System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting regional information of a user; means for inputting family structure information and physical information of the user; means for evaluating a disaster risk based on the regional information input to a server; means for calculating a type and an amount of a necessary disaster prevention stockpile based on the disaster risk; means for learning stockpile data of a similar user and proposing a recommended stockpile; and means for managing an item stockpiled by the user and a use-by date.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Because it is impossible to know when a disaster will strike, it is recommended that individuals stockpile disaster preparedness supplies. However, the type and quantity of supplies that should be stockpiled varies greatly depending on family structure and region. This makes it difficult for many people to select appropriate supplies, resulting in inadequate preparations when a disaster occurs. Stockpiling appropriate medicines is particularly important for people with special health conditions, and even greater consideration is needed. Managing the expiration dates of existing stockpiles is also time-consuming, and delays in updating pose a risk of the stockpile becoming unusable. Thus, there is a need for an easy way to select and manage disaster preparedness supplies optimized for individual circumstances. [Means for solving the problem]

[0005] This invention proposes the following means: First, a means is provided for users to input regional information, family composition information, and physical information. Second, a means is provided for the server to assess disaster risk based on regional information and calculate the type and quantity of disaster preparedness supplies needed based on the results. Third, a means is provided for the server to learn the stockpile data of similar users and suggest recommended stockpile items to the user. Furthermore, a means is provided for recommending specific medicines to users with special health conditions. Finally, a means is provided for users to manage the items they have stockpiled and their expiration dates, and a function is provided to send alerts for stockpile items that are approaching their expiration date, thereby enabling the selection and management of disaster preparedness supplies optimized for each individual household's circumstances. These means enable users to quickly and effectively stockpile necessary disaster preparedness supplies, ensuring sufficient preparation in the event of an emergency.

[0006] "User information" refers to data such as the user's area information, family structure, and physical information.

[0007] "Regional information" refers to information about the place where the user lives, specifically the city, town, village, address, etc.

[0008] "Family composition" is information indicating the number and relationships of members in the user's household, including the number of adults, children, and pets.

[0009] "Physical information" refers to data such as the height, weight, and health status of the user and their family members.

[0010] "Disaster risk" refers to the predicted probability of occurrence of natural disasters such as earthquakes, typhoons, and floods, and the extent of their impact.

[0011] "Disaster preparedness supplies" are items that are needed in the event of a disaster, including drinking water, food, medicine, and disaster prevention goods.

[0012] "Recommendation" refers to a list of additional stockpiles that the server recommends based on information about similar users.

[0013] "Expiration date" is information indicating the date by which stockpiled goods can be safely used, and refers to the validity period of the stockpiled goods.

[0014] "Alerts" refer to warnings or reminders that notify users about stockpiled items that are approaching their expiration date.

[0015] A "server" refers to a computer system that receives input information from users and performs processes such as disaster risk assessment, calculation of emergency supplies, generation of recommendations, and data management.

[0016] "Terminal" refers to the device used by a user to enter information and view results, including smartphones, tablets, and personal computers.

[0017] A "hazard map" is a map that visually shows the risk of disasters such as earthquakes, floods, and tsunamis, and allows users to check the probability of disasters occurring and the impact of each disaster in each region.

[0018] "Stockpile management" refers to recording information about disaster preparedness stockpiles owned by users and properly understanding and managing expiration dates and inventory status. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention relates to a system for proposing and managing optimal disaster preparedness supplies based on a user's area information, family structure, and physical information.

[0041] System Overview

[0042] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies to stockpile accordingly. It also learns from the stockpile data of similar users and presents recommended emergency supplies. It also manages the expiration dates of existing emergency supplies and provides necessary alerts to the user.

[0043] Program processing flow

[0044] 1. User information registration

[0045] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[0046] 2. Disaster risk assessment

[0047] The server refers to a hazard map based on regional information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area. In the case of Yokohama, the risk of earthquakes and typhoons is judged to be high. Based on this information, the server performs a disaster risk assessment and sends the results back to the terminal.

[0048] 3. Calculate the necessary supplies

[0049] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four (two adults and two children) needs 3 liters of water per person per day for seven days, for a total of 84 liters. It also determines that diabetics need certain medications. The results are displayed to the user via their device.

[0050] 4. Generating Recommendations

[0051] The server learns similar user data and suggests additional stockpiles based on "items stockpiled by other users." For example, it presents information about "cooling sheets" or "portable generators" that other users with similar conditions have.

[0052] 5. Emergency supplies management function

[0053] The user inputs the items they have stockpiled and their expiration dates, and the device sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the device, allowing the user to update their stockpiles appropriately.

[0054] Specific examples

[0055] For example, if the user is a family of four (two adults, two children, one of whom is a diabetic) living in Yokohama, Kanagawa Prefecture, the system operates as follows.

[0056] 1. User information registration

[0057] The user enters the local information "Yokohama City, Kanagawa Prefecture."

[0058] Family composition: 2 adults, 2 children, 1 diabetic.

[0059] Physical information: One of the adults is diabetic and requires medication.

[0060] 2. Disaster risk assessment

[0061] The server references the hazard map based on local information.

[0062] Assessing earthquake and typhoon risks in Yokohama City.

[0063] 3. Calculate the necessary supplies

[0064] Water required: 84 litres.

[0065] Suggesting specific medications for diabetics.

[0066] Generate a list of other emergency supplies (flashlights, radios, etc.).

[0067] 4. Generating Recommendations

[0068] The server learns similar user data from other users in the same area.

[0069] Additional recommended stockpiles include cooling sheets and portable generators.

[0070] 5. Emergency supplies management function

[0071] The user inputs the stockpile items and their expiration dates.

[0072] The server generates an alert when the expiration date approaches and notifies the user.

[0073] This system allows users to quickly and effectively stockpile disaster supplies tailored to their individual household circumstances, ensuring they are adequately prepared in the event of an emergency.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] The user opens the application and enters local information, family composition information, and physical information. For example, the local information is "Yokohama, Kanagawa Prefecture," the family composition is "2 adults, 2 children," and the physical information is "1 adult has diabetes." The device receives this data and sends it to the server.

[0077] Step 2:

[0078] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[0079] Step 3:

[0080] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day is needed for seven days, for a total of 84 liters. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[0081] Step 4:

[0082] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[0083] Step 5:

[0084] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[0085] Step 6:

[0086] The server receives stockpile data, stores it in a database, and manages expiration dates. The server periodically checks the data and generates an alert when the expiration date approaches.

[0087] Step 7:

[0088] The server generates an alert for stockpiled items that are approaching their expiration date and sends it to the terminal. The terminal notifies the user of the alert and prompts the user to update the stockpiled items.

[0089] This process allows users to easily manage and secure disaster preparedness stockpiles that are optimized for their own household situation.

[0090] Example 1

[0091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0092] In recent years, with the increase in natural disasters, it has become increasingly important for each household to stockpile disaster preparedness supplies appropriately. However, it is difficult to select the appropriate stockpile items based on family composition and local risks, and managing stockpiles is also complicated, so many households are not adequately prepared. To solve this problem, a system is needed that can automatically suggest and manage the optimal disaster preparedness supplies according to the user's specific situation.

[0093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0094] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information input to the central processing unit, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, and means for providing the user with an alert when the expiration date is approaching. This enables the user to easily prepare and appropriately manage the optimal disaster preparedness supplies based on their own family composition and regional risks.

[0095] "User" refers to an individual or household who uses the system to input local information, family composition information, and physical information.

[0096] "Region information" refers to information related to the geographic area in which a user resides.

[0097] "Family composition information" refers to information about the number and relationships of people living in a user's household (such as adults, children, and those with certain health conditions).

[0098] "Physical Information" refers to information relating to the health status or specific medical needs of a user or their family members.

[0099] "Central processing unit" refers to a computer or server that performs calculations and analysis based on information input by a user.

[0100] "Disaster risk" refers to information assessing the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in a particular area.

[0101] "Stockpiles" refer to food, medicine, disaster prevention goods, etc. stored in the home in preparation for disasters.

[0102] "Expiration date" refers to the date by which stockpiled goods can be safely used.

[0103] "Alert" refers to a warning that notifies the user when an expiration date is approaching or other important notices are issued.

[0104] This invention relates to a system that proposes and manages optimal disaster preparedness supplies based on a user's area information, family structure, and physical information. The system for implementing this invention has various functions that allow a user to input area information, family structure information, and physical information and, based on that, to carry out appropriate disaster preparedness stockpiling.

[0105] 1. User information registration

[0106] The user enters local information, family composition information, and physical information through the application. For example, if the user enters "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes," the device sends this data to the server. The server stores the received information in a database. This step registers the user's basic information in the system.

[0107] 2. Disaster risk assessment

[0108] Based on the regional information, the server uses the central processing unit to refer to the hazard map database. The server evaluates the risk of earthquakes, typhoons, floods, etc. for each region and sends the results back to the terminal. For example, Yokohama City may be judged to be at particularly high risk of earthquakes and typhoons, and this information will be provided to the user.

[0109] 3. Calculate the necessary supplies

[0110] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on the user's family composition and physical information. For example, for a family of four (two adults and two children), it calculates that each person needs 3 liters of water per day for seven days, for a total of 84 liters. It also determines that diabetics need specific medications. The results are displayed to the user from the server via their device.

[0111] 4. Generating Recommendations

[0112] The server analyzes similar user data using a machine learning model and generates additional recommended stockpiles based on the items stockpiled by other users. For example, cooling sheets or portable generators are suggested. This information is then sent to the user via their device.

[0113] 5. Emergency supplies management function

[0114] Users input the items they have stockpiled and their expiration dates, and the terminal sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the terminal. This allows users to properly manage expiration dates.

[0115] Specific examples

[0116] For example, if the user is a family of four (two adults, two children, one with diabetes) living in Yokohama, Kanagawa Prefecture, the system operates as follows:

[0117] 1. The user enters the following information into the application: "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[0118] 2. The server references hazard map data based on regional information and sends the results of its assessment of earthquake and typhoon risk in Yokohama City to the terminal.

[0119] 3. Calculate the amount of water needed (84 liters) or the specific medications needed for a diabetic patient, and send the calculations to the terminal.

[0120] 4. The server learns similar user data and sends a list of recommended stockpiles, such as "cooling sheets" and "portable generators," to the device.

[0121] 5. The user inputs the current stockpile items and their expiration dates, and the server generates an alert when the expiration date approaches, and the terminal notifies the user.

[0122] This system allows users to quickly and effectively stockpile supplies for disasters, and also allows them to properly manage expiration dates and quantities.

[0123] Prompt Sentence Examples

[0124] "Please generate a list of disaster preparedness supplies for a household with two adults, two children, and one diabetic living in Yokohama City, Kanagawa Prefecture. I would also like to set up alerts for when the expiration date is approaching. Please provide detailed information on the suggested supplies and how to manage them."

[0125] The present invention provides a system for proposing and managing optimal disaster preparedness supplies according to the needs of individual households and regional risks, thereby supporting users in continuing to live safely.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1: Register user information

[0128] Input: The user inputs regional information, family composition information, and physical information through the application interface.

[0129] Specific operation: The user enters information such as "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[0130] Data processing: The terminal formats these input information and sends them as data packets to the server.

[0131] Output: Data packets sent from the device to the server.

[0132] Step 2: Save user information

[0133] Input: The server receives a data packet of user information sent from the terminal.

[0134] Specific operation: The server analyzes the data packet and extracts regional information (Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one person is a diabetic).

[0135] Data processing: The extracted information is stored in a database and a user ID is generated and associated with it.

[0136] Output: User information stored in the database and the generated user ID.

[0137] Step 3: Disaster risk assessment

[0138] Input: The server uses the stored locality information (Yokohama, Kanagawa Prefecture).

[0139] Specific operation: The server queries the hazard map API and obtains the corresponding hazard data (earthquake, typhoon risk, etc.).

[0140] Data processing: Analyze the acquired hazard data and run a risk assessment algorithm to assess the disaster risk of the area, for example, calculating an earthquake risk rate of 70% and a typhoon risk rate of 60%.

[0141] Output: The disaster risk assessment results are sent from the server to the terminal and displayed to the user.

[0142] Step 4: Calculate your supply needs

[0143] Input: The server bases the user's family information (2 adults, 2 children) and physical information (1 diabetic).

[0144] Specific behavior: Calculates the necessary stockpiles according to the criteria. For example, the water requirement is calculated as 3 liters per person per day for 7 days, which is 84 liters for a family of four. Also, a specific medication list is generated for diabetics.

[0145] Data processing: Generate a list of necessary supplies and their quantities, and organize the data.

[0146] Output: The generated stockpile list is sent from the server to the terminal and displayed to the user.

[0147] Step 5: Generate recommendations

[0148] Input: The server performs analysis based on similar user data and a generated AI model.

[0149] Specific operation: The server analyzes similar area and family structure data using a generative AI model to learn from data on stockpiles held by other users. For example, it checks whether recommended stockpiles of items such as "cooling sheets" and "portable generators" are common.

[0150] Data processing: Generate a list of additional recommended supplies and organize the data.

[0151] Output: The generated list of recommended stockpiles is sent from the server to the terminal and displayed to the user.

[0152] Step 6: Stockpile management function

[0153] Input: The user inputs the items they have stockpiled and their expiration dates into the application.

[0154] Specific operation: The user inputs the existing stockpile items (e.g., water, medicine, etc.) and their expiration dates. The terminal sends this as a data packet to the server.

[0155] Data processing: The server stores the received stockpile information and expiration date in a database and checks it periodically.

[0156] Output: When the expiration date is approaching, an alert is generated and sent from the server to the terminal to notify the user.

[0157] By using the above specific processing steps, this system can provide users with the function of suggesting and managing optimal disaster preparedness supplies.

[0158] (Application example 1)

[0159] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0160] In managing disaster preparedness supplies, there are issues with the lack of optimal product recommendations and expiration date management that take into account each user's regional characteristics, family structure, and health status. Furthermore, there is a lack of systems that can suggest recommended stockpiles based on similar user data, and there is also a lack of systems that can provide appropriate alerts when stockpiles are approaching their expiration dates.

[0161] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0162] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, means for alerting the user about stockpiled items approaching their expiration dates, and means for inputting and managing user information using a smartphone application, thereby enabling the proposal and management of disaster preparedness supplies optimal for each individual user.

[0163] "User area information" is information for identifying the area in which the user resides.

[0164] "Family composition information" is information that indicates the number of people in the user's household and their relationships.

[0165] "Physical information" is information that indicates the health status or specific medical needs of the user or their family members.

[0166] The "means for assessing disaster risk" is a means for calculating and assessing the risk of disasters such as earthquakes, typhoons, and floods based on the user's local information.

[0167] "Means for calculating the types and quantities of disaster preparedness supplies required" refers to means for calculating the types and quantities of disaster preparedness supplies required based on disaster risk, family composition, and physical information.

[0168] The "means for proposing recommended stockpiles" is a means for learning data of similar users and recommending optimal stockpiles to the user.

[0169] The "means for managing items stockpiled by the user and their expiration dates" refers to a means for registering stockpiled items and their expiration dates entered by the user in a database and managing them.

[0170] The "means for providing an alert about stockpiled goods approaching their expiration date" is a means for notifying the user when the expiration date of a stockpiled item is approaching.

[0171] A "smartphone application" is software that runs on a portable electronic device and allows users to input and manage information and generate alerts.

[0172] To implement this invention, it is necessary to build a system that inputs the user's area information, family composition information, and physical information and proposes and manages disaster preparedness supplies. This system includes the following main components, hardware, and software:

[0173] System Overview

[0174] The server evaluates disaster risk based on the area information entered by the user, calculates the type and quantity of disaster preparedness supplies needed, and has the function of learning from data on similar users to suggest recommended stockpiles. It also alerts users when stockpiles are nearing their expiration date.

[0175] The user terminal (such as a smartphone) provides an application for inputting user information (regional information, family composition information, physical information) and communicating with the server. This application also allows management of stockpiled supplies and receiving alerts.

[0176] Hardware and software used

[0177] Programming language: Python

[0178] Database: MongoDB or SQLite (for data management)

[0179] API: Google Maps API or OpenStreetMap API for disaster risk assessment

[0180] Cloud services: AWS Lambda (serverless computing), Amazon S3 (data storage)

[0181] Processing flow example

[0182] 1. User information registration

[0183] A user opens a smartphone application and enters information about their area, family structure, and physical condition. For example, they might enter information like "I live in Tokyo, have one adult and one child, and I have high blood pressure."

[0184] The application sends this information to the server.

[0185] 2. Disaster risk assessment

[0186] The server uses the Google Maps API and OpenStreetMap API to assess the risk of earthquakes and typhoons based on local information. For example, it may assess that "Tokyo has a high earthquake risk."

[0187] 3. Calculating the necessary disaster preparedness supplies

[0188] The server calculates the type and amount of supplies needed based on the user's family composition and health information. For example, it calculates "42 liters of water and a one-month supply of high blood pressure medication."

[0189] 4. Recommended stockpiles

[0190] The server learns data from similar users and further recommends items to stock up on, such as a portable generator and cooling sheets.

[0191] 5. Emergency supplies management function

[0192] Users use the application to register their stockpiles and their expiration dates. The server manages this information and generates an alert to notify the user when the expiration date approaches.

[0193] Examples

[0194] For example, if a user enters information such as "a household of one adult and one child living in Tokyo, where the adult has high blood pressure," the system will operate as follows:

[0195] 1. User information registration:

[0196] The user inputs the region information "Tokyo", family composition "1 adult, 1 child", and health information "adult has high blood pressure".

[0197] 2. Disaster risk assessment:

[0198] The server uses the Google Maps API or OpenStreetMap API to assess that "Tokyo is at high risk of earthquakes."

[0199] 3. Calculate the necessary supplies:

[0200] The amount of water needed is 42 liters. It is calculated that a one-month supply of high blood pressure medication is needed.

[0201] 4. Recommended stockpile items:

[0202] The server will suggest additional recommended supplies, such as a "portable generator" or "cooling sheets."

[0203] 5. Expiration date management and alert generation:

[0204] When the expiration date of the stockpiled items registered by the user approaches, an alert will be sent via the application.

[0205] Prompt Sentence Examples

[0206] An example of an input prompt for the generative AI model to be used next:

[0207] User Information:

[0208] Region: Tokyo

[0209] Family composition: 1 adult, 1 child

[0210] Health condition: High blood pressure in adults

[0211] Suggested supplies to stockpile:

[0212] Please suggest the most appropriate disaster preparedness supplies based on the disaster risk assessment results.

[0213] Learn from data of similar users and suggest additional recommended stockpiles.

