Information processing device, information processing method, and program

Abstract

To provide a service that suggests a more suitable action for a user when suggesting a future action to the user based on past actions.SOLUTION: A server 1 comprises a past action acquisition unit 41, an element extraction unit 42, and an action suggestion unit 44. The past action acquisition unit 41 acquires information related to a tour (prescribed past action) such as a sightseeing tour using a fixed-price taxi in which the user has participated, as past action information. The element extraction unit 42 extracts one or more elements that are determined to be positive (impressions of the user such as "having a meal before lunch time was good" and facial expressions of the user at that time, etc.) from the prescribed past actions based on the past action information as positive elements. The action suggestion unit 44 generates information including a suggestion content (a sightseeing tour where a meal comes before lunch time) for a future action of the user (next tour) based on the one or more positive elements, as action suggestion information.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] There is a technique for proposing future actions (travel) that eliminate points (negative points) dissatisfied with past actions (travel) (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, although the conventional technology proposes future actions to the user based on past actions, it is not always a suitable action for the user.

[0005] The present invention has been made in view of such a situation, and an object thereof is to provide a service capable of proposing a more suitable action for the user when proposing a future action to the user based on past actions.

Means for Solving the Problems

[0006] To achieve the above object, an information processing apparatus according to an aspect of the present invention includes: a past action acquisition unit that acquires information on a predetermined past action as past action information; an element extraction unit that extracts one or more elements determined to be positive among the predetermined past actions as positive elements based on the past action information; Based on the above positive elements, action proposal means for generating information including proposed content regarding the user's future actions as action proposal information; comprising.

[0007] Each of the information processing method and program according to one aspect of the present invention is respectively a method and program corresponding to the information processing system according to one aspect of the present invention.

Effect of the Invention

[0008] According to the present invention, when proposing future actions to the user based on past actions, it is possible to provide a service that can propose more suitable actions for the user.

Brief Description of the Drawings

[0009]

Figure 1

Figure 2

Figure 3

Figure 4

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Figure 9

Embodiments for Carrying Out the Invention

[0010] Here, prior to explaining the embodiments of the present invention, the services in general that are the premise of the present invention will be briefly explained.

[0011] Japan has entered a super-aging society where one in four people is 65 years old or older, and not only problems related to medical care and welfare but also problems related to transportation have arisen. Specifically, for example, according to the survey results by the Ministry of Land, Infrastructure, Transport and Tourism, among those aged 65 to 74, about 20% have difficulty walking more than about 500 m a day, and among those 75 years old and older, it is said to be about 50%.

[0012] On the other hand, traffic accidents caused by the driving of the elderly are increasing year by year and are expected to continue to increase in the future. With the progress of aging, the number of drivers holding a driver's license aged 75 and older is expected to reach 5.33 million in 2018, and it is necessary to take measures for creating an environment where the elderly can live without problems even if they do not drive. As one of such measures, for example, an urban form (compact city) in which various functions are concentrated in the center and the urban area is kept in a compact scale can be considered, but especially in rural areas, it is difficult to realize because various bases and residences are scattered.

[0013] Due to such a situation, especially among the elderly in rural areas, there are often problems and concerns such as "the distance that can be walked decreases with aging", "traffic accidents are scary, but not being able to drive a car causes problems in life", and "there is no neighborhood interaction and one is confined to one's home, or there is no one to rely on when something happens".

[0014] Furthermore, not only for the elderly but also for ordinary people, it is usually costly to purchase and maintain a private car.

[0015] Therefore, in order to support the local life of the elderly, it is required to build a platform that provides the value of monitoring support, local life support, and local mobility support (free movement within the area), and to provide comprehensive services for the elderly.

[0016] The service to which the information processing system including the information processing apparatus according to an embodiment of the present invention is applied (hereinafter referred to as "this service") aims to realize "a free and desired life" and "a life full of meaning" for users including the elderly, and for those who provide the service (employees of service providers described later, etc.), it aims at a "cycle of meaning" in which the service is carried out with a sense of "being utilized" and "real feeling and fulfillment".

[0017] Subsequently, in aiming at such a "cycle of meaning", the local life support platform to be constructed will be briefly described. The local life support platform is a service proposed by providers of this service, etc., and is a service providing platform that cooperates with other businesses, etc., and provides comprehensive services for the elderly, etc. That is, values such as "monitoring support", "local life support", and "free movement within a predetermined area" are provided to the elderly, etc. Specifically, the local life support platform includes services such as "flat-rate taxi", "concierge", "local mobility support", "aggregation and provision of local information", "provision of going-out tickets (local currency)", and "action proposal service".

[0018] As described above, prior to the description of an embodiment of the present invention, the general services that are the premise of the present invention have been briefly described. In the following description, an example of the "action proposal service" for users who use the "flat-rate taxi" service among the above various services will be described.

[0019] First, the fixed-fare taxi will be described. In the regional mobility support service, the fare for traveling within a predetermined area using a predetermined taxi is uniformly set within the said predetermined area. A taxi with a uniformly set fare is referred to as a fixed-fare taxi. Here, "uniformly" means that the fare when the taxi travels within the predetermined area with a passenger on board is constant in a predetermined time unit (for example, one month). However, the fare per predetermined time unit (for example, one month) is not the same for everyone. When multiple categories such as the three categories of pine, bamboo, and plum are set, it will vary for each category. In the following example, it is assumed that a person using this service (hereinafter referred to as "user") uses a fixed-fare taxi by paying a fixed amount each month (for example, an amount determined for each category). As a result, the user can freely use the fixed-fare taxi to travel within the predetermined area without worrying about the fare, just by paying a fixed amount each month.

