Information processing device, information processing system, and information processing method

Abstract

This disclosure relates to information processing apparatus, information processing system, and information processing method. A technique for promoting the recycling of goods is provided. This involves acquiring sensing data obtained by sensing a user, inferring, based on the sensing data, whether the user needs or does not need an item, and, based on the result of the inference, performing predetermined processing related to the buying, selling, or acquiring of the needed or unwanted item.

Description

Technical Field

[0001] This disclosure relates to technologies for promoting the recycling of articles. Background Technology

[0002] As people's lives change, there are new needs for household goods, furniture, etc., or situations where household goods, furniture, etc., become unnecessary. Furthermore, in recent years, the recycling of unused goods through trading platforms has been actively developing. As a related technology, for example, Patent Document 1 discloses a platform that matches users who wish to transfer recycled goods with users who wish to acquire those recycled goods.

[0003] Existing technical documents

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Publication No. 2003-050859 Summary of the Invention

[0006] In existing technologies, users need to access the platform to exchange details of the transferred goods, contact the destination, etc., but there is room for improvement in reducing the hassle for users.

[0007] The purpose of this disclosure is to provide a technology for promoting the recycling of articles.

[0008] The first aspect of this disclosure is an information processing apparatus having a control unit that performs: acquiring sensing data obtained by sensing a user; inferring, based on the sensing data, whether a desired item or an unwanted item is available for the user; and performing predetermined processing related to the buying, selling, or transferring of the desired or unwanted item based on the result of the inference.

[0009] Furthermore, a second aspect of this disclosure is an information processing system comprising a first information processing device and a second information processing device. The first information processing device has a first control unit that performs the following actions: acquiring sensing data obtained by sensing a user; inferring, based on the sensing data, whether a desired item or an unwanted item exists for the user; and sending "need data" indicating whether each user needs the item to the second information processing device. The second information processing device has a second control unit that performs predetermined processing related to the buying, selling, or acquiring of the desired or unwanted item based on the "need data."

[0010] In addition, the third aspect of this disclosure is an information processing method, including: the step of obtaining sensing data obtained by sensing a user; and the step of inferring whether a needed item or an unwanted item is available to the user based on the sensing data.

[0011] Alternatively, as another option, one could provide a program for causing a computer to perform the aforementioned information processing method, or a computer-readable storage medium that non-temporarily stores the aforementioned program.

[0012] According to this disclosure, it is possible to provide technologies for promoting the recycling of articles. Attached Figure Description

[0013] Figure 1 This is a diagram illustrating the outline of the system involved in the first embodiment.

[0014] Figure 2 This is a diagram showing in detail the constituent elements of the home server according to the first embodiment.

[0015] Figure 3 This is a diagram illustrating the relationship between the modules in the first embodiment.

[0016] Figure 4 It is a diagram illustrating the data stored in the storage unit.

[0017] Figure 5 This is a diagram showing in detail the constituent elements of the central server according to the first embodiment.

[0018] Figure 6 This is a flowchart of the processing performed by the home server in the first embodiment.

[0019] Figure 7 This is a flowchart of the processing performed by the central server in the first embodiment.

[0020] Figure 8 This is a diagram showing in detail the constituent elements of the central server according to the second embodiment.

[0021] Figure 9 This is a diagram illustrating the outline of the system involved in the second embodiment.

[0022] Figure 10 This is a flowchart of the processing performed by the central server in the second embodiment.

[0023] Figure 11 This is a diagram illustrating the outline of the system involved in the third embodiment.

[0024] (Symbol Explanation)

[0025] 100: Home server; 101, 301: Control unit; 102, 302: Storage unit; 103, 303: Communication unit; 104: Input / output unit; 200: Sensor group; 300: Central server; 400: Carrier server; 500: Vehicle management device; 510: Autonomous vehicle. Detailed Implementation

[0026] This specification discloses an information processing device that determines whether a user needs items such as household goods or furniture based on observations of the user. For a given user, the system determines whether a new need for an item has arisen or whether an item has become unnecessary, thereby, for example, facilitating the exchange of secondhand goods between users.

