Support system for persons in need of support, method for extracting persons in need of support, and program

Abstract

A help-requiring person aiding support system (1) according to one embodiment of the present invention includes: a disaster situation acquisition unit (11) that acquires disaster information (21); an information extraction unit (12) that extracts personal data (23) from information (22) of regional residents; a reference unit (15) that creates capability data (25) of persons on the basis of the personal data (23); a determination unit (16) that creates, on the basis of the capability data (25) of the persons, help-requiring person data (26) and determines help-requiring persons; a target person extraction unit (17) that extracts target persons requiring help in a disaster region and creates target person data (28), on the basis of the disaster information (21) and the help-requiring person data (26); and a presentation unit (40) that presents the target person data (28) and the help-requiring person data (26).

Description

Technical Field

[0001] The present invention relates to a support system for disaster victims in case of disasters, a method for extracting disaster victims, and a program.

Background Art

[0002] A disaster victim (vulnerable person in disaster) refers to a person who lacks the ability to perceive a danger (disaster) approaching to himself / herself, or has difficulty in perceiving it, a person who cannot take appropriate actions or has difficulty in taking appropriate actions even when perceiving a danger approaching to himself / herself, a person who cannot receive information for notifying a danger or has difficulty in receiving it, or a person who cannot take appropriate actions or has difficulty in taking appropriate actions even when receiving information for notifying a danger.

[0003] In the event of a natural disaster, disaster victims (vulnerable persons in disaster) are in a position where they are likely to suffer damages such as being late to escape because they have handicaps in terms of physical condition, information collection, communication ability, or intelligence. In past volcanic eruptions, floods, earthquakes, etc., many casualties occurred due to the delay in evacuation of vulnerable persons such as the elderly. In order to minimize damages in case of disasters, a support system for disaster victims in the local community at the time of disasters is necessary.

[0004] In conventional disaster support, in order to perceive the disaster situation in the area, information related to weather such as earthquakes and tsunamis, and information related to traffic such as the traffic conditions of roads and bridges are used. Thereby, the disaster situation for each area can be grasped, and the area to be preferentially supported can be discriminated (Non-Patent Document 1). When a disaster occurs, a rescue request is notified to a fire department or the like. Based on the notification, support is dispatched to the area where the disaster has occurred, and rescue of the people affected by the disaster is carried out.

[0005] In addition, regarding the support for the disaster victims in the community, particular attention has been paid to the elderly, and systems have been studied that anticipate in advance the groups that are likely to experience difficulties in evacuation or give up evacuation, taking into account the living conditions of the elderly (Non-Patent Document 2), as well as systems that simulate the evacuation behavior of disaster victims from the place of residence of the disaster victims and calculate the likelihood of being affected (Non-Patent Document 3).

[0006] Furthermore, in relation to understanding the need for support for community residents, the status of residents receiving care services is recorded in care records. A system has been proposed that efficiently inputs care records (Non-Patent Document 4) and is useful for communication among relevant parties.

[0007] For example, efforts have been made to understand the disaster situation in each region and identify the regions that should be given priority support, or to consider sending support requests to the relatives of those who have been registered in advance as disaster victims and their evacuation behavior during disasters. In such conventional mechanisms, those who are registered in advance as support targets are often those who have received care certification or those who hold a disability handbook.

[0008] On the other hand, there are residents in the community who actually do not have care certification but are in a situation where they need support, such as being in the gap between systems. Since the existence of residents who may need support cannot be fully grasped, there is a possibility that the necessary people may not receive adequate support.

[0009] Regarding the understanding of the need for support for community residents, there are activity records recorded by supporters such as neighborhood commissioners and community comprehensive support centers. Supporters such as neighborhood commissioners and community comprehensive support centers provide support to community residents, not limited to those who have received care certification or those who hold a disability handbook. From these records, it is also possible to infer the physical and mental state of residents and their relationships with the surrounding environment.

Prior Art Documents

Non-Patent Documents

[0010]

Non-Patent Document 1

Non-Patent Document 2

Non-Patent Document 3

Non-Patent Document 4

Summary of the Invention

Problems to be Solved by the Invention

[0011] The present invention has been made in view of these points. That is, in the support system for persons in need of assistance, the present invention uses information on local residents possessed by local supporters such as neighborhood commissioners or community comprehensive support centers. And, knowledge from welfare experts such as social workers is added to the information on local residents. As a result, it is possible to identify persons (persons in need of assistance) who may potentially require support among local residents, and based on the information on local residents to which the knowledge of experts has been added, to provide a support system for persons in need of assistance that can calculate the degree of need for support for persons in need of assistance.

Means for Solving the Problems

[0012] One aspect of the support system for persons in need of assistance includes a disaster situation acquisition unit that acquires disaster information,including name, date of birth, gender, medical history, degree of care needed, and address From the information of local residents extract information about an individual and create individual-level An information extraction unit that extracts personal data, from a database of welfare expert data that includes items corresponding to each of name, date of birth, gender, medical history, degree of care needed, and address Based on the personal data extract the findings of welfare experts including support or support goals for the corresponding data subjects, and add the findings to the individual's data A reference unit that creates the personal capability data of the individual, and the personal capability data add the degree of care needed calculated based on the individual's capability data Create data for those in need of assistance, Based on the degree of care needed in the data of care recipients A determination unit that determines those in need of assistance, disaster information, and based on the data of those in need of assistance, an object extraction unit that extracts the target persons in the disaster area and creates target person data, and a presentation unit that presents the target person data and the data of those in need of assistance.

Effect of the Invention

[0013] According to the embodiment, the extraction accuracy of people who may potentially need support during a disaster can be improved.

Brief Explanation of Drawings

[0014]

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Best Mode for Carrying Out the Invention

[0015] Hereinafter, embodiments will be described with reference to the drawings. In the following description, components having the same function and configuration are given common reference numerals.

[0016] 1. Embodiment 1.1 Configuration of the Support System for Persons Requiring Assistance First, with reference to FIG. 1, an example of the configuration of the support system for persons requiring assistance will be described. FIG. 1 is a block diagram showing an example of the configuration of the support system 1 for persons requiring assistance.

[0017] As shown in FIG. 1, the support system 1 for persons requiring assistance includes a control unit 10, a storage unit 20, an input unit 30, a presentation unit 40, and a communication unit 50.

[0018] The control unit 10 controls the entire support system 1 for persons requiring assistance. The control unit 10 is a processor for executing the support system for persons requiring assistance. The control unit 10 includes, for example, a CPU (Central Processing Unit), a RAM (Random Access Memory), and a ROM (Read Only Memory) not shown in the figure. For example, the CPU expands a program stored in the ROM or the storage unit 20 as a non-temporary storage medium into the RAM. Then, the control unit 10 interprets and executes the program expanded in the RAM by the CPU to control the support system 1 for persons requiring assistance. Note that the control unit 10 may be, for example, a computer device such as a personal computer, or a CPU device such as a microprocessor. Also, at least some functions of the control unit 10 may be performed by other integrated circuits such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a graphics processing unit (GPU).

[0019] The control unit 10 includes a regional disaster situation acquisition unit 11, a regional resident information extraction unit 12, an expert data acquisition unit 13, an expert data database update unit 14, a reference unit 15, a person in need of assistance determination unit 16, and a regional target person extraction unit 17.