[0214] In this way, users can properly manage their disaster preparedness supplies and prepare for emergencies.

[0215] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0216] Step 1:

[0217] Registering user information

[0218] Input: The user enters regional information, family composition information, and physical information into the smartphone application. Example: "Living in Tokyo, one adult, one child, with high blood pressure."

[0219] Data processing: Parse the information entered by the user into JSON format.

[0220] Output: Sends the parsed data to the server.

[0221] Specific behavior: The user enters region information, family composition, and health information into the application's input form and taps the "Submit" button. The application converts the entered data into JSON format and sends it as a POST request to the server's API endpoint.

[0222] Step 2:

[0223] Disaster risk assessment

[0224] Input: The locale information received by the server in step 1.

[0225] Data calculation: The server calls the hazard map API (Google Maps API or OpenStreetMap API) based on local information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area.

[0226] Output: Generate disaster risk assessment results and store them in a database.

[0227] Specific operation: The server calls the hazard map API based on regional information and obtains risk data. It processes the data and evaluates earthquake risk as "high," typhoon risk as "medium," etc. The evaluation results are then stored in a database.

[0228] Step 3:

[0229] Calculating necessary disaster preparedness supplies

[0230] Input: Family composition information and physical information received by the server in step 1, and disaster risk assessment results obtained in step 2.

[0231] Data calculation: The server calculates the type and quantity of supplies needed based on the user's family composition and health information using formulas and rules.

[0232] Output: Generate and send data to display the calculation results on the user's terminal.

[0233] Specific operation: The server calculates the necessary supplies (e.g., 42 liters of water, one month's supply of high blood pressure medication) based on the input data, and notifies the user's device (smartphone) of the results.

[0234] Step 4:

[0235] Recommended stockpiles

[0236] Input: The stockpile data calculated by the server in step 3, and stockpile data of similar users in the database.

[0237] Data calculation: The server uses a generative AI model to learn from data of similar users and generate additional stockpile recommendations.

[0238] Output: Send the recommended stockpile list to the user's device.

[0239] How it works: The server uses the generative AI model to analyze data from similar users. For example, it generates a list of recommendations for items stockpiled by other users, such as portable generators or cooling sheets, and presents this to the user's device.

[0240] Step 5:

[0241] Stockpile management function

[0242] Input: The user inputs the stockpile items and their expiration dates into the smartphone application.

[0243] Data processing: The input stockpile information and expiration date are converted into JSON format and sent to the server.

[0244] Output: Saved in a database for expiration date management.

[0245] Specific operation: A user registers a stockpile item (e.g., 20 liters of water) and its expiration date (e.g., March 1, 2024) through the application. The application sends this data to the server, which stores it in a database.

[0246] Step 6:

[0247] Expiration date alert generation

[0248] Input: Expiration date information of stockpiled items stored in the database.

[0249] Data calculation: The server compares the current date with the expiration date of each stockpile item and generates an alert if the expiration date is approaching.

[0250] Output: Sends an alert notification to the user's device.

[0251] Specific operation: The server periodically checks expiration dates and generates an alert message for any stockpiled items that are approaching their expiration date, notifying the smartphone application. For example, it sends a message such as, "The expiration date for your water is approaching. Please consume it by March 1, 2024."

[0252] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0253] This invention relates to a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine.

[0254] System Overview

[0255] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies accordingly. It then learns from similar users' emergency stockpiles to suggest recommended emergency supplies, and uses an emotion engine to respond to the user's emotional state. It also manages expiration dates for existing emergency supplies and provides necessary alerts to the user.

[0256] Program processing flow

[0257] 1. User information registration

[0258] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[0259] 2. Disaster risk assessment

[0260] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[0261] 3. Calculate the necessary supplies

[0262] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day for seven days is 84 liters in total. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[0263] 4. Generating Recommendations

[0264] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[0265] 5. Emergency supplies management function

[0266] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[0267] 6. Emotion engine integration

[0268] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety.

[0269] 7. Tailoring recommendations based on emotions

[0270] The emotion engine analyzes the user's emotional state and adjusts recommended supplies as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). In addition, for users in a positive emotional state, it reinforces reminders to regularly manage and update their supplies.

[0271] 8. Expiration date management and alerts

[0272] The server stores expiration dates in a database and periodically checks them. When the expiration date approaches, an alert is generated and sent to the terminal. The terminal notifies the user of this alert and alerts them to update their stockpiles, allowing them to update their stockpiles in a timely manner.

[0273] Specific examples

[0274] Let's take the example of a user who is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture." The user inputs information about the area, family composition, and physical information, and the server performs a disaster risk assessment and calculates the necessary stockpiles. The server also uses an emotion engine to detect the user's anxiety and stress, and suggests stockpiles that have a relaxing effect. Furthermore, the server periodically manages the expiration dates of existing stockpiles and notifies the user via alerts.

[0275] This system allows users to easily manage and secure disaster preparedness supplies that are optimized for their own household situation and emotional state, enabling them to respond appropriately in the event of an emergency.

[0276] The processing flow will be explained below.

[0277] Step 1:

[0278] The user opens the application and enters local information (e.g., Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one adult has diabetes). The device then sends this data to the server.

[0279] Step 2:

[0280] Based on the regional information received, the server refers to the relevant hazard map and calculates the disaster risk of earthquakes, typhoons, floods, etc. in the relevant region. Specifically, the server obtains earthquake and typhoon risk data for Yokohama City and sends the risk assessment results to the terminal.

[0281] Step 3:

[0282] The server calculates the types and quantities of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that 84 liters of water is needed (3 liters per person per day x 7 days). It also includes a list of specific medications for diabetics, and sends the calculation results to the device and displays them to the user.

[0283] Step 4:

[0284] The server learns similar user data and generates recommended stockpiles based on the items stockpiled by other users. For example, "cooling sheets" and "portable generators" are recommended. The recommended results are sent to the device and displayed to the user.

[0285] Step 5:

[0286] The user inputs the items they have already stockpiled and their expiration dates into the terminal, such as "15 bottles of stored water, expiration date October 2024," and the terminal sends the data to the server.

[0287] Step 6:

[0288] The server stores the received information on stockpiled items and their expiration dates in a database, and prepares to alert users to stockpiled items that are approaching their expiration date. For example, it periodically checks for stockpiled items that are within one month of their expiration date.

[0289] Step 7:

[0290] The emotion engine recognizes the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety and stress. For example, if a user's expression becomes grim after viewing disaster information, anxiety is detected.

[0291] Step 8:

[0292] The emotion engine adjusts recommended supplies based on the user's emotional state. For example, if anxiety or stress levels are high, it will suggest adding items with a relaxing effect (aroma oils or stress relief products). The device will display these suggestions to the user.

[0293] Step 9:

[0294] The server periodically checks the expiration dates in the database, generates alerts for stockpiled items that are approaching their expiration date, and sends them to the terminal. The terminal notifies the user of the alert, allowing the user to update their stockpiled items at the appropriate time.

[0295] This detailed process flow allows users to manage disaster preparedness supplies optimized for their home situation and emotional state, and respond quickly and effectively in the event of an emergency.

[0296] Example 2

[0297] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0298] Conventional disaster preparedness stockpile management systems assessed disaster risk and calculated stockpiles based on the user's area information, family composition, and physical information, but lacked functionality to respond to the user's emotional state and health condition. As a result, they were unable to suggest stockpiles appropriate for stressful situations or specific health conditions, making it difficult to provide satisfactory stockpile management. In addition, some systems required manual management of stockpile expiration dates, making efficient management difficult.

[0299] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0300] In this invention, the server integrates an emotion engine for analyzing the user's emotional state and includes means for adjusting recommended stockpiles based on the user's emotional state, means for inputting the user's regional information, and means for inputting the user's family composition information and physical information. This makes it possible to suggest stockpiles with relaxing effects based on the user's emotional state and recommend medicines for specific health conditions. Furthermore, by comprehensively managing the expiration dates of stockpiles and sending alerts when the expiration date is approaching, effective and automated stockpiling management can be achieved.

[0301] "Region information" refers to information relating to the geographical location where the user resides, including the city, town, or village, address, and so on.

[0302] "Family composition information" refers to information about the composition of people in the user's household, including the number of adults and children, their ages, and specific health conditions.

[0303] "Physical information" refers to information about the health status of the user and their family members, including specific illnesses and allergies.

[0304] "Server" refers to a centralized computer system that processes information entered by users and performs calculations for disaster risk assessments and emergency supplies.

[0305] "Disaster risk" refers to the results of an assessment of the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in the area where the user lives, and the resulting impact.

[0306] "Stockpiles" refer to supplies such as food and drink, medicine, and disaster prevention goods that are prepared in advance in preparation for disasters.

[0307] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and respond accordingly.

[0308] "Recommendation" refers to a function that suggests optimal options or products based on a user's past behavior and data.

[0309] "Expiration date" refers to the date by which stockpiled goods can be consumed or used, and means that quality and safety can no longer be guaranteed after this date.

[0310] An "alert" is a warning or reminder that the system sends to the user when a certain condition has been met.

[0311] This invention is a system for supporting disaster preparedness stockpiling management, which proposes and manages optimal stockpiles based on the user's regional information, family composition information, physical information, and emotional state. This system utilizes hardware and software such as a server, terminals, and an emotion engine.

[0312] First, the user uses the device to input local information, family composition information, and physical information. For example, the user might input information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes" into the application. The device then sends this information to the server.

[0313] The server accesses a hazard map database based on local information and evaluates the disaster risk of the area. For example, it calculates the risk of earthquakes and typhoons and produces results such as "Earthquake risk: High" and "Typhoon risk: Medium." This is then sent to the device and displayed to the user.

[0314] The server then uses family composition and physical information to calculate the type and amount of supplies needed. Taking the amount of drinking water needed for two adults and two children, it calculates that 3 liters of water per person per day for seven days, for a total of 84 liters. It also adds medication for diabetics to the list. These calculation results are sent to the device and displayed to the user.

[0315] The server then learns from data on similar users. Based on the data of users with similar family structures in the same area, it analyzes the additional stockpiles it recommends. For example, it creates a list of recommended stockpiles, such as "cooling sheets" and "portable generators," and sends this to the device.

[0316] The user inputs the stockpiled items and their expiration dates. For example, information such as "I have 15 bottles of stockpiled water, and the expiration date is October 2024" is entered into the application, and the device sends this information to the server. The server stores this information in a database and manages the expiration dates. When the expiration date approaches, the server generates an alert and sends it to the device. The device notifies the user of this alert and encourages them to update their stockpiles.

[0317] The emotion engine analyzes the user's facial expressions and tone of voice. When the user is using the application, the device captures the user's face and records their voice. This data is sent to the emotion engine to detect emotions such as anxiety and stress. For example, it can detect a user who becomes anxious after seeing disaster information and suggest items with a relaxing effect, such as aroma oils or stress-relieving products. In addition, for users in a positive emotional state, it can reinforce reminders to regularly manage and update their emergency supplies.

[0318] As a concrete example, let's consider a four-person family (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture. When the user inputs local information, family composition, and physical information, the server performs a disaster risk assessment and calculates the necessary stockpiles. An emotion engine is used to monitor the user's emotional state, detecting anxiety and stress and suggesting appropriate stockpiles. By suggesting medicines according to specific health conditions, users can manage their stockpiles with peace of mind. In addition, alerts are sent as expiration dates approach, allowing them to update their stockpiles in a timely manner.

[0319] An example of a prompt to be input to the generative AI model would be, "Please suggest the optimal disaster preparedness supplies and how to manage them for a family of four (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture."

[0320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0321] System program processing flow and specific explanation

[0322] Step 1: Register user information

[0323] Input: Regional information, family information, physical information

[0324] Output: User information sent to the server

[0325] 1.1 The user enters regional information, family composition information, and physical information into the application. Specifically, the user enters the following data: "Yokohama City, Kanagawa Prefecture," "2 adults, 2 children," and "1 person has diabetes."

[0326] 1.2 The device sends this information to the server using the HTTPS protocol.

[0327] Step 2: Disaster risk assessment

[0328] Input: Region information

[0329] Output: Disaster risk assessment results

[0330] 2.1 The server accesses the hazard map database based on the received regional information.

[0331] 2.2 The server retrieves disaster risk data such as earthquakes, typhoons, and floods from the hazard map database and runs the risk assessment algorithm.

[0332] 2.3 Earthquake risk and typhoon risk are quantified as "high" or "medium" and the results are sent to the terminal. Specifically, the results include assessments such as "earthquake risk: high" and "typhoon risk: medium."

[0333] Step 3: Calculate your supply needs

[0334] Input: Family composition information, physical information

[0335] Output: Stockpile list and quantities

[0336] 3.1 The server runs an algorithm to calculate the necessary amount of various supplies based on the user's family composition and physical information.

[0337] 3.2 For example, for two adults and two children, each person needs 3 litres of water per day for seven days, for a total of 84 litres. Also include medication for diabetics.

[0338] 3.3 This stockpile list and calculation results are sent to the terminal and displayed to the user.

[0339] Step 4: Generate recommendations

[0340] Input: Similar user data

[0341] Output: Additional recommended supplies list

[0342] 4.1 The server collects similar user data in the same area and analyzes it using machine learning algorithms.

[0343] 4.2 Based on the stockpile item data recommended by similar users, we create a list of additional recommended stockpile items.

[0344] 4.3 For example, items such as "cooling sheets" and "portable generators" are selected as recommended stockpiles, and these are sent to the terminal and suggested to the user.

[0345] Step 5: Stockpile management function

[0346] Input: Information about stockpiled items and expiration dates held by the user

[0347] Output: Emergency stockpile information and expiration date management stored on the server

[0348] 5.1 The user inputs the items and expiration dates of their stockpiles into the application. For example, they input "15 bottles of water, expiration date October 2024."

[0349] 5.2 The terminal sends this information to the server, and the server stores the stockpile information in a database.

[0350] Step 6: Integrating the Emotion Engine

[0351] Input: User's facial expression data, voice tone data

[0352] Output: Emotional state analyzed by the emotion engine

[0353] 6.1 While a user is using an application, the device captures the user's facial expressions with a camera and collects the tone of voice with a microphone.

[0354] 6.2 The device sends this data to the server in real time, and the server analyzes it using an emotion engine to detect an emotional state, for example, "Anxiety state: High."

[0355] Step 7: Adjusting recommendations based on sentiment

[0356] Input: Emotional state analysis results

[0357] Output: Adjusted recommended stockpile list

[0358] 7.1 The server adjusts the recommended stockpile list based on the analysis results of the emotion engine, for example, "Anxiety state: High."

[0359] 7.2 Stock up on relaxing items, such as aroma oils and stress relievers.

[0360] 7.3 The adjusted recommended stockpile list is sent to the terminal and displayed to the user.

[0361] Step 8: Expiration date management and alerts

[0362] Input: Expiration date information in the database

[0363] Output: Alert when expiration date is approaching

[0364] 8.1 The server periodically checks the expiration date information in the database.

[0365] 8.2 When the expiration date approaches, the server generates an alert and sends it to the device.

[0366] 8.3 The device notifies the user of this alert via a push notification, displaying a message such as "Your water bottle expires in October 2024 and requires renewal."

[0367] (Application example 2)

[0368] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0369] In recent years, the frequency of disasters has increased, making the management and recommendation of disaster preparedness supplies increasingly important. However, while conventional disaster preparedness supply management systems can recommend necessary items based on a user's regional information and family composition, they are unable to provide optimal recommendations that take into account the health and emotional state of each individual user. Furthermore, expiration dates of stockpiled supplies are not adequately managed, posing challenges for maintaining the quality of stockpiled supplies. Therefore, the present invention aims to provide a management system that proposes optimal disaster preparedness supplies that take into account the user's individual circumstances and emotional state, and also includes expiration date management.

[0370] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0371] In this invention, the server includes means for inputting the user's regional information, means for inputting the user's family composition information and physical information, means for assessing disaster risk based on the regional information input to the server, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpile data of similar users and proposing recommended stockpile items, means for analyzing the user's emotional state and adjusting the recommended stockpile items, means for managing the items stockpiled by the user and their expiration dates, means for detecting the user's anxiety and stress using an emotion engine, and means for proposing supplies. This makes it possible to propose and manage disaster preparedness supplies optimized for each user's situation.

[0372] "Regional information" is information about the area where the user lives, and is data about the local government, regional characteristics, and the like.

[0373] "Family composition information" is information about the composition of members in the user's household, including data such as the number of people, age groups, and health conditions.

[0374] "Physical information" refers to information about the physical health status of the user and their family members.

[0375] "Disaster risk" refers to the assessment results regarding the predicted probability of occurrence of disasters such as earthquakes, typhoons, and floods in a specific region, as well as the extent of their impact.

[0376] "Disaster preparedness supplies" are items such as food, drink, medical supplies, and daily necessities that are needed in the event of a disaster.

[0377] "Recommended stockpiles" are disaster preparedness stockpiles that are particularly recommended based on the user's situation and data on similar users.

[0378] "Emotional state" refers to the psychological state of the user, and is information relating to emotions such as anxiety, stress, and a sense of security.

[0379] The "emotion engine" is a system that recognizes and evaluates the user's emotional state by analyzing facial expressions, tone of voice, etc.

[0380] The "expiration date" is the end of the period during which the stockpiled goods can be used and the date by which their quality is guaranteed.

[0381] "Supplies" are items that should be stockpiled in addition as needed.

[0382] The present invention is a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine. Specific embodiments of the system are described below.

[0383] Registering user information

[0384] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device (e.g., smartphone or tablet) then sends this data to the server.

[0385] Disaster risk assessment

[0386] The server refers to a hazard map based on regional information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. For example, the server evaluates the earthquake and typhoon risks in Yokohama City and sends the results of the risk evaluation to the terminal. The hardware used is a database server, and the software is a program that implements a risk evaluation algorithm.

[0387] Calculating necessary supplies

[0388] The server calculates the amount of food, drink, and disaster prevention supplies needed based on family composition and physical information. For example, a family of four (two adults and two children) will need 3 liters of water per person per day for seven days, for a total of 84 liters. A list is also generated that includes specific medications for diabetics. The server sends the calculation results to the terminal, which displays them to the user. The software used is a data calculation program written in Python.

[0389] Generating recommendations

[0390] The server takes in similar user data and learns from it. For example, it analyzes recommended additional stockpiles based on stockpiling data from users with similar family structures in the same area. It creates a list of recommended stockpiles, such as "cooling sheets" or "portable generators," and sends the results to the device. A machine learning model could be used.