[0027] The information processing apparatus of this embodiment includes a control unit that performs: acquiring sensing data obtained by sensing a user; predicting, based on the sensing data, whether a needed item or an unwanted item is available for the user; and performing predetermined processing related to the buying, selling, or acquiring of the needed or unwanted item based on the prediction result.

[0028] Sensing data refers to data obtained by sensing a user's life, actions, etc. Sensing data can be, for example, data obtained by directly observing the user (e.g., image data, sound data). Alternatively, sensing data can also be data obtained by indirectly observing the user (e.g., location information of the user's terminal, network traffic volume of that terminal, etc.).

[0029] The items disclosed herein typically refer to furniture, daily necessities, household goods, travel goods, etc., but are not limited to these.

[0030] Based on sensing data, the control unit can predict whether a specific user needs (or will need) new items, or whether the items they already own will become unnecessary (or will become unnecessary in the future).

[0031] As a pre-arranged process, such as acting as an intermediary for the buying, selling, or renting of secondhand goods, user convenience can be improved.

[0032] In addition, the control unit can also determine the user category corresponding to the user based on the sensing data.

[0033] User categories refer to classifications of a user's lifestyle and current situation, such as "within a predetermined age range," "with a predetermined family composition," or "employed in a predetermined occupation." User categories can also be related to the user's cohabitants. For example, user categories could include "children are within a predetermined age range" or "children have started school." Additionally, user categories can also represent future events such as "expected delivery," "expected to start school," or "expected to move."

[0034] Based on the sensor data, the control unit determines the user category corresponding to the target user. For example, if the number of people living in a household increases or decreases, it can be determined that the user category based on the family composition has changed.

[0035] Additionally, the information processing device may also be characterized by having a storage unit that stores product data that associates items that a user may use in their daily life with each user category, and the control unit makes the inference based on the user category and the product data.

[0036] Product data, for example, can be used to define, for each user category, items that they tend to use in their daily lives.

[0037] Based on the above structure, for example, it is possible to make a judgment such as "the user belongs to the category of 'expected delivery,' so there is a high probability that a crib is needed."

[0038] Additionally, the user category may also be characterized by including attributes related to the user and attributes related to the user's family.

[0039] Additionally, the attribute may also be characterized by including at least any of the following attributes: health status, family composition, and age.

[0040] The reason is that the size and quantity of equipment, props, and furniture needed in daily life may vary depending on health status, family composition, age, etc.

[0041] Alternatively, the sensing data may include the user's location information received from the user terminal, and the control unit determines the user category based on the history of the user's location information.

[0042] By using a user's historical location information, it's possible to determine user categories. For example, if a user regularly visits an obstetrics and gynecology clinic, it can be inferred that they are expecting. Similarly, if a user visits a daycare center or kindergarten during the morning or evening, it can be inferred that they have a child.

[0043] Alternatively, the predetermined process may be characterized by generating "need-to-have" data indicating whether each user needs the item, and registering the "need-to-have" data in a database.

[0044] Need data, for example, indicates whether a user needs (or has become needy) a certain item, or does not need (or has become unnecessary) a certain item. By registering this data in a database, the recycling of unused items can be facilitated.

[0045] In addition, the second aspect of this disclosure is an information processing system that includes the aforementioned information processing device (first information processing device) and the second information processing device.

[0046] The first information processing device has a first control unit that sends the aforementioned whether-needed data to the second information processing device, and the second information processing device has a second control unit that performs predetermined processing related to the buying, selling, or transferring of the required or unneeded item based on the whether-needed data.

[0047] Alternatively, in the second control unit, as part of the predetermined process, a process can be performed to match a first user who provides the item with a second user who receives the item based on whether data is required.

[0048] Based on the above structure, it is possible to mediate the exchange of items between multiple users.

[0049] Alternatively, the second control unit may generate an instruction to deliver the item from the first user to the second user.

[0050] This instruction can also be sent to delivery companies or devices managed by transportation operators. This allows for the automatic scheduling of items for delivery.