[0020] Note that the regional disaster situation acquisition unit 11, the regional resident information extraction unit 12, the expert data acquisition unit 13, the expert data database update unit 14, the reference unit 15, the person in need of assistance determination unit 16, and the regional target person extraction unit 17 may be configured by a program executed by the control unit 10, may be configured by hardware or firmware provided in the control unit 10, or may be configured by individual circuits controlled by the control unit 10. Hereinafter, a case where the functions of these circuits are realized based on the support program 29 executed by the control unit 10 will be described.

[0021] The regional disaster situation acquisition unit 11 acquires, for example, information such as disaster prevention meteorological information or evacuation advisories (hereinafter also referred to as "disaster prevention / evacuation information") from the outside. The disaster prevention meteorological information is forecasts and information on meteorology, earthquakes, volcanoes, etc. announced by the Japan Meteorological Agency. For example, the disaster prevention meteorological information includes, as flood and wind disaster-related information, special warnings: heavy rain, storm, high tide, wave, blizzard, heavy snow, heavy rain warnings, and earthquake and tsunami-related information such as: earthquake early warning, large tsunami warning, etc. Evacuation advisories are announced by, for example, municipalities. For example, evacuation advisories include evacuation preparation, evacuation start for the elderly, etc., evacuation advisories, and evacuation instructions (emergency), etc.

[0022] The regional disaster situation acquisition unit 11 acquires (extracts) the disaster information 21 of the region in charge from the disaster prevention / evacuation information. Then, the regional disaster situation acquisition unit 11 transmits the regional disaster information 21 to the regional target person extraction unit 17. Note that the regional disaster situation acquisition unit 11 may store the regional disaster information 21 in the storage unit 20.

[0023] The regional resident information extraction unit 12 extracts personal data 23 from the regional resident information 22. The regional resident information 22 includes, for example, activity records of neighborhood commissioners, activity records of regional comprehensive support centers, work logs of neighborhood commissioners and regional comprehensive support centers, resident assessment results, care plans, conference minutes, care records (daily reports), and other multiple pieces of information. The regional resident information 22 can be updated at any time based on the daily activities of neighborhood commissioners and regional comprehensive support centers. The regional resident information 22 is stored, for example, in the storage unit 20. The regional resident information extraction unit 12 extracts information about individuals from the regional resident information 22 and creates personal data 23 in individual units. The regional resident information extraction unit 12 transmits the personal data 23 to the reference unit 15. Also, the regional resident information extraction unit 12 stores the personal data 23 in the storage unit 20.

[0024] The expert data acquisition unit 13 acquires expert data from the outside. The expert data is knowledge data regarding the physical and mental states and support methods of the data subject, created by welfare experts such as social workers. The expert data acquisition unit 13 transmits the acquired expert data to the expert data database update unit 14.

[0025] The expert data database update unit 14 updates the expert data database 24 stored in the storage unit 20 using the expert data. The expert data database 24 is updated at any time with the acquisition of expert data. Note that the support and assistance system 1 for persons in need of care may not include the expert data acquisition unit 13 and the expert data database update unit 14. In this case, the support and assistance system 1 for persons in need of care acquires the expert data database 24 updated from the outside.

[0026] The reference unit 15 refers to the database 24 of expert data to convert the personal data 23 into the personal capability data 25 of the individual. The personal capability data 25 of the individual is data obtained by adding the knowledge of experts based on the database 24 of expert data to the personal data 23. The reference unit 15 transmits the personal capability data 25 of the individual to the person-in-need-of-care determination unit 16. Also, the reference unit 15 stores the personal capability data 25 of the individual in the storage unit 20.

[0027] Based on the personal capability data 25 of the individual, the person-in-need-of-care determination unit 16 creates person-in-need-of-care data 26 and determines whether the data subject is a person in need of care. More specifically, for example, the person-in-need-of-care determination unit 16 performs weighting (hereinafter referred to as "basic weighting") on each item in the personal capability data 25 of the individual, that is, the content of the information, based on a weighting table possessed by the person-in-need-of-care determination unit 16. By performing basic weighting on each item of the personal capability data 25 of the individual, information that should be considered prioritarily is extracted. A specific example of the weighting table will be described later. Also, the person-in-need-of-care determination unit 16 sets a coefficient considering the importance to the individual for each item in the personal capability data 25 of the individual. The importance to the individual is a value set based on the input content of the personal capability data 25 of the individual. The importance to the individual can be set to different values for each data subject. Details of the importance to the individual will be described later. The person-in-need-of-care determination unit 16 calculates the degree of need for care based on the basic weighting and the importance to the individual. The degree of need for care is an index indicating the degree of possibility that support (assistance) is required. That is, the person-in-need-of-care determination unit 16 creates person-in-need-of-care data 26 with the degree of need for care added to the personal capability data 25 of the individual. The person-in-need-of-care determination unit 16 determines whether the data subject is a person in need of care based on the degree of need for care in the person-in-need-of-care data 26. The person-in-need-of-care determination unit 16 stores the person-in-need-of-care data 26 in the storage unit 20. Note that the person-in-need-of-care determination unit 16 may cause the presentation unit 40 to present the person-in-need-of-care data 26. At this time, the person-in-need-of-care determination unit 16 may cause the persons in need of care to be presented in descending order of the degree of need for care.

[0028] When the target person extraction unit 17 in the region receives the regional disaster information 21 from the regional disaster situation acquisition unit 11, it creates the regional target person data 28 based on the person-in-need-of-help data 26 and the regional disaster information 21 while referring to the response content data 27 of the target region. The response content data 27 of the target region is data regarding the response content of the support predetermined for each region based on, for example, the content of the disaster (warning level) and the situation of the target region (topography, traffic conditions, residential conditions of residents, etc.). The response content data 27 of the target region can be updated at any time. The regional target person data 28 is data obtained by extracting the persons to be supported within the disaster target region. Note that the target person extraction unit 17 in the region may calculate the priority of support (assistance) for the regional target persons based on the degree of need for help in the person-in-need-of-help data 26. In other words, the target person extraction unit 17 in the region may rank the priorities of support for a plurality of target persons. Note that the target person extraction unit 17 in the region may use the degree of need for help in the person-in-need-of-help data 26 as the priority of support. The target person extraction unit 17 in the region transmits the regional target person data 28 to the presentation unit 40. Note that the target person extraction unit 17 in the region may transmit the regional target person data 28 and the person-in-need-of-help data 26 together to the presentation unit 40, or may transmit the regional target person data 28, the person-in-need-of-help data 26, and the calculation result of the priority together. The target person extraction unit 17 in the region stores the regional target person data 28 in the storage unit 20.

[0029] The storage unit 20 stores data and programs related to the support of persons in need of assistance. For example, the storage unit 20 stores regional disaster information 21, information on regional residents 22, personal data 23, a database of expert data 24, the person's capability data 25, data on persons in need of assistance 26, data on response contents for the target region 27, and data on target persons in the region 28. Further, the storage unit 20 stores a support program 29 as a non-temporary storage medium. The support program 29 is a program for causing the control unit 10 to execute support for persons in need of assistance. Note that the storage unit 20 may include various storage devices such as a magnetic disk storage device (HDD: Hard Disk Drive) or a solid state drive (SSD: Solid State Drive) as an external storage. Furthermore, the storage unit 20 may include, for example, a drive for reading a program stored in a CD (Compact Disc) or a DVD (Digital Versatile Disc) or the like as a non-temporary storage medium.