[0020] Next, with reference to FIG. 1, an example of the "behavior proposal service" (hereinafter referred to as "this service") for a user using the above-mentioned "fixed-fare taxi" service will be described.

[0021] FIG. 1 is a diagram showing an example of a service to which an information processing system including an information processing apparatus according to an embodiment of the present invention is applied. In this service, as shown in FIG. 1, in step S1, when the user performs an action such as traveling using, for example, a bus tour or a fixed-fare taxi, information regarding the user's predetermined past action is acquired as past action information. Examples of cases where action history information is acquired include cases where a smartphone automatically acquires action history data, cases where the user manually acquires it from a questionnaire filled out by the user himself / herself, cases where actions are acquired from reports recorded by others (such as passengers or taxi drivers), cases where action history is acquired from photos taken by the user or others, and various other cases. In addition to action history information, past action information can also be acquired from, for example, biometric information.

[0022] Subsequently, in step S2, based on the past behavior information, the service extracts one or more elements determined to be positive among predetermined past behaviors as positive elements. For example, if the user answered in a questionnaire that it was good that they had lunch at 11 am, that information is extracted as a positive element.

[0023] Then, in step S3, based on one or more positive elements, the service generates information including proposed content regarding the user's future behavior as action proposal information and recommends the next action. As an example, for instance, a tour to visit a restaurant in the morning is recommended as the next action. Note that "judgment" of being positive includes not only cases where the user explicitly judges it to be positive, but also cases where the information processing device obtains the judgment result and determines it to be positive based on a predetermined algorithm (such as artificial intelligence like AI, etc.). If the predetermined algorithm has an algorithm that determines, for example, that parts where the user has "many smiles" are positive, and if biometric information such as a group photo (an image taken with a smartphone, etc.) including the user is obtained by the information processing device as past behavior information, then based on the expression of the user captured in the group photo, past behaviors with many smiles during the time zone of the shooting time recorded as attribute information of the group photo can be determined to be positive. As described above, according to this service, the service acquires the history of the user's past actions as past behavior information, extracts positive elements that the user has determined to be positive based on the past behavior information, and recommends the next user action based on the positive elements. Therefore, when proposing future actions to the user based on past actions, a service that can propose more suitable actions for the user can be provided.

[0024] Hereinafter, with reference to FIG. 2, an information processing system for realizing the service of FIG. 1 will be described. FIG. 2 is a diagram showing the configuration of an information processing system for realizing the service of FIG. 1.

[0025] As shown in FIG. 2, the information processing system is configured to include a server 1 managed by the provider of this service, user terminals 2-1 to 2-m (m is an arbitrary integer), and taxi terminals 3-1 to 3-n (n is an arbitrary integer) respectively installed in each of the flat-rate taxis T-1 to T-n (n is an arbitrary integer).

[0026] The server 1, each of the user terminals 2-1 to 2-m, and each of the taxi terminals 3-1 to 3-n are interconnected via a predetermined network N such as the Internet.

[0027] Hereinafter, when it is not necessary to individually distinguish each of the user terminals 2-1 to 2-m, they are collectively referred to as "user terminal 2". Also, when it is not necessary to individually distinguish each of the flat-rate taxis T-1 to T-n, they are collectively referred to as "flat-rate taxi T". When referring to the flat-rate taxi T, the taxi terminals 3-1 to 3-n are collectively referred to as "taxi terminal 3".

[0028] FIG. 3 is a block diagram showing the hardware configuration of the server in the information processing system of FIG. 2.

[0029] The server 1 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an output unit 16, an input unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0030] The CPU 11 executes various processes according to a program recorded in the ROM 12 or a program loaded from the storage unit 18 to the RAM 13.

[0031] In the RAM 13, data and the like necessary for the CPU 11 to execute various processes are also appropriately stored.

[0032] The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14. An output unit 16, an input unit 17, a storage unit 18, a communication unit 19, and a drive 20 are connected to the input / output interface 15.

[0033] The output unit 16 is composed of a speaker, a display unit, etc., and outputs various information as images and sounds. The input unit 17 is composed of a keyboard, a mouse, etc., and inputs various information.

[0034] The storage unit 18 is composed of a DRAM (Dynamic Random Access Memory), etc., and stores various data. The communication unit 19 controls communication with other devices (user terminal 2 and taxi terminal 3 in the example of FIG. 2) via a network N including the Internet.

[0035] A removable medium 31 made of a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, etc., is appropriately mounted on the drive 20. The program read from the removable medium 31 by the drive 20 is installed in the storage unit 18 as necessary. Also, the removable medium 31 can store various data stored in the storage unit 18.

[0036] The configurations of the user terminal 2 or the taxi terminal 3 are basically the same as that of the server 1 except that they may be equipped with a touch panel display, a camera function, etc., so the descriptions thereof are omitted here.

[0037] FIG. 4 is a functional block diagram showing the functional configuration of the server in FIG. 3. In the CPU 11 of the server 1, a past behavior acquisition unit 41, an element extraction unit 42, an analysis unit 43, and a behavior proposal unit 44 function. As an area of the storage unit 18, a user DB 51 and a past behavior information DB 52 are provided. The user database 51 stores personal information of users and access information (such as login IDs and passwords) to the server 1 or the application. In the past behavior information database 52, past behavior information of the user's past actions is sequentially stored for each user by the past behavior acquisition unit 41. In addition, the past behavior information stored in the past behavior information database 52 is read out by the element extraction unit 42, the analysis unit 43, the behavior proposal unit 44, etc., and respective processes are executed based on the past behavior information.