[0051] Alternatively, the second control unit may perform the predetermined process of generating contract data related to the leasing or sale of the item based on whether data is required.

[0052] Contract data, for example, can be used by operators engaged in the leasing or sales of goods.

[0053] Additionally, the second control unit may generate instructions for delivering the item to the user or for retrieving the item from the user.

[0054] Based on the above structure, arrangements for lending and returning items can be made automatically.

[0055] Alternatively, it may be characterized in that the second control unit sends the instructions to a server device that manages the mobile body transporting the items.

[0056] The mobile vehicle used to transport goods can be either a human-driven vehicle or an autonomous vehicle. When using an autonomous vehicle as a mobile vehicle, the delivery and recycling of goods can be automated.

[0057] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. The structures of the following embodiments are illustrative, and the present disclosure is not limited to the structures of the embodiments.

[0058] (First embodiment)

[0059] Reference Figure 1 This section provides an overview of the information processing system according to the first embodiment. The system configuration of this embodiment includes a home server 100 located in the user's home, a sensor group 200 associated with the home server 100, and a central server 300.

[0060] Home server 100 is a computer located in the user's home. Home server 100 uses a sensor array 200 to sense the user and, based on the results, infers the occurrence of new necessities or items that become unnecessary in the user's life. Furthermore, based on the inference results, the associated data is sent to central server 300.

[0061] Furthermore, there may be multiple home servers 100. In this embodiment, the multiple home servers associated with multiple users (or multiple households) are collectively referred to as home servers 100. Additionally, the items are referred to as goods.

[0062] Central server 300 is a computer that manages multiple home servers 100. Based on data received from the multiple home servers 100, central server 300 matches users who need a certain product with users who no longer need that product.

[0063] Figure 2 This diagram shows in more detail the constituent elements of the home server 100 and the sensor group 200 involved in this embodiment.

[0064] First, the sensors included in sensor group 200 will be described.

[0065] The sensor group 200 is configured to include multiple sensors 200A, 200B, etc., installed indoors. Regarding these multiple sensors, any sensor capable of acquiring data for detecting a user's presence, actions, attributes, lifestyle, or living environment is acceptable, regardless of its type. For example, it could be a camera (image sensor) that acquires visible light or infrared images, or a sound collection device. Alternatively, a combination of these could also be used. Furthermore, in cases where multiple people reside indoors, sensors capable of identifying each individual could be used.

[0066] Multiple sensors are configured to output sensor data. When the sensor is an image sensor, the sensor data can also be image data.

[0067] The sensors included in the sensor group 200 are preferably installed in multiple locations in a manner capable of sensing the user. For example, if the user's own home is the target, sensors can be installed in multiple rooms.

[0068] Home server 100 determines whether a user needs the ordered goods based on sensor data obtained from sensing the user and pre-stored data, and sends the result to central server 300. The detailed method will be described later.

[0069] The home server 100 can be configured using a general-purpose computer. That is, the home server 100 can be configured as a computer with a processor such as a CPU and GPU, main storage devices such as RAM and ROM, and auxiliary storage devices such as EPROM, hard disk drives, and removable media. Furthermore, the removable media can be, for example, a USB flash drive or a disc recording medium such as a CD or DVD. The auxiliary storage device stores the operating system (OS), various programs, various tables, etc., and executes them by loading the programs stored therein into the operating area of ​​the main storage device. Through program execution control of various structural units, various functions conforming to the predetermined purpose can be achieved, as described later. However, some or all of the functions can also be implemented using hardware circuits such as ASICs or FPGAs.

[0070] The control unit 101 is a computing device that manages the control of the home server 100. The control unit 101 can be implemented using a computing processing device such as a CPU (Central Processing Unit).

[0071] The control unit 101 is configured with three functional modules: a data acquisition unit 1011, a category classification unit 1012, and an evaluation unit 1013. Each functional module can also be implemented by the CPU executing a program stored in the storage unit 102 described later.

[0072] Refer to the diagram illustrating the sending and receiving of data between modules. Figure 3 This describes three functional modules.