[0030] The input unit 30 includes input devices such as a keyboard, a mouse, a touch panel, or a button switch. For example, a user of the support system 1 for persons in need of assistance may input various data using these input devices.

[0031] The presentation unit 40 includes, for example, a display screen (e.g., an LCD (Liquid Crystal Display) or an EL (Electroluminescence) display, etc.) as a display device. Further, the presentation unit 40 may include an output device such as a printer. The presentation unit 40 presents, for example, either or both of the data on target persons in the region 28 and the data on persons in need of assistance 26.

[0032] The communication unit 50 is an interface for transmitting and receiving data between the support assistance system 1 for persons in need of assistance and the outside (external devices or cloud servers, etc.). The communication unit 50 has a function of connecting to a network. Various communication standards can be used for connection to the outside. The communication unit 50 receives, for example, disaster prevention / evacuation information, information 22 of local residents, expert data, and response content data 27 of the target area. Then, the communication unit 50 transmits personal data 23, personal capability data 25, data 26 of persons in need of assistance, or target person data 28 of the area, etc. to the outside.

[0033] 1.2 Data flow in the support assistance system for persons in need of assistance Next, with reference to FIG. 2, an example of the data flow in the support assistance system 1 for persons in need of assistance will be described. FIG. 2 is a block diagram showing an example of the data processing flow in the functional configuration of the support assistance system 1 for persons in need of assistance.

[0034] As shown in FIG. 2, for example, disaster prevention / evacuation information 61, information 22 of local residents, expert data 60, and response content data 27 of the target area are input to the support assistance system 1 for persons in need of assistance. The disaster prevention / evacuation information 61 is input at the time of disaster forecast announcement and at the time of disaster occurrence. The information 22 of local residents, expert data 60, and response content data 27 of the target area can be updated at any time based on activities in normal times (when no disaster is occurring), for example.

[0035] The information 22 of local residents is input to the local resident information extraction unit 12. The local resident information extraction unit 12 creates personal data 23 based on the information 22 of local residents. The local resident information extraction unit 12 outputs the personal data 23.

[0036] The expert data 60 is input to the expert data acquisition unit 13. The expert data acquisition unit 13 acquires the expert data 60. The expert data acquisition unit 13 transmits the expert data 60 to the database update unit 14 of the expert data.

[0037] The database update unit 14 of the expert data updates the database 24 of the expert data based on the expert data 60. The database update unit 14 of the expert data outputs the database 24 of the expert data.

[0038] The personal data 23 and the database 24 of the expert data are input to the reference unit 15. The reference unit 15 refers to the database 24 of the expert data and creates the personal capability data 25 of the individual based on the personal data 23. The reference unit 15 outputs the personal capability data 25 of the individual.

[0039] The personal capability data 25 of the individual is input to the person in need of assistance determination unit 16. The person in need of assistance determination unit 16 creates the person in need of assistance data 26 based on the personal capability data 25 of the individual. The person in need of assistance determination unit 16 outputs the person in need of assistance data 26.

[0040] The person in need of assistance data 26 is transmitted to the target person extraction unit 17 in the region. Note that the person in need of assistance data 26 may also be transmitted to the presentation unit 40.

[0041] The disaster prevention / evacuation information 61 is input to the regional disaster situation acquisition unit 11. The regional disaster situation acquisition unit 11 acquires the regional disaster information 21 based on the disaster prevention / evacuation information 61. The regional disaster situation acquisition unit 11 outputs the regional disaster information 21.

[0042] The response content data 27 for the target region, the regional disaster information 21, and the person in need of assistance data 26 are input to the target person extraction unit 17 in the region. The target person extraction unit 17 in the region creates the target person data 28 in the region based on the regional disaster information 21 and the person in need of assistance data 26 while referring to the response content data 27 for the target region. Note that the target person extraction unit 17 in the region may calculate the priority of the target person based on the person in need of assistance data 26. The target person extraction unit 17 in the region outputs the target person data 28 in the region. Note that the target person extraction unit 17 in the region may also output the person in need of assistance data 26 together with the target person data 28 in the region, or may output the person in need of assistance data 26 and the priority of the target person together with the target person data 28 in the region.

[0043] The target person data 28 of the region is input to the presentation unit 40. Note that the person in need of support data 26 may be input together with the target person data 28 of the region, or the person in need of support data 26 and the priority of the target person may be input. The presentation unit 40 presents the target person data 28 of the region. Note that the presentation unit 40 may present the target person data 28 of the region and the person in need of support data 26 together, or may present the target person data 28 of the region, the person in need of support data 26, and the priority of the target person together. Hereinafter, the data presented by the presentation unit 40 is referred to as "presentation data". The presentation data 62 may be output to the outside. The presentation data output to the outside can be used for support (assistance) activities.

[0044] 1.3 Overall flow of extracting target persons in the region Next, with reference to FIG. 3, an example of the overall flow of extracting target persons in the region will be described. FIG. 3 is a flowchart showing an example of the overall flow of extracting target persons in the region.

[0045] As shown in FIG. 3, the extraction of target persons in the region at the time of a disaster roughly includes a normal-time implementation process (step S1), a disaster-occurrence-time implementation process (step S2), and a target-person extraction process (step S3).

[0046] 1.3.1 Normal-time implementation process An example of the normal-time implementation process (step S1) will be described. The normal-time implementation process is a process of creating data on persons in need of support in preparation for a disaster, mainly during normal times, along with updates to the database 24 of information on regional residents 22 and expert data. Note that the normal-time implementation process may be carried out at the time of issuing a disaster forecast and at the time of a disaster occurrence.

[0047] First, the support system 1 for persons in need of support acquires the information 22 of regional residents (step S10). The information 22 of regional residents may be input by the user of the support system 1 for persons in need of support using the input unit 30, or may be received from the outside via the communication unit 50.

[0048] Next, based on the information 22 of the local residents, the local resident information extraction unit 12 creates personal data 23 (step S11). More specifically, the local resident information extraction unit 12 extracts the information of the items set in the extraction rule from the information 22 of the local residents based on the preset extraction rule.

[0049] Next, for example, when the personal data 23 is newly created (or updated), or when the database 24 of the expert data is updated, the reference unit 15 refers to the database 24 of the expert data and creates the personal's capability data 25 from the personal data 23 (step S12).

[0050] Next, the person in need of assistance determination unit 16 creates person-in-need-of-assistance data 26 based on the personal's capability data 25 (step S13). More specifically, the person-in-need-of-assistance determination unit 16 adds basic weighting and importance to the individual for each item of the personal's capability data 25. The person-in-need-of-assistance determination unit 16 calculates the degree of need for assistance based on the basic weighting and the importance to the individual. The person-in-need-of-assistance determination unit 16 adds the degree of need for assistance to the personal's capability data 25. The data with basic weighting, importance to the individual, and degree of need for assistance added to the personal's capability data 25 is the person-in-need-of-assistance data 26. The person-in-need-of-assistance determination unit 16 determines whether the data subject is a person in need of assistance based on the degree of need for assistance in the person-in-need-of-assistance data 26. At this time, the person-in-need-of-assistance determination unit 16 may determine a preset number of the top-ranked persons in terms of the degree of need for assistance as persons in need of assistance, or may determine a data subject with a degree of need for assistance higher than a preset threshold as a person in need of assistance. The person-in-need-of-assistance data 26 is stored in the storage unit 20. Note that the person-in-need-of-assistance data 26 may be presented to the presentation unit 40 or output to the outside via the communication unit 50.