[0038] The past behavior acquisition unit 41 acquires information regarding a predetermined past action as past behavior information. In addition, the past behavior acquisition unit 41 acquires action history information regarding a user's predetermined past action as past behavior information. The past behavior acquisition unit 41 acquires, as past behavior information, action history information obtained by an input operation to the user terminal 2 or the taxi terminal 3 of the driver (a third party) of the taxi, or action history information including captured images output from a camera function of a smartphone according to a shooting operation of the user or the driver. Third parties include, in addition to taxi drivers, for example, passengers on a bus tour. Specifically, the past behavior acquisition unit 41 acquires, as past behavior information, information regarding a user's predetermined past action, such as photos and questionnaires when the user travels using a fixed-rate taxi, business reports of taxi drivers and passengers (third parties), etc., and stores it in the past behavior information database 52. The past behavior acquisition unit 41 acquires action history information obtained by the exertion of the functions of a predetermined terminal as past behavior information. The predetermined terminal is, for example, an acceleration sensor or a vital sensor worn by the user. The past behavior acquisition unit 41 acquires numerical values such as the user's movement, number of steps, and heart rate detected by these sensors. In addition, the past behavior acquisition unit 41 acquires biometric information in a time period during or before and after the execution of a predetermined past action of the user or a third party as past behavior information. Here, the biometric information is, for example, the face of the user smiling at the travel destination, and information such as the actions at that time, that is, the user enjoying a meal at a dining place visited in the early morning during the trip, captured by the camera function of the smartphone, is obtained as past action information.

[0039] Based on the past action information, the element extraction unit 42 extracts one or more elements determined to be positive among a predetermined past actions as positive elements. Furthermore, based on the past action information, the element extraction unit 42 extracts one or more elements determined to be negative among a predetermined past actions as negative elements. Specifically, the element extraction unit 42 reads out the past action information of the designated user from the past action information DB 52, and extracts one or more elements determined to be positive among the predetermined past actions of the user included in the past action information, such as event actions like traveling, as positive elements. Specifically, the AI determines a photographed image taken at a dining place visited in the early morning during the trip, and extracts one or more positive elements such as the user's face expression in the photo being smiling, outputs them to the analysis unit 43, the action proposal unit 44, etc., and associates and stores the positive elements with the past action information of the user in the past action information DB 52. As positive elements, what the actions were, the time when the user was positive (smiling face), etc. are associated and stored.

[0040] Based on one or more positive elements and one or more negative elements of each of the one or more past action information, the analysis unit 43 executes a predetermined analysis. Specifically, when the analysis unit 43 is equipped with AI, based on the positive element that the user was smiling at a dining place visited in the early morning during the trip, the AI analyzes the user's preferences and derives analysis results such as the user prefers to have an early meal when traveling.

[0041] Based on one or more positive elements output from the element extraction unit 42, the action proposal unit 44 generates information including proposed content regarding the user's future actions as action proposal information, and outputs it to the user terminal 2. In addition, the action proposal unit 44 generates action proposal information based on the analysis result by the analysis unit 43 and proposes it to the user. For example, from the analysis result of the analysis unit 43 that the user prefers to have an early meal when traveling, the action proposal unit 44 proposes a tour such as "How about the next tour being a tour with an early lunch?" Note that when the user's thoughts can be clearly obtained, information including proposed content regarding the user's future actions may be generated as action proposal information based on one or more positive elements output from the element extraction unit 42 without going through the analysis unit 43, and output to the user terminal 2. Specifically, when a positive response such as "I stopped by a dining place and had a meal before noon during the tour, and it was great because the dining place was empty and I could enjoy the meal comfortably" is obtained for the content described by the user in the questionnaire during or after the tour, the action proposal unit 44 may propose a tour such as "How about the next tour being a tour with an early lunch?"

[0042] According to the server 1 of the embodiment in this way, for example, past action information about a tour that the user participated in the past is acquired, and based on the past action information, one or more positive elements that are determined that the user became positive during the tour are extracted, and based on the one or more positive elements, a next tour that is expected to be preferred by the user is proposed. As a result, for example, when the user answered in the questionnaire about a past trip that "it was great to have lunch at 11 am before noon", as a future action for the user, for example, a tour that visits a restaurant before noon is presented to the user terminal 2 as the next action and recommended to the user, so that a service that can propose more suitable actions for the user can be provided.

[0043] The following describes examples of specific action proposals in this service (the server of the information processing system of the embodiment) ([Example 1] and [Example 2]). [Example 1] Example 1 is a case where the user has used a flat-rate taxi in the past. For example, assume that users such as the elderly use the above-mentioned "flat-rate taxi" as a service for performing minimum actions in life, such as going to the hospital, bank, shopping, etc. The flat-rate taxi can be used not only for performing minimum actions in life but also for going out to enjoy life. For example, it can be used to go to karaoke or eat soba.

[0044] This service proposes to the user information on going out for the user of the flat-rate taxi to enjoy life as action proposal information. Specifically, when the user has gone to, for example, Location A by flat-rate taxi in the past, this service obtains the action history information (an example of past action information) from the user's user terminal 2, or obtains the questionnaire results from the user about going to Location A as action history information. If Location A is, for example, a hospital, and it is extracted as a positive element from the action history information that eating soba every time going to the hospital is the user's pleasure, information such as it is advisable to go to a soba restaurant (Location B) with a high evaluation in the eating log by flat-rate taxi can be presented to the user as action proposal information.

[0045] Also, the degree of sleep can be adopted as biological information (another example of past action information). If that day is enjoyable, one will sleep deeply, and if that day is gloomy, one will sleep lightly. For example, if biological information is obtained that the sleep is deep on the day of taking a walk and the sleep is light on the day of not taking a walk, a positive element that taking a walk will make the user's life fulfilling is extracted. In this case, for example, information such as it is advisable to go to a tourist spot C suitable for taking a walk by flat-rate taxi can be presented to the user as action proposal information.