[0073] The data acquisition unit 1011 acquires sensor data from the sensors included in the sensor group 200. The acquired sensor data can be image data (visible light image, infrared image) or sound data. In addition, it can also be other data or combinations thereof.

[0074] In addition, the data acquisition unit 1011 can also perform predetermined processing on the acquired sensor data. For example, it can transform the sensor data into feature quantities, or it can analyze the sensor data to obtain results.

[0075] For example, when the sensor data is image data, image recognition can be performed to obtain identifiers, number of people, height, status, posture, etc., of the people contained in the image. Similarly, when the sensor data is sound data, sound recognition can be performed to obtain text representing the content of a conversation.

[0076] The category classification unit 1012 uses the data acquired by the data acquisition unit 1011 and a pre-built machine learning model (hereinafter referred to as the category classification model) to classify users into predetermined categories. In this embodiment, the category classification is performed based on a machine learning model (category classification model) that pre-defines multiple categories and performs category classification for each category.

[0077] The category classification model is a pre-built machine learning model that classifies input data into one of several predefined categories. The category classification unit 1012 inputs the data acquired by the data acquisition unit 1011 into the category classification model and outputs the classification result. In this example, for instance, it obtains the category "Preparing for childbirth".

[0078] The defined user categories can also be categories associated with the actions, status, and attributes of users and their families. Additionally, user categories can be categories associated with future events that will occur for users and their families (childbirth, starting school, employment, relocation, marriage, etc.). Furthermore, user categories can also be categories associated with health status (healthy, difficulty walking, needing support, needing care, etc.), family composition (whether there is a spouse, children, cohabiting relatives, etc.), and age group.

[0079] In addition, a user can belong to more than two user categories at the same time.

[0080] The evaluation unit 1013 determines, based on the product data 102A and user data 102B stored in the storage unit 102 described below, which are products that belong to a certain category and that the user needs (or will need in the future) or products that the user no longer needs (or will no longer need in the future).

[0081] Here, we will explain the product data 102A and the user data 102B.

[0082] Figure 4 (A) is an example of Product Data 102A. Product Data 102A is data that associates the types of goods a user needs in their daily life with each user category. Figure 4 In example (A), for instance, if the user category is "preparing for childbirth", the definition requires the meaning of "crib", "stroller", and "baby bath".

[0083] Figure 4 (B) is an example of user data 102B. User data 102B is a list of goods held by the user. Home server 100 updates user data 102B when the user purchases, sells, disposes of, or leases goods. User data 102B can be managed by the user or updated automatically by the system based on sensing results.

[0084] The evaluation department 1013, referring to the product data 102A and user data 102B, determines that the user "needs products that are not currently available" if the following conditions are met.

[0085] (1) Associate one or more goods with at least one user category corresponding to the user.

[0086] (2) The user does not currently hold the goods.

[0087] In addition, the evaluation department 1013 determines that the user "no longer needs the goods currently in their possession" if the following conditions are met.

[0088] (1) The user currently has goods in stock.

[0089] (2) The product is not associated with any of the user categories corresponding to the user.

[0090] Based on the judgment results, the evaluation department 1013 generates whether data is needed. This data associates the user's identifier, the product's identifier, and whether the product is needed.

[0091] Figure 4 (C) is an example of whether data is needed. Furthermore, a value of "1" in the "Need?" column indicates that "goods not currently in stock are needed." Conversely, "0" indicates that "goods currently in stock are not needed."

[0092] In addition, whether or not data is needed can also be maintained regarding information related to product details (such as size, color, etc.).

[0093] Furthermore, in this example, a single user is shown, but if there are multiple users in the object, the evaluation unit 1013 can also generate whether data is needed for each of the multiple users.

[0094] The evaluation department 1013 sends the generated "need" data to the central server 300.

[0095] The storage unit 102 is configured to include a main storage device and a secondary storage device. The main storage device is a memory that contains the program executed by the control unit 101 and the data used by the control program. The secondary storage device is a device that stores the program executed by the control unit 101 and the data used by the program. Alternatively, the secondary storage device may store examples of programs executed by the control unit 101 packaged as applications. Additionally, it may store the operating system used to execute these applications. The processing described later is performed by loading the program stored in the secondary storage device into the main storage device and executing it by the control unit 101.