[0051] 1.3.2 Implementation Process during Disaster Occurrence An example of the implementation process during disaster occurrence (step S2) will be described.

[0052] First, the support system 1 for those in need of assistance acquires disaster prevention / evacuation information 61 from the outside (step S20).

[0053] The regional disaster situation acquisition unit 11 acquires regional disaster information 21 based on the disaster prevention / evacuation information 61 (step S21). The regional disaster situation acquisition unit 11 transmits the regional disaster information 21 to the regional target extraction unit 17.

[0054] 1.3.3 Target extraction process An example of the target extraction process (step S3) will be described.

[0055] When the regional target extraction unit 17 acquires the regional disaster information 21, it creates regional target data 28 based on the regional disaster information 21 and the data of those in need of assistance 26 while referring to the response content data 27 of the target area (step S30). At this time, the regional target extraction unit 17 may calculate the priority of the target based on the degree of need for assistance in the data of those in need of assistance 26. That is, the regional target extraction unit 17 may perform prioritization of support (assistance). In addition, the regional target extraction unit 17 may, for example, sum up the degrees of need for assistance of the top-ranked ones in terms of the degree of need for assistance for a preset number of people to estimate the degree of need for assistance.

[0056] The presentation unit 40 presents presentation data (step S31). Note that the presentation unit 40 may present the regional target data 28 and the data of those in need of assistance 26 together as the presentation data. In addition, the presentation unit 40 may present the regional target data 28, the data of those in need of assistance 26, and the priority of the target together as the presentation data. The data presented to the presentation unit 40 may be output to the outside via the communication unit 50.

[0057] Note that the support system 1 for those in need of assistance may have a function of transmitting information to the targets and the regional personnel (such as neighborhood commissioners, staff of the regional comprehensive support centers, fire and police personnel, etc.) who support (assist) the targets based on the regional target data 28, and a function of acquiring the situation of the targets based on the contacts from the targets and the regional personnel, etc.

[0058] 1.4. Personal Data Next, with reference to FIGS. 4 to 7, an example of the details of the personal data 23 will be described. FIGS. 4 and 5 are examples of the extraction rules for the personal data 23. FIGS. 6 and 7 are examples of the personal data 23.

[0059] As shown in FIGS. 4 and 5, the personal data 23 includes, for example, six categories: "Basic Attributes", "Basic Information", "Utilization of Information Receiving Means", "Physical and Mental States", "Relationships", and "Abilities and Experiences". Note that the setting of the categories is arbitrary. Extraction rules are set for each category. Then, the regional resident information extraction unit 12 extracts the "items" of each category and the "details" regarding those items from the regional resident information 22 according to the extraction rules. The extracted "item" and "detail" information is output from the regional resident information extraction unit 12 as the personal data 23.

[0060] "Basic Attributes" is a category regarding the name, date of birth, gender, medical history, and degree of support or care required of the data subject. As shown in FIG. 4, for example, when extracting "Basic Attributes", the "items" and "details" are extracted according to the following extraction rule procedures.

[0061] 1. When extracting information regarding the name, enter "Name" in the "item" and the extracted name in the "detail". 2. When extracting information regarding the date of birth, calculate the current age from the date of birth. Then, enter "Age Group" in the "item" and the age group of that age in the "detail". 3. When extracting information regarding gender, enter "Gender" in the "item" and enter "Male" or "Female" in the "detail". 4. When extracting information regarding the past medical history or current medical history, enter the past medical history or current medical history in the "item" and enter the name of the disease in the "detail". 5. When extracting information regarding the degree of support or care required, enter "Degree of Support / Care Required" in the "item" and enter the extracted degree of support or care required in the "detail".

[0062] For example, in the case of the personal data 23 in FIG. 6, when "Name: XXXXXXXX" is input in the information 22 of the local residents, "Name" is input in the item of basic attributes, and "XXXXXXXX" is input in detail. When "Date of Birth: October 10, 1945" is input in the information 22 of the local residents, "Age group" is input in the item, and "70s" is input in detail. When "Gender: Female" is input in the information 22 of the local residents, "Gender" is input in the item, and "Female" is input in detail. When "Medical history: Hypertension, Alzheimer's disease, sequelae of cerebral infarction (no paralysis in the 60s, but numbness remains in the left half of the body)" is input in the information 22 of the local residents, "Medical history" is input in the item, and "Hypertension, Alzheimer's disease, sequelae of cerebral infarction (no paralysis in the 60s, but numbness remains in the left half of the body)" is input in detail. When "Degree of need for support or care: Care level 2" is input in the information 22 of the local residents, "Degree of need for support or care" is input in the item, and "Care level 2" is input in detail.

[0063] "Basic information" is, for example, a category related to the address, telephone number, emergency contact, etc. of the data subject. As shown in FIG. 4, for example, when extracting "basic information", "item" and "detail" are extracted according to the following extraction rule procedures.

[0064] 1. When extracting information related to the address, proceed with the input in the order of 1-1 to 1-3. 1-1. If it is a noun representing a prefecture: Input "Address (prefecture)" in "item", and input the extracted noun in "detail". 1-2. If it is a noun representing a city or ward: Input "Address (city / ward)" in "item", and input the extracted noun in "detail". 1-3. Input "Address (detail)" in "item", and input the address excluding the prefecture and city / ward in "detail". 2. When extracting information related to the telephone number, input "Telephone number" in "item", and input the extracted telephone number in "detail". 3. When extracting information related to the emergency contact, input "Emergency contact" in "item", and input the extracted emergency contact in "detail".

[0065] For example, in the example of the personal data 23 in FIG. 6, when "Address: No. x, x-chome, xx-machi, Ota-ku, Tokyo" is input in the information 22 of the local residents, first, "Prefecture of Address" is input in the item, and "Tokyo" is input in detail. Next, "City of Address" is input in the item, and "Ota-ku" is input in detail. Finally, "Detailed Address" is input in the item, and "No. x, x-chome, xx-machi" is input in detail. When "Phone Number: 000-0000-0000" is input in the information 22 of the local residents, "Phone Number" is input in the item, and "000-0000-0000" is input in detail. When "Emergency Contact: xxx-xxxx-xxxx" is input in the information 22 of the local residents, "Emergency Contact" is input in the item, and "xxx-xxxx-xxxx" is input in detail.

[0066] "Utilization of means for receiving information" is a category related to the means for receiving information and the physical state related to the reception of information. As shown in FIG. 4, for example, when extracting "Utilization of means for receiving information", "Item" and "Detail" are extracted according to the following extraction rule procedure.