[0046] [Second Example] The second example is a case where the user has participated in a tour with a companion (hereinafter referred to as "Tour A") in the past. For example, if the past behavior was Tour A, assume the following past behavior information was obtained. (a) Report submitted by the companion to the company after Tour A (b) Photos taken by the companion during Tour A (c) Questionnaire results of the user (Tour A participant) after Tour A (d) Activity history information obtained by the user with a mobile terminal during Tour A (e) Photos taken by the user during Tour A

[0047] The following positive elements are extracted from the above past behavior information ((a) to (e)). (a) Positive points of the user from the perspective of the companion (if there is a report such as leaving shiitake mushrooms but eating the main venison immediately as delicious during the meal, the point of "liking venison") are extracted as positive elements. (b) Photos taken while holding something in the restaurant → The appearance of the user eating venison with a smile is extracted as a positive element. (c) Questionnaire results of the user (Tour A participant) after Tour A, the point that "having lunch at 11 am before noon" was good as in the example of Figure 1, is extracted as a positive element. (d) Photos of "venison" uploaded to SNS → "Venison" is extracted as a positive element. (e) No positive elements were extracted from the photos taken by the user during Tour A.

[0048] And based on the above positive elements ((a) to (d)) extracted, for example, the next action proposal information such as "a tour to visit a restaurant where you can enjoy game dishes (venison) before noon" is recommended (presented) to the user. As for the method of outputting action proposal information, the action proposal unit 44 may read it from a database that associates input information (conditions) with output information (recommended content). Alternatively, the action proposal unit 44 may be an AI, and the recommended content may be output as the next action proposal information as a result of inputting conditions of one or more positive elements.

[0049] Note that the following examples described as "third parties" above are also included in this second case. For example, when a user is the organizer of a trip of a predetermined group, other members of the predetermined group correspond to third parties. The travel questionnaire filled out by other members is an example of "action history information obtained by input operations on a third party's terminal", and snapshot photos taken by other members during the trip are examples of "imaging images output from a camera according to a third party's shooting operation".

[0050] In this case, by using the user's own past action information, proposal content based on positive points for the user can be obtained. On the other hand, by using the past action information of each member of the predetermined group, proposal content based on positive points for the predetermined group (although it may not be suitable for the user himself / herself as the organizer, it is suitable for the predetermined group going on a group trip) can be obtained.

[0051] Furthermore, by using the past action information of some members (for example, if the members of a predetermined group can be divided into members who often go home directly after the first meeting and members who often go to the second meeting, the latter members who often go to the second meeting) instead of all members of the predetermined group, proposal content based on positive points for some members (for example, candidates for the second meeting venue of the next travel destination, distributing taxi tickets to members who go to the second meeting, etc.) can be proposed to the user.

[0052] Note that, as an element of biometric information acquired from the user, there is, for example, context. Context refers to all of the user's internal and external states. The user's internal state refers to information obtained from the user's body, such as facial expressions, overall body movements, eye movements, and information about the body measured from the user himself or herself (voice, heart rate, body temperature, blood pressure, number of steps, etc.). In addition, the user's external state refers to spatial or temporal information (temporal arrangement and location) from outside the user, such as information obtained from the smartphone that the user operates.

[0053] Next, with reference to FIGS. 5 and 6, a specific example of a series of operations from data acquisition to utilization of self-data in the above-described server will be described. FIG. 5 is a diagram showing a specific example of an operation of collecting activity data from data acquisition in a server having the functional configuration of FIG. 4. FIG. 6 is a diagram showing a specific example of an operation of utilizing self-data from activity data in a server having the functional configuration of FIG. 4.

[0054] Examples of information sources include electronic devices such as menu terminals, POS registers, and surveillance cameras installed in places where one can move by fixed-rate taxi, and portable terminals carried by the user. Examples of places include restaurants, supermarkets, convenience stores, hot springs, public baths, local hospitals, gyms, karaoke shops, golf courses, clothing stores, etc., as shown in FIG. 5. The information acquired from the information source by Server 1 is described below. For example, from a restaurant, recommended menus and congestion information can be obtained. From a supermarket or convenience store, special sale information and congestion information can be obtained. From a hot spring or public bath, settlement data (information on services used by the user (bath fee and massage fee)) and congestion information can be obtained. From a local hospital, the user's hospital visit information and congestion information can be obtained. From a gym, congestion information, training proposals recommended to the user, etc. can be obtained. From a karaoke shop, congestion information, new song information, visitor information (the user's friends, etc.) can be obtained. From a golf course, vacancy information and free competition information can be obtained. From a clothing store, information on recommended going-out trends can be obtained.

[0055] As information obtained by a user using a flat-rate taxi, there is flat-rate usage movement information. The flat-rate usage movement information is, for example, a series of action information (usage history, movement information, etc.) such as the user operates a portable terminal at home to start a flat-rate taxi app installed on the portable terminal, selects a destination from the app screen, makes a round-trip flat-rate application, actually has a flat-rate taxi come to pick up and drop off by flat-rate service, and after usage 1 to usage n, returns home by flat-rate service, which is obtained from the flat-rate taxi app by server 1. Usage 1 to usage n includes the usage status of the service at the pick-up and drop-off location (if it is a tour with restaurant dining, the content of the dishes eaten and the dining cost) and the action content (if it is a karaoke parlor tour, the song names sung by the user and the names of friends who went together, etc.).