[0096] The primary storage device may also include RAM (Random Access Memory) or ROM (Read-Only Memory). Additionally, secondary storage devices may include EPROM (Erasable Programmable ROM) or HDD (Hard Disk Drive). Furthermore, secondary storage devices may also include removable media, i.e., portable recording media. Removable media include, for example, USB (Universal Serial Bus) storage devices, or disc recording media such as CD (Compact Disc) or DVD (Digital Versatile Disc).

[0097] In addition, the aforementioned product data 102A and user data 102B are stored in the storage unit 102.

[0098] Return to Figure 2 Let me continue explaining.

[0099] The communication unit 103 is a wireless communication interface for connecting the home server 100 to the network. The communication unit 103 is configured, for example, to communicate with the central server 300 via mobile communication services such as wireless LAN, 3G, LTE, and 5G.

[0100] The input / output unit 104 is a unit that accepts input operations from the user and provides prompts to the user. In this embodiment, it consists of a touch panel display. That is, it consists of a liquid crystal display and its control unit, and a touch panel and its control unit.

[0101] Next, we will explain the central server 300. Figure 5 This is a diagram showing in more detail the constituent elements of the central server 300 involved in this embodiment.

[0102] The central server 300 is a server device that matches users who provide goods with users who request goods based on whether data is needed sent from multiple home servers 100.

[0103] The central server 300 can also be configured using a general-purpose computer, just like the home server 100. That is, the central server 300 can be configured as a computer with processors such as CPU and GPU, main storage devices such as RAM and ROM, auxiliary storage devices such as EPROM, hard disk drives, and removable media.

[0104] The control unit 301 is a computing device that manages the control operations performed by the central server 300. The control unit 301 can be implemented using a computing processing device such as a CPU (Central Processing Unit).

[0105] The control unit 301 is configured with two functional modules: a data collection unit 3011 and a matching unit 3012. Each functional module can also be implemented by the CPU executing a program stored in the storage unit 302 (described later).

[0106] The data collection unit 3011 collects whether data is needed from multiple home servers 100 and stores it in the storage unit 302 described later.

[0107] The matching unit 3012 matches users with each other based on the need / dislike data stored in the storage unit 302, and provides the results to the corresponding home server 100. Specifically, it matches users who are determined not to need a certain product and users who are determined to need the product, and sends the results to the home server 100 corresponding to each user respectively.

[0108] The storage unit 302 is configured to include a main storage device and an auxiliary storage device. The main storage device is a memory that displays the program executed by the control unit 101 and the data used by the control program. The auxiliary storage device is a device that stores the program executed in the control unit 301 and the data used by the control program.

[0109] In storage unit 302, data collected from home server 100 is stored to determine whether data is needed.

[0110] Communication unit 303 has the same communication interface as communication unit 103. Communication unit 303 is configured, for example, to communicate with home server 100 via a wide area network such as the Internet.

[0111] also, Figure 2 as well as Figure 5 The structure shown is an example; all or part of the functions illustrated can also be executed using specially designed circuitry. Alternatively, programs can be stored or executed using a combination of main and auxiliary storage devices, other than those shown in the diagram.

[0112] Next, we will explain the processing performed by home server 100. Figure 6 This is a flowchart of the processes performed by the home server 100.

[0113] First, in step S11, the data acquisition unit 1011 acquires sensor data transmitted from the sensors included in the sensor group 200. Furthermore, the data acquisition unit 1011 may temporarily accumulate sensor data until a sufficient amount of data for categorization is collected. Additionally, the data acquisition unit 1011 may perform analysis, processing, etc., on the acquired sensor data.

[0114] Next, in step S12, the category classification unit 1012 inputs the data obtained by the data acquisition unit 1011 into the category classification model to obtain the classification result (user category).

[0115] In step S13, the evaluation unit 1013 generates whether data is needed based on the user category, product data 102A, and user data 102B obtained by the category classification unit 1012 through the above processing.

