Processing system and processing method

Abstract

Identify the needs of users such as disaster victims during disasters, etc. [Solution] A user terminal 100 stores, in association with a user identifier, multiple personal data sets PS that associate information about the user of the user terminal 100 with each data type of information. A processing device 200 includes a collection unit 221 that collects the user identifier and the multiple personal data sets from the user terminal 100, and an identification unit 223 that identifies the needs of the user of the user terminal 100 for each type from the types of the multiple personal data sets and the user information.

Description

[Technical Field]

[0001] The present disclosure relates to a processing system and a processing method. [Background technology]

[0002] Disaster prevention measures are essential for Japan. Disasters can cause communication network disruptions, disrupt transportation networks, and damage to medical staff and other support personnel. Ensuring medical care and protecting victims during disasters is essential.

[0003] Non-Patent Documents 1-3 disclose evacuation drills and the provision of hazard maps on the Metaverse. Non-Patent Document 4 discloses the activities of the Japan Medical Association Team (JMAT) and others in the event of a disaster. Non-Patent Document 5 discloses AI technology that supports the Metaverse. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Masahiro Arima and 1 other, "Possibilities and Challenges of Utilizing City-Linked Metaverses for Disaster Prevention," [online], 2022, 84th National Conference of the Japan Society for Information and Management, [Retrieved August 8, 2024], Internet〈URL: https: / / www.jstage.jst.go.jp / article / jsimconf / 84 / 0 / 84_93 / _pdf〉 [Non-patent document 2] Harada, Takeomi, and five others, "Practical efforts to improve hazard maps using the metaverse ~iHazard map project~," [online], 2023, AI and Data Science Papers, Vol. 4, No. 2, 2023, [Retrieved August 8, 2024], Internet〈URL:ttps: / / www.jstage.jst.go.jp / article / jsceiii / 4 / 2 / 4_102 / _pdf / -char / ja〉 [Non-patent document 3] Kyushu University, "Digital evacuation drill and demonstration experiment using generative AI and real-space metaverse," [online], 2024, [Retrieved August 8, 2024], Internet〈URL: https: / / www.kyushu-u.ac.jp / ja / notices / view / 2610 / 〉 [Non-patent document 4] Satoru Arai and three others, "Tokyo Medical Association's Efforts and Future Plans for Disaster Medical Care," [online], February 2023, Journal of Tokyo Women's Medical University 93(1): 35-39, [Retrieved August 8, 2024], Internet〈URL:https: / / www.jstage.jst.go.jp / article / jtwmu / 93 / 1 / 93_35 / _pdf / -char / ja〉 [Non-patent document 5] Yoichiro Miyake, "Commentary Paper: Technology Supporting the Metaverse - AI (Artificial Intelligence) Technology -", [online], 2023, Communications Society Magazine No. 67 Winter Issue 2023, [Retrieved August 8, 2024], Internet〈URL: https: / / www.jstage.jst.go.jp / article / bplus / 17 / 3 / 17_207 / _pdf / -char / ja〉 Summary of the Invention [Problem to be solved by the invention]

[0005] During a disaster, demands different from normal ones may occur. However, it may be difficult to identify the demands of disaster victims due to communication network failures and other issues.

[0006] The present disclosure has been made in consideration of the above circumstances, and an object of the present disclosure is to provide a technology that can identify the needs of users such as disaster victims during a disaster or the like. [Means for solving the problem]

[0007] A processing system according to one aspect of the present disclosure includes a user terminal and a processing device connected to the user terminal, wherein the user terminal stores a plurality of personal data sets that associate information about a user of the user terminal with each data type of the information, in association with an identifier of the user, and the processing device includes a collection unit that collects the identifier of the user and the plurality of personal data sets from the user terminal; The system further includes an identification unit that identifies the needs of the user of the user terminal for each of the types based on the types of the plurality of personal data sets and the user information.

