderly people check their delivery status, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. In the delivery notification unit, for example, when elderly people check their delivery status, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. For example, they can ask questions about the delivery status through chat and receive an immediate answer. The delivery notification unit also resolves elderly people's questions and concerns about the delivery status through the support chat. For example, it provides real-time answers to questions about delivery delays or changes. In addition, the delivery notification unit predicts questions that may arise when elderly people check their delivery status and provides guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows elderly people to receive real-time support when checking their delivery status, allowing them to immediately resolve any questions they may have.

[0091] The delivery notification unit uses the emotion estimation function to analyze how elderly people feel about delivery status notifications and adjust the content of the notifications accordingly. For example, the delivery notification unit uses the emotion estimation function to analyze in real time how elderly people feel about delivery status notifications. For example, if the elderly person expresses positive emotions toward the notifications, the notification method is continued. Furthermore, if the elderly person feels anxious or suspicious about the delivery status notifications, the delivery notification unit uses the generation AI to detect those emotions and provide detailed explanations and support. For example, if a delivery delay occurs, the delivery notification unit notifies the elderly person of the reason and the new estimated arrival time. Furthermore, the delivery notification unit uses the emotion estimation function to analyze whether elderly people feel positive emotions toward delivery status notifications and adjust the content of the notifications accordingly. For example, if the delivery is progressing smoothly, the delivery notification unit sends a message that conveys reassurance. This allows for more appropriate notifications by adjusting the content of delivery status notifications based on the emotions of elderly people.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The needs understanding department can suggest related products and services based on the hobbies and interests of elderly people. For example, if an elderly person's hobby is gardening, gardening supplies, plant seeds, fertilizer, etc. will be suggested. For example, seasonal flower seeds and gardening tools will be suggested. Furthermore, if an elderly person's hobby is reading, the needs understanding department will suggest the latest bestsellers and recommended books by genre. For example, mystery novels and history books will be suggested. Furthermore, if an elderly person's hobby is cooking, the needs understanding department will suggest cooking recipe books, cooking utensils, and special ingredients. For example, Japanese cuisine recipe books and high-quality kitchen knives will be suggested. This makes it possible to make more appropriate product suggestions by making product suggestions based on the hobbies and interests of elderly people.

[0094] The needs understanding department can suggest regional products based on the living environment of the elderly. For example, for elderly people living in urban areas, it can suggest convenient delivery services and products suitable for urban life. For example, it can suggest delivery lunch boxes and small urban home appliances. For elderly people living in suburban areas, it can suggest products that can make use of gardens and large spaces. For example, it can suggest kits for home gardening and outdoor equipment. For elderly people living in rural areas, it can suggest local specialties and products useful for farm work. For example, it can suggest fresh local vegetables and gloves for farm work. This makes it possible to suggest more appropriate products by making product suggestions based on the living environment of the elderly.

[0095] The needs understanding unit uses the emotion estimation function to analyze in real time how seniors feel about product proposals and adjust the content of the proposals. For example, the generation AI analyzes the seniors' facial expressions and voices to analyze their emotions toward the product proposals in real time. For example, if the seniors show a happy expression toward the proposed product, that product will be suggested first. Furthermore, if the seniors are dissatisfied or have doubts about the proposed product, the generation AI detects that emotion and suggests a different product. For example, if the seniors have a negative reaction to the proposed product, an alternative product will be suggested. Furthermore, the needs understanding unit uses the emotion estimation function to analyze whether seniors have positive emotions toward the proposed product and adjust the content of the proposals. For example, if the seniors show interest in the proposed product, other products related to that product will also be suggested. This enables more appropriate product proposals to be made by adjusting product proposals in real time based on the seniors' emotions.