[0067] 1-1. Extract sentences containing nouns related to hearing, vision, communication means, and perception verbs. 1-2. In the case of nouns related to body parts and communication means, set "Noun" in "Item" and input the extracted sentence in "Detail". 1-3. In the case of verbs related to perception verbs, extract the modifier if the verb is a modifier as "Item", extract the object if the verb is a transitive verb as "Item", and extract the predicate and the modifier applied to the predicate as "Detail".

[0068] For example, in the example of the personal data 23 in FIG. 6, when "hard to hear" is input in the information 22 of the local residents, "ear" is input in the item, and "hard to hear" is input in detail. When "not noticing even when the phone rings" is input in the information 22 of the local residents, "phone" is input in the item, and "not noticing even when the phone rings" is input in detail. When "hard to see due to blurred vision" is input in the information 22 of the local residents, "eye" is input in the item, and "hard to see due to blurred vision" is input in detail. When "I have a mobile phone but don't know how to use it" is input in the information 22 of the local residents, "mobile phone" is input in the item, and "I have a mobile phone but don't know how to use it" is input in detail.

[0069] "Physical and mental state" is a category related to daily life and physical and mental states. As shown in FIG. 4, for example, when extracting "physical and mental state", "item" and "detail" are extracted according to the following extraction rule procedures.

[0070] 1-1. Extract a sentence containing a noun representing a daily life action, a place related to going out or the area, a noun representing a body part, or a verb or adjective representing a physical and mental state. 1-2. In the case of a noun representing a place related to the area, set "noun" in the "item", and input the extracted sentence in the "detail". 1-3. In the case of a verb related to the physical and mental state, if it is an intransitive verb, extract the modifier as the "item", and if it is a transitive verb, extract the object as the "item", and extract the predicate and the modifier modifying the predicate as the "detail".

[0071] For example, in the example of the personal data 23 in FIG. 6, when "going to the pool twice a week" is input in the information 22 of the local residents, "pool" is input in the item, and "going to the pool twice a week" is input in the details. When "worried and anxious about the condition of my husband's illness" is input in the information 22 of the local residents, "anxious" is input in the item, and "worried and anxious about the condition of my husband's illness" is input in the details. When "lonely without someone to talk to" is input in the information 22 of the local residents, "lonely" is input in the item, and "lonely without someone to talk to" is input in the details. When "my feet hurt and it's difficult to walk" is input in the information 22 of the local residents, "feet" is input in the item, and "my feet hurt and it's difficult to walk" is input in the details.

[0072] "Relationship" is a category related to the relationship with family or the local area, etc. As shown in FIG. 5, for example, when extracting "relationship", "item" and "details" are extracted according to the following extraction rule procedures.

[0073] 1-1. Extract sentences containing nouns representing family, personal names, or locations related to the local area. 1-2. In the case of nouns related to family, set "noun (family relationship)" in "item", and input the extracted sentence in "details". 1-3. In the case of nouns other than those related to family that represent personal names, set "noun (surrounding people)" in "item", and input the extracted sentence in "details". 1-4. In the case of nouns representing place names or locations related to the local area, set "noun (local area·location)" in "item", and input the extracted sentence in "details". 2. Extract sentences representing current habits (words indicating time + ~ている).

[0074] For example, in the case of the personal data 23 in FIG. 7, when "There are five siblings, and I have taken care of my younger brother since childhood." is input into the information 22 of the local residents, "Younger brother (family relationship)" is input into the item, and "There are five siblings, and I have taken care of my younger brother since childhood." is input in detail. When "This house was built by my husband and me with great effort, so I have to protect it." is input into the information 22 of the local residents, "Husband (family relationship)" is input into the item, and "This house was built by my husband and me with great effort, so I have to protect it." is input in detail. When "On days off, I often go to a familiar coffee shop." is input into the information 22 of the local residents, "Coffee shop (local area / place)" is input into the item, and "On days off, I often go to a familiar coffee shop." is input in detail. When "After retirement, I served as the president of the local women's association for many years." is input into the information 22 of the local residents, "Local women's association (local area / place)" is input into the item, and "After retirement, I served as the president of the local women's association for many years." is input in detail. When "I spend my evenings watching TV." is input into the information 22 of the local residents, "TV" is input into the item, and "I spend my evenings watching TV." is input in detail. When "I am worried about my husband's illness." is input into the information 22 of the local residents, "Husband (family relationship)" is input into the item, and "I am worried about my husband's illness." is input in detail.

[0075] "Abilities and experiences" is a category related to work, etc. As shown in FIG. 5, for example, when extracting "abilities and experiences", "item" and "detail" are extracted according to the following extraction rule procedures.

[0076] 1-1. Extract sentences containing nouns related to occupations or verbs related to work or labor. 1-2. In the case of a noun related to an occupation, extract the noun as the "item". And when the extracted noun is the subject, extract the predicate and the modifier attached to the predicate as the "detail". When the extracted noun is the predicate or the modifier, extract the entire sentence as the "detail". 1-3. For verbs related to working, as the "item", if the verb is intransitive, extract the modifier; if it is transitive, extract the object. And as the "detail", extract the predicate and the modifier attached to the predicate. 2-1. Extract sentences representing past experiences (words indicating time in the past + ~ていた). 2-2. Extract the time expression + verb as the "item", and extract the object or modifier of the verb as the "detail".

[0077] For example, in the example of the personal data 23 in FIG. 7, when "Work history: Elementary school teacher" is input in the information 22 of the local residents, "Elementary school teacher" is input as the item. When "Married in her 20s to the husband of the same teacher" is input in the information 22 of the local residents, "Teacher" is input as the item, and "Married in her 20s to the husband of the same teacher" is input as the detail. When "Worked until retirement in Town M where her home is located" is input in the information 22 of the local residents, "Work" is input as the item, and "Worked until retirement in Town M where her home is located" is input as the detail. When "Served as the president of the women's association in the town for many years after retirement" is input in the information 22 of the local residents, "Women's association in the town" is input as the item, and "Served for many years" is input as the detail. When "Has lived in Town M since childhood" is input in the information 22 of the local residents, "Town M" is input as the item, and "Has lived since childhood" is input as the detail. When "Learned to dance when she was a child" is input in the information 22 of the local residents, "Dance" is input as the item, and "Learned to dance when she was a child" is input as the detail.

[0078] 1.5. Personal capability data Next, with reference to FIGS. 8 to 11, an example of the details of the personal capability data 25 will be described. FIGS. 8 to 11 are an example of the personal capability data 25.

[0079] My capability data 25 is data obtained by adding the knowledge of experts to my data 23. The reference unit 15 extracts the knowledge of experts corresponding to the details of each item of my data 23 from the database 24 of expert data. More specifically, for example, phrases corresponding to "insight", "hypothesis of approach", and "hypothesis of support / target" are extracted from the database 24 of expert data as the knowledge of experts. "Insight" is the state of the data subject that can be insight from "details". "Hypothesis of approach" is a hypothesis regarding the approach to the data subject. "Hypothesis of support / target" is a hypothesis regarding the support or the target of support for the data subject.

[0080] As shown in FIG. 8, for example, in terms of basic attributes, when the detail of the item "age group" is "in their 70s", phrases such as "possibility of being hard of hearing", "possibility of difficulty hearing the other person's voice", "decrease in contact with society", "loss of social role and family role", and "decrease in conversation opportunities" are extracted as "insight". As the "hypothesis of approach", the phrase "due to the influence of self-loss caused by physical and mental changes, there may be few contacts with the surroundings" is extracted. And as the "hypothesis of support / target", phrases such as "possibility that the person is in a physical and mental state without the ability to judge the situation", "possibility that there is no one around who can support the judgment of the situation", "confirm the connection that can support the judgment of the situation", and "if there is no connection, request support from local stakeholders" are extracted.