[0056] Server 1 extracts (collects) data related to the activities of the user as activity data from the information obtained from the above-described information sources. For example, from the information obtained from a restaurant, register order data is extracted. From the ingredients and amounts described in the provided menu, the nutritional value consumed by the user is extracted. From the information obtained from a supermarket convenience store, register POS data and data on purchased ingredients are extracted. From the information obtained from a hot spring or public bath, the content of the service received by the user (for example, the bath fee and the name and cost of the massage) is extracted. From the information obtained from a local hospital (for example, a regular doctor), electronic medical record data, treatment, symptoms, etc. are extracted. From the information obtained from a gym, calorie consumption is extracted from the user's training data and training content. From the information obtained from a wearable device at a karaoke parlor, the frequency of interaction (how many times a month the user goes to karaoke with friends, etc.) is extracted, and further, the degree of stress divergence is obtained by analyzing the frequency of interaction. From the information obtained from a wearable device at a golf course, the frequency of interaction (how many times a month the user comes to play golf with friends, etc.) is extracted, and further, the degree of stress divergence, etc. is obtained by analyzing the frequency of interaction. From the information obtained from a clothing store, sales POS data is extracted, and further, the user's favorite color data and favorite style data are obtained by analyzing the sales POS data. In addition, by wearing a wearable device and taking a walk, the user can obtain the number of steps and the walking distance, and further calculate the calories consumed from the number of steps and the walking distance. Information can also be obtained from the user's daily life activities at home. From the meal content, the names and intake amounts of the cooking ingredients can be obtained, and further the nutritional value can be calculated from the intake amounts of the ingredients. From the sleep data, the depth of sleep can be determined, and further the amount of stress on the user can be calculated from the depth of sleep. The degree of stress relief can be obtained from the user's TV viewing situation.

[0057] By using the activity data obtained in this way as the user's own self-data, Server 1 provides advice (proposals) on the user's actions and provides information to other people and organizations (companies) as shown in FIG. 6. Specifically, for example, by regularly transmitting the user's self-data to a local hospital or pharmacy and providing it to the attending physician or pharmacist, the user can receive health advice and life guidance from the physician or pharmacist. By providing the user's self-data to a dietitian or a chef at a restaurant, the user can receive diet advice and cooking advice using the ingredients in the refrigerator. By providing the user's self-data to a gym, the user can receive guidance on training at the gym and guidance on daily exercise. By providing the user's self-data to a clothing store, the user can receive recommendations for clothes to purchase and manage the inventory of the clothes stored in the wardrobe.

[0058] In addition, by providing the user's self-data to service providers such as concierge services, all of the user's self-data can be organized and the user's lifestyle can be reported to, for example, family members in a remote location. The report can be made at preset intervals (daily, weekly, monthly, etc.).

[0059] Furthermore, by accumulating the self-data of multiple users, it can be utilized as big data. For example, by providing the amount of movement, the amount of communication, time = IN / OUT time, usage amount, physical calorie consumption, mental stress release amount, etc. as unified information to life insurance companies, property insurance companies, tourism information, town magazine companies, pharmaceutical companies, financial institutions, etc., they can be utilized respectively. Also, by categorizing human behavior by area, gender, age, time zone, day of the week, etc. and analyzing human behavior, data statistically analyzing human behavior can be generated and provided to institutions that need the data of the analysis results.

[0060] Subsequently, referring to FIGS. 7 and 8, an example of subscribing to the entire life of a user and proposing actions will be described. FIG. 7 is a diagram showing a specific example of creating a recommended outing plan considering the entire life of a user. FIG. 8 is a diagram showing an example of the action plan for a certain day in the recommended outing plan of FIG. 7.

[0061] Server 1 proposes positive actions such as the movement, eating, exercise, and entertainment of the user to be taken next on the screen of the app of the user's mobile terminal from the user's self-data. For example, as shown in FIG. 7, actions in daily life within the action range (area) of the user are proposed. Specifically, information on shopping, beauty salons, culture schools, and eating out is provided to the user, and as +α (plus alpha), popular walking courses, recommended facilities / experiences, town tour courses, culture school experiences, etc. are proposed. At the same time, the recreation information (rec information) of friends pre-registered by the user for this service is provided. The registered friends share the user's action plan (places often visited, days of the week and times, etc.).

[0062] When the user performs an operation to request the creation of a plan from the screen of the app on the mobile terminal for the content proposed by Server 1, Server 1 creates a recommended outing plan based on the user's past behavior history, and the recommended outing plan is presented on the app screen of the user's mobile terminal in the form of a calendar as shown in Figure 7. Note that the plan of the recommended outing plan includes the pick-up and drop-off of a flat-rate taxi.

[0063] When the user clicks on the column of the desired date among the recommended outing plans presented on the app screen, as shown in Figure 8, the action schedule for that day is displayed. Here, not only user A but also other users B and C are automatically added as participants to the action schedule for the karaoke reservation at 1 pm. As a result, the service provider, the flat-rate taxi operating company, can obtain the effect of improving the carpooling efficiency. In the case of the conventional method where each individual user makes an application separately (application method), since carpooling is not used for the whole, the carpooling efficiency, which was 0 (1 person), can be increased to 3 people (3 times).

[0064] On the other hand, in the case of a method (semi-compulsory method) where the service provider presents a plan to the user and the user does not apply for the plan that the user thinks is unnecessary, such as in this service, for example, when 10 plans are proposed, it is expected that the user will apply for about 7 of them, so the utilization rate of the flat-rate taxi can be increased.

[0065] Next, referring to Figure 9, the flow of the service to which this information processing system is applied will be described. Figure 9 is a diagram showing the flow of the service to which the information processing system including the server in Figure 3 is applied.