[0391] Stockpile management function

[0392] The user inputs the items they have stockpiled and their expiration dates. For example, the user inputs information such as "I have stockpiled 15 bottles of water, the expiration date of which is October 2024," and the device sends this data to the server. The server then periodically checks the expiration dates and generates an alert when the expiration date approaches. This alert is sent to the device and notifies the user. The software used is a database and alert system.

[0393] Emotion engine integration

[0394] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety. This is done using an emotion analysis engine (API) and the camera and microphone of the smartphone or tablet.

[0395] Tailoring recommendations based on sentiment

[0396] The emotion engine analyzes the user's emotional state and adjusts the recommended items as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). For users in a positive emotional state, it reinforces reminders to regularly manage and update their inventory. The program implements logic to list recommended items based on the results of emotion analysis.

[0397] Specific examples

[0398] If the user is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture," all of the above processes will be carried out, and a list of necessary stockpiles, expiration date alerts, and emotion-based recommendations will be provided.

[0399] Prompt Sentence Examples

[0400] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's area information, family composition, and physical information, and suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state.

[0401] Please use "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[0402] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0403] Step 1:

[0404] The user enters regional information, family composition information, and physical information. The user opens the application and enters information such as "A family of two adults and two children living in Yokohama City, Kanagawa Prefecture, one of whom has diabetes." The device sends this data to the server. The input data is sent in JSON format and is analyzed by the server.

[0405] Step 2:

[0406] The server refers to a hazard map based on regional information and assesses the disaster risk of the relevant region. The server uses a disaster risk assessment algorithm to assess the risks of earthquakes, typhoons, floods, etc. and calculates the results. The server generates earthquake and typhoon risk assessment results for Yokohama City and sends them to the terminal. The input is regional information and the output is the risk assessment results.

[0407] Step 3:

[0408] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four needs 3 liters of water per person per day for seven days. It also calculates the amount of specific medications needed for diabetics. The server lists the calculation results and sends them to the terminal. The input is family composition and physical information, and the output is a list of the necessary supplies.

[0409] Step 4:

[0410] The server uses similar user data to suggest recommended stockpiles. The server uses a machine learning model to analyze stockpiles data from users with similar family structures in the same area and lists additional recommended stockpiles. Items such as "cooling sheets" and "portable generators" may be included in the list. The input is existing user data, and the output is a list of recommended stockpiles.

[0411] Step 5:

[0412] The user inputs the stockpiled items and their expiration dates. For example, they input information such as "I have 15 bottles of water in stock, and the expiration date is October 2024." The device sends this data to the server. The server stores it in a database, periodically checks the expiration date, and generates an alert when the expiration date approaches and sends it to the device. The input is stockpiled item information and expiration date, and the output is alert information.

[0413] Step 6:

[0414] The system uses an emotion engine to recognize the user's emotional state. It uses a camera and microphone to collect facial expressions and tone of voice while the user is using the application, and detects anxiety and stress. The emotion engine then sends the analysis results to a server. The input is facial expressions and tone of voice, and the output is an evaluation of the user's emotional state.

[0415] Step 7:

[0416] The emotion engine analyzes the user's emotional state and adjusts recommended stockpiles as needed. If anxiety or stress is high, it suggests stockpiles with a relaxing effect (such as aroma oils or stress relief products). If the emotional state is positive, it reinforces reminders to regularly manage and update stockpiles. The input is the emotion analysis results, and the output is recommended stockpiles or reminder information.

[0417] Example prompt sentence:

[0418] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's region, family composition, and physical information, and then suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state. Use "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[0419] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0420] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0421] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0422] [Second embodiment]

[0423] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0424] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0425] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0426] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0427] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0428] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0429] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0430] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0431] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0432] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0433] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0434] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0435] The present invention relates to a system for proposing and managing optimal disaster preparedness supplies based on a user's area information, family structure, and physical information.

[0436] System Overview

[0437] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies to stockpile accordingly. It also learns from the stockpile data of similar users and presents recommended emergency supplies. It also manages the expiration dates of existing emergency supplies and provides necessary alerts to the user.

[0438] Program processing flow

[0439] 1. User information registration

[0440] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[0441] 2. Disaster risk assessment

[0442] The server refers to a hazard map based on regional information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area. In the case of Yokohama, the risk of earthquakes and typhoons is judged to be high. Based on this information, the server performs a disaster risk assessment and sends the results back to the terminal.

[0443] 3. Calculate the necessary supplies

[0444] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four (two adults and two children) needs 3 liters of water per person per day for seven days, for a total of 84 liters. It also determines that diabetics need certain medications. The results are displayed to the user via their device.

[0445] 4. Generating Recommendations

[0446] The server learns similar user data and suggests additional stockpiles based on "items stockpiled by other users." For example, it presents information about "cooling sheets" or "portable generators" that other users with similar conditions have.

[0447] 5. Emergency supplies management function

[0448] The user inputs the items they have stockpiled and their expiration dates, and the device sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the device, allowing the user to update their stockpiles appropriately.

[0449] Specific examples

[0450] For example, if the user is a family of four (two adults, two children, one of whom is a diabetic) living in Yokohama, Kanagawa Prefecture, the system operates as follows.

[0451] 1. User information registration

[0452] The user enters the local information "Yokohama City, Kanagawa Prefecture."

[0453] Family composition: 2 adults, 2 children, 1 diabetic.

[0454] Physical information: One of the adults is diabetic and requires medication.

[0455] 2. Disaster risk assessment

[0456] The server references the hazard map based on local information.

[0457] Assessing earthquake and typhoon risks in Yokohama City.

[0458] 3. Calculate the necessary supplies

[0459] Water required: 84 litres.

[0460] Suggesting specific medications for diabetics.

[0461] Generate a list of other emergency supplies (flashlights, radios, etc.).

[0462] 4. Generating Recommendations

[0463] The server learns similar user data from other users in the same area.

[0464] Additional recommended stockpiles include cooling sheets and portable generators.

[0465] 5. Emergency supplies management function

[0466] The user inputs the stockpile items and their expiration dates.

[0467] The server generates an alert when the expiration date approaches and notifies the user.

[0468] This system allows users to quickly and effectively stockpile disaster supplies tailored to their individual household circumstances, ensuring they are adequately prepared in the event of an emergency.

[0469] The processing flow will be explained below.

[0470] Step 1:

[0471] The user opens the application and enters local information, family composition information, and physical information. For example, the local information is "Yokohama, Kanagawa Prefecture," the family composition is "2 adults, 2 children," and the physical information is "1 adult has diabetes." The device receives this data and sends it to the server.

[0472] Step 2:

[0473] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[0474] Step 3:

[0475] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day is needed for seven days, for a total of 84 liters. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[0476] Step 4:

[0477] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[0478] Step 5:

[0479] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[0480] Step 6:

[0481] The server receives stockpile data, stores it in a database, and manages expiration dates. The server periodically checks the data and generates an alert when the expiration date approaches.

[0482] Step 7:

[0483] The server generates an alert for stockpiled items that are approaching their expiration date and sends it to the terminal. The terminal notifies the user of the alert and prompts the user to update the stockpiled items.

[0484] This process allows users to easily manage and secure disaster preparedness stockpiles that are optimized for their own household situation.

[0485] Example 1

[0486] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0487] In recent years, with the increase in natural disasters, it has become increasingly important for each household to stockpile disaster preparedness supplies appropriately. However, it is difficult to select the appropriate stockpile items based on family composition and local risks, and managing stockpiles is also complicated, so many households are not adequately prepared. To solve this problem, a system is needed that can automatically suggest and manage the optimal disaster preparedness supplies according to the user's specific situation.

[0488] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0489] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information input to the central processing unit, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, and means for providing the user with an alert when the expiration date is approaching. This enables the user to easily prepare and appropriately manage the optimal disaster preparedness supplies based on their own family composition and regional risks.

[0490] "User" refers to an individual or household who uses the system to input local information, family composition information, and physical information.

[0491] "Region information" refers to information related to the geographic area in which a user resides.

[0492] "Family composition information" refers to information about the number and relationships of people living in a user's household (such as adults, children, and those with certain health conditions).

[0493] "Physical Information" refers to information relating to the health status or specific medical needs of a user or their family members.

[0494] "Central processing unit" refers to a computer or server that performs calculations and analysis based on information input by a user.

[0495] "Disaster risk" refers to information assessing the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in a particular area.

[0496] "Stockpiles" refer to food, medicine, disaster prevention goods, etc. stored in the home in preparation for disasters.

[0497] "Expiration date" refers to the date by which stockpiled goods can be safely used.

[0498] "Alert" refers to a warning that notifies the user when an expiration date is approaching or other important notices are issued.

[0499] This invention relates to a system that proposes and manages optimal disaster preparedness supplies based on a user's area information, family structure, and physical information. The system for implementing this invention has various functions that allow a user to input area information, family structure information, and physical information and, based on that, to carry out appropriate disaster preparedness stockpiling.

[0500] 1. User information registration

[0501] The user enters local information, family composition information, and physical information through the application. For example, if the user enters "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes," the device sends this data to the server. The server stores the received information in a database. This step registers the user's basic information in the system.

[0502] 2. Disaster risk assessment

[0503] Based on the regional information, the server uses the central processing unit to refer to the hazard map database. The server evaluates the risk of earthquakes, typhoons, floods, etc. for each region and sends the results back to the terminal. For example, Yokohama City may be judged to be at particularly high risk of earthquakes and typhoons, and this information will be provided to the user.

[0504] 3. Calculate the necessary supplies

[0505] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on the user's family composition and physical information. For example, for a family of four (two adults and two children), it calculates that each person needs 3 liters of water per day for seven days, for a total of 84 liters. It also determines that diabetics need specific medications. The results are displayed to the user from the server via their device.

[0506] 4. Generating Recommendations

[0507] The server analyzes similar user data using a machine learning model and generates additional recommended stockpiles based on the items stockpiled by other users. For example, cooling sheets or portable generators are suggested. This information is then sent to the user via their device.

[0508] 5. Emergency supplies management function

[0509] Users input the items they have stockpiled and their expiration dates, and the terminal sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the terminal. This allows users to properly manage expiration dates.

[0510] Specific examples

[0511] For example, if the user is a family of four (two adults, two children, one with diabetes) living in Yokohama, Kanagawa Prefecture, the system operates as follows:

[0512] 1. The user enters the following information into the application: "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[0513] 2. The server references hazard map data based on regional information and sends the results of its assessment of earthquake and typhoon risk in Yokohama City to the terminal.

[0514] 3. Calculate the amount of water needed (84 liters) or the specific medications needed for a diabetic patient, and send the calculations to the terminal.

[0515] 4. The server learns similar user data and sends a list of recommended stockpiles, such as "cooling sheets" and "portable generators," to the device.

[0516] 5. The user inputs the current stockpile items and their expiration dates, and the server generates an alert when the expiration date approaches, and the terminal notifies the user.

[0517] This system allows users to quickly and effectively stockpile supplies for disasters, and also allows them to properly manage expiration dates and quantities.

[0518] Prompt Sentence Examples

[0519] "Please generate a list of disaster preparedness supplies for a household with two adults, two children, and one diabetic living in Yokohama City, Kanagawa Prefecture. I would also like to set up alerts for when the expiration date is approaching. Please provide detailed information on the suggested supplies and how to manage them."

[0520] The present invention provides a system for proposing and managing optimal disaster preparedness supplies according to the needs of individual households and regional risks, thereby supporting users in continuing to live safely.

[0521] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0522] Step 1: Register user information

[0523] Input: The user inputs regional information, family composition information, and physical information through the application interface.

[0524] Specific operation: The user enters information such as "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[0525] Data processing: The terminal formats these input information and sends them as data packets to the server.

[0526] Output: Data packets sent from the device to the server.

[0527] Step 2: Save user information

[0528] Input: The server receives a data packet of user information sent from the terminal.

[0529] Specific operation: The server analyzes the data packet and extracts regional information (Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one person is a diabetic).

[0530] Data processing: The extracted information is stored in a database and a user ID is generated and associated with it.

[0531] Output: User information stored in the database and the generated user ID.

[0532] Step 3: Disaster risk assessment

[0533] Input: The server uses the stored locality information (Yokohama, Kanagawa Prefecture).

[0534] Specific operation: The server queries the hazard map API and obtains the corresponding hazard data (earthquake, typhoon risk, etc.).

[0535] Data processing: Analyze the acquired hazard data and run a risk assessment algorithm to assess the disaster risk of the area, for example, calculating an earthquake risk rate of 70% and a typhoon risk rate of 60%.

[0536] Output: The disaster risk assessment results are sent from the server to the terminal and displayed to the user.

[0537] Step 4: Calculate your supply needs

[0538] Input: The server bases the user's family information (2 adults, 2 children) and physical information (1 diabetic).

[0539] Specific behavior: Calculates the necessary stockpiles according to the criteria. For example, the water requirement is calculated as 3 liters per person per day for 7 days, which is 84 liters for a family of four. Also, a specific medication list is generated for diabetics.

[0540] Data processing: Generate a list of necessary supplies and their quantities, and organize the data.

[0541] Output: The generated stockpile list is sent from the server to the terminal and displayed to the user.

[0542] Step 5: Generate recommendations

[0543] Input: The server performs analysis based on similar user data and a generated AI model.

[0544] Specific operation: The server analyzes similar area and family structure data using a generative AI model to learn from data on stockpiles held by other users. For example, it checks whether recommended stockpiles of items such as "cooling sheets" and "portable generators" are common.

[0545] Data processing: Generate a list of additional recommended supplies and organize the data.

[0546] Output: The generated list of recommended stockpiles is sent from the server to the terminal and displayed to the user.

[0547] Step 6: Stockpile management function

[0548] Input: The user inputs the items they have stockpiled and their expiration dates into the application.

[0549] Specific operation: The user inputs the existing stockpile items (e.g., water, medicine, etc.) and their expiration dates. The terminal sends this as a data packet to the server.

[0550] Data processing: The server stores the received stockpile information and expiration date in a database and checks it periodically.

[0551] Output: When the expiration date is approaching, an alert is generated and sent from the server to the terminal to notify the user.

[0552] By using the above specific processing steps, this system can provide users with the function of suggesting and managing optimal disaster preparedness supplies.

[0553] (Application example 1)

[0554] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0555] In managing disaster preparedness supplies, there are issues with the lack of optimal product recommendations and expiration date management that take into account each user's regional characteristics, family structure, and health status. Furthermore, there is a lack of systems that can suggest recommended stockpiles based on similar user data, and there is also a lack of systems that can provide appropriate alerts when stockpiles are approaching their expiration dates.

[0556] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0557] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, means for alerting the user about stockpiled items approaching their expiration dates, and means for inputting and managing user information using a smartphone application, thereby enabling the proposal and management of disaster preparedness supplies optimal for each individual user.

[0558] "User area information" is information for identifying the area in which the user resides.

[0559] "Family composition information" is information that indicates the number of people in the user's household and their relationships.

[0560] "Physical information" is information that indicates the health status or specific medical needs of the user or their family members.

[0561] The "means for assessing disaster risk" is a means for calculating and assessing the risk of disasters such as earthquakes, typhoons, and floods based on the user's local information.

[0562] "Means for calculating the types and quantities of disaster preparedness supplies required" refers to means for calculating the types and quantities of disaster preparedness supplies required based on disaster risk, family composition, and physical information.

[0563] The "means for proposing recommended stockpiles" is a means for learning data of similar users and recommending optimal stockpiles to the user.

[0564] The "means for managing items stockpiled by the user and their expiration dates" refers to a means for registering stockpiled items and their expiration dates entered by the user in a database and managing them.

[0565] The "means for providing an alert about stockpiled goods approaching their expiration date" is a means for notifying the user when the expiration date of a stockpiled item is approaching.

[0566] A "smartphone application" is software that runs on a portable electronic device and allows users to input and manage information and generate alerts.

[0567] To implement this invention, it is necessary to build a system that inputs the user's area information, family composition information, and physical information and proposes and manages disaster preparedness supplies. This system includes the following main components, hardware, and software:

[0568] System Overview

[0569] The server evaluates disaster risk based on the area information entered by the user, calculates the type and quantity of disaster preparedness supplies needed, and has the function of learning from data on similar users to suggest recommended stockpiles. It also alerts users when stockpiles are nearing their expiration date.

[0570] The user terminal (such as a smartphone) provides an application for inputting user information (regional information, family composition information, physical information) and communicating with the server. This application also allows management of stockpiled supplies and receiving alerts.

[0571] Hardware and software used

[0572] Programming language: Python

[0573] Database: MongoDB or SQLite (for data management)

[0574] API: Google Maps API or OpenStreetMap API for disaster risk assessment

[0575] Cloud services: AWS Lambda (serverless computing), Amazon S3 (data storage)

[0576] Processing flow example

[0577] 1. User information registration

[0578] A user opens a smartphone application and enters information about their area, family structure, and physical condition. For example, they might enter information like "I live in Tokyo, have one adult and one child, and I have high blood pressure."

[0579] The application sends this information to the server.

[0580] 2. Disaster risk assessment

[0581] The server uses the Google Maps API and OpenStreetMap API to assess the risk of earthquakes and typhoons based on local information. For example, it may assess that "Tokyo has a high earthquake risk."

[0582] 3. Calculating the necessary disaster preparedness supplies

[0583] The server calculates the type and amount of supplies needed based on the user's family composition and health information. For example, it calculates "42 liters of water and a one-month supply of high blood pressure medication."

[0584] 4. Recommended stockpiles

[0585] The server learns data from similar users and further recommends items to stock up on, such as a portable generator and cooling sheets.

[0586] 5. Emergency supplies management function

[0587] Users use the application to register their stockpiles and their expiration dates. The server manages this information and generates an alert to notify the user when the expiration date approaches.

[0588] Examples

[0589] For example, if a user enters information such as "a household of one adult and one child living in Tokyo, where the adult has high blood pressure," the system will operate as follows:

[0590] 1. User information registration:

[0591] The user inputs the region information "Tokyo", family composition "1 adult, 1 child", and health information "adult has high blood pressure".

[0592] 2. Disaster risk assessment:

[0593] The server uses the Google Maps API or OpenStreetMap API to assess that "Tokyo is at high risk of earthquakes."

[0594] 3. Calculate the necessary supplies:

[0595] The amount of water needed is 42 liters. It is calculated that a one-month supply of high blood pressure medication is needed.

[0596] 4. Recommended stockpile items:

[0597] The server will suggest additional recommended supplies, such as a "portable generator" or "cooling sheets."

[0598] 5. Expiration date management and alert generation:

[0599] When the expiration date of the stockpiled items registered by the user approaches, an alert will be sent via the application.