[0081] For example, when the detail of the item "current medical history" is "fracture", the phrase "from one's own physical condition, there is a possibility of losing confidence in oneself and losing the will to live" is extracted as "insight". As the "hypothesis of approach", the phrase "not being positive about necessary care such as rehabilitation may be due to the loss of the will to live" is extracted. And as the "hypothesis of support / target", the phrase "possibility that the person is in a physical and mental state where they cannot take appropriate actions" is extracted.

[0082] For example, when the details of the item "Requires Support / Care Level" are "Care Level 2", as the "Support / Hypothesis of Goals", phrases such as "The possibility that the individual is in a physical and mental state without the ability to judge the situation" and "The possibility that the individual is in a state without the ability to collect / confirm information" are extracted.

[0083] As shown in FIG. 9, for example, in the item "Phone Number" of the basic information, as the "Insight", a phrase such as "The possibility that even if the individual has a means to receive information, they cannot utilize it due to their physical and mental state" is extracted.

[0084] For example, in the "Utilization of Means to Receive Information", when the details of the item "Ear" are "Difficult to Hear", as the "Insight", phrases such as "The possibility of poor hearing", "The possibility of difficulty hearing the other person's voice", and "The possibility that even if having a communication means, one cannot use it oneself" are extracted. And as the "Support / Hypothesis of Goals", phrases such as "The possibility that the individual is in a physical and mental state without the ability to judge the situation" and "The possibility that the individual is in a state without the ability to collect / confirm information, → Confirm the connection to support information collection and confirmation, → If there is no connection, request support from local stakeholders" are extracted.

[0085] For example, when the details of the item "Phone" are "Not Aware Even When the Phone Rings", as the "Insight", a phrase such as "The possibility that even if having a means to collect information, one cannot use it oneself" is extracted. And as the "Support / Hypothesis of Goals", phrases such as "The possibility that the individual is in a physical and mental state without the ability to judge the situation" and "The possibility that the individual is in a state without the ability to collect / confirm information, → Confirm the connection to support information collection and confirmation for those around, → If there is no connection, request support from local stakeholders" are extracted.

[0086] As shown in Fig. 10, for example, when the details of the item "eyes" are "the eyes are hazy and difficult to see clearly", as "insight", the phrase "the possibility that even if one has means of collecting information, one cannot use it oneself" is extracted. And as "support / hypothesis of goal", the phrases "the possibility that the person is in a mental and physical state without the ability to judge the situation" and "the possibility that the person is in a state without the ability to collect / confirm information, → check for connections to support information collection and confirmation from those around, → if there is no connection, request support from local relevant parties" are extracted.

[0087] For example, when the details of the item "mobile phone" are "I have a mobile phone, but I don't know how to use it", as "insight", the phrase "the possibility that even if one has means of collecting information, one cannot use it oneself" is extracted. And as "support / hypothesis of goal", the phrases "the possibility that the person is in a state without the ability to collect / confirm information, → check for connections to support information collection and confirmation from those around, → if there is no connection, request support from local relevant parties" are extracted.

[0088] For example, in the "mental and physical state", when the details of the item "anxiety" are "worried and anxious about my husband's illness", as "insight", the phrase "the possibility that there is no psychological leeway from one's own living state" is extracted. And as "support / hypothesis of goal", the phrase "the possibility that the person is in a mental and physical state where they cannot take appropriate actions" is extracted.

[0089] For example, when the details of the item "lonely" are "lonely because there is no one to talk to", as "insight", the phrase "the possibility that the will to live is decreasing from one's own living state" is extracted. And as "support / hypothesis of goal", the phrases "the possibility that the person is in a mental and physical state where they cannot take appropriate actions" and "the possibility that there is no one around who can support the judgment of the situation" are extracted.

[0090] As shown in Fig. 11, for example, when the details of the item "foot" are "the foot hurts and it is difficult to walk", as "support / hypothesis of goal", the phrase "the possibility that the person is in a mental and physical state where they cannot take appropriate actions" is extracted.

[0091] For example, in "Relationship", when the details of the item "Chairperson of the local women's association" are "has served for many years", as "Insight", the phrase "Since they have participated in local activities, there is a possibility of strong relationship with the local area (judgment of the strength of the relationship with the local area)" is extracted. As "Hypothesis of approach", the phrases "Explore support involving local people because there is a possibility of strong relationship with the local area", "Explore people with deep connections in the local area", and "Explore the presence or absence of neighboring acquaintances" are extracted. And as "Hypothesis of support·goal", the phrases "There is a possibility that there are relevant people who can recognize the situation around", and "There is a possibility that there are relevant people who can support the action around" are extracted.

[0092] For example, when the details of the item "Welfare committee member" are "has been a welfare committee member in the neighborhood", as "Insight", the phrase "Since they have participated in local activities, there is a possibility of strong relationship with the local area" is extracted. As "Hypothesis of approach", the phrases "Judgment of the strength of the relationship with the local area" and "If the relationship with the local area is strong, explore support involving local people" are extracted. And as "Hypothesis of support·goal", the phrases "There is a possibility that there are relevant people who can recognize the situation around", and "There is a possibility that there are relevant people who can support the action around" are extracted.

[0093] 1.6. Data of those in need of support Next, the details of the data 26 of those in need of support will be described.

[0094] 1.6.1 Basic weighting First, with reference to FIGS. 12 and 13, an example of basic weighting will be described. FIGS. 12 and 13 are an example of a weighting table.

[0095] As shown in FIG. 12, for example, the person in need of support determination unit 16 performs basic weighting on items corresponding to the weighting table ( "age", "current medical history", and "degree of need for support and care") in the basic attributes of the person's capability data 25. More specifically, for example, in the item "age" of the basic attributes, when the details are "in their 70s" or "in their 80s", "2" is set as the basic weighting value of the item "age". Also, when the details are "in their 90s" or "in their 100s", "3" is set as the basic weighting value of the item "age". In the item "current medical history", when there is an input of details, "2" is set as the basic weighting value of the item "current medical history". In the item "degree of need for support and care", when the details are "need for support 1" or "need for support 2", "2" is set as the basic weighting value of the item "degree of need for support and care". Also, in the item "degree of need for support and care", when the details are "care level 2", "3" is set as the basic weighting value of the item "degree of need for support and care". Note that when the care level is 2 or higher, the person in need of support determination unit 16 may determine that the data corresponding person is a person in need of support.

[0096] As shown in FIG. 13, for example, the person in need of support determination unit 16 performs basic weighting in units of categories of the person's capability data 25. For example, when the category is "utilization of means to receive information" or "physical and mental state", "2" is set as the basic weighting value of these categories. Also, when the category is "relationship" or "ability / experience", "3" is set as the basic weighting value of these categories.

[0097] 1.6.2 Importance to the individual Next, with reference to FIG. 14, an example of the importance to the individual will be described. FIG. 14 is an example of the calculation rule for the importance to the individual.