[0008] In one aspect of the processing method of the present disclosure, a user terminal stores a plurality of personal datasets that correspond to an identifier of a user of the user terminal, information about the user, and each data type of the information, a processing device connected to the user terminal collects the plurality of personal datasets from the user terminal, and the processing device identifies the user's needs for each type based on the types of the plurality of personal datasets and the user's information. [Effects of the Invention]

[0009] According to the present disclosure, it is possible to provide a technology that can identify the needs of disaster victims in the event of a disaster. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating the system configuration of a processing system according to the present disclosure and functional blocks of a user terminal and a processing device. [Figure 2] FIG. 2 is a diagram illustrating an example in which a user terminal and a processing device are connected by short-range communication. [Figure 3] FIG. 3 is a diagram illustrating an example in which a user terminal and a processing device are connected via a public communication network. [Figure 4] FIG. 4 is a diagram illustrating an example in which a user terminal and a processing device are connected via short-range communication and a public communication network. [Figure 5]FIG. 5 is a diagram illustrating an example of the data structure and data of a personal data set held by a user terminal. [Figure 6] FIG. 6 is a diagram illustrating an example of the data structure and data of the dictionary data. [Figure 7] FIG. 7 is a flowchart illustrating an example of a generation process performed by the generation unit of the user terminal. [Figure 8] FIG. 8 is a diagram illustrating an example of the data structure and data of personal data held by the processing device. [Figure 9] FIG. 9 is a flowchart illustrating an example of the reproduction process performed by the reproduction unit of the processing device. [Figure 10] FIG. 10 is a diagram illustrating the hardware configuration of a computer used in the processing device and the user terminal. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the description of the drawings, the same parts are designated by the same reference numerals and the description thereof will be omitted.

[0012] (Processing System) The processing system 1 shown in Fig. 1 appropriately grasps the needs of disaster victims during times of disasters and the like. The processing system 1 includes a user terminal 100 and a processing device 200. A user who uses the user terminal 100 is, for example, a disaster victim. The processing system 1 shown in Fig. 1 includes one user terminal 100, but may also include multiple user terminals 100.

[0013] In the present disclosure, the user terminal 100 and the processing device 200 are connected to each other so that they can communicate with each other, but the connection method may be variable depending on the network failure situation. An example of the connection method in the processing system 1 will be described with reference to Figures 2-4.

[0014] FIG. 2 shows a processing system 1a in which a user terminal 100 and a processing device 200 are connected via short-range communication 2. Both the user terminal 100 and the processing device 200 shown in FIG. 2 are installed in a predetermined area such as an evacuation shelter. The processing system 1 identifies the demand of users in the predetermined area. The connection method shown in FIG. 2 is suitable for identifying the demand of users in a predetermined area even when the public communication network is not functioning due to a failure.

[0015] The short-range communication 2 shown in Fig. 2 is wired communication possible between computers connected by a cable, or wireless communication provided in a specific area. Examples of cables used in wired communication include a Universal Serial Bus (USB) cable or a wired Local Area Network (LAN) cable. Examples of wireless communication include Wi-Fi (Wireless Fidelity), local 5G, and contactless Integrated Circuit (IC) communication. Contact IC communication may also be included in short-range communication.

[0016] FIG. 3 shows a processing system 1b in which a user terminal 100 and a processing device 200 are connected via a public communication network 3. The user terminal 100 and processing device 200 shown in FIG. 3 can be installed in any location. The user terminal 100 may be located in a disaster area, and the processing device 200 may be located in a data center away from the disaster area. The connection method shown in FIG. 3 is suitable for cases in which the demands of users in multiple areas are identified from data held by the user terminal 100, or in which the processing device 200 collects information from each user terminal 100 under normal circumstances.

[0017] The public communication network 3 is the Internet, a wireless communication network provided by a communication carrier, a satellite communication network, or a combination of these.

[0018] FIG. 4 shows a processing system 1 c in which a user terminal 100 and a processing device 200 a are connected via short-range communication 2 , and the processing device 200 a is connected to another processing device 200 b via a public communication network 3 .

[0019] 4 is suitable for cases where the number of terminals that can connect to the public communication network 3 is limited. For example, a processing device 200a that can communicate with the user terminal 100 over short distances is installed in an area where the public communication network 3 does not reach. After communicating with the user terminal 100, the processing device 200a is moved and connected to the public communication network 3, whereby the processing device 200b can collect information on users in multiple areas.