[0096] The purchase support unit can analyze the operation history of elderly people and suggest frequently used operations as shortcuts. For example, it can analyze the operation history of elderly people and suggest frequently used operations as shortcuts. For example, it can display a button that allows frequently purchased items to be added to a cart with one click. The purchase support unit can also provide functions and settings that elderly people often use as shortcuts based on the operation history. For example, it can present options to automatically select frequently used payment methods and delivery addresses. The purchase support unit can also analyze the operation patterns of elderly people and suggest shortcuts to efficiently proceed with the purchase process. For example, it can display a list of products that have been purchased in the past, making it easy to repurchase them. In this way, by suggesting shortcuts based on the elderly people's operation history, the purchase process can be carried out efficiently.

[0097] The purchasing support department can customize the font size of the interface and the voice guidance according to the visual and hearing conditions of the elderly person. For example, the font size of the interface can be automatically adjusted according to the visual condition of the elderly person. For example, if the elderly person's eyesight is impaired, a larger font size can be used. The purchasing support department also customizes the volume and speed of the voice guidance according to the hearing condition. For example, if the elderly person's hearing is impaired, the volume can be increased and the guidance can be given at a slower speed. The purchasing support department also adjusts the color and contrast of the interface based on the visual and hearing conditions of the elderly person. For example, if the elderly person has color vision deficiency, a color that is easy to see can be used. In this way, customizing the interface according to the visual and hearing conditions of the elderly person makes the purchasing process go more smoothly.

[0098] In the purchasing support department, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. For example, when seniors go through the purchasing process, the generation AI provides a support chat in real time, allowing them to immediately resolve any questions they may have. For example, they can ask about problems that arise during the purchasing process through chat and receive an immediate answer. The purchasing support department also uses the support chat to resolve any questions or concerns seniors may have regarding the purchasing process. For example, it provides real-time answers to questions about changing payment methods or shipping addresses. The purchasing support department also uses the generation AI to predict questions that seniors may have during the purchasing process and provide guidance in advance through the support chat. For example, it automatically displays answers to frequently asked questions. This allows seniors to receive real-time support as they go through the purchasing process, allowing them to immediately resolve any questions they may have.

[0099] The purchasing support department can use the emotion estimation function to detect in real time any anxieties or questions that seniors may have during the process and provide appropriate support. For example, the emotion estimation function can be used to detect in real time any anxieties or questions that seniors may have during the process and provide appropriate support. For example, if they are feeling anxious, detailed explanations or guides can be displayed. Furthermore, if a senior has a question during the process, the purchasing support department's generation AI can detect that emotion and immediately provide an answer through a support chat. For example, questions about payment methods can be answered in real time. Furthermore, the purchasing support department can use the emotion estimation function to provide support to reduce the stress that seniors feel during the process. For example, if the procedure is complicated, it can guide them to a simplified procedure. In this way, the purchasing process can be carried out smoothly by detecting in real time any anxieties or questions that seniors may have during the process and providing appropriate support.

[0100] The product proposal department can also suggest exercise equipment and fitness programs based on the health condition of the elderly person. For example, it proposes appropriate exercise equipment taking into consideration the health condition of the elderly person. For example, it proposes an exercise bike that is gentle on the joints or a stretching mat. The product proposal department also proposes individually customized fitness programs based on the health condition. For example, it proposes low-impact exercise or yoga programs. The product proposal department also proposes equipment and programs to maximize the effects of exercise based on the exercise data of the elderly person. For example, it proposes a walking program while monitoring the heart rate. This makes it possible to suggest more appropriate products by suggesting exercise equipment and fitness programs based on the health condition of the elderly person.

[0101] The product proposal department can propose recipes and meal plans that take into account the health condition of the elderly person and provide ingredients based on them. For example, it proposes recipes that take into account the health condition of the elderly person and provides ingredients based on them. For example, it proposes low-salt meal plans or carbohydrate-restricted recipes. The product proposal department also customizes meal plans that take into account the health condition and provides the necessary ingredients all at once. For example, it proposes ingredient sets based on weekly meal plans. The product proposal department also proposes recipes that take into account the nutritional balance of the elderly person and provides ingredients based on them. For example, it proposes recipes that include ingredients rich in vitamins and minerals. This makes it possible to propose more appropriate products by proposing recipes and meal plans that take into account the health condition of the elderly person and providing ingredients based on them.