[0600] Prompt Sentence Examples

[0601] An example of an input prompt for the generative AI model to be used next:

[0602] User Information:

[0603] Region: Tokyo

[0604] Family composition: 1 adult, 1 child

[0605] Health condition: High blood pressure in adults

[0606] Suggested supplies to stockpile:

[0607] Please suggest the most appropriate disaster preparedness supplies based on the disaster risk assessment results.

[0608] Learn from data of similar users and suggest additional recommended stockpiles.

[0609] In this way, users can properly manage their disaster preparedness supplies and prepare for emergencies.

[0610] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0611] Step 1:

[0612] Registering user information

[0613] Input: The user enters regional information, family composition information, and physical information into the smartphone application. Example: "Living in Tokyo, one adult, one child, with high blood pressure."

[0614] Data processing: Parse the information entered by the user into JSON format.

[0615] Output: Sends the parsed data to the server.

[0616] Specific behavior: The user enters region information, family composition, and health information into the application's input form and taps the "Submit" button. The application converts the entered data into JSON format and sends it as a POST request to the server's API endpoint.

[0617] Step 2:

[0618] Disaster risk assessment

[0619] Input: The locale information received by the server in step 1.

[0620] Data calculation: The server calls the hazard map API (Google Maps API or OpenStreetMap API) based on local information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area.

[0621] Output: Generate disaster risk assessment results and store them in a database.

[0622] Specific operation: The server calls the hazard map API based on regional information and obtains risk data. It processes the data and evaluates earthquake risk as "high," typhoon risk as "medium," etc. The evaluation results are then stored in a database.

[0623] Step 3:

[0624] Calculating necessary disaster preparedness supplies

[0625] Input: Family composition information and physical information received by the server in step 1, and disaster risk assessment results obtained in step 2.

[0626] Data calculation: The server calculates the type and quantity of supplies needed based on the user's family composition and health information using formulas and rules.

[0627] Output: Generate and send data to display the calculation results on the user's terminal.

[0628] Specific operation: The server calculates the necessary supplies (e.g., 42 liters of water, one month's supply of high blood pressure medication) based on the input data, and notifies the user's device (smartphone) of the results.

[0629] Step 4:

[0630] Recommended stockpiles

[0631] Input: The stockpile data calculated by the server in step 3, and stockpile data of similar users in the database.

[0632] Data calculation: The server uses a generative AI model to learn from data of similar users and generate additional stockpile recommendations.

[0633] Output: Send the recommended stockpile list to the user's device.

[0634] How it works: The server uses the generative AI model to analyze data from similar users. For example, it generates a list of recommendations for items stockpiled by other users, such as portable generators or cooling sheets, and presents this to the user's device.

[0635] Step 5:

[0636] Stockpile management function

[0637] Input: The user inputs the stockpile items and their expiration dates into the smartphone application.

[0638] Data processing: The input stockpile information and expiration date are converted into JSON format and sent to the server.

[0639] Output: Saved in a database for expiration date management.

[0640] Specific operation: A user registers a stockpile item (e.g., 20 liters of water) and its expiration date (e.g., March 1, 2024) through the application. The application sends this data to the server, which stores it in a database.

[0641] Step 6:

[0642] Expiration date alert generation

[0643] Input: Expiration date information of stockpiled items stored in the database.

[0644] Data calculation: The server compares the current date with the expiration date of each stockpile item and generates an alert if the expiration date is approaching.

[0645] Output: Sends an alert notification to the user's device.

[0646] Specific operation: The server periodically checks expiration dates and generates an alert message for any stockpiled items that are approaching their expiration date, notifying the smartphone application. For example, it sends a message such as, "The expiration date for your water is approaching. Please consume it by March 1, 2024."

[0647] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0648] This invention relates to a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine.

[0649] System Overview

[0650] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies accordingly. It then learns from similar users' emergency stockpiles to suggest recommended emergency supplies, and uses an emotion engine to respond to the user's emotional state. It also manages expiration dates for existing emergency supplies and provides necessary alerts to the user.

[0651] Program processing flow

[0652] 1. User information registration

[0653] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[0654] 2. Disaster risk assessment

[0655] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[0656] 3. Calculate the necessary supplies

[0657] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day for seven days is 84 liters in total. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[0658] 4. Generating Recommendations

[0659] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[0660] 5. Emergency supplies management function

[0661] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[0662] 6. Emotion engine integration

[0663] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety.

[0664] 7. Tailoring recommendations based on emotions

[0665] The emotion engine analyzes the user's emotional state and adjusts recommended supplies as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). In addition, for users in a positive emotional state, it reinforces reminders to regularly manage and update their supplies.

[0666] 8. Expiration date management and alerts

[0667] The server stores expiration dates in a database and periodically checks them. When the expiration date approaches, an alert is generated and sent to the terminal. The terminal notifies the user of this alert and alerts them to update their stockpiles, allowing them to update their stockpiles in a timely manner.

[0668] Specific examples

[0669] Let's take the example of a user who is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture." The user inputs information about the area, family composition, and physical information, and the server performs a disaster risk assessment and calculates the necessary stockpiles. The server also uses an emotion engine to detect the user's anxiety and stress, and suggests stockpiles that have a relaxing effect. Furthermore, the server periodically manages the expiration dates of existing stockpiles and notifies the user via alerts.

[0670] This system allows users to easily manage and secure disaster preparedness supplies that are optimized for their own household situation and emotional state, enabling them to respond appropriately in the event of an emergency.

[0671] The processing flow will be explained below.

[0672] Step 1:

[0673] The user opens the application and enters local information (e.g., Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one adult has diabetes). The device then sends this data to the server.

[0674] Step 2:

[0675] Based on the regional information received, the server refers to the relevant hazard map and calculates the disaster risk of earthquakes, typhoons, floods, etc. in the relevant region. Specifically, the server obtains earthquake and typhoon risk data for Yokohama City and sends the risk assessment results to the terminal.

[0676] Step 3:

[0677] The server calculates the types and quantities of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that 84 liters of water is needed (3 liters per person per day x 7 days). It also includes a list of specific medications for diabetics, and sends the calculation results to the device and displays them to the user.

[0678] Step 4:

[0679] The server learns similar user data and generates recommended stockpiles based on the items stockpiled by other users. For example, "cooling sheets" and "portable generators" are recommended. The recommended results are sent to the device and displayed to the user.

[0680] Step 5:

[0681] The user inputs the items they have already stockpiled and their expiration dates into the terminal, such as "15 bottles of stored water, expiration date October 2024," and the terminal sends the data to the server.

[0682] Step 6:

[0683] The server stores the received information on stockpiled items and their expiration dates in a database, and prepares to alert users to stockpiled items that are approaching their expiration date. For example, it periodically checks for stockpiled items that are within one month of their expiration date.

[0684] Step 7:

[0685] The emotion engine recognizes the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety and stress. For example, if a user's expression becomes grim after viewing disaster information, anxiety is detected.

[0686] Step 8:

[0687] The emotion engine adjusts recommended supplies based on the user's emotional state. For example, if anxiety or stress levels are high, it will suggest adding items with a relaxing effect (aroma oils or stress relief products). The device will display these suggestions to the user.

[0688] Step 9:

[0689] The server periodically checks the expiration dates in the database, generates alerts for stockpiled items that are approaching their expiration date, and sends them to the terminal. The terminal notifies the user of the alert, allowing the user to update their stockpiled items at the appropriate time.

[0690] This detailed process flow allows users to manage disaster preparedness supplies optimized for their home situation and emotional state, and respond quickly and effectively in the event of an emergency.

[0691] Example 2

[0692] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0693] Conventional disaster preparedness stockpile management systems assessed disaster risk and calculated stockpiles based on the user's area information, family composition, and physical information, but lacked functionality to respond to the user's emotional state and health condition. As a result, they were unable to suggest stockpiles appropriate for stressful situations or specific health conditions, making it difficult to provide satisfactory stockpile management. In addition, some systems required manual management of stockpile expiration dates, making efficient management difficult.

[0694] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0695] In this invention, the server integrates an emotion engine for analyzing the user's emotional state and includes means for adjusting recommended stockpiles based on the user's emotional state, means for inputting the user's regional information, and means for inputting the user's family composition information and physical information. This makes it possible to suggest stockpiles with relaxing effects based on the user's emotional state and recommend medicines for specific health conditions. Furthermore, by comprehensively managing the expiration dates of stockpiles and sending alerts when the expiration date is approaching, effective and automated stockpiling management can be achieved.

[0696] "Region information" refers to information relating to the geographical location where the user resides, including the city, town, or village, address, and so on.

[0697] "Family composition information" refers to information about the composition of people in the user's household, including the number of adults and children, their ages, and specific health conditions.

[0698] "Physical information" refers to information about the health status of the user and their family members, including specific illnesses and allergies.

[0699] "Server" refers to a centralized computer system that processes information entered by users and performs calculations for disaster risk assessments and emergency supplies.

[0700] "Disaster risk" refers to the results of an assessment of the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in the area where the user lives, and the resulting impact.

[0701] "Stockpiles" refer to supplies such as food and drink, medicine, and disaster prevention goods that are prepared in advance in preparation for disasters.

[0702] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and respond accordingly.

[0703] "Recommendation" refers to a function that suggests optimal options or products based on a user's past behavior and data.

[0704] "Expiration date" refers to the date by which stockpiled goods can be consumed or used, and means that quality and safety can no longer be guaranteed after this date.

[0705] An "alert" is a warning or reminder that the system sends to the user when a certain condition has been met.

[0706] This invention is a system for supporting disaster preparedness stockpiling management, which proposes and manages optimal stockpiles based on the user's regional information, family composition information, physical information, and emotional state. This system utilizes hardware and software such as a server, terminals, and an emotion engine.

[0707] First, the user uses the device to input local information, family composition information, and physical information. For example, the user might input information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes" into the application. The device then sends this information to the server.

[0708] The server accesses a hazard map database based on local information and evaluates the disaster risk of the area. For example, it calculates the risk of earthquakes and typhoons and produces results such as "Earthquake risk: High" and "Typhoon risk: Medium." This is then sent to the device and displayed to the user.

[0709] The server then uses family composition and physical information to calculate the type and amount of supplies needed. Taking the amount of drinking water needed for two adults and two children, it calculates that 3 liters of water per person per day for seven days, for a total of 84 liters. It also adds medication for diabetics to the list. These calculation results are sent to the device and displayed to the user.

[0710] The server then learns from data on similar users. Based on the data of users with similar family structures in the same area, it analyzes the additional stockpiles it recommends. For example, it creates a list of recommended stockpiles, such as "cooling sheets" and "portable generators," and sends this to the device.

[0711] The user inputs the stockpiled items and their expiration dates. For example, information such as "I have 15 bottles of stockpiled water, and the expiration date is October 2024" is entered into the application, and the device sends this information to the server. The server stores this information in a database and manages the expiration dates. When the expiration date approaches, the server generates an alert and sends it to the device. The device notifies the user of this alert and encourages them to update their stockpiles.

[0712] The emotion engine analyzes the user's facial expressions and tone of voice. When the user is using the application, the device captures the user's face and records their voice. This data is sent to the emotion engine to detect emotions such as anxiety and stress. For example, it can detect a user who becomes anxious after seeing disaster information and suggest items with a relaxing effect, such as aroma oils or stress-relieving products. In addition, for users in a positive emotional state, it can reinforce reminders to regularly manage and update their emergency supplies.

[0713] As a concrete example, let's consider a four-person family (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture. When the user inputs local information, family composition, and physical information, the server performs a disaster risk assessment and calculates the necessary stockpiles. An emotion engine is used to monitor the user's emotional state, detecting anxiety and stress and suggesting appropriate stockpiles. By suggesting medicines according to specific health conditions, users can manage their stockpiles with peace of mind. In addition, alerts are sent as expiration dates approach, allowing them to update their stockpiles in a timely manner.

[0714] An example of a prompt to be input to the generative AI model would be, "Please suggest the optimal disaster preparedness supplies and how to manage them for a family of four (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture."

[0715] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0716] System program processing flow and specific explanation

[0717] Step 1: Register user information

[0718] Input: Regional information, family information, physical information

[0719] Output: User information sent to the server

[0720] 1.1 The user enters regional information, family composition information, and physical information into the application. Specifically, the user enters the following data: "Yokohama City, Kanagawa Prefecture," "2 adults, 2 children," and "1 person has diabetes."

[0721] 1.2 The device sends this information to the server using the HTTPS protocol.

[0722] Step 2: Disaster risk assessment

[0723] Input: Region information

[0724] Output: Disaster risk assessment results

[0725] 2.1 The server accesses the hazard map database based on the received regional information.

[0726] 2.2 The server retrieves disaster risk data such as earthquakes, typhoons, and floods from the hazard map database and runs the risk assessment algorithm.

[0727] 2.3 Earthquake risk and typhoon risk are quantified as "high" or "medium" and the results are sent to the terminal. Specifically, the results include assessments such as "earthquake risk: high" and "typhoon risk: medium."

[0728] Step 3: Calculate your supply needs

[0729] Input: Family composition information, physical information

[0730] Output: Stockpile list and quantities

[0731] 3.1 The server runs an algorithm to calculate the necessary amount of various supplies based on the user's family composition and physical information.

[0732] 3.2 For example, for two adults and two children, each person needs 3 litres of water per day for seven days, for a total of 84 litres. Also include medication for diabetics.

[0733] 3.3 This stockpile list and calculation results are sent to the terminal and displayed to the user.

[0734] Step 4: Generate recommendations

[0735] Input: Similar user data

[0736] Output: Additional recommended supplies list

[0737] 4.1 The server collects similar user data in the same area and analyzes it using machine learning algorithms.

[0738] 4.2 Based on the stockpile item data recommended by similar users, we create a list of additional recommended stockpile items.

[0739] 4.3 For example, items such as "cooling sheets" and "portable generators" are selected as recommended stockpiles, and these are sent to the terminal and suggested to the user.

[0740] Step 5: Stockpile management function

[0741] Input: Information about stockpiled items and expiration dates held by the user

[0742] Output: Emergency stockpile information and expiration date management stored on the server

[0743] 5.1 The user inputs the items and expiration dates of their stockpiles into the application. For example, they input "15 bottles of water, expiration date October 2024."

[0744] 5.2 The terminal sends this information to the server, and the server stores the stockpile information in a database.

[0745] Step 6: Integrating the Emotion Engine

[0746] Input: User's facial expression data, voice tone data

[0747] Output: Emotional state analyzed by the emotion engine

[0748] 6.1 While a user is using an application, the device captures the user's facial expressions with a camera and collects the tone of voice with a microphone.

[0749] 6.2 The device sends this data to the server in real time, and the server analyzes it using an emotion engine to detect an emotional state, for example, "Anxiety state: High."

[0750] Step 7: Adjusting recommendations based on sentiment

[0751] Input: Emotional state analysis results

[0752] Output: Adjusted recommended stockpile list

[0753] 7.1 The server adjusts the recommended stockpile list based on the analysis results of the emotion engine, for example, "Anxiety state: High."

[0754] 7.2 Stock up on relaxing items, such as aroma oils and stress relievers.

[0755] 7.3 The adjusted recommended stockpile list is sent to the terminal and displayed to the user.

[0756] Step 8: Expiration date management and alerts

[0757] Input: Expiration date information in the database

[0758] Output: Alert when expiration date is approaching

[0759] 8.1 The server periodically checks the expiration date information in the database.

[0760] 8.2 When the expiration date approaches, the server generates an alert and sends it to the device.

[0761] 8.3 The device notifies the user of this alert via a push notification, displaying a message such as "Your water bottle expires in October 2024 and requires renewal."

[0762] (Application example 2)

[0763] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0764] In recent years, the frequency of disasters has increased, making the management and recommendation of disaster preparedness supplies increasingly important. However, while conventional disaster preparedness supply management systems can recommend necessary items based on a user's regional information and family composition, they are unable to provide optimal recommendations that take into account the health and emotional state of each individual user. Furthermore, expiration dates of stockpiled supplies are not adequately managed, posing challenges for maintaining the quality of stockpiled supplies. Therefore, the present invention aims to provide a management system that proposes optimal disaster preparedness supplies that take into account the user's individual circumstances and emotional state, and also includes expiration date management.

[0765] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0766] In this invention, the server includes means for inputting the user's regional information, means for inputting the user's family composition information and physical information, means for assessing disaster risk based on the regional information input to the server, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpile data of similar users and proposing recommended stockpile items, means for analyzing the user's emotional state and adjusting the recommended stockpile items, means for managing the items stockpiled by the user and their expiration dates, means for detecting the user's anxiety and stress using an emotion engine, and means for proposing supplies. This makes it possible to propose and manage disaster preparedness supplies optimized for each user's situation.

[0767] "Regional information" is information about the area where the user lives, and is data about the local government, regional characteristics, and the like.

[0768] "Family composition information" is information about the composition of members in the user's household, including data such as the number of people, age groups, and health conditions.

[0769] "Physical information" refers to information about the physical health status of the user and their family members.

[0770] "Disaster risk" refers to the assessment results regarding the predicted probability of occurrence of disasters such as earthquakes, typhoons, and floods in a specific region, as well as the extent of their impact.

[0771] "Disaster preparedness supplies" are items such as food, drink, medical supplies, and daily necessities that are needed in the event of a disaster.

[0772] "Recommended stockpiles" are disaster preparedness stockpiles that are particularly recommended based on the user's situation and data on similar users.

[0773] "Emotional state" refers to the psychological state of the user, and is information relating to emotions such as anxiety, stress, and a sense of security.

[0774] The "emotion engine" is a system that recognizes and evaluates the user's emotional state by analyzing facial expressions, tone of voice, etc.

[0775] The "expiration date" is the end of the period during which the stockpiled goods can be used and the date by which their quality is guaranteed.

[0776] "Supplies" are items that should be stockpiled in addition as needed.

[0777] The present invention is a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine. Specific embodiments of the system are described below.

[0778] Registering user information

[0779] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device (e.g., smartphone or tablet) then sends this data to the server.

[0780] Disaster risk assessment

[0781] The server refers to a hazard map based on regional information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. For example, the server evaluates the earthquake and typhoon risks in Yokohama City and sends the results of the risk evaluation to the terminal. The hardware used is a database server, and the software is a program that implements a risk evaluation algorithm.

[0782] Calculating necessary supplies

[0783] The server calculates the amount of food, drink, and disaster prevention supplies needed based on family composition and physical information. For example, a family of four (two adults and two children) will need 3 liters of water per person per day for seven days, for a total of 84 liters. A list is also generated that includes specific medications for diabetics. The server sends the calculation results to the terminal, which displays them to the user. The software used is a data calculation program written in Python.