[0066] As shown in Figure 9, when the user acts on their own and uses a flat-rate unlimited ride service such as a flat-rate taxi to go to a supermarket, convenience store, restaurant, hospital, massage, etc., the action information of the user at that time is acquired by Server 1 as self-data.

[0067] At Server 1, the element extraction unit 42 extracts data (positive elements) in which the user has taken positive actions in terms of action history, hobbies, health, etc. from the acquired self-data, and the data that can be statistically used or used as the basis for plan creation is input to the action proposal unit 44 as self-required information. For the extracted data, analysis processing is executed by the analysis unit 43 (AI) as necessary. In the analysis processing, for example, the factors of positive actions are analyzed to identify the actions preferred by the user.

[0068] Based on the self-required information, the action proposal unit 44 creates various plans to facilitate the user's positive actions and proposes them to the user. In addition, based on the self-required information, the action proposal unit 44 provides the information required by businesses, concierges, etc. who receive consultations from the user to the businesses, concierges, etc.

[0069] Specifically, for the user, an advertisement (flyer) and the next month's calendar (next month's action plan) including the created plan are distributed to the app screen of the user's smartphone, tablet, or mobile terminal. Note that an advertisement frame is arranged on the back or the next page of the flyer, and advertisements of partner local businesses, etc. are posted in the frame. By placing advertisements of local businesses on the flyer, advertising revenue can be obtained, and it can be used for the server operating costs of the service provider, etc.

[0070] The user can check the next month's calendar and apply for the plan they want to participate in from it. In addition, the calendar (next month's action plan) of the requester (user) is distributed to the concierge's tablet. By checking the calendar, the concierge can make a regular visit at the timing when the requester is at home, become a conversation partner, or conduct physical condition consultations, hobby consultations, etc. Regarding the business operator's computer (PC), the user's next month's action plan is transmitted, so the business operator can receive consultations, reservations, etc. from the user.

[0071] Next, several cases of data utilization in the information processing system including the server in FIG. 3 will be described. First, the first case will be described. The first case is the first example of utilizing data when a user uses a flat-rate taxi. In the course of a user's daily life, when using a flat-rate taxi, as outgoing data, shopping data, data on what kind of cooking was done at home, data on what was eaten for eating out, data on how much was walked, etc. are acquired by Server 1. Server 1 combines the acquired data (the amount eaten and the amount moved by the user) with basic data such as the user's weight, analyzes the food tendency, and proposes guidance on nutrient intake and advice on exercise (what kind of exercise and to what extent).

[0072] Subsequently, the second case will be described. The second case is the second example of utilizing data when a user uses a flat-rate taxi. In the course of a user's daily life, when using a flat-rate taxi, Server 1 combines data such as who the user was meeting with when going out, what the user was doing, and the depth of sleep data among the acquired data, and analyzes from the points of when the user has a deep sleep when meeting with someone and when doing something, that is, a deep sleep means having spent a fulfilling day, reads the psychological tendency such as the person who the user unconsciously pays attention to, and presents advice on future actions to the user.

[0073] Next, the third case will be described. The third case is an example when data is acquired when a user participates in a travel tour or a day trip such as a Food Camp. Food Camp is a tour that allows you to experience the culture and local conditions of a region through food. Specifically, a taxi will pick you up from your home or the station, and around 10:00, you will take a bus from the tour company's office to the destination. Around 11:00, after arriving at the destination, you will be guided by the producer to visit the fields and have a harvesting experience. Around 12:00, enjoy lunch at the open-air restaurant for that day only. Around 15:00, return to the tour company's office by bus and then be sent home or to the station by taxi. It is a package tour like this. In this case, in addition to the tour participation history data, the server 1 uses the comments by our staff (the crew staff records the comments on what they noticed about each member during the tour) as the original data to make a proposal to each member user that they would like to take a trip like this (especially "family trips") in the future. Also, in the case of heavy users who often use the tour, they are often in a state where they can know the preferences and personalities of the members better than their family members who live separately. Therefore, the server 1 proposes a "family tour" to the member user and their family while sharing the past participation information with the family with the consent of the member user.

[0074] Next, the fourth case will be explained. The fourth case is the third example of utilizing the data when the user uses a flat-rate taxi. In this case, the server 1 shares the obtained going-out data and analysis data of the user who is a member of the flat-rate taxi with the family members who live separately, reports the daily situation of the member to the family, and proposes a "family trip" as a way to support the mental state of the user that the company and others cannot fully support and as a trigger for it.

[0075] Next, the fifth case will be explained. In this case, in addition to the tour participation history data, the server 1 creates a new plan specialized in a theme using the comments by our staff (the crew staff records the comments on what they noticed about each member during the tour) as the original data. In addition, the server 1 refers to past participation data and introduces the planned products to predetermined members (member users who like the theme (users with high favorability)) in the same theme. Here, as the predetermined members, only those who have participated in XX or more tours that match the past theme are eligible, and there are restrictions such as only one person who has been introduced can apply together. As a result, the people who participate in this tour will gather people with similar interests, so the participating users will be able to have more positive thoughts.

[0076] Next, the sixth case will be described. This sixth case is an example of providing support related to the meaning of life of users. In this case, the server 1 proposes karaoke outings and dining out with friends during the free time in the user's schedule, and supports going out for work (to be useful to someone). Specifically, the server 1 analyzes the themes that the user is interested in from the user's tour participation record, and proposes to help with short-term work (jobs) with a shortage of manpower in the field of that theme. For example, when there is a shortage of manpower for jobs such as rice planting and rice harvesting, each member user (travel member, flat-rate taxi member, etc.) is presented with problems in the area and asked to help during their free time. Here, the problems are not about labor, but about matching to satisfy the user's sense of fulfillment. The consideration for the help is not a labor fee, but a gift in kind as a token of gratitude (such as receiving vegetables from the farmer who was helped).