[0020] As another example, the processing system 1c may identify users in isolated areas caused by road closures or the like, or users who have suffered damage from landslides or the like. A drone equipped with a processing device 200a capable of short-range communication with user terminals 100 flies in the isolated area or the area where a landslide has occurred. The processing device 200a can collect user data from the user terminals 100 of the affected users and share that data with the processing device 200b. The processing device 200a equipped on the drone can collect identifiers of the affected users and identify detailed information about the affected users by cooperating with the processing device 200b, which has previously collected and stored user data.

[0021] The connection method shown in FIG. 2-4 is an example, and other methods may be adopted.

[0022] (user terminal) The user terminal 100 includes a plurality of personal data sets PS11, PS12, PS13, . . . , dictionary data 111, a generation unit 121, and a transmission unit 122.

[0023] Personal data sets PS11, PS12, PS13, etc. are data of information related to users. In the present disclosure, any one or more personal data sets among personal data sets PS11, PS12, PS13, etc. may be referred to as personal data set PS.

[0024] One personal data set PS typically contains a group of information, like a card, and is formed as one file. Multiple personal data sets PS may be included in one file in CSV format.

[0025] In the present disclosure, each personal data set PS is provided independently and, in principle, is not linked to other personal data sets, etc. In another embodiment, one personal data set PS may be linked to other personal data sets, etc.

[0026] 5, the personal data set PS associates information about the user of the user terminal 100 with each type of data for that information. The personal data sets PS11, PS12, PS13, etc. may further associate the time and location of an event that occurred to the user in relation to the user information. The user terminal 100 stores multiple personal data sets PS in association with the user's identifier.

[0027] The types of personal data sets PS are, for example, medical, family, physical, wish list, etc. The types may be set in advance as defaults, or may be arbitrarily set by the user.

[0028] The dictionary data 111 is data that is referenced by the generation unit 121, which will be described later. The dictionary data 111 associates words with the types of personal datasets PS in which the words are registered, as shown in Fig. 6. The dictionary data 111 is referenced when the generation unit 121 generates the personal dataset PS by natural language processing.

[0029] The dictionary data 111 associates frequently appearing words with each type of personal data set PS, for example, by referring to a plurality of personal data sets PS generated by a plurality of user terminals 100. For example, the keywords "antihypertensive drug," "salt," and "soy sauce" related to high blood pressure are associated with the types "medicine," "salt," and "wish list," respectively.

[0030] The generation unit 121 generates a personal dataset PS and stores it in the user terminal 100. The generation unit 121 generates the personal dataset PS in response to a user instruction. Alternatively, the generation unit 121 generates the personal dataset PS by detecting a user action. Here, the user action may be, for example, the user's use of another app, detection by a sensor provided in the user terminal 100, etc.

[0031] When generating template data from a personal data set PS in response to a user instruction, the generation unit 121 prompts the user to select a type and displays template data corresponding to the selected type. The template data has input fields for inputting "time" and "location" as input items common to each type. The template data also has input fields for inputting "information" items corresponding to the selected type. For example, for the "medical" type, fields for inputting the name and quantity of prescribed medications, test results, doctor's interview results, etc. are displayed. These fields may be filled in manually by the user, or may be filled in using, for example, image data of a prescription or test results and an OCR (Optical Character Reader) function.

[0032] When generating the personal data set PS by detecting a user's action, the generation unit 121 acquires the user's operation on the user terminal 100 or sensing information from a sensor mounted on the user terminal 100. For example, when a microphone mounted on the user terminal 100 detects the user's conversation, the generation unit 121 analyzes the user's voice and generates the personal data set PS.

[0033] At this time, the generation unit 121 may identify data to be set in the personal dataset PS through natural language processing using the dictionary data 111. The generation unit 121 generates, from the dictionary data 111, a personal dataset PS that associates words with types corresponding to words identified from data acquired by a sensor mounted on the user terminal 100. For example, when it is detected that the user has uttered "soy sauce," the generation unit 121 generates a personal dataset PS in which the type "wish list" and the information "soy sauce" are set. When it is detected that the user has uttered "antihypertensive drug," the generation unit 121 generates a personal dataset PS in which the type "medicine" and the information "antihypertensive drug" are set.