[0102] The product proposal unit can use the emotion estimation function to analyze how seniors feel about health-related proposals and adjust the content of the proposals. For example, the emotion estimation function can be used to analyze in real time how seniors feel about health-related proposals. For example, if a senior expresses positive feelings about a recommended health food, the product proposal unit will prioritize the recommendation of that product. Furthermore, if a senior expresses anxiety or doubt about a health-related proposal, the product proposal unit's generation AI can detect that emotion and make a different proposal. For example, if a senior expresses anxiety about a recommended exercise program, the product proposal unit can suggest a different program. Furthermore, the product proposal unit can use the emotion estimation function to analyze whether seniors feel positive feelings about health-related proposals and adjust the content of the proposals. For example, if a senior expresses interest in a recommended recipe, the product proposal unit can also suggest other recipes related to that recipe. This allows for more appropriate product proposals to be made by adjusting the content of health-related proposals based on the senior's emotions.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The needs understanding unit understands the needs of seniors. For example, the needs understanding unit analyzes data such as seniors' past purchase history, preferences, and health status to understand their individual needs. It can also use the generation AI to estimate the emotions of seniors and adjust the products it recommends based on those emotions. For example, the generation AI can estimate the emotions of seniors and suggest products that have a relaxing effect when they are under a lot of stress. Step 2: The product proposal department proposes products based on the needs of seniors as understood by the needs understanding department. For example, the product proposal department can use generative AI to analyze the lifestyle patterns of seniors and propose products that are optimal for specific time periods. It can also propose health-conscious products based on the seniors' health conditions. Step 3: The purchasing support department assists with the purchase process for the product suggested by the product proposal department. For example, the purchasing support department uses generative AI to help seniors smoothly complete online purchase procedures. It can also estimate the emotions of seniors and make suggestions to simplify the process if they are feeling stressed.

[0105] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0106] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0110] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0111] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0112] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0113] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0114] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0115] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0116] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0117] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0118] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0119] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0120] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0121] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0123] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0124] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0125] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0126] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0127] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0128] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0129] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0130] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0131] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0132] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0133] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0134] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0135] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0136] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0137] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0138] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0139] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0140] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0141] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0142] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0143] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0144] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0145] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0146] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0147] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0148] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0149] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0150] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0151] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0152] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0153] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0154] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0155] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0156] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0157] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0158] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0159] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0160] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0161] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0162] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0163] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0164] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0165] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0166] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0167] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0168] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0169] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0170] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0171] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0172] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. The Needs Understanding Department, which understands the needs of the elderly, a product suggestion unit that suggests products based on the needs of the elderly people understood by the needs understanding unit; a purchase support unit that supports the purchase procedure of the product proposed by the product proposal unit. A system characterized by:

2. The needs understanding department Estimating the feelings of the elderly person and adjusting the products to be proposed based on the feelings.

2. The system of claim 1.

3. The needs understanding department Suggesting related products and services based on the elderly person's hobbies and interests 2. The system of claim 1.

4. The purchasing support department The feelings of the elderly person are estimated, and if the elderly person is feeling stressed, a proposal to simplify the procedure is made.

2. The system of claim 1.

5. The product proposal unit Propose health-conscious products based on the health status of the elderly.

2. The system of claim 1.

6. The subscription proposal department The feelings of the elderly person are estimated, and consideration is given to ensuring that the proposal of a regular purchase does not cause stress to the elderly person.

2. The system of claim 1.

7. The delivery notification section The feelings of the elderly person are estimated, and the notification of delivery status is considered to reduce the anxiety of the elderly person.

2. The system of claim 1.

8. The delivery notification section Analyze how the elderly feel about delivery status notifications and adjust the content of the notifications.

2. The system of claim 1.

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