[0784] Generating recommendations

[0785] The server takes in similar user data and learns from it. For example, it analyzes recommended additional stockpiles based on stockpiling data from users with similar family structures in the same area. It creates a list of recommended stockpiles, such as "cooling sheets" or "portable generators," and sends the results to the device. A machine learning model could be used.

[0786] Stockpile management function

[0787] The user inputs the items they have stockpiled and their expiration dates. For example, the user inputs information such as "I have stockpiled 15 bottles of water, the expiration date of which is October 2024," and the device sends this data to the server. The server then periodically checks the expiration dates and generates an alert when the expiration date approaches. This alert is sent to the device and notifies the user. The software used is a database and alert system.

[0788] Emotion engine integration

[0789] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety. This is done using an emotion analysis engine (API) and the camera and microphone of the smartphone or tablet.

[0790] Tailoring recommendations based on sentiment

[0791] The emotion engine analyzes the user's emotional state and adjusts the recommended items as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). For users in a positive emotional state, it reinforces reminders to regularly manage and update their inventory. The program implements logic to list recommended items based on the results of emotion analysis.

[0792] Specific examples

[0793] If the user is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture," all of the above processes will be carried out, and a list of necessary stockpiles, expiration date alerts, and emotion-based recommendations will be provided.

[0794] Prompt Sentence Examples

[0795] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's area information, family composition, and physical information, and suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state.

[0796] Please use "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[0797] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0798] Step 1:

[0799] The user enters regional information, family composition information, and physical information. The user opens the application and enters information such as "A family of two adults and two children living in Yokohama City, Kanagawa Prefecture, one of whom has diabetes." The device sends this data to the server. The input data is sent in JSON format and is analyzed by the server.

[0800] Step 2:

[0801] The server refers to a hazard map based on regional information and assesses the disaster risk of the relevant region. The server uses a disaster risk assessment algorithm to assess the risks of earthquakes, typhoons, floods, etc. and calculates the results. The server generates earthquake and typhoon risk assessment results for Yokohama City and sends them to the terminal. The input is regional information and the output is the risk assessment results.

[0802] Step 3:

[0803] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four needs 3 liters of water per person per day for seven days. It also calculates the amount of specific medications needed for diabetics. The server lists the calculation results and sends them to the terminal. The input is family composition and physical information, and the output is a list of the necessary supplies.

[0804] Step 4:

[0805] The server uses similar user data to suggest recommended stockpiles. The server uses a machine learning model to analyze stockpiles data from users with similar family structures in the same area and lists additional recommended stockpiles. Items such as "cooling sheets" and "portable generators" may be included in the list. The input is existing user data, and the output is a list of recommended stockpiles.

[0806] Step 5:

[0807] The user inputs the stockpiled items and their expiration dates. For example, they input information such as "I have 15 bottles of water in stock, and the expiration date is October 2024." The device sends this data to the server. The server stores it in a database, periodically checks the expiration date, and generates an alert when the expiration date approaches and sends it to the device. The input is stockpiled item information and expiration date, and the output is alert information.

[0808] Step 6:

[0809] The system uses an emotion engine to recognize the user's emotional state. It uses a camera and microphone to collect facial expressions and tone of voice while the user is using the application, and detects anxiety and stress. The emotion engine then sends the analysis results to a server. The input is facial expressions and tone of voice, and the output is an evaluation of the user's emotional state.

[0810] Step 7:

[0811] The emotion engine analyzes the user's emotional state and adjusts recommended stockpiles as needed. If anxiety or stress is high, it suggests stockpiles with a relaxing effect (such as aroma oils or stress relief products). If the emotional state is positive, it reinforces reminders to regularly manage and update stockpiles. The input is the emotion analysis results, and the output is recommended stockpiles or reminder information.

[0812] Example prompt sentence:

[0813] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's region, family composition, and physical information, and then suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state. Use "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[0814] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0815] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0816] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0817] [Third embodiment]

[0818] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0819] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0820] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0821] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0822] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0823] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0824] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0825] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0826] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0827] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0828] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0829] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0830] The present invention relates to a system for proposing and managing optimal disaster preparedness supplies based on a user's area information, family structure, and physical information.

[0831] System Overview

[0832] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies to stockpile accordingly. It also learns from the stockpile data of similar users and presents recommended emergency supplies. It also manages the expiration dates of existing emergency supplies and provides necessary alerts to the user.

[0833] Program processing flow

[0834] 1. User information registration

[0835] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[0836] 2. Disaster risk assessment

[0837] The server refers to a hazard map based on regional information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area. In the case of Yokohama, the risk of earthquakes and typhoons is judged to be high. Based on this information, the server performs a disaster risk assessment and sends the results back to the terminal.

[0838] 3. Calculate the necessary supplies

[0839] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four (two adults and two children) needs 3 liters of water per person per day for seven days, for a total of 84 liters. It also determines that diabetics need certain medications. The results are displayed to the user via their device.

[0840] 4. Generating Recommendations

[0841] The server learns similar user data and suggests additional stockpiles based on "items stockpiled by other users." For example, it presents information about "cooling sheets" or "portable generators" that other users with similar conditions have.

[0842] 5. Emergency supplies management function

[0843] The user inputs the items they have stockpiled and their expiration dates, and the device sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the device, allowing the user to update their stockpiles appropriately.

[0844] Specific examples

[0845] For example, if the user is a family of four (two adults, two children, one of whom is a diabetic) living in Yokohama, Kanagawa Prefecture, the system operates as follows.

[0846] 1. User information registration

[0847] The user enters the local information "Yokohama City, Kanagawa Prefecture."

[0848] Family composition: 2 adults, 2 children, 1 diabetic.

[0849] Physical information: One of the adults is diabetic and requires medication.

[0850] 2. Disaster risk assessment

[0851] The server references the hazard map based on local information.

[0852] Assessing earthquake and typhoon risks in Yokohama City.

[0853] 3. Calculate the necessary supplies

[0854] Water required: 84 litres.

[0855] Suggesting specific medications for diabetics.

[0856] Generate a list of other emergency supplies (flashlights, radios, etc.).

[0857] 4. Generating Recommendations

[0858] The server learns similar user data from other users in the same area.

[0859] Additional recommended stockpiles include cooling sheets and portable generators.

[0860] 5. Emergency supplies management function

[0861] The user inputs the stockpile items and their expiration dates.

[0862] The server generates an alert when the expiration date approaches and notifies the user.

[0863] This system allows users to quickly and effectively stockpile disaster supplies tailored to their individual household circumstances, ensuring they are adequately prepared in the event of an emergency.

[0864] The processing flow will be explained below.

[0865] Step 1:

[0866] The user opens the application and enters local information, family composition information, and physical information. For example, the local information is "Yokohama, Kanagawa Prefecture," the family composition is "2 adults, 2 children," and the physical information is "1 adult has diabetes." The device receives this data and sends it to the server.

[0867] Step 2:

[0868] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[0869] Step 3:

[0870] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day is needed for seven days, for a total of 84 liters. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[0871] Step 4:

[0872] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[0873] Step 5:

[0874] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[0875] Step 6:

[0876] The server receives stockpile data, stores it in a database, and manages expiration dates. The server periodically checks the data and generates an alert when the expiration date approaches.

[0877] Step 7:

[0878] The server generates an alert for stockpiled items that are approaching their expiration date and sends it to the terminal. The terminal notifies the user of the alert and prompts the user to update the stockpiled items.

[0879] This process allows users to easily manage and secure disaster preparedness stockpiles that are optimized for their own household situation.

[0880] Example 1

[0881] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0882] In recent years, with the increase in natural disasters, it has become increasingly important for each household to stockpile disaster preparedness supplies appropriately. However, it is difficult to select the appropriate stockpile items based on family composition and local risks, and managing stockpiles is also complicated, so many households are not adequately prepared. To solve this problem, a system is needed that can automatically suggest and manage the optimal disaster preparedness supplies according to the user's specific situation.

[0883] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0884] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information input to the central processing unit, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, and means for providing the user with an alert when the expiration date is approaching. This enables the user to easily prepare and appropriately manage the optimal disaster preparedness supplies based on their own family composition and regional risks.

[0885] "User" refers to an individual or household who uses the system to input local information, family composition information, and physical information.

[0886] "Region information" refers to information related to the geographic area in which a user resides.

[0887] "Family composition information" refers to information about the number and relationships of people living in a user's household (such as adults, children, and those with certain health conditions).

[0888] "Physical Information" refers to information relating to the health status or specific medical needs of a user or their family members.

[0889] "Central processing unit" refers to a computer or server that performs calculations and analysis based on information input by a user.

[0890] "Disaster risk" refers to information assessing the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in a particular area.

[0891] "Stockpiles" refer to food, medicine, disaster prevention goods, etc. stored in the home in preparation for disasters.

[0892] "Expiration date" refers to the date by which stockpiled goods can be safely used.

[0893] "Alert" refers to a warning that notifies the user when an expiration date is approaching or other important notices are issued.

[0894] This invention relates to a system that proposes and manages optimal disaster preparedness supplies based on a user's area information, family structure, and physical information. The system for implementing this invention has various functions that allow a user to input area information, family structure information, and physical information and, based on that, to carry out appropriate disaster preparedness stockpiling.

[0895] 1. User information registration

[0896] The user enters local information, family composition information, and physical information through the application. For example, if the user enters "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes," the device sends this data to the server. The server stores the received information in a database. This step registers the user's basic information in the system.

[0897] 2. Disaster risk assessment

[0898] Based on the regional information, the server uses the central processing unit to refer to the hazard map database. The server evaluates the risk of earthquakes, typhoons, floods, etc. for each region and sends the results back to the terminal. For example, Yokohama City may be judged to be at particularly high risk of earthquakes and typhoons, and this information will be provided to the user.

[0899] 3. Calculate the necessary supplies

[0900] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on the user's family composition and physical information. For example, for a family of four (two adults and two children), it calculates that each person needs 3 liters of water per day for seven days, for a total of 84 liters. It also determines that diabetics need specific medications. The results are displayed to the user from the server via their device.

[0901] 4. Generating Recommendations

[0902] The server analyzes similar user data using a machine learning model and generates additional recommended stockpiles based on the items stockpiled by other users. For example, cooling sheets or portable generators are suggested. This information is then sent to the user via their device.

[0903] 5. Emergency supplies management function

[0904] Users input the items they have stockpiled and their expiration dates, and the terminal sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the terminal. This allows users to properly manage expiration dates.

[0905] Specific examples

[0906] For example, if the user is a family of four (two adults, two children, one with diabetes) living in Yokohama, Kanagawa Prefecture, the system operates as follows:

[0907] 1. The user enters the following information into the application: "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[0908] 2. The server references hazard map data based on regional information and sends the results of its assessment of earthquake and typhoon risk in Yokohama City to the terminal.

[0909] 3. Calculate the amount of water needed (84 liters) or the specific medications needed for a diabetic patient, and send the calculations to the terminal.

[0910] 4. The server learns similar user data and sends a list of recommended stockpiles, such as "cooling sheets" and "portable generators," to the device.

[0911] 5. The user inputs the current stockpile items and their expiration dates, and the server generates an alert when the expiration date approaches, and the terminal notifies the user.

[0912] This system allows users to quickly and effectively stockpile supplies for disasters, and also allows them to properly manage expiration dates and quantities.

[0913] Prompt Sentence Examples

[0914] "Please generate a list of disaster preparedness supplies for a household with two adults, two children, and one diabetic living in Yokohama City, Kanagawa Prefecture. I would also like to set up alerts for when the expiration date is approaching. Please provide detailed information on the suggested supplies and how to manage them."

[0915] The present invention provides a system for proposing and managing optimal disaster preparedness supplies according to the needs of individual households and regional risks, thereby supporting users in continuing to live safely.

[0916] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0917] Step 1: Register user information

[0918] Input: The user inputs regional information, family composition information, and physical information through the application interface.

[0919] Specific operation: The user enters information such as "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[0920] Data processing: The terminal formats these input information and sends them as data packets to the server.

[0921] Output: Data packets sent from the device to the server.

[0922] Step 2: Save user information

[0923] Input: The server receives a data packet of user information sent from the terminal.

[0924] Specific operation: The server analyzes the data packet and extracts regional information (Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one person is a diabetic).

[0925] Data processing: The extracted information is stored in a database and a user ID is generated and associated with it.

[0926] Output: User information stored in the database and the generated user ID.

[0927] Step 3: Disaster risk assessment

[0928] Input: The server uses the stored locality information (Yokohama, Kanagawa Prefecture).

[0929] Specific operation: The server queries the hazard map API and obtains the corresponding hazard data (earthquake, typhoon risk, etc.).

[0930] Data processing: Analyze the acquired hazard data and run a risk assessment algorithm to assess the disaster risk of the area, for example, calculating an earthquake risk rate of 70% and a typhoon risk rate of 60%.

[0931] Output: The disaster risk assessment results are sent from the server to the terminal and displayed to the user.

[0932] Step 4: Calculate your supply needs

[0933] Input: The server bases the user's family information (2 adults, 2 children) and physical information (1 diabetic).

[0934] Specific behavior: Calculates the necessary stockpiles according to the criteria. For example, the water requirement is calculated as 3 liters per person per day for 7 days, which is 84 liters for a family of four. Also, a specific medication list is generated for diabetics.

[0935] Data processing: Generate a list of necessary supplies and their quantities, and organize the data.

[0936] Output: The generated stockpile list is sent from the server to the terminal and displayed to the user.

[0937] Step 5: Generate recommendations

[0938] Input: The server performs analysis based on similar user data and a generated AI model.

[0939] Specific operation: The server analyzes similar area and family structure data using a generative AI model to learn from data on stockpiles held by other users. For example, it checks whether recommended stockpiles of items such as "cooling sheets" and "portable generators" are common.

[0940] Data processing: Generate a list of additional recommended supplies and organize the data.

[0941] Output: The generated list of recommended stockpiles is sent from the server to the terminal and displayed to the user.

[0942] Step 6: Stockpile management function

[0943] Input: The user inputs the items they have stockpiled and their expiration dates into the application.

[0944] Specific operation: The user inputs the existing stockpile items (e.g., water, medicine, etc.) and their expiration dates. The terminal sends this as a data packet to the server.

[0945] Data processing: The server stores the received stockpile information and expiration date in a database and checks it periodically.

[0946] Output: When the expiration date is approaching, an alert is generated and sent from the server to the terminal to notify the user.

[0947] By using the above specific processing steps, this system can provide users with the function of suggesting and managing optimal disaster preparedness supplies.

[0948] (Application example 1)

[0949] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0950] In managing disaster preparedness supplies, there are issues with the lack of optimal product recommendations and expiration date management that take into account each user's regional characteristics, family structure, and health status. Furthermore, there is a lack of systems that can suggest recommended stockpiles based on similar user data, and there is also a lack of systems that can provide appropriate alerts when stockpiles are approaching their expiration dates.

[0951] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0952] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, means for alerting the user about stockpiled items approaching their expiration dates, and means for inputting and managing user information using a smartphone application, thereby enabling the proposal and management of disaster preparedness supplies optimal for each individual user.

[0953] "User area information" is information for identifying the area in which the user resides.

[0954] "Family composition information" is information that indicates the number of people in the user's household and their relationships.

[0955] "Physical information" is information that indicates the health status or specific medical needs of the user or their family members.

[0956] The "means for assessing disaster risk" is a means for calculating and assessing the risk of disasters such as earthquakes, typhoons, and floods based on the user's local information.

[0957] "Means for calculating the types and quantities of disaster preparedness supplies required" refers to means for calculating the types and quantities of disaster preparedness supplies required based on disaster risk, family composition, and physical information.

[0958] The "means for proposing recommended stockpiles" is a means for learning data of similar users and recommending optimal stockpiles to the user.

[0959] The "means for managing items stockpiled by the user and their expiration dates" refers to a means for registering stockpiled items and their expiration dates entered by the user in a database and managing them.

[0960] The "means for providing an alert about stockpiled goods approaching their expiration date" is a means for notifying the user when the expiration date of a stockpiled item is approaching.

[0961] A "smartphone application" is software that runs on a portable electronic device and allows users to input and manage information and generate alerts.

[0962] To implement this invention, it is necessary to build a system that inputs the user's area information, family composition information, and physical information and proposes and manages disaster preparedness supplies. This system includes the following main components, hardware, and software:

[0963] System Overview

[0964] The server evaluates disaster risk based on the area information entered by the user, calculates the type and quantity of disaster preparedness supplies needed, and has the function of learning from data on similar users to suggest recommended stockpiles. It also alerts users when stockpiles are nearing their expiration date.

[0965] The user terminal (such as a smartphone) provides an application for inputting user information (regional information, family composition information, physical information) and communicating with the server. This application also allows management of stockpiled supplies and receiving alerts.

[0966] Hardware and software used

[0967] Programming language: Python

[0968] Database: MongoDB or SQLite (for data management)

[0969] API: Google Maps API or OpenStreetMap API for disaster risk assessment

[0970] Cloud services: AWS Lambda (serverless computing), Amazon S3 (data storage)

[0971] Processing flow example

[0972] 1. User information registration

[0973] A user opens a smartphone application and enters information about their area, family structure, and physical condition. For example, they might enter information like "I live in Tokyo, have one adult and one child, and I have high blood pressure."

[0974] The application sends this information to the server.

[0975] 2. Disaster risk assessment

[0976] The server uses the Google Maps API and OpenStreetMap API to assess the risk of earthquakes and typhoons based on local information. For example, it may assess that "Tokyo has a high earthquake risk."

[0977] 3. Calculating the necessary disaster preparedness supplies

[0978] The server calculates the type and amount of supplies needed based on the user's family composition and health information. For example, it calculates "42 liters of water and a one-month supply of high blood pressure medication."

[0979] 4. Recommended stockpiles

[0980] The server learns data from similar users and further recommends items to stock up on, such as a portable generator and cooling sheets.

[0981] 5. Emergency supplies management function

[0982] Users use the application to register their stockpiles and their expiration dates. The server manages this information and generates an alert to notify the user when the expiration date approaches.

[0983] Examples

[0984] For example, if a user enters information such as "a household of one adult and one child living in Tokyo, where the adult has high blood pressure," the system will operate as follows:

[0985] 1. User information registration:

[0986] The user inputs the region information "Tokyo", family composition "1 adult, 1 child", and health information "adult has high blood pressure".

[0987] 2. Disaster risk assessment:

[0988] The server uses the Google Maps API or OpenStreetMap API to assess that "Tokyo is at high risk of earthquakes."