[0098] As shown in FIG. 14, the person in need of support determination unit 16 calculates the importance to the individual based on the "items" and "details" of the person's capability data 25. More specifically, the importance to the individual is calculated according to the following calculation rule procedure.

[0099] 1-1. Among the words included in the sentences of "Items" and "Details" entered in each category of "Utilization of means for receiving information", "Physical and mental state", "Relationship", and "Abilities and experiences", extract nouns. At this time, the person in need of support determination unit 16 treats synonymous words as words with the same meaning among the extracted nouns (for example, teacher and elementary school teacher, husband and spouse, etc.). 1-2. Perform noun weighting using existing weighting methods such as weighting by simple frequently occurring phrases or weighting by phrases that have frequently occurred recently. Also, for example, words that have frequently occurred in the past x months may be weighted.

[0100] For example, assume that in the target category, the total number of extracted words is 42, and among them, the number of occurrences of the word "husband" is 2, and the number of occurrences of the word "ear" is 3. Then, the TF (Term Frequency) value of the word "husband" is calculated as 2 / 42 ≈ 0.05. Also, the TF value of the word "ear" is calculated as 3 / 42 ≈ 0.07. The person in need of support determination unit 16 sets the calculated TF value as the importance for the person of each item.

[0101] 1.6.3 Details of Person in Need of Support Data Next, with reference to FIGS. 15 and 16, an example of the details of the person in need of support data 26 will be described. FIGS. 15 and 16 are an example of the person in need of support data 26. In the examples of FIGS. 15 and 16, for the sake of simplifying the explanation, the categories of "Basic Information", "Physical and mental state", "Relationship", and "Abilities and experiences" are omitted.

[0102] As shown in FIGS. 15 and 16, first, based on the weighting table, the basic weighting values of each item of the person's capability data 25 are input. In the example of FIG. 15, in the items of "Age", "Current medical history", and "Degree of need for support and care" in the "Basic attributes", "2" is input as the basic weighting value. Also, as the basic weighting for the category, for example, "2" is input as the basic weighting value for each item of "Utilization of means for receiving information".

[0103] Next, the importance for the individual is calculated. In the example of FIG. 16, “0.07” is input as the importance for the individual for the item “Ear”, and “0.06” is input as the importance for the individual for the item “Telephone”.

[0104] When the basic weighting and the importance for the individual are input, the caregiver determination unit 16 calculates the score for each item based on the basic weighting and the importance for the individual. For example, in the case of the above-described method for setting the importance for the individual, for the category of “Basic Attributes”, the importance for the individual is not input. In such a case, for each item in “Basic Attributes”, the basic weighting value is directly used as the score. In the example of FIG. 15, for example, “2” is input as the score for the items “Age”, “Medical history”, and “Degree of need for support / care”. In the case of an item for which the importance for the individual is input, the product of the basic weighting and the importance for the individual is calculated as the score. In the example of FIG. 16, “0.14” is input as the score for the item “Ear”, and “0.12” is input as the score for the item “Telephone”.

[0105] Next, the caregiver determination unit 16 calculates the sum of the scores for each item as the degree of need for care. In this way, the caregiver determination unit 16 adds the basic weighting, the importance for the individual, the score, and the degree of need for care to the individual's capability data 25 to create caregiver data 26.

[0106] 1.7. Disaster information of the region Next, with reference to FIG. 17, an example of the details of the regional disaster information 21 will be described. FIG. 17 is an example of the regional disaster information 21.

[0107] As shown in FIG. 17, the regional disaster information 21 includes, for example, two categories: "disaster information" and "information on the target area". Note that the setting of the categories is arbitrary. And extraction rules are set for each category. Then, according to the extraction rules, from the disaster prevention / evacuation information 61, the "items" of each category and the "details" regarding those items are extracted. The extracted "item" and "detail" information is output as the regional disaster information 21.

[0108] For "disaster information", the "items" and "details" are extracted according to the following extraction rule procedure.

[0109] 1-1. Extract the nouns representing the information transmitted from the disaster prevention meteorological information. 1-2. Input "disaster prevention meteorological information" into the "item", and input the extracted noun into the "detail".

[0110] For example, when "heavy rain special warning" is input as the disaster prevention / evacuation information 61, "disaster prevention meteorological information" is input into the item, and "heavy rain special warning" is input into the detail. Note that items and details corresponding to the warning level for the warning may also be set in the item. For example, in the case of "heavy rain special warning", "warning level" is input into the item, and "warning level 5" is input into the detail.

[0111] Next, for the "information on the target area", the "items" and "details" are extracted according to the following extraction rule procedure.

[0112] 1-1. In the case of a noun related to a prefecture, input "prefecture" into the "item", and input the extracted noun into the "detail". 1-2. In the case of a noun representing "city" or "ward", input "city area" into the "item", and input the extracted noun into the "detail".

[0113] For example, when "Ota Ward, Tokyo" is input as the information on the target area, "prefecture" is input into the "item", and "Tokyo" is input into the detail. Further, "city area" is input into the "item", and "Ota Ward" is input into the detail.

[0114] Note that, as a category, for example, "Evacuation Advice" may be set. When information regarding evacuation advice or the like is input as disaster prevention / evacuation information 61, for example, "Evacuation Advice" is input as an "Item", and the content of the information is input in "Details".

[0115] 1.8. Target Person Data of the Region Next, with reference to FIG. 18, an example of the details of the target person data 28 of the region will be described. FIG. 18 is an example of the target person data 28 of the region. For example, the target person extraction unit 17 of the region extracts target persons in descending order of the priority of support (degree of need for assistance).

[0116] As shown in FIG. 18, the target person extraction unit 17 of the region extracts "Items" and "Details" from the regional disaster information 21 and the data of persons in need of assistance 26 according to the following extraction rule procedure to create the target person data 28 of the region.

[0117] 1-1. Extract target persons whose address in the data of persons in need of assistance 26 matches the target area in the regional disaster information 21. 1-2. Input "Name" in "Items" and input the name of the target person in "Details". 1-3. Input the "Information on the Target Area" and "Disaster Information" in the regional disaster information 21. 1-4. Input "Degree of Need for Assistance" in "Items" and input the degree of need for assistance of the target person in "Details". 1-5. Input "Alert Level" in "Items" and input the alert level extracted from the regional disaster information 21 in "Details".

[0118] For example, when "Name: XXXXXXXX" is input as the target person 1, "Name" is input in the basic attribute item, and "XXXXXXXX" is input in detail. When a prefecture is input in the "Target Area Information" category of the regional disaster information 21, "Target Area (Prefecture)" is input in the item, and the noun of the prefecture (Tokyo Metropolis in the example of Fig. 18) is input in detail. Also, when a ward is input in the "Target Area Information" category of the regional disaster information 21, "Target Area (Ward)" is input in the item, and the noun of the ward (Ota Ward in the example of Fig. 18) is input in detail. When a heavy rain special warning is input as disaster prevention meteorological information in the "Disaster Information" category of the regional disaster information 21, "Disaster Prevention Meteorological Information" is input in the item, and "Heavy Rain Special Warning" is input in detail. Further, "Warning Level" is input in the item, and "Warning Level 5" is input in detail. When the degree of assistance required of the person requiring assistance data 26 is 6.3, "Degree of Assistance Required" is input in the item, and the degree of assistance required "6.3" is input in detail.