[0077] Next, the seventh case will be described. This seventh case is an example of externally utilizing a large amount of data obtained from multiple users by the server 1 when each of the multiple users uses a flat-rate taxi in their daily lives. At Server 1, the Action Proposal Unit 44 provides at least a part of the information extracted from the information (past behavior information) obtained based on the user's past behavior (for example, at least a part of the regional area, age, family composition, hobbies, health status, and information on which the user has acted), or the past behavior information, by including it in a part of the past data in the Past Behavior Information DB 52 and processing the information (for example, taking statistics using a certain index (such as family composition among tour participants, etc.)) to a predetermined organization (such as a sales-requesting company, etc.) that is the request source. In this case, based on the personal information obtained by Server 1 when multiple users use a flat-rate taxi, etc., Server 1 can realize an improvement in the personal QOL (quality of life) by making a proposal for beneficial data utilization to the individual member users who are the source of the personal information. As a result, it promotes the understanding of the importance of accumulating information and requests cooperation for further data acquisition. In this way, with the consent of the individual, the detailed personal information accumulated in Server 1 is converted into big data and made into statistical data so that the individual cannot be identified, and then the data is sold to companies that need the data. Regarding the profit obtained from data sales, a part of it is returned to the individual member users who provided the personal information as a dividend. As an example of the return method, for example, it is returned in the form of service utilization, rather than an equivalent return in terms of monetary value, such as being able to have lunch for free within the region.

[0078] Here, the companies that receive the data can obtain data in more detailed categories because the information is based on the consent of the individual, such as regional area, age, family composition, hobbies, health status, etc., and can utilize it as more meaningful information for the development of social services. Rather than having a negative image of companies misusing personal information without the consent of the individuals to make a profit, it is hoped that many people will understand that the behavioral data of each individual is the basic data necessary to greatly change society. As a member user, there is nothing particularly special to do. Just having an enjoyable daily life itself can contribute to that social transformation. By doing so, users are encouraged to positively view the provision of personal information and allow it to be utilized as a social contribution.

[0079] As described above, one embodiment of the present invention has been explained. However, the present invention is not limited to the above-described embodiment, and modifications, improvements, etc. within the scope that can achieve the object of the present invention are considered to be included in the present invention.

[0080] For example, the system configuration shown in FIG. 3 and the hardware configurations of the server 1, user terminal 2, and taxi terminal 3 shown in FIG. 4 are merely examples for achieving the object of the present invention and are not particularly limited.

[0081] Also, the functional block diagram shown in FIG. 4 is merely an example and is not particularly limited. That is, it is sufficient if the information processing system of FIG. 2 is equipped with the function of executing the various processes described above as a whole. What kind of functional blocks and databases are used to realize this function is not particularly limited to the example of FIG. 4.

[0082] Also, the location of the functional blocks and databases is not limited to FIG. 4 and can be arbitrary. Specifically, for example, the past behavior acquisition unit 41, element extraction unit 42, analysis unit 43, behavior proposal unit 44, etc. arranged in the server 1 may be configured as components provided in the taxi terminal 3.

[0083] For example, the above-described series of processes can be executed by hardware or by software. Also, one functional block and database may be configured by hardware alone, by software alone, or by a combination thereof. In other words, the functional configuration of FIG. 4 is merely illustrative and not particularly limited. That is, it suffices that the server 1 is equipped with a function capable of executing the above-described series of processes as a whole, and the functional blocks used to realize this function are not particularly limited to the example of FIG. 4.

[0084] When a series of processes are to be executed by software, the program constituting the software is installed in a computer or the like from a network or a recording medium. The computer may be a computer incorporated in dedicated hardware. Also, the computer may be a computer capable of executing various functions by installing various programs, for example, a general-purpose personal computer.

[0085] The recording medium containing such a program is not only constituted by the removable medium 31 of FIG. 3 distributed separately from the apparatus main body to provide the program to the user, but also constituted by a recording medium or the like provided to the user in a state pre-installed in the apparatus main body. The removable medium 31 is constituted by, for example, a magnetic disk (including a floppy disk), an optical disk, or a magneto-optical disk. The optical disk is constituted by, for example, a CD-ROM (Compact Disk - Read Only Memory), a DVD (Digital Versatile Disk), etc. The magneto-optical disk is constituted by an MD (Mini-Disk), etc. Also, the recording medium provided to the user in a state pre-installed in the apparatus main body is constituted by, for example, the ROM 12 of FIG. 3 in which a program is recorded or a hard disk included in the storage unit 18.

[0086] Note that in this specification, the execution processes arranged in the order from this application to other applications include not only processes performed in chronological order along that order, but also processes executed in parallel or individually even if they are not necessarily processed in chronological order. In addition, in this specification, the term "system" shall mean the overall device composed of a plurality of devices, a plurality of means, etc.

[0087] To summarize, the information processing apparatus to which the present invention is applied only needs to have the following configuration, and can take various embodiments. (1) That is, the information processing apparatus (for example, the server 1 in FIG. 4) to which the present invention is applied a past action acquisition means (for example, the past action acquisition unit 41 in FIG. 4) that acquires information on a predetermined past action as past action information, an element extraction means (for example, the element extraction unit 42 in FIG. 4) that extracts one or more elements determined to be positive among the predetermined past actions as positive elements based on the past action information, an action proposal means (for example, the action proposal unit 44 in FIG. 4) that generates information including a proposal content for the future action of the user as action proposal information based on one or more of the positive elements, is sufficient.