[0989] 3. Calculate the necessary supplies:

[0990] The amount of water needed is 42 liters. It is calculated that a one-month supply of high blood pressure medication is needed.

[0991] 4. Recommended stockpile items:

[0992] The server will suggest additional recommended supplies, such as a "portable generator" or "cooling sheets."

[0993] 5. Expiration date management and alert generation:

[0994] When the expiration date of the stockpiled items registered by the user approaches, an alert will be sent via the application.

[0995] Prompt Sentence Examples

[0996] An example of an input prompt for the generative AI model to be used next:

[0997] User Information:

[0998] Region: Tokyo

[0999] Family composition: 1 adult, 1 child

[1000] Health condition: High blood pressure in adults

[1001] Suggested supplies to stockpile:

[1002] Please suggest the most appropriate disaster preparedness supplies based on the disaster risk assessment results.

[1003] Learn from data of similar users and suggest additional recommended stockpiles.

[1004] In this way, users can properly manage their disaster preparedness supplies and prepare for emergencies.

[1005] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1006] Step 1:

[1007] Registering user information

[1008] Input: The user enters regional information, family composition information, and physical information into the smartphone application. Example: "Living in Tokyo, one adult, one child, with high blood pressure."

[1009] Data processing: Parse the information entered by the user into JSON format.

[1010] Output: Sends the parsed data to the server.

[1011] Specific behavior: The user enters region information, family composition, and health information into the application's input form and taps the "Submit" button. The application converts the entered data into JSON format and sends it as a POST request to the server's API endpoint.

[1012] Step 2:

[1013] Disaster risk assessment

[1014] Input: The locale information received by the server in step 1.

[1015] Data calculation: The server calls the hazard map API (Google Maps API or OpenStreetMap API) based on local information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area.

[1016] Output: Generate disaster risk assessment results and store them in a database.

[1017] Specific operation: The server calls the hazard map API based on regional information and obtains risk data. It processes the data and evaluates earthquake risk as "high," typhoon risk as "medium," etc. The evaluation results are then stored in a database.

[1018] Step 3:

[1019] Calculating necessary disaster preparedness supplies

[1020] Input: Family composition information and physical information received by the server in step 1, and disaster risk assessment results obtained in step 2.

[1021] Data calculation: The server calculates the type and quantity of supplies needed based on the user's family composition and health information using formulas and rules.

[1022] Output: Generate and send data to display the calculation results on the user's terminal.

[1023] Specific operation: The server calculates the necessary supplies (e.g., 42 liters of water, one month's supply of high blood pressure medication) based on the input data, and notifies the user's device (smartphone) of the results.

[1024] Step 4:

[1025] Recommended stockpiles

[1026] Input: The stockpile data calculated by the server in step 3, and stockpile data of similar users in the database.

[1027] Data calculation: The server uses a generative AI model to learn from data of similar users and generate additional stockpile recommendations.

[1028] Output: Send the recommended stockpile list to the user's device.

[1029] How it works: The server uses the generative AI model to analyze data from similar users. For example, it generates a list of recommendations for items stockpiled by other users, such as portable generators or cooling sheets, and presents this to the user's device.

[1030] Step 5:

[1031] Stockpile management function

[1032] Input: The user inputs the stockpile items and their expiration dates into the smartphone application.

[1033] Data processing: The input stockpile information and expiration date are converted into JSON format and sent to the server.

[1034] Output: Saved in a database for expiration date management.

[1035] Specific operation: A user registers a stockpile item (e.g., 20 liters of water) and its expiration date (e.g., March 1, 2024) through the application. The application sends this data to the server, which stores it in a database.

[1036] Step 6:

[1037] Expiration date alert generation

[1038] Input: Expiration date information of stockpiled items stored in the database.

[1039] Data calculation: The server compares the current date with the expiration date of each stockpile item and generates an alert if the expiration date is approaching.

[1040] Output: Sends an alert notification to the user's device.

[1041] Specific operation: The server periodically checks expiration dates and generates an alert message for any stockpiled items that are approaching their expiration date, notifying the smartphone application. For example, it sends a message such as, "The expiration date for your water is approaching. Please consume it by March 1, 2024."

[1042] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1043] This invention relates to a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine.

[1044] System Overview

[1045] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies accordingly. It then learns from similar users' emergency stockpiles to suggest recommended emergency supplies, and uses an emotion engine to respond to the user's emotional state. It also manages expiration dates for existing emergency supplies and provides necessary alerts to the user.

[1046] Program processing flow

[1047] 1. User information registration

[1048] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[1049] 2. Disaster risk assessment

[1050] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[1051] 3. Calculate the necessary supplies

[1052] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day for seven days is 84 liters in total. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[1053] 4. Generating Recommendations

[1054] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[1055] 5. Emergency supplies management function

[1056] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[1057] 6. Emotion engine integration

[1058] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety.

[1059] 7. Tailoring recommendations based on emotions

[1060] The emotion engine analyzes the user's emotional state and adjusts recommended supplies as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). In addition, for users in a positive emotional state, it reinforces reminders to regularly manage and update their supplies.

[1061] 8. Expiration date management and alerts

[1062] The server stores expiration dates in a database and periodically checks them. When the expiration date approaches, an alert is generated and sent to the terminal. The terminal notifies the user of this alert and alerts them to update their stockpiles, allowing them to update their stockpiles in a timely manner.

[1063] Specific examples

[1064] Let's take the example of a user who is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture." The user inputs information about the area, family composition, and physical information, and the server performs a disaster risk assessment and calculates the necessary stockpiles. The server also uses an emotion engine to detect the user's anxiety and stress, and suggests stockpiles that have a relaxing effect. Furthermore, the server periodically manages the expiration dates of existing stockpiles and notifies the user via alerts.

[1065] This system allows users to easily manage and secure disaster preparedness supplies that are optimized for their own household situation and emotional state, enabling them to respond appropriately in the event of an emergency.

[1066] The processing flow will be explained below.

[1067] Step 1:

[1068] The user opens the application and enters local information (e.g., Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one adult has diabetes). The device then sends this data to the server.

[1069] Step 2:

[1070] Based on the regional information received, the server refers to the relevant hazard map and calculates the disaster risk of earthquakes, typhoons, floods, etc. in the relevant region. Specifically, the server obtains earthquake and typhoon risk data for Yokohama City and sends the risk assessment results to the terminal.

[1071] Step 3:

[1072] The server calculates the types and quantities of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that 84 liters of water is needed (3 liters per person per day x 7 days). It also includes a list of specific medications for diabetics, and sends the calculation results to the device and displays them to the user.

[1073] Step 4:

[1074] The server learns similar user data and generates recommended stockpiles based on the items stockpiled by other users. For example, "cooling sheets" and "portable generators" are recommended. The recommended results are sent to the device and displayed to the user.

[1075] Step 5:

[1076] The user inputs the items they have already stockpiled and their expiration dates into the terminal, such as "15 bottles of stored water, expiration date October 2024," and the terminal sends the data to the server.

[1077] Step 6:

[1078] The server stores the received information on stockpiled items and their expiration dates in a database, and prepares to alert users to stockpiled items that are approaching their expiration date. For example, it periodically checks for stockpiled items that are within one month of their expiration date.

[1079] Step 7:

[1080] The emotion engine recognizes the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety and stress. For example, if a user's expression becomes grim after viewing disaster information, anxiety is detected.

[1081] Step 8:

[1082] The emotion engine adjusts recommended supplies based on the user's emotional state. For example, if anxiety or stress levels are high, it will suggest adding items with a relaxing effect (aroma oils or stress relief products). The device will display these suggestions to the user.

[1083] Step 9:

[1084] The server periodically checks the expiration dates in the database, generates alerts for stockpiled items that are approaching their expiration date, and sends them to the terminal. The terminal notifies the user of the alert, allowing the user to update their stockpiled items at the appropriate time.

[1085] This detailed process flow allows users to manage disaster preparedness supplies optimized for their home situation and emotional state, and respond quickly and effectively in the event of an emergency.

[1086] Example 2

[1087] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1088] Conventional disaster preparedness stockpile management systems assessed disaster risk and calculated stockpiles based on the user's area information, family composition, and physical information, but lacked functionality to respond to the user's emotional state and health condition. As a result, they were unable to suggest stockpiles appropriate for stressful situations or specific health conditions, making it difficult to provide satisfactory stockpile management. In addition, some systems required manual management of stockpile expiration dates, making efficient management difficult.

[1089] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1090] In this invention, the server integrates an emotion engine for analyzing the user's emotional state and includes means for adjusting recommended stockpiles based on the user's emotional state, means for inputting the user's regional information, and means for inputting the user's family composition information and physical information. This makes it possible to suggest stockpiles with relaxing effects based on the user's emotional state and recommend medicines for specific health conditions. Furthermore, by comprehensively managing the expiration dates of stockpiles and sending alerts when the expiration date is approaching, effective and automated stockpiling management can be achieved.

[1091] "Region information" refers to information relating to the geographical location where the user resides, including the city, town, or village, address, and so on.

[1092] "Family composition information" refers to information about the composition of people in the user's household, including the number of adults and children, their ages, and specific health conditions.

[1093] "Physical information" refers to information about the health status of the user and their family members, including specific illnesses and allergies.

[1094] "Server" refers to a centralized computer system that processes information entered by users and performs calculations for disaster risk assessments and emergency supplies.

[1095] "Disaster risk" refers to the results of an assessment of the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in the area where the user lives, and the resulting impact.

[1096] "Stockpiles" refer to supplies such as food and drink, medicine, and disaster prevention goods that are prepared in advance in preparation for disasters.

[1097] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and respond accordingly.

[1098] "Recommendation" refers to a function that suggests optimal options or products based on a user's past behavior and data.

[1099] "Expiration date" refers to the date by which stockpiled goods can be consumed or used, and means that quality and safety can no longer be guaranteed after this date.

[1100] An "alert" is a warning or reminder that the system sends to the user when a certain condition has been met.

[1101] This invention is a system for supporting disaster preparedness stockpiling management, which proposes and manages optimal stockpiles based on the user's regional information, family composition information, physical information, and emotional state. This system utilizes hardware and software such as a server, terminals, and an emotion engine.

[1102] First, the user uses the device to input local information, family composition information, and physical information. For example, the user might input information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes" into the application. The device then sends this information to the server.

[1103] The server accesses a hazard map database based on local information and evaluates the disaster risk of the area. For example, it calculates the risk of earthquakes and typhoons and produces results such as "Earthquake risk: High" and "Typhoon risk: Medium." This is then sent to the device and displayed to the user.

[1104] The server then uses family composition and physical information to calculate the type and amount of supplies needed. Taking the amount of drinking water needed for two adults and two children, it calculates that 3 liters of water per person per day for seven days, for a total of 84 liters. It also adds medication for diabetics to the list. These calculation results are sent to the device and displayed to the user.

[1105] The server then learns from data on similar users. Based on the data of users with similar family structures in the same area, it analyzes the additional stockpiles it recommends. For example, it creates a list of recommended stockpiles, such as "cooling sheets" and "portable generators," and sends this to the device.

[1106] The user inputs the stockpiled items and their expiration dates. For example, information such as "I have 15 bottles of stockpiled water, and the expiration date is October 2024" is entered into the application, and the device sends this information to the server. The server stores this information in a database and manages the expiration dates. When the expiration date approaches, the server generates an alert and sends it to the device. The device notifies the user of this alert and encourages them to update their stockpiles.

[1107] The emotion engine analyzes the user's facial expressions and tone of voice. When the user is using the application, the device captures the user's face and records their voice. This data is sent to the emotion engine to detect emotions such as anxiety and stress. For example, it can detect a user who becomes anxious after seeing disaster information and suggest items with a relaxing effect, such as aroma oils or stress-relieving products. In addition, for users in a positive emotional state, it can reinforce reminders to regularly manage and update their emergency supplies.

[1108] As a concrete example, let's consider a four-person family (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture. When the user inputs local information, family composition, and physical information, the server performs a disaster risk assessment and calculates the necessary stockpiles. An emotion engine is used to monitor the user's emotional state, detecting anxiety and stress and suggesting appropriate stockpiles. By suggesting medicines according to specific health conditions, users can manage their stockpiles with peace of mind. In addition, alerts are sent as expiration dates approach, allowing them to update their stockpiles in a timely manner.

[1109] An example of a prompt to be input to the generative AI model would be, "Please suggest the optimal disaster preparedness supplies and how to manage them for a family of four (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture."

[1110] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1111] System program processing flow and specific explanation

[1112] Step 1: Register user information

[1113] Input: Regional information, family information, physical information

[1114] Output: User information sent to the server

[1115] 1.1 The user enters regional information, family composition information, and physical information into the application. Specifically, the user enters the following data: "Yokohama City, Kanagawa Prefecture," "2 adults, 2 children," and "1 person has diabetes."

[1116] 1.2 The device sends this information to the server using the HTTPS protocol.

[1117] Step 2: Disaster risk assessment

[1118] Input: Region information

[1119] Output: Disaster risk assessment results

[1120] 2.1 The server accesses the hazard map database based on the received regional information.

[1121] 2.2 The server retrieves disaster risk data such as earthquakes, typhoons, and floods from the hazard map database and runs the risk assessment algorithm.

[1122] 2.3 Earthquake risk and typhoon risk are quantified as "high" or "medium" and the results are sent to the terminal. Specifically, the results include assessments such as "earthquake risk: high" and "typhoon risk: medium."

[1123] Step 3: Calculate your supply needs

[1124] Input: Family composition information, physical information

[1125] Output: Stockpile list and quantities

[1126] 3.1 The server runs an algorithm to calculate the necessary amount of various supplies based on the user's family composition and physical information.

[1127] 3.2 For example, for two adults and two children, each person needs 3 litres of water per day for seven days, for a total of 84 litres. Also include medication for diabetics.

[1128] 3.3 This stockpile list and calculation results are sent to the terminal and displayed to the user.

[1129] Step 4: Generate recommendations

[1130] Input: Similar user data

[1131] Output: Additional recommended supplies list

[1132] 4.1 The server collects similar user data in the same area and analyzes it using machine learning algorithms.

[1133] 4.2 Based on the stockpile item data recommended by similar users, we create a list of additional recommended stockpile items.

[1134] 4.3 For example, items such as "cooling sheets" and "portable generators" are selected as recommended stockpiles, and these are sent to the terminal and suggested to the user.

[1135] Step 5: Stockpile management function

[1136] Input: Information about stockpiled items and expiration dates held by the user

[1137] Output: Emergency stockpile information and expiration date management stored on the server

[1138] 5.1 The user inputs the items and expiration dates of their stockpiles into the application. For example, they input "15 bottles of water, expiration date October 2024."

[1139] 5.2 The terminal sends this information to the server, and the server stores the stockpile information in a database.

[1140] Step 6: Integrating the Emotion Engine

[1141] Input: User's facial expression data, voice tone data

[1142] Output: Emotional state analyzed by the emotion engine

[1143] 6.1 While a user is using an application, the device captures the user's facial expressions with a camera and collects the tone of voice with a microphone.

[1144] 6.2 The device sends this data to the server in real time, and the server analyzes it using an emotion engine to detect an emotional state, for example, "Anxiety state: High."

[1145] Step 7: Adjusting recommendations based on sentiment

[1146] Input: Emotional state analysis results

[1147] Output: Adjusted recommended stockpile list

[1148] 7.1 The server adjusts the recommended stockpile list based on the analysis results of the emotion engine, for example, "Anxiety state: High."

[1149] 7.2 Stock up on relaxing items, such as aroma oils and stress relievers.

[1150] 7.3 The adjusted recommended stockpile list is sent to the terminal and displayed to the user.

[1151] Step 8: Expiration date management and alerts

[1152] Input: Expiration date information in the database

[1153] Output: Alert when expiration date is approaching

[1154] 8.1 The server periodically checks the expiration date information in the database.

[1155] 8.2 When the expiration date approaches, the server generates an alert and sends it to the device.

[1156] 8.3 The device notifies the user of this alert via a push notification, displaying a message such as "Your water bottle expires in October 2024 and requires renewal."

[1157] (Application example 2)

[1158] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1159] In recent years, the frequency of disasters has increased, making the management and recommendation of disaster preparedness supplies increasingly important. However, while conventional disaster preparedness supply management systems can recommend necessary items based on a user's regional information and family composition, they are unable to provide optimal recommendations that take into account the health and emotional state of each individual user. Furthermore, expiration dates of stockpiled supplies are not adequately managed, posing challenges for maintaining the quality of stockpiled supplies. Therefore, the present invention aims to provide a management system that proposes optimal disaster preparedness supplies that take into account the user's individual circumstances and emotional state, and also includes expiration date management.

[1160] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1161] In this invention, the server includes means for inputting the user's regional information, means for inputting the user's family composition information and physical information, means for assessing disaster risk based on the regional information input to the server, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpile data of similar users and proposing recommended stockpile items, means for analyzing the user's emotional state and adjusting the recommended stockpile items, means for managing the items stockpiled by the user and their expiration dates, means for detecting the user's anxiety and stress using an emotion engine, and means for proposing supplies. This makes it possible to propose and manage disaster preparedness supplies optimized for each user's situation.

[1162] "Regional information" is information about the area where the user lives, and is data about the local government, regional characteristics, and the like.

[1163] "Family composition information" is information about the composition of members in the user's household, including data such as the number of people, age groups, and health conditions.

[1164] "Physical information" refers to information about the physical health status of the user and their family members.

[1165] "Disaster risk" refers to the assessment results regarding the predicted probability of occurrence of disasters such as earthquakes, typhoons, and floods in a specific region, as well as the extent of their impact.

[1166] "Disaster preparedness supplies" are items such as food, drink, medical supplies, and daily necessities that are needed in the event of a disaster.

[1167] "Recommended stockpiles" are disaster preparedness stockpiles that are particularly recommended based on the user's situation and data on similar users.

[1168] "Emotional state" refers to the psychological state of the user, and is information relating to emotions such as anxiety, stress, and a sense of security.

[1169] The "emotion engine" is a system that recognizes and evaluates the user's emotional state by analyzing facial expressions, tone of voice, etc.

[1170] The "expiration date" is the end of the period during which the stockpiled goods can be used and the date by which their quality is guaranteed.

[1171] "Supplies" are items that should be stockpiled in addition as needed.

[1172] The present invention is a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine. Specific embodiments of the system are described below.

[1173] Registering user information

[1174] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device (e.g., smartphone or tablet) then sends this data to the server.