[0116] In step S14, the evaluation unit 1013 determines whether the necessary conditions for sending whether data is needed to the central server 300 are met.

[0117] For example, judging the user category only once may not accurately determine whether an item is needed. For instance, if the number of people in a household increases, it's difficult to immediately determine whether it's due to an increase in residents or visitors. Therefore, steps S11 to S13 can be repeatedly executed, sending a request for data only when the necessary conditions are met (e.g., the same user category has been visited more than a predetermined number of times). This allows sending a request for data only when the likelihood is high.

[0118] If the decision is positive in step S14, the process proceeds to step S15, where the evaluation unit 1013 sends a message to the central server 300 indicating whether data is needed. If the decision is negative, the process returns to step S11.

[0119] Whether the data sent is needed is received by the central server 300 (data collection unit 3011) and stored in the storage unit 302.

[0120] Next, we will explain the processing performed by the central server 300. Figure 7 This is a flowchart of the process performed by the central server 300 (matching unit 3012). The process illustrated is performed, for example, at a predetermined cycle.

[0121] First, in step S21, the latest need data stored in the storage unit 302 is obtained.

[0122] Next, in step S22, the items containing whether or not data is needed are used as keywords to attempt matching users with each other. That is, matching users who no longer need (or are expected to no longer need) a certain item with users who do need (or are expected to need) that item.

[0123] As a result, if a match is determined (step S23 - "Yes"), the process proceeds to step S24, where the transfer and acceptance of the goods are explored for both users. For example, for the user on the side providing the goods, it is confirmed whether the goods can be transferred, and for the user on the side accepting the transfer, it is confirmed whether they wish to accept the goods. Furthermore, at this time, queries related to the transfer price of the goods can also be performed.

[0124] In step S23, if the match is determined to be invalid, the process ends.

[0125] When both users accept the proposal (step S25 - "Yes"), the process proceeds to step S26, where information is provided to both users. This allows the users to exchange goods. If either user does not accept the proposal, the process ends.

[0126] As explained above, in the information processing system according to the first embodiment, the category to which the user belongs is determined based on the results obtained from sensing the user, and based on the category, it is determined whether the user needs or does not need an item. By performing this on multiple users, it is possible to automatically match users who are transferring items with each other.

[0127] (A variation of the first embodiment)

[0128] The sensors included in sensor group 200 are not limited to those that directly sense the user. For example, they can also be set up at the user's own network switch to obtain the communication traffic caused by the user. That is, a computer can also be used to capture the data sent and received by the user as sensor data.

[0129] For example, if a user wants information about childbirth-related subsidies, it can be inferred that the user belongs to a category such as "preparing for childbirth".

[0130] Furthermore, the sensors included in the sensor group 200 do not necessarily need to be fixed. For example, a user's terminal (user terminal) can also be used as a sensor. In this case, the sensor data can be sent from the user terminal to the home server 100. For example, the user terminal can periodically send location information to the home server 100, and the home server 100 can process the location information into sensor data corresponding to the user.

[0131] In this case, the home server 100 can acquire data related to the user's movement (such as the locations visited by the user, dates and times, frequency, etc.) and store it in the storage unit 102. Furthermore, the category classification unit 1012 can determine the user category based on such data (such as historical location information). Therefore, the home server 100 can also store data (such as tables, machine learning models) used to determine the user category based on historical location information.

[0132] In addition, in the first embodiment, users are matched only based on whether data is needed, but user matching can also take other factors (such as the user's address) into account.

[0133] In addition, in the first embodiment, the process of introducing users to each other is performed, but it is also possible not to directly introduce users, but only to inform users who want goods or users who can provide goods, and guide them to other services.

[0134] (Second embodiment)

[0135] In the first embodiment, the transfer of items (second-hand goods) is mediated by matching users with each other. In contrast, the second embodiment is an implementation that automatically performs procedures for purchasing or renting items.

[0136] Figure 8 This is a diagram showing in more detail the constituent elements of the central server 300 according to the second embodiment.