[0088] In this way, since the server 1 analyzes the past actions of the user and proposes a more suitable future action for the user from the past actions, when proposing a future action to the user based on the past actions, it is possible to provide a service that can propose a more suitable action for the user.

[0089] (2) In the above-described information processing apparatus (for example, the server 1 in FIG. 4), the element extraction means (for example, the element extraction unit 42 in FIG. 4) further extracts one or more elements determined to be negative among the predetermined past actions as negative elements based on the past action information, further includes an analysis means (for example, the analysis unit 43 in FIG. 4) that executes a predetermined analysis based on each of the one or more past action information, the one or more positive elements, and the one or more negative elements, the action proposal means (for example, the action proposal unit 44 in FIG. 4) generates the action proposal information based on the analysis result by the analysis means (for example, the analysis unit 43 in FIG. 4). can do.

[0090] (3) In the above information processing apparatus (for example, the server 1 in FIG. 4), the past action acquisition means (for example, the past action acquisition unit 41 in FIG. 4) acquires the action history information about the predetermined past actions of the user as the past action information. can do.

[0091] (4) In the above information processing apparatus (for example, the server 1 in FIG. 4), the past action acquisition means (for example, the past action acquisition unit 41 in FIG. 4) acquires the action history information (such as body movement, heart rate, number of steps, etc.) obtained by the function of a predetermined terminal (such as an acceleration sensor or a vital sensor worn by the user) as the past action information. can do.

[0092] (5) In the above information processing apparatus (for example, the server 1 in FIG. 4), the past action acquisition means (for example, the past action acquisition unit 41 in FIG. 4) acquires the action history information obtained by an input operation on the terminal of the user or a third party (for example, the driver or passenger of the taxi T, etc.) (such as the user terminal 2 or the taxi terminal 3), or the action history information including the captured image output from a camera (such as the camera function of a smartphone, etc.) according to the shooting operation of the user or the third party as the past action information. can do.

[0093] (6) In the above information processing apparatus (for example, the server 1 in FIG. 4), the past action acquisition means (for example, the past action acquisition unit 41 in FIG. 4) acquires the biological information (such as a snapshot photo showing the user's face, etc.) in the time period during or around the execution of the predetermined past actions of the user or a third party as the past action information. can do. (7) In the above information processing apparatus (for example, the server 1 in FIG. 4), the action proposal means (for example, the action proposal unit 44 in FIG. 4) Provide at least a part of the information extracted from the past action information, or the information obtained by processing the past action information as a part of past data, to a predetermined organization of the requester. As a result, when each of a plurality of users uses a flat-rate taxi in their daily lives, a vast amount of data obtained from the plurality of users can be utilized externally (e.g., by companies, etc.).

Explanation of Signs

[0094] N... Network, T, T-1 to T-n... Flat-rate taxi, 1... Server, 2... User terminal, 3, 3-1 to 3-n... Taxi terminal, 11... CPU, 12... ROM, 13... RAM, 14... Bus, 15... Input / output interface, 16... Input section, 17... Display section, 18... Storage section, 19... Communication section, 20... Drive, 31... Removable media, 41... Past action acquisition section, 42... Element extraction section, 43... Analysis section, 44... Action proposal section, 51... User DB, 52... Past action information DB

Claims

1. past behavior acquiring means for acquiring information regarding a predetermined past behavior as past behavior information; an element extraction means for extracting, as a positive element, one or more elements that are determined to be positive from the predetermined past behavior based on the past behavior information; an action suggestion means for generating information including suggestions for the user's future actions as action suggestion information based on one or more of the positive elements; An information processing device comprising:

2. The element extraction means further extracts, based on the past behavior information, one or more elements that are determined to be negative from the predetermined past behavior as negative elements; The method further includes an analysis means for performing a predetermined analysis based on the one or more positive elements and the one or more negative elements of each of the one or more pieces of past behavior information, The action suggestion means generates the action suggestion information based on an analysis result by the analysis means. The information processing device according to claim 1 .

3. The past behavior acquisition means acquires behavior history information regarding the predetermined past behavior of the user as the past behavior information. The information processing device according to claim 1 .

4. The past behavior acquisition means acquires behavior history information obtained by performing a function of a predetermined terminal as the past behavior information. The information processing device according to claim 1 .

5. The past behavior acquisition means acquires, as the past behavior information, the behavior history information obtained by an input operation to a terminal of the user or a third party, or the behavior history information including a captured image output from a camera in accordance with a shooting operation of the user or the third party. The information processing device according to claim 1 .

6. The past behavior acquisition means acquires, as the past behavior information, biological information of the user or a third party at the time of performing the predetermined past behavior or in a time period before or after the predetermined past behavior. The information processing device according to claim 1 .

7. The action suggestion means includes: providing at least a portion of the information extracted from the past behavior information, or information obtained by processing the past behavior information as a part of past data, to a predetermined organization that has made a request; The information processing device according to claim 1 .

8. An information processing method executed by an information processing device, a past behavior acquisition step of acquiring information about a predetermined past behavior as past behavior information; an element extraction step of extracting, as a positive element, one or more elements that are determined to be positive from the predetermined past behavior based on the past behavior information; a behavior suggestion step of generating information including a suggestion for a future behavior of the user based on one or more of the positive elements as behavior suggestion information; An information processing method comprising:

9. On the computer, a past behavior acquisition step of acquiring information about a predetermined past behavior as past behavior information; an element extraction step of extracting, as a positive element, one or more elements that are determined to be positive from the predetermined past behavior based on the past behavior information; a behavior suggestion step of generating information including a suggestion for a future behavior of the user based on one or more of the positive elements as behavior suggestion information; A program that executes control processing including:

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