[0034] The generation unit 121 may also refer to environmental information data (not shown) that records weather, disasters, etc., and the user's location identified by a GPS (Global Positioning System) receiver of the user terminal 100. The generation unit 121 may analyze the user's utterances and identify data to be set in the personal dataset PS, taking into consideration the weather, disasters, etc., in the user's location. For example, if the user utters "I have a cough at night," and an infectious disease related to the cough is registered in the environmental information data, the generation unit 121 may generate a personal dataset PS that associates the user's utterance with the infectious disease.

[0035] 1, the dictionary data 111 is stored in the user terminal 100, but this is not limiting. The dictionary data 111, environmental information data, and the natural language processing function of the generation unit 121 may be stored in a server to which the user terminal 100 can connect, and the generation unit 121 may identify the data to be set in the personal dataset PS in cooperation with the server.

[0036] The generation process performed by the generation unit 121 will be described with reference to FIG.

[0037] In step S101, the generation unit 121 detects a trigger for generating personal data set PS and allocates processing depending on the type of trigger. When an instruction to generate personal data set PS is input from the user, the generation unit 121 proceeds to step S102. When a user action is detected, the generation unit 121 proceeds to step S103.

[0038] When an instruction to generate a personal data set PS is input, in step S102 the generation unit 121 generates the personal data set PS from the type and information specified by the user. At this time, the generation unit 121 first prompts the user to input the type. The generation unit 121 may display an input screen corresponding to template data according to the input type, and prompt the user to input each item of the personal data set PS.

[0039] Upon detecting a user's action, in step S103 the generation unit 121 converts the information detected by the user's action into text data. Here, the generation unit 121 may use natural language processing. In step S104, the generation unit 121 identifies the type of personal dataset PS to be generated from the words included in the text data converted in step S103 and the dictionary data 111. In step S105, the generation unit 121 generates personal dataset PS from the type identified in step S104 and the text data converted in step S103.

[0040] When the personal data set PS is generated in step S102 or step S105, the generation unit 121 returns to step S101 and waits for a new trigger.

[0041] The transmission unit 122 transmits data held by the user terminal 100 to the processing device 200. The data held by the user terminal 100 includes a user identifier, a personal data set PS, and the like.

[0042] The transmission unit 122 transmits data of a type requested by the processing device 200 to the processing device 200. The transmission unit 122 may transmit only the user identifier among the user identifier and a plurality of personal data sets PS, or may transmit personal data sets PS of a specified type. The transmission unit 122 may also determine the data to be transmitted depending on the connection method with the processing device 200. For example, when the communication bandwidth with the processing device 200 is narrow, the transmission unit 122 may transmit only the user identifier.

[0043] (Processing device) 1, the processing device 1 includes personal data 211, demand data 212, and assistance data 213, and functions of a collection unit 221, a reproduction unit 222, an identification unit 223, and a matching unit 224. Each piece of data is stored in a storage device such as a memory 902 or a storage 903. Each function is implemented in a CPU 901.

[0044] The personal data 211 is data including the personal data set PS collected from each user terminal 100. The personal data 211 is data that associates a user identifier with data in the personal data set PS owned by the user, for example, as shown in Fig. 8.

[0045] The demand data 212 is data that identifies the demand of a user identified by the identification unit 223. The demand data 212, for example, associates a user identifier with data that identifies the demand of the user. For example, the identifier of a certain user is associated with data that indicates the user's demand, such as "I will need to see an internal medicine doctor and take antihypertensive medication around the 20th."

[0046] The demand data 212 may be data in which the demand of each user is aggregated by demand type. For example, the demand data 212 may associate the aggregate value of the number of antihypertensive drugs required by each user with "antihypertensive drugs." The processing device 200 may order drugs and the like to meet the demand of the user according to the demand data 212.