[0137] The second embodiment differs from the first embodiment in that the control unit 301 replaces the matching unit 3012 and has a contract unit 3013.

[0138] like Figure 9 As shown, in the second embodiment, the central server 300 is configured to also communicate with the operator server 400. The operator server 400 is a server device for operator management, used for leasing or selling goods. The operator server 400 may also exist for each of multiple operators.

[0139] Contract Department 3013 generates contract data for Carrier Server 400.

[0140] Contract data can be, for example, data like the following.

[0141] • Data from the rental agreement used to apply for the item

[0142] • Data on the termination of rental contracts used to apply for items

[0143] • Data used to apply for the purchase of items

[0144] • Data used to apply for the sale of items

[0145] Contract data includes, for example, data about the items used to identify the object, the contract period (in the case of renting the items), and user information.

[0146] Figure 10 This is a flowchart of the processing performed by the central server 300 (contract unit 3013) in the second embodiment.

[0147] In the second embodiment, after obtaining whether data is needed in step S21, in step S22A, an operator capable of disposing of the item is retrieved. For example, by communicating with an external device, an operator capable of lending, selling, purchasing, etc., the item can be retrieved.

[0148] Next, in step S23A, it is determined whether a carrier has been identified. If no carrier is found, the process ends.

[0149] In step S24A, contract data is generated and displayed to the user. If the user accepts the contract (step S25A - "Yes"), the process proceeds to step S26A, where the contract data is sent to the operator server 400. If the user does not accept the contract (step S25A - "No"), the process ends.

[0150] According to the second embodiment, it is possible to simplify negotiations with operators who handle the items.

[0151] In addition, contract data is generated in this embodiment, but it is also possible not to generate contract data and only introduce the operator (recommended).

[0152] (Third Implementation)

[0153] In the first and second embodiments, users and operators must make arrangements for transporting items. In contrast, the third embodiment is an embodiment in which the central server 300 arranges autonomous vehicles to transport items when they need to be transported.

[0154] like Figure 11As shown, in the third embodiment, the central server 300 is configured to communicate with the vehicle management device 500. The vehicle management device 500 is a device for managing multiple autonomous vehicles 510.

[0155] The vehicle management device 500 collects information about each of the multiple autonomous vehicles 510 under its management (vehicle information, such as location information and current vehicle status). Furthermore, it sends operation instructions (operation commands) to each of the multiple autonomous vehicles 510 under its management. This enables the autonomous vehicles 510 to operate along a designated path.

[0156] The execution command can also include data specifying the driving route, transit points, and destination. Additionally, the execution command can include data specifying the processes to be performed along the route. Examples of processes to be performed along the route include user calls, loading of goods, and handover of goods.

[0157] When the third implementation method is combined with the first implementation method, the central server 300 generates an execution instruction meaning "to collect an item from the user who is the transferor and deliver the item to the user who is the transferee." This process... Figure 7 Execute after step S26 is completed.

[0158] Furthermore, when combining the third and second embodiments, the central server 300, for example, generates an operation instruction meaning "to collect items from the operator providing the items (rental operator or sales operator) and deliver the items to the user." Alternatively, it generates an operation instruction meaning "to retrieve items from the user as return items and deliver the items to the rental operator." This process... Figure 10 Execute after step S26A is completed.

[0159] In addition, the central server 300 can also determine the date and time for the autonomous vehicle 510 to run after confirming the schedules of the users or operators who are the parties involved, as well as the schedules of the vehicles.

[0160] According to the third embodiment, the arrangement for transporting items can be performed automatically.

[0161] (Modified Example)

[0162] The above-described embodiments are merely examples, and this disclosure can be adapted and implemented in a manner appropriate to the extent necessary without departing from its spirit.

[0163] For example, the processes and units described in this disclosure can be freely combined and implemented as long as they do not create technical contradictions.

[0164] In addition, in the description of the implementation method, procedures related to the sale and transfer of items are carried out as a predetermined process, but it may also be recommended only.