[0119] The same extraction rules are applied to the target person 2. In the case of the target person 2, for example, the degree of assistance required "6" is input. The other items are the same as those of the target person 1.

[0120] Based on the degree of assistance required, the priority of the target person is determined for the target person 1 and the target person 2. Therefore, the target person 1 has a higher priority for support than the target person 2.

[0121] 1.9. Presentation Data Next, with reference to Figs. 19 to 21, an example of the presentation data in the presentation unit 40 will be described. Figs. 19 to 21 are an example of the presentation data when presenting the regional target person data 28 and the person requiring assistance data 26 together. Note that in the examples of Figs. 19 to 21, for the sake of simplicity of explanation, the categories of "physical and mental state", "relationship", and "ability / experience" are omitted.

[0122] As shown in Figs. 19 to 21, the presentation unit 40 presents data combining the regional target person data 28 and the person requiring assistance data 26 on, for example, a display screen or the like.

[0123] More specifically, the presented data includes categories of "disaster information", "basic attributes", "basic information", and "utilization of information reception means". In the category of "disaster information", information based on the target person data 28 of the region is presented. For example, the items of the target person data 28 of the region, "target region (prefecture)", "target region (city ward)", "degree of assistance required", "disaster prevention meteorological information", and "warning level" are presented. Furthermore, details corresponding to each item are presented.

[0124] In the categories of "basic attributes", "basic information", and "utilization of information reception means", information based on the person requiring assistance data 26 is presented. More specifically, the "items", "details" of the person requiring assistance data 26, as well as the "insights", "hypotheses of approaches", and "hypotheses of support / goals" of the experts' knowledge are presented. In the examples of FIGS. 19 to 21, "basic weighting", "importance to the individual", and "points" are omitted, but each may be presented.

[0125] The presented data can be output externally via the communication unit 50.

[0126] 1.10. Effects according to the embodiment In the case of the configuration according to the present embodiment, the support system 1 for persons in need of support can create personal data 23 using information 22 of local residents based on the activities of neighborhood commissioners or regional comprehensive support centers. Based on the personal data 23 and the database 24 of expert data by welfare experts such as social workers, the personal capability data 25 can be created. Based on the personal capability data 25 of the person, the degree of need for support can be calculated, and the data 26 of the person in need of support can be created. In addition, the support system 1 for persons in need of support can create regional disaster information 21 when a disaster occurs. And when a disaster occurs, the support system 1 for persons in need of support can create the target person data of the region based on the regional disaster information 21 and the data 26 of the person in need of support while referring to the response content data 27 of the target region. Thereby, the support system 1 for persons in need of support can extract, as target persons, persons who may require support (assistance) including those who have not received care certification. Therefore, the extraction accuracy of persons who may potentially require support at the time of a disaster can be improved.

[0127] Furthermore, in the case of the configuration according to the present embodiment, based on the degree of need for support, the priority of support for a plurality of target persons can be calculated. Thereby, persons who are more in need of support can be supported preferentially.

[0128] Furthermore, by using the information 22 of local residents, detailed information of the target person can be obtained. By using the database of expert data, the situation of the target person can be predicted. Therefore, the optimal support can be provided to the target person.

[0129] 2. Others Various modifications can be applied to the above-described embodiment.

[0130] Note that the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the gist thereof at the implementation stage. Also, the respective embodiments may be implemented in appropriate combination, and in that case, the combined effects can be obtained. Furthermore, the above embodiments include various inventions, and various inventions can be extracted by combinations selected from a plurality of disclosed constituent elements. For example, even if some constituent elements are deleted from all the constituent elements shown in the embodiments, if the problem can be solved and the effects can be obtained, the configuration from which these constituent elements are deleted can be extracted as an invention.

Explanation of Reference Numerals

[0131] 1…Support and Assistance System 10…Control Unit 11…Regional Disaster Situation Acquisition Unit 12…Regional Resident Information Extraction Unit 13…Expert Data Acquisition Unit 14…Database Update Unit for Expert Data 15…Reference Unit 16…Person Requiring Assistance Determination Unit 17…Regional Target Person Extraction Unit 20…Storage Unit 21…Regional Disaster Information 22…Regional Resident Information 23…Personal Data 24…Database of Expert Data 25…Personal Capability Data 26…Person Requiring Assistance Data 27…Response Content Data for Target Region 28…Regional Target Person Data 29…Support and Assistance Program 30…Input Unit 40…Presentation Unit 50…Communication Unit 60…Expert Data 61…Disaster Prevention / Evacuation Information 62…Presentation Data

Claims

1. A disaster situation acquisition unit that acquires disaster information, An information extraction unit that extracts personal information from information of local residents including name, date of birth, gender, medical history, degree of care need, and address, and creates personal data for each individual including items corresponding to each of the name, the date of birth, the gender, the medical history, the degree of care need, and the address, A reference unit that extracts the knowledge of the welfare experts including support or support goals for the data corresponding person from the database of welfare expert data, and creates the person's capability data with the knowledge added to the personal data, A determination unit that creates care-requiring person data by adding a degree of care need calculated based on the person's capability data to the person's capability data, and determines a care-requiring person based on the degree of care need of the care-requiring person data, A target person extraction unit that extracts target persons in need of care in the disaster area based on the disaster information and the care-requiring person data, and creates target person data, A presentation unit that presents the target person data and the care-requiring person data A support system for care-requiring persons, comprising:

2. The target person extraction unit calculates the priority of assistance among a plurality of the target persons, The presentation unit presents the target person data, the care-requiring person data, and the priority together, The support system for care-requiring persons according to Claim 1.

3. The information of the local residents includes at least one of the activity records of the neighborhood association members, the activity records of the comprehensive regional support centers, and the care records, The support system for care-requiring persons according to Claim 1.

4. The knowledge of the welfare experts further includes an insight into the state of the data corresponding person and a hypothesis for approaching the data corresponding person, The support system for care-requiring persons according to Claim 1.

5. The determination unit calculates the degree of care need based on the weighting for each item of the person's capability data and the importance for the data corresponding person, The support system for care-requiring persons according to Claim 1.

6. The target person extraction unit extracts the target persons by referring to the response content data of the target area including the response content of the support predetermined for each area based on the content of the disaster and the situation of the target area, The support system for care-requiring persons according to Claim 1.

7. Acquiring disaster information, Extract personal information from the information of local residents including name, date of birth, gender, medical history, degree of care need, and address, and create personal data for each individual including items corresponding to each of the name, date of birth, gender, medical history, degree of care need, and address. Extract the knowledge of welfare experts including support or support goals for the data subjects corresponding to the personal data from the database of welfare expert data, and create personal capability data with the knowledge added to the personal data. Create care-requiring person data with the degree of care need calculated based on the personal capability data added to the personal capability data of the individual, and determine whether the individual is a care-requiring person based on the degree of care need in the care-requiring person data. Extract care-requiring target persons in the disaster area based on the disaster information and the care-requiring person data, and create target person data. Present the target person data and the care-requiring person data. A method for extracting care-requiring persons, comprising the above steps.

8. A program for causing a computer to function as each part included in the care-requiring person support system according to any one of Claims 1 to 6.

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