[0047] The assistance data 213 is data that associates the identifier of a supporter with the assistance content of that supporter. For example, in the event of a disaster, the assistance data 213 is stored in a processing device 200 connected to the public communication network 3, specifically, the processing device 200 in Fig. 3 or the processing device 200b in Fig. 4. The assistance data 213 is generated from input to the supporter terminal 300.

[0048] The supporter is typically located outside the disaster area. The supporter terminal 300 used by the supporter transmits the support content that the supporter can provide to the processing device 200 via the public communication network 3. As another example, the supporter may be located within the disaster area. The supporter terminal 300 may transmit to the processing device 200 the identifier of the evacuation shelter where the supporter is located and the support content that the supporter can provide.

[0049] The collection unit 221 collects a user identifier and a plurality of personal data sets PS from the user terminal 100. The collection unit 221 may collect a plurality of personal data sets PS from each of a plurality of user terminals 100.

[0050] The collection unit 221 stores user identifiers and multiple personal data sets PS collected from multiple user terminals 100 in personal data 211. The collection unit 221 may collect multiple personal data sets PS from user terminals 100 in multiple areas during normal times, or may collect multiple personal data sets PS from user terminals 100 in a limited area during a disaster.

[0051] For example, the collection unit 221 may be mounted on a processing device 200a of a processing system 1c shown in Fig. 4 and may collect identifiers of users of user terminals 100 through short-range communication in a predetermined area. For example, using the processing system 1c shown in Fig. 4, a drone equipped with a processing device 200a capable of short-range communication with the user terminal 100 flies over an isolated area caused by road closures or the like, or an area damaged by a landslide or the like. The collection unit 221 of the processing device 200a collects user identifiers from the user terminals 100.

[0052] The reproducing unit 222 extracts a personal data set PS at a predetermined time from the multiple personal data sets PS. The reproducing unit 222 places an avatar of each user in a virtual space, the avatar reflecting the state of the user identified from the user information of each extracted personal data set PS.

[0053] The reproduction unit 222 extracts the personal data set PS collected from each user from the personal data 211 and identifies the user's state at a predetermined time. This user's state may be, for example, details of the user's location, the user's movements, the user's physical state such as whether or not the user is injured, etc. The reproduction unit 222 identifies the location and information of a certain user from the data extracted from the personal data 211.

[0054] For example, if the user is currently receiving treatment at a certain internal medicine clinic, the reproducing unit 222 sets up the internal medicine hospital in the virtual space, and sets up an avatar of the internal medicine doctor and an avatar of the user who is currently receiving treatment from the internal medicine doctor's avatar at the hospital. In this way, the reproducing unit 222 can estimate the state of each user at a predetermined time from the personal data 211 and generate a virtual space that reproduces the state of each user at that time.

[0055] The reproduction process by the reproduction unit 222 will be described with reference to FIG.

[0056] In step S201, the reproducing unit 222 acquires the time and place to be reproduced.

[0057] In step S202, the reproducing unit 222 identifies a user who is present at the time and place acquired in step S201 from the personal data 211. In step S203, the reproducing unit 222 identifies, from the personal data 222, the state of the user identified in step S202.

[0058] In step S204, the reproducing unit 222 reflects the state of the user identified in step S204 in the avatar, and places the avatar in the virtual space.

[0059] In this way, the personal dataset PS according to the present disclosure can be used to reproduce a specific time and a specific place in the past.

[0060] The identifying unit 223 identifies information about the user from the personal data set PS collected by the collecting unit 221.

[0061] For example, the identification unit 223 identifies the user's needs as the user information. The identification unit 223 identifies the user's needs of the user terminal 100 for each type from the types of multiple personal data sets PS and the user information.

[0062] For example, the identification unit 223 estimates that an event is a regular event of the user when a predetermined type of event occurs multiple times in multiple personal data sets PS acquired from the user terminal 100. The identification unit 223 estimates the occurrence time of the next event from the occurrence time of the event in the acquired multiple personal data sets PS, and identifies that there is demand for the predetermined type of user at the estimated occurrence time.