[1175] Disaster risk assessment

[1176] The server refers to a hazard map based on regional information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. For example, the server evaluates the earthquake and typhoon risks in Yokohama City and sends the results of the risk evaluation to the terminal. The hardware used is a database server, and the software is a program that implements a risk evaluation algorithm.

[1177] Calculating necessary supplies

[1178] The server calculates the amount of food, drink, and disaster prevention supplies needed based on family composition and physical information. For example, a family of four (two adults and two children) will need 3 liters of water per person per day for seven days, for a total of 84 liters. A list is also generated that includes specific medications for diabetics. The server sends the calculation results to the terminal, which displays them to the user. The software used is a data calculation program written in Python.

[1179] Generating recommendations

[1180] The server takes in similar user data and learns from it. For example, it analyzes recommended additional stockpiles based on stockpiling data from users with similar family structures in the same area. It creates a list of recommended stockpiles, such as "cooling sheets" or "portable generators," and sends the results to the device. A machine learning model could be used.

[1181] Stockpile management function

[1182] The user inputs the items they have stockpiled and their expiration dates. For example, the user inputs information such as "I have stockpiled 15 bottles of water, the expiration date of which is October 2024," and the device sends this data to the server. The server then periodically checks the expiration dates and generates an alert when the expiration date approaches. This alert is sent to the device and notifies the user. The software used is a database and alert system.

[1183] Emotion engine integration

[1184] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety. This is done using an emotion analysis engine (API) and the camera and microphone of the smartphone or tablet.

[1185] Tailoring recommendations based on sentiment

[1186] The emotion engine analyzes the user's emotional state and adjusts the recommended items as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). For users in a positive emotional state, it reinforces reminders to regularly manage and update their inventory. The program implements logic to list recommended items based on the results of emotion analysis.

[1187] Specific examples

[1188] If the user is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture," all of the above processes will be carried out, and a list of necessary stockpiles, expiration date alerts, and emotion-based recommendations will be provided.

[1189] Prompt Sentence Examples

[1190] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's area information, family composition, and physical information, and suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state.

[1191] Please use "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[1192] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1193] Step 1:

[1194] The user enters regional information, family composition information, and physical information. The user opens the application and enters information such as "A family of two adults and two children living in Yokohama City, Kanagawa Prefecture, one of whom has diabetes." The device sends this data to the server. The input data is sent in JSON format and is analyzed by the server.

[1195] Step 2:

[1196] The server refers to a hazard map based on regional information and assesses the disaster risk of the relevant region. The server uses a disaster risk assessment algorithm to assess the risks of earthquakes, typhoons, floods, etc. and calculates the results. The server generates earthquake and typhoon risk assessment results for Yokohama City and sends them to the terminal. The input is regional information and the output is the risk assessment results.

[1197] Step 3:

[1198] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four needs 3 liters of water per person per day for seven days. It also calculates the amount of specific medications needed for diabetics. The server lists the calculation results and sends them to the terminal. The input is family composition and physical information, and the output is a list of the necessary supplies.

[1199] Step 4:

[1200] The server uses similar user data to suggest recommended stockpiles. The server uses a machine learning model to analyze stockpiles data from users with similar family structures in the same area and lists additional recommended stockpiles. Items such as "cooling sheets" and "portable generators" may be included in the list. The input is existing user data, and the output is a list of recommended stockpiles.

[1201] Step 5:

[1202] The user inputs the stockpiled items and their expiration dates. For example, they input information such as "I have 15 bottles of water in stock, and the expiration date is October 2024." The device sends this data to the server. The server stores it in a database, periodically checks the expiration date, and generates an alert when the expiration date approaches and sends it to the device. The input is stockpiled item information and expiration date, and the output is alert information.

[1203] Step 6:

[1204] The system uses an emotion engine to recognize the user's emotional state. It uses a camera and microphone to collect facial expressions and tone of voice while the user is using the application, and detects anxiety and stress. The emotion engine then sends the analysis results to a server. The input is facial expressions and tone of voice, and the output is an evaluation of the user's emotional state.

[1205] Step 7:

[1206] The emotion engine analyzes the user's emotional state and adjusts recommended stockpiles as needed. If anxiety or stress is high, it suggests stockpiles with a relaxing effect (such as aroma oils or stress relief products). If the emotional state is positive, it reinforces reminders to regularly manage and update stockpiles. The input is the emotion analysis results, and the output is recommended stockpiles or reminder information.

[1207] Example prompt sentence:

[1208] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's region, family composition, and physical information, and then suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state. Use "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[1209] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1210] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1211] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1212] [Fourth embodiment]

[1213] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1214] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1215] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1216] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1217] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1218] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1219] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1220] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1221] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1222] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1223] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1224] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1225] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1226] The present invention relates to a system for proposing and managing optimal disaster preparedness supplies based on a user's area information, family structure, and physical information.

[1227] System Overview

[1228] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies to stockpile accordingly. It also learns from the stockpile data of similar users and presents recommended emergency supplies. It also manages the expiration dates of existing emergency supplies and provides necessary alerts to the user.

[1229] Program processing flow

[1230] 1. User information registration

[1231] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[1232] 2. Disaster risk assessment

[1233] The server refers to a hazard map based on regional information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area. In the case of Yokohama, the risk of earthquakes and typhoons is judged to be high. Based on this information, the server performs a disaster risk assessment and sends the results back to the terminal.

[1234] 3. Calculate the necessary supplies

[1235] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four (two adults and two children) needs 3 liters of water per person per day for seven days, for a total of 84 liters. It also determines that diabetics need certain medications. The results are displayed to the user via their device.

[1236] 4. Generating Recommendations

[1237] The server learns similar user data and suggests additional stockpiles based on "items stockpiled by other users." For example, it presents information about "cooling sheets" or "portable generators" that other users with similar conditions have.

[1238] 5. Emergency supplies management function

[1239] The user inputs the items they have stockpiled and their expiration dates, and the device sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the device, allowing the user to update their stockpiles appropriately.

[1240] Specific examples

[1241] For example, if the user is a family of four (two adults, two children, one of whom is a diabetic) living in Yokohama, Kanagawa Prefecture, the system operates as follows.

[1242] 1. User information registration

[1243] The user enters the local information "Yokohama City, Kanagawa Prefecture."

[1244] Family composition: 2 adults, 2 children, 1 diabetic.

[1245] Physical information: One of the adults is diabetic and requires medication.

[1246] 2. Disaster risk assessment

[1247] The server references the hazard map based on local information.

[1248] Assessing earthquake and typhoon risks in Yokohama City.

[1249] 3. Calculate the necessary supplies

[1250] Water required: 84 litres.

[1251] Suggesting specific medications for diabetics.

[1252] Generate a list of other emergency supplies (flashlights, radios, etc.).

[1253] 4. Generating Recommendations

[1254] The server learns similar user data from other users in the same area.

[1255] Additional recommended stockpiles include cooling sheets and portable generators.

[1256] 5. Emergency supplies management function

[1257] The user inputs the stockpile items and their expiration dates.

[1258] The server generates an alert when the expiration date approaches and notifies the user.

[1259] This system allows users to quickly and effectively stockpile disaster supplies tailored to their individual household circumstances, ensuring they are adequately prepared in the event of an emergency.

[1260] The processing flow will be explained below.

[1261] Step 1:

[1262] The user opens the application and enters local information, family composition information, and physical information. For example, the local information is "Yokohama, Kanagawa Prefecture," the family composition is "2 adults, 2 children," and the physical information is "1 adult has diabetes." The device receives this data and sends it to the server.

[1263] Step 2:

[1264] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[1265] Step 3:

[1266] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day is needed for seven days, for a total of 84 liters. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[1267] Step 4:

[1268] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[1269] Step 5:

[1270] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[1271] Step 6:

[1272] The server receives stockpile data, stores it in a database, and manages expiration dates. The server periodically checks the data and generates an alert when the expiration date approaches.

[1273] Step 7:

[1274] The server generates an alert for stockpiled items that are approaching their expiration date and sends it to the terminal. The terminal notifies the user of the alert and prompts the user to update the stockpiled items.

[1275] This process allows users to easily manage and secure disaster preparedness stockpiles that are optimized for their own household situation.

[1276] Example 1

[1277] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1278] In recent years, with the increase in natural disasters, it has become increasingly important for each household to stockpile disaster preparedness supplies appropriately. However, it is difficult to select the appropriate stockpile items based on family composition and local risks, and managing stockpiles is also complicated, so many households are not adequately prepared. To solve this problem, a system is needed that can automatically suggest and manage the optimal disaster preparedness supplies according to the user's specific situation.

[1279] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1280] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information input to the central processing unit, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, and means for providing the user with an alert when the expiration date is approaching. This enables the user to easily prepare and appropriately manage the optimal disaster preparedness supplies based on their own family composition and regional risks.

[1281] "User" refers to an individual or household who uses the system to input local information, family composition information, and physical information.

[1282] "Region information" refers to information related to the geographic area in which a user resides.

[1283] "Family composition information" refers to information about the number and relationships of people living in a user's household (such as adults, children, and those with certain health conditions).

[1284] "Physical Information" refers to information relating to the health status or specific medical needs of a user or their family members.

[1285] "Central processing unit" refers to a computer or server that performs calculations and analysis based on information input by a user.

[1286] "Disaster risk" refers to information assessing the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in a particular area.

[1287] "Stockpiles" refer to food, medicine, disaster prevention goods, etc. stored in the home in preparation for disasters.

[1288] "Expiration date" refers to the date by which stockpiled goods can be safely used.

[1289] "Alert" refers to a warning that notifies the user when an expiration date is approaching or other important notices are issued.

[1290] This invention relates to a system that proposes and manages optimal disaster preparedness supplies based on a user's area information, family structure, and physical information. The system for implementing this invention has various functions that allow a user to input area information, family structure information, and physical information and, based on that, to carry out appropriate disaster preparedness stockpiling.

[1291] 1. User information registration

[1292] The user enters local information, family composition information, and physical information through the application. For example, if the user enters "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes," the device sends this data to the server. The server stores the received information in a database. This step registers the user's basic information in the system.

[1293] 2. Disaster risk assessment

[1294] Based on the regional information, the server uses the central processing unit to refer to the hazard map database. The server evaluates the risk of earthquakes, typhoons, floods, etc. for each region and sends the results back to the terminal. For example, Yokohama City may be judged to be at particularly high risk of earthquakes and typhoons, and this information will be provided to the user.

[1295] 3. Calculate the necessary supplies

[1296] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on the user's family composition and physical information. For example, for a family of four (two adults and two children), it calculates that each person needs 3 liters of water per day for seven days, for a total of 84 liters. It also determines that diabetics need specific medications. The results are displayed to the user from the server via their device.

[1297] 4. Generating Recommendations

[1298] The server analyzes similar user data using a machine learning model and generates additional recommended stockpiles based on the items stockpiled by other users. For example, cooling sheets or portable generators are suggested. This information is then sent to the user via their device.

[1299] 5. Emergency supplies management function

[1300] Users input the items they have stockpiled and their expiration dates, and the terminal sends this information to the server. When the expiration date approaches, the server generates an alert and notifies the user via the terminal. This allows users to properly manage expiration dates.

[1301] Specific examples

[1302] For example, if the user is a family of four (two adults, two children, one with diabetes) living in Yokohama, Kanagawa Prefecture, the system operates as follows:

[1303] 1. The user enters the following information into the application: "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[1304] 2. The server references hazard map data based on regional information and sends the results of its assessment of earthquake and typhoon risk in Yokohama City to the terminal.

[1305] 3. Calculate the amount of water needed (84 liters) or the specific medications needed for a diabetic patient, and send the calculations to the terminal.

[1306] 4. The server learns similar user data and sends a list of recommended stockpiles, such as "cooling sheets" and "portable generators," to the device.

[1307] 5. The user inputs the current stockpile items and their expiration dates, and the server generates an alert when the expiration date approaches, and the terminal notifies the user.

[1308] This system allows users to quickly and effectively stockpile supplies for disasters, and also allows them to properly manage expiration dates and quantities.

[1309] Prompt Sentence Examples

[1310] "Please generate a list of disaster preparedness supplies for a household with two adults, two children, and one diabetic living in Yokohama City, Kanagawa Prefecture. I would also like to set up alerts for when the expiration date is approaching. Please provide detailed information on the suggested supplies and how to manage them."

[1311] The present invention provides a system for proposing and managing optimal disaster preparedness supplies according to the needs of individual households and regional risks, thereby supporting users in continuing to live safely.

[1312] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1313] Step 1: Register user information

[1314] Input: The user inputs regional information, family composition information, and physical information through the application interface.

[1315] Specific operation: The user enters information such as "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic."

[1316] Data processing: The terminal formats these input information and sends them as data packets to the server.

[1317] Output: Data packets sent from the device to the server.

[1318] Step 2: Save user information

[1319] Input: The server receives a data packet of user information sent from the terminal.

[1320] Specific operation: The server analyzes the data packet and extracts regional information (Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one person is a diabetic).

[1321] Data processing: The extracted information is stored in a database and a user ID is generated and associated with it.

[1322] Output: User information stored in the database and the generated user ID.

[1323] Step 3: Disaster risk assessment

[1324] Input: The server uses the stored locality information (Yokohama, Kanagawa Prefecture).

[1325] Specific operation: The server queries the hazard map API and obtains the corresponding hazard data (earthquake, typhoon risk, etc.).

[1326] Data processing: Analyze the acquired hazard data and run a risk assessment algorithm to assess the disaster risk of the area, for example, calculating an earthquake risk rate of 70% and a typhoon risk rate of 60%.

[1327] Output: The disaster risk assessment results are sent from the server to the terminal and displayed to the user.

[1328] Step 4: Calculate your supply needs

[1329] Input: The server bases the user's family information (2 adults, 2 children) and physical information (1 diabetic).

[1330] Specific behavior: Calculates the necessary stockpiles according to the criteria. For example, the water requirement is calculated as 3 liters per person per day for 7 days, which is 84 liters for a family of four. Also, a specific medication list is generated for diabetics.

[1331] Data processing: Generate a list of necessary supplies and their quantities, and organize the data.

[1332] Output: The generated stockpile list is sent from the server to the terminal and displayed to the user.

[1333] Step 5: Generate recommendations

[1334] Input: The server performs analysis based on similar user data and a generated AI model.

[1335] Specific operation: The server analyzes similar area and family structure data using a generative AI model to learn from data on stockpiles held by other users. For example, it checks whether recommended stockpiles of items such as "cooling sheets" and "portable generators" are common.

[1336] Data processing: Generate a list of additional recommended supplies and organize the data.

[1337] Output: The generated list of recommended stockpiles is sent from the server to the terminal and displayed to the user.

[1338] Step 6: Stockpile management function

[1339] Input: The user inputs the items they have stockpiled and their expiration dates into the application.

[1340] Specific operation: The user inputs the existing stockpile items (e.g., water, medicine, etc.) and their expiration dates. The terminal sends this as a data packet to the server.

[1341] Data processing: The server stores the received stockpile information and expiration date in a database and checks it periodically.

[1342] Output: When the expiration date is approaching, an alert is generated and sent from the server to the terminal to notify the user.

[1343] By using the above specific processing steps, this system can provide users with the function of suggesting and managing optimal disaster preparedness supplies.

[1344] (Application example 1)

[1345] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1346] In managing disaster preparedness supplies, there are issues with the lack of optimal product recommendations and expiration date management that take into account each user's regional characteristics, family structure, and health status. Furthermore, there is a lack of systems that can suggest recommended stockpiles based on similar user data, and there is also a lack of systems that can provide appropriate alerts when stockpiles are approaching their expiration dates.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1348] In this invention, the server includes means for inputting the user's regional information, means for inputting family composition information and physical information, means for assessing disaster risk based on the regional information, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpiled data of similar users and proposing recommended stockpiled items, means for managing the items stockpiled by the user and their expiration dates, means for alerting the user about stockpiled items approaching their expiration dates, and means for inputting and managing user information using a smartphone application, thereby enabling the proposal and management of disaster preparedness supplies optimal for each individual user.

[1349] "User area information" is information for identifying the area in which the user resides.

[1350] "Family composition information" is information that indicates the number of people in the user's household and their relationships.

[1351] "Physical information" is information that indicates the health status or specific medical needs of the user or their family members.

[1352] The "means for assessing disaster risk" is a means for calculating and assessing the risk of disasters such as earthquakes, typhoons, and floods based on the user's local information.

[1353] "Means for calculating the types and quantities of disaster preparedness supplies required" refers to means for calculating the types and quantities of disaster preparedness supplies required based on disaster risk, family composition, and physical information.

[1354] The "means for proposing recommended stockpiles" is a means for learning data of similar users and recommending optimal stockpiles to the user.

[1355] The "means for managing items stockpiled by the user and their expiration dates" refers to a means for registering stockpiled items and their expiration dates entered by the user in a database and managing them.

[1356] The "means for providing an alert about stockpiled goods approaching their expiration date" is a means for notifying the user when the expiration date of a stockpiled item is approaching.

[1357] A "smartphone application" is software that runs on a portable electronic device and allows users to input and manage information and generate alerts.

[1358] To implement this invention, it is necessary to build a system that inputs the user's area information, family composition information, and physical information and proposes and manages disaster preparedness supplies. This system includes the following main components, hardware, and software:

[1359] System Overview

[1360] The server evaluates disaster risk based on the area information entered by the user, calculates the type and quantity of disaster preparedness supplies needed, and has the function of learning from data on similar users to suggest recommended stockpiles. It also alerts users when stockpiles are nearing their expiration date.

[1361] The user terminal (such as a smartphone) provides an application for inputting user information (regional information, family composition information, physical information) and communicating with the server. This application also allows management of stockpiled supplies and receiving alerts.

[1362] Hardware and software used

[1363] Programming language: Python

[1364] Database: MongoDB or SQLite (for data management)

[1365] API: Google Maps API or OpenStreetMap API for disaster risk assessment

[1366] Cloud services: AWS Lambda (serverless computing), Amazon S3 (data storage)

[1367] Processing flow example

[1368] 1. User information registration

[1369] A user opens a smartphone application and enters information about their area, family structure, and physical condition. For example, they might enter information like "I live in Tokyo, have one adult and one child, and I have high blood pressure."

[1370] The application sends this information to the server.

[1371] 2. Disaster risk assessment

[1372] The server uses the Google Maps API and OpenStreetMap API to assess the risk of earthquakes and typhoons based on local information. For example, it may assess that "Tokyo has a high earthquake risk."

[1373] 3. Calculating the necessary disaster preparedness supplies

[1374] The server calculates the type and amount of supplies needed based on the user's family composition and health information. For example, it calculates "42 liters of water and a one-month supply of high blood pressure medication."