[0165] Furthermore, it can be shown that processing intended for one device can also be performed by multiple devices. Alternatively, it can be shown that processing intended for different devices can also be performed by one device. In a computer system, it is possible to flexibly change the hardware architecture (server architecture) used to implement various functions.

[0166] This disclosure can also be implemented by supplying a computer program with the functions described in the above embodiments to a computer, which then reads and executes the program using one or more processors. Such a computer program can be provided to the computer either through a non-transitory computer-readable storage medium that can be connected to the computer's system bus, or via a network. Non-transitory computer-readable storage media include, for example, any type of disk such as a hard disk (floppy disk, hard disk drive (HDD)), an optical disk (CD-ROM, DVD / Blu-ray disc, etc.), read-only memory (ROM), random access memory (RAM), EPROM, EEPROM, magnetic cards, flash memory, optical cards, and any type of medium suitable for storing electronic commands.

Claims

1. An information processing device, comprising: The storage department stores product data that associates items that a user might use in their daily life with each user category; and The control department performs the following: Acquire sensing data obtained by sensing the user, the sensing data including the user's location information received from the user terminal; Based on the user's location history, a user category corresponding to the user is determined. The user category includes attributes related to the user and attributes related to the user's family. The attributes include at least one of health status, family composition, and age. Obtain user data including the history of items acquired by the user; Based on the user category, the product data, and the user data, infer items that the user may now need or no longer need; and Based on the results of the aforementioned predictions, pre-arranged procedures will be carried out related to the buying, selling, or transferring of items that are newly needed or have become no longer needed. The predetermined process is to generate "need-to-have" data indicating whether each user needs the item, and to register the "need-to-have" data in a database.

2. An information processing system, comprising a first information processing device and a second information processing device, wherein, The first information processing device has: The storage department stores product data that associates items that a user might use in their daily life with each user category; and The first control unit performs the following: Acquire sensing data obtained by sensing the user, the sensing data including the user's location information received from the user terminal; Based on the user's location history, a user category corresponding to the user is determined. The user category includes attributes related to the user and attributes related to the user's family. The attributes include at least one of health status, family composition, and age. Obtain user data including the history of items acquired by the user; Based on the user category, the product data, and the user data, infer items that the user may now need or no longer need; as well as Based on the inference results, need data indicating whether each user needs the item will be sent to the second information processing device. The second information processing device has a second control unit that performs predetermined processing related to the buying, selling, or transferring of items that are newly needed or have become no longer needed, depending on whether the data is needed.

3. The information processing system according to claim 2, wherein, The first information processing device generates the data requirement status for each of the multiple users.

4. The information processing system according to claim 2 or 3, wherein, In the second control unit, as part of the predetermined process, a process is performed to match the first user who provides the item with the second user who receives the item based on whether data is required.

5. The information processing system according to claim 4, wherein, The second control unit generates an instruction to deliver the item from the first user to the second user.

6. The information processing system according to claim 2 or 3, wherein, In the second control unit, as part of the predetermined process, processing is performed to generate contract data related to the rental or sale of the item based on whether data is required.

7. The information processing system according to claim 6, wherein, The second control unit generates instructions for delivering the item to the user or for retrieving the item from the user.

8. The information processing system according to claim 5 or 7, wherein, The second control unit sends the instruction to the server device that manages the mobile body transporting the item.

9. An information processing method, comprising: The steps to obtain product data that associates items that users may use in their daily lives with each user category; The step of obtaining sensing data obtained by sensing the user, wherein the sensing data includes the user's location information received from the user terminal; The step of determining the user category corresponding to the user based on the user's historical location information, wherein the user category includes attributes related to the user and attributes related to the user's family, wherein the attributes include at least one of health status, family composition, and age; The step of obtaining user data including the user's history of acquiring items; Based on the user category, the product data, and the user data, the steps for inferring items that the user may now need or no longer need; and Based on the predicted results, predetermined processing steps will be performed related to the buying, selling, or transferring of the newly needed or no longer needed items. The predetermined process is to generate "need-to-have" data indicating whether each user needs the item, and to register the "need-to-have" data in a database.

Images