[0063] Specifically, suppose that in a plurality of personal data sets PS of a certain user, the user visits an internal medicine doctor and is prescribed an antihypertensive drug around the 20th of each month. In this case, the identifying unit 223 identifies that there will be a demand for an antihypertensive drug around the next 20th. For example, suppose that in the event of a disaster, the processing device 200 is installed in an evacuation shelter where the user is staying as an evacuee, and the collecting unit 221 collects the personal data set PS of the user on the 15th of a certain month. In this situation, the identifying unit 223 identifies a demand that the user will need to visit an internal medicine doctor and be prescribed an antihypertensive drug five days later, around the 20th.

[0064] The identification unit 223 may calculate the total demand required by each user from each personal data set PS. For example, the identification unit 223 counts the number of antihypertensive drugs required by each user during a predetermined period from each personal data set PS to identify the demands of multiple users.

[0065] The identification unit 223 stores the identified demand in the demand data 212. The identification unit 223 associates the user's identifier with data indicating that the user needs to "see an internal medicine doctor and take antihypertensive medication around the 20th," and stores the data in the demand data 212. The identification unit 223 also associates the aggregated value of the number of antihypertensive medications required by each user with "antihypertensive medication."

[0066] For example, the identification unit 223 identifies current information of a user as user information. The identification unit 223 identifies the current states of a plurality of users from the current information of a plurality of users collected from a plurality of user terminals 100. Each user at a shelter sets their current state in a personal dataset PS. The current state may include, for example, whether or not the user is injured, whether or not assistance is needed, whether or not there is a surplus or shortage of food, etc. The collection unit 221 collects the personal dataset PS from the user terminal of each user at a shelter. The identification unit 223 tally up the demand at the shelter, the number of injured people, etc. from the current state of each user collected from each user terminal 100, and stores the data in the demand data 212. At this time, the identification unit 223 may tally up the number of injured people, etc. for each shelter or each area.

[0067] The identification unit 223 may identify the status of a user who is in an isolated area caused by road disruption or the like, or an area damaged by a landslide or the like. The processing device 200a of the processing system 1c shown in FIG. 4 is mounted on a drone or the like, flies over the isolated area or an area damaged by a landslide or the like, and collects user identifiers through short-range communication with user terminals 100 in the area. The identification unit 223 of the processing device 200b of the processing system 1c can grasp the status of a user who is in an isolated area caused by road disruption or the like, or an area damaged by a landslide or the like, by matching the user identifiers collected by the collection unit 221 with the personal data 211 held in advance by the processing device 200b.

[0068] The matching unit 224 associates the user's identifier with the identifier of a supporter whose support content matches the user's needs, by referring to the support data 213. For example, if the user's need is to see an internal medicine doctor and the supporter's support content is not available or is merely a medical examination, the matching unit 224 outputs the user's identifier and the supporter's identifier in association with each other as a matching result.

[0069] There are several possible methods for the matching unit 224 to output the matching result. The matching unit 224 may notify both the matched supporter terminal 300 and the matched user terminal 100 that the match has been established, along with each other's contact information.

[0070] The matching unit 224 may provide each terminal with a virtual space such as a metaverse in which the matched supporter and each terminal of the user can participate. When the supporter participates in the virtual space, the matching unit 224 may notify the user of this and encourage the user to have the supporter undergo an internal medicine examination in the virtual space.

[0071] When a supporter sets the identifier of the shelter where the supporter is located as the support content, the matching unit 224 may send the identifier of the shelter where the supporter is located to the terminal of the user who is matched with the supporter.

[0072] In this way, the matching unit 224 matches the support content of the supporter with the user's needs and supports contact between the supporter and the user.

[0073] As described above, in the processing system 1 according to the present disclosure, the user terminal 100 holds a user identifier and a personal dataset PS that stores user information, and the processing device 200 collects the user identifier and the personal dataset PS from the user terminal 100. The processing device 200 uses the information collected from the user to estimate the current or past situation and identify the current user needs. The processing device 200 can also match the support content input from the support provider terminal 300 with the current user needs, and link the user needs with support.

[0074] In this way, the processing system 1 according to the present disclosure can identify the needs of users such as disaster victims in the event of a disaster or the like.

[0075] The user terminal 100 and the processing device 200 according to the present disclosure described above each use a general-purpose computer system including, for example, a CPU (Central Processing Unit, processor) 901, a memory 902, a storage 903 (HDD: Hard Disk Drive, SSD: Solid State Drive), a communication device 904, an input device 905, and an output device 906. In this computer system, the CPU 901 executes a program loaded on the memory 902, thereby realizing the respective functions of the user terminal 100 and the processing device 200.

[0076] The user terminal 100 and the processing device 200 may each be implemented by a single computer or by multiple computers, or may each be a virtual machine implemented on a computer.

[0077] The programs of the user terminal 100 and the processing device 200 can be stored in a computer-readable recording medium such as an HDD, SSD, USB (Universal Serial Bus) memory, CD (Compact Disc), DVD (Digital Versatile Disc), or can be distributed via a network. The computer-readable recording medium is, for example, a non-transitory recording medium.

[0078] The present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure. [Explanation of symbols]

[0079] 1 Processing System 100 user terminals 111 Dictionary Data 121 Generation part 122 Transmitter 200 Processing Equipment 211 Personal Data 212 Demand Data 213 Support Data 221 Collection Department 222 Recapitulation 223 Specific part 224 Matching Department 300 Supporter Terminal 901 CPU 902 memory 903 Storage 904 Communication equipment 905 Input Device 906 Output Device PS Personal Data Set

Claims

1. A user terminal; a processing device connected to the user terminal; The user terminal storing a plurality of personal data sets that associate information about the user of the user terminal with each data type of the information in association with an identifier of the user; The processing device includes: a collection unit that collects an identifier of the user and a plurality of personal data sets from the user terminal; an identification unit that identifies the demand of the user of the user terminal for each of the types based on the types of the plurality of personal data sets and the information of the user; A processing system comprising:

2. The personal data set further associates the occurrence times of events that occurred to the user with the information of the user; When a predetermined type of event occurs multiple times in a plurality of personal data sets acquired from the user terminal, the identification unit estimates that the event is a regular event of the user, estimates the occurrence time of the next event from the occurrence time of the event in the acquired plurality of personal data sets, and identifies that there is a demand for the predetermined type of event from the user at the estimated occurrence time. The processing system of claim 1 .

3. the collection unit is connected to a plurality of user terminals via short-range communication; The user's information is current information of the user, The identification unit identifies current states of the plurality of users from current information of the plurality of users collected from the plurality of user terminals. The processing system of claim 1 .

4. The collecting unit storing the user's identifier and the plurality of personal data sets collected from the plurality of user terminals in personal data; Collecting identifiers of users of the user terminals through short-range communication in a predetermined area; The identification unit refers to the personal data, extracts a personal data set associated with the collected user identifier, and identifies the state of the user in the predetermined area from the extracted personal data set. The processing system of claim 1 .

5. The user terminal From dictionary data that associates words with the types of the personal data sets in which the words are registered, a personal data set is generated that associates the types of words identified from data acquired by a sensor mounted on the user terminal with the words. The processing system of claim 1 .

6. The processing device includes: a matching unit that refers to support data that associates the identifiers of supporters with the support contents of the supporters, identifies the identifiers of the supporters whose support contents match the needs of the user, and associates the identifiers of the user and the identifiers of the supporters; The processing system of claim 1 further comprising:

7. The personal data set further associates the occurrence times of events that occurred to the user with the information of the user; the collection unit stores a plurality of personal data sets collected from a plurality of user terminals; The processing device includes: a reproduction unit that collects personal data sets at a predetermined time from the plurality of personal data sets, and places an avatar of each user that reflects the state of the user identified from the information of the user in each personal data set in a virtual space; The processing system of claim 1 further comprising:

8. a user terminal stores a plurality of personal data sets that associate an identifier of a user of the user terminal, information about the user, and each data type of the information; a processing device connected to the user terminal collects a plurality of personal data sets from the user terminal; The processing device identifies the needs of the user for each of the types of the plurality of personal data sets based on the types and the user information. Processing method.

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