[1375] 4. Recommended stockpiles

[1376] The server learns data from similar users and further recommends items to stock up on, such as a portable generator and cooling sheets.

[1377] 5. Emergency supplies management function

[1378] Users use the application to register their stockpiles and their expiration dates. The server manages this information and generates an alert to notify the user when the expiration date approaches.

[1379] Examples

[1380] For example, if a user enters information such as "a household of one adult and one child living in Tokyo, where the adult has high blood pressure," the system will operate as follows:

[1381] 1. User information registration:

[1382] The user inputs the region information "Tokyo", family composition "1 adult, 1 child", and health information "adult has high blood pressure".

[1383] 2. Disaster risk assessment:

[1384] The server uses the Google Maps API or OpenStreetMap API to assess that "Tokyo is at high risk of earthquakes."

[1385] 3. Calculate the necessary supplies:

[1386] The amount of water needed is 42 liters. It is calculated that a one-month supply of high blood pressure medication is needed.

[1387] 4. Recommended stockpile items:

[1388] The server will suggest additional recommended supplies, such as a "portable generator" or "cooling sheets."

[1389] 5. Expiration date management and alert generation:

[1390] When the expiration date of the stockpiled items registered by the user approaches, an alert will be sent via the application.

[1391] Prompt Sentence Examples

[1392] An example of an input prompt for the generative AI model to be used next:

[1393] User Information:

[1394] Region: Tokyo

[1395] Family composition: 1 adult, 1 child

[1396] Health condition: High blood pressure in adults

[1397] Suggested supplies to stockpile:

[1398] Please suggest the most appropriate disaster preparedness supplies based on the disaster risk assessment results.

[1399] Learn from data of similar users and suggest additional recommended stockpiles.

[1400] In this way, users can properly manage their disaster preparedness supplies and prepare for emergencies.

[1401] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1402] Step 1:

[1403] Registering user information

[1404] Input: The user enters regional information, family composition information, and physical information into the smartphone application. Example: "Living in Tokyo, one adult, one child, with high blood pressure."

[1405] Data processing: Parse the information entered by the user into JSON format.

[1406] Output: Sends the parsed data to the server.

[1407] Specific behavior: The user enters region information, family composition, and health information into the application's input form and taps the "Submit" button. The application converts the entered data into JSON format and sends it as a POST request to the server's API endpoint.

[1408] Step 2:

[1409] Disaster risk assessment

[1410] Input: The locale information received by the server in step 1.

[1411] Data calculation: The server calls the hazard map API (Google Maps API or OpenStreetMap API) based on local information and calculates the risk of earthquakes, typhoons, floods, etc. in the relevant area.

[1412] Output: Generate disaster risk assessment results and store them in a database.

[1413] Specific operation: The server calls the hazard map API based on regional information and obtains risk data. It processes the data and evaluates earthquake risk as "high," typhoon risk as "medium," etc. The evaluation results are then stored in a database.

[1414] Step 3:

[1415] Calculating necessary disaster preparedness supplies

[1416] Input: Family composition information and physical information received by the server in step 1, and disaster risk assessment results obtained in step 2.

[1417] Data calculation: The server calculates the type and quantity of supplies needed based on the user's family composition and health information using formulas and rules.

[1418] Output: Generate and send data to display the calculation results on the user's terminal.

[1419] Specific operation: The server calculates the necessary supplies (e.g., 42 liters of water, one month's supply of high blood pressure medication) based on the input data, and notifies the user's device (smartphone) of the results.

[1420] Step 4:

[1421] Recommended stockpiles

[1422] Input: The stockpile data calculated by the server in step 3, and stockpile data of similar users in the database.

[1423] Data calculation: The server uses a generative AI model to learn from data of similar users and generate additional stockpile recommendations.

[1424] Output: Send the recommended stockpile list to the user's device.

[1425] How it works: The server uses the generative AI model to analyze data from similar users. For example, it generates a list of recommendations for items stockpiled by other users, such as portable generators or cooling sheets, and presents this to the user's device.

[1426] Step 5:

[1427] Stockpile management function

[1428] Input: The user inputs the stockpile items and their expiration dates into the smartphone application.

[1429] Data processing: The input stockpile information and expiration date are converted into JSON format and sent to the server.

[1430] Output: Saved in a database for expiration date management.

[1431] Specific operation: A user registers a stockpile item (e.g., 20 liters of water) and its expiration date (e.g., March 1, 2024) through the application. The application sends this data to the server, which stores it in a database.

[1432] Step 6:

[1433] Expiration date alert generation

[1434] Input: Expiration date information of stockpiled items stored in the database.

[1435] Data calculation: The server compares the current date with the expiration date of each stockpile item and generates an alert if the expiration date is approaching.

[1436] Output: Sends an alert notification to the user's device.

[1437] Specific operation: The server periodically checks expiration dates and generates an alert message for any stockpiled items that are approaching their expiration date, notifying the smartphone application. For example, it sends a message such as, "The expiration date for your water is approaching. Please consume it by March 1, 2024."

[1438] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1439] This invention relates to a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine.

[1440] System Overview

[1441] This system first assesses disaster risk based on information input by the user, then calculates the type and quantity of emergency supplies accordingly. It then learns from similar users' emergency stockpiles to suggest recommended emergency supplies, and uses an emotion engine to respond to the user's emotional state. It also manages expiration dates for existing emergency supplies and provides necessary alerts to the user.

[1442] Program processing flow

[1443] 1. User information registration

[1444] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device then sends this data to the server.

[1445] 2. Disaster risk assessment

[1446] The server refers to a hazard map based on local information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. The server evaluates the risk of earthquakes and typhoons in Yokohama City and sends the risk assessment results to the terminal.

[1447] 3. Calculate the necessary supplies

[1448] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, for a family of four (two adults and two children), it calculates that 3 liters of water per person per day for seven days is 84 liters in total. It also generates a list that includes specific medications for diabetics. The server sends the calculation results to the device, which displays them to the user.

[1449] 4. Generating Recommendations

[1450] The server takes in similar user data and learns from it. Based on the stockpile data of users with similar family structures in the same area, the server analyzes the additional stockpile items to recommend. For example, it lists recommended stockpile items such as "cooling sheets" and "portable generators" and sends the results to the device.

[1451] 5. Emergency supplies management function

[1452] The user inputs the items they have stockpiled and their expiration dates. For example, "I have 15 bottles of water stockpiled, and the expiration date is October 2024." The device then sends this data to the server.

[1453] 6. Emotion engine integration

[1454] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety.

[1455] 7. Tailoring recommendations based on emotions

[1456] The emotion engine analyzes the user's emotional state and adjusts recommended supplies as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). In addition, for users in a positive emotional state, it reinforces reminders to regularly manage and update their supplies.

[1457] 8. Expiration date management and alerts

[1458] The server stores expiration dates in a database and periodically checks them. When the expiration date approaches, an alert is generated and sent to the terminal. The terminal notifies the user of this alert and alerts them to update their stockpiles, allowing them to update their stockpiles in a timely manner.

[1459] Specific examples

[1460] Let's take the example of a user who is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture." The user inputs information about the area, family composition, and physical information, and the server performs a disaster risk assessment and calculates the necessary stockpiles. The server also uses an emotion engine to detect the user's anxiety and stress, and suggests stockpiles that have a relaxing effect. Furthermore, the server periodically manages the expiration dates of existing stockpiles and notifies the user via alerts.

[1461] This system allows users to easily manage and secure disaster preparedness supplies that are optimized for their own household situation and emotional state, enabling them to respond appropriately in the event of an emergency.

[1462] The processing flow will be explained below.

[1463] Step 1:

[1464] The user opens the application and enters local information (e.g., Yokohama, Kanagawa Prefecture), family composition information (two adults, two children), and physical information (one adult has diabetes). The device then sends this data to the server.

[1465] Step 2:

[1466] Based on the regional information received, the server refers to the relevant hazard map and calculates the disaster risk of earthquakes, typhoons, floods, etc. in the relevant region. Specifically, the server obtains earthquake and typhoon risk data for Yokohama City and sends the risk assessment results to the terminal.

[1467] Step 3:

[1468] The server calculates the types and quantities of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that 84 liters of water is needed (3 liters per person per day x 7 days). It also includes a list of specific medications for diabetics, and sends the calculation results to the device and displays them to the user.

[1469] Step 4:

[1470] The server learns similar user data and generates recommended stockpiles based on the items stockpiled by other users. For example, "cooling sheets" and "portable generators" are recommended. The recommended results are sent to the device and displayed to the user.

[1471] Step 5:

[1472] The user inputs the items they have already stockpiled and their expiration dates into the terminal, such as "15 bottles of stored water, expiration date October 2024," and the terminal sends the data to the server.

[1473] Step 6:

[1474] The server stores the received information on stockpiled items and their expiration dates in a database, and prepares to alert users to stockpiled items that are approaching their expiration date. For example, it periodically checks for stockpiled items that are within one month of their expiration date.

[1475] Step 7:

[1476] The emotion engine recognizes the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety and stress. For example, if a user's expression becomes grim after viewing disaster information, anxiety is detected.

[1477] Step 8:

[1478] The emotion engine adjusts recommended supplies based on the user's emotional state. For example, if anxiety or stress levels are high, it will suggest adding items with a relaxing effect (aroma oils or stress relief products). The device will display these suggestions to the user.

[1479] Step 9:

[1480] The server periodically checks the expiration dates in the database, generates alerts for stockpiled items that are approaching their expiration date, and sends them to the terminal. The terminal notifies the user of the alert, allowing the user to update their stockpiled items at the appropriate time.

[1481] This detailed process flow allows users to manage disaster preparedness supplies optimized for their home situation and emotional state, and respond quickly and effectively in the event of an emergency.

[1482] Example 2

[1483] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1484] Conventional disaster preparedness stockpile management systems assessed disaster risk and calculated stockpiles based on the user's area information, family composition, and physical information, but lacked functionality to respond to the user's emotional state and health condition. As a result, they were unable to suggest stockpiles appropriate for stressful situations or specific health conditions, making it difficult to provide satisfactory stockpile management. In addition, some systems required manual management of stockpile expiration dates, making efficient management difficult.

[1485] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1486] In this invention, the server integrates an emotion engine for analyzing the user's emotional state and includes means for adjusting recommended stockpiles based on the user's emotional state, means for inputting the user's regional information, and means for inputting the user's family composition information and physical information. This makes it possible to suggest stockpiles with relaxing effects based on the user's emotional state and recommend medicines for specific health conditions. Furthermore, by comprehensively managing the expiration dates of stockpiles and sending alerts when the expiration date is approaching, effective and automated stockpiling management can be achieved.

[1487] "Region information" refers to information relating to the geographical location where the user resides, including the city, town, or village, address, and so on.

[1488] "Family composition information" refers to information about the composition of people in the user's household, including the number of adults and children, their ages, and specific health conditions.

[1489] "Physical information" refers to information about the health status of the user and their family members, including specific illnesses and allergies.

[1490] "Server" refers to a centralized computer system that processes information entered by users and performs calculations for disaster risk assessments and emergency supplies.

[1491] "Disaster risk" refers to the results of an assessment of the likelihood of natural disasters such as earthquakes, typhoons, and floods occurring in the area where the user lives, and the resulting impact.

[1492] "Stockpiles" refer to supplies such as food and drink, medicine, and disaster prevention goods that are prepared in advance in preparation for disasters.

[1493] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and respond accordingly.

[1494] "Recommendation" refers to a function that suggests optimal options or products based on a user's past behavior and data.

[1495] "Expiration date" refers to the date by which stockpiled goods can be consumed or used, and means that quality and safety can no longer be guaranteed after this date.

[1496] An "alert" is a warning or reminder that the system sends to the user when a certain condition has been met.

[1497] This invention is a system for supporting disaster preparedness stockpiling management, which proposes and manages optimal stockpiles based on the user's regional information, family composition information, physical information, and emotional state. This system utilizes hardware and software such as a server, terminals, and an emotion engine.

[1498] First, the user uses the device to input local information, family composition information, and physical information. For example, the user might input information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes" into the application. The device then sends this information to the server.

[1499] The server accesses a hazard map database based on local information and evaluates the disaster risk of the area. For example, it calculates the risk of earthquakes and typhoons and produces results such as "Earthquake risk: High" and "Typhoon risk: Medium." This is then sent to the device and displayed to the user.

[1500] The server then uses family composition and physical information to calculate the type and amount of supplies needed. Taking the amount of drinking water needed for two adults and two children, it calculates that 3 liters of water per person per day for seven days, for a total of 84 liters. It also adds medication for diabetics to the list. These calculation results are sent to the device and displayed to the user.

[1501] The server then learns from data on similar users. Based on the data of users with similar family structures in the same area, it analyzes the additional stockpiles it recommends. For example, it creates a list of recommended stockpiles, such as "cooling sheets" and "portable generators," and sends this to the device.

[1502] The user inputs the stockpiled items and their expiration dates. For example, information such as "I have 15 bottles of stockpiled water, and the expiration date is October 2024" is entered into the application, and the device sends this information to the server. The server stores this information in a database and manages the expiration dates. When the expiration date approaches, the server generates an alert and sends it to the device. The device notifies the user of this alert and encourages them to update their stockpiles.

[1503] The emotion engine analyzes the user's facial expressions and tone of voice. When the user is using the application, the device captures the user's face and records their voice. This data is sent to the emotion engine to detect emotions such as anxiety and stress. For example, it can detect a user who becomes anxious after seeing disaster information and suggest items with a relaxing effect, such as aroma oils or stress-relieving products. In addition, for users in a positive emotional state, it can reinforce reminders to regularly manage and update their emergency supplies.

[1504] As a concrete example, let's consider a four-person family (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture. When the user inputs local information, family composition, and physical information, the server performs a disaster risk assessment and calculates the necessary stockpiles. An emotion engine is used to monitor the user's emotional state, detecting anxiety and stress and suggesting appropriate stockpiles. By suggesting medicines according to specific health conditions, users can manage their stockpiles with peace of mind. In addition, alerts are sent as expiration dates approach, allowing them to update their stockpiles in a timely manner.

[1505] An example of a prompt to be input to the generative AI model would be, "Please suggest the optimal disaster preparedness supplies and how to manage them for a family of four (two adults, two children, one with diabetes) living in Yokohama City, Kanagawa Prefecture."

[1506] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1507] System program processing flow and specific explanation

[1508] Step 1: Register user information

[1509] Input: Regional information, family information, physical information

[1510] Output: User information sent to the server

[1511] 1.1 The user enters regional information, family composition information, and physical information into the application. Specifically, the user enters the following data: "Yokohama City, Kanagawa Prefecture," "2 adults, 2 children," and "1 person has diabetes."

[1512] 1.2 The device sends this information to the server using the HTTPS protocol.

[1513] Step 2: Disaster risk assessment

[1514] Input: Region information

[1515] Output: Disaster risk assessment results

[1516] 2.1 The server accesses the hazard map database based on the received regional information.

[1517] 2.2 The server retrieves disaster risk data such as earthquakes, typhoons, and floods from the hazard map database and runs the risk assessment algorithm.

[1518] 2.3 Earthquake risk and typhoon risk are quantified as "high" or "medium" and the results are sent to the terminal. Specifically, the results include assessments such as "earthquake risk: high" and "typhoon risk: medium."

[1519] Step 3: Calculate your supply needs

[1520] Input: Family composition information, physical information

[1521] Output: Stockpile list and quantities

[1522] 3.1 The server runs an algorithm to calculate the necessary amount of various supplies based on the user's family composition and physical information.

[1523] 3.2 For example, for two adults and two children, each person needs 3 litres of water per day for seven days, for a total of 84 litres. Also include medication for diabetics.

[1524] 3.3 This stockpile list and calculation results are sent to the terminal and displayed to the user.

[1525] Step 4: Generate recommendations

[1526] Input: Similar user data

[1527] Output: Additional recommended supplies list

[1528] 4.1 The server collects similar user data in the same area and analyzes it using machine learning algorithms.

[1529] 4.2 Based on the stockpile item data recommended by similar users, we create a list of additional recommended stockpile items.

[1530] 4.3 For example, items such as "cooling sheets" and "portable generators" are selected as recommended stockpiles, and these are sent to the terminal and suggested to the user.

[1531] Step 5: Stockpile management function

[1532] Input: Information about stockpiled items and expiration dates held by the user

[1533] Output: Emergency stockpile information and expiration date management stored on the server

[1534] 5.1 The user inputs the items and expiration dates of their stockpiles into the application. For example, they input "15 bottles of water, expiration date October 2024."

[1535] 5.2 The terminal sends this information to the server, and the server stores the stockpile information in a database.

[1536] Step 6: Integrating the Emotion Engine

[1537] Input: User's facial expression data, voice tone data

[1538] Output: Emotional state analyzed by the emotion engine

[1539] 6.1 While a user is using an application, the device captures the user's facial expressions with a camera and collects the tone of voice with a microphone.

[1540] 6.2 The device sends this data to the server in real time, and the server analyzes it using an emotion engine to detect an emotional state, for example, "Anxiety state: High."

[1541] Step 7: Adjusting recommendations based on sentiment

[1542] Input: Emotional state analysis results

[1543] Output: Adjusted recommended stockpile list

[1544] 7.1 The server adjusts the recommended stockpile list based on the analysis results of the emotion engine, for example, "Anxiety state: High."

[1545] 7.2 Stock up on relaxing items, such as aroma oils and stress relievers.

[1546] 7.3 The adjusted recommended stockpile list is sent to the terminal and displayed to the user.

[1547] Step 8: Expiration date management and alerts

[1548] Input: Expiration date information in the database

[1549] Output: Alert when expiration date is approaching

[1550] 8.1 The server periodically checks the expiration date information in the database.

[1551] 8.2 When the expiration date approaches, the server generates an alert and sends it to the device.

[1552] 8.3 The device notifies the user of this alert via a push notification, displaying a message such as "Your water bottle expires in October 2024 and requires renewal."

[1553] (Application example 2)

[1554] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1555] In recent years, the frequency of disasters has increased, making the management and recommendation of disaster preparedness supplies increasingly important. However, while conventional disaster preparedness supply management systems can recommend necessary items based on a user's regional information and family composition, they are unable to provide optimal recommendations that take into account the health and emotional state of each individual user. Furthermore, expiration dates of stockpiled supplies are not adequately managed, posing challenges for maintaining the quality of stockpiled supplies. Therefore, the present invention aims to provide a management system that proposes optimal disaster preparedness supplies that take into account the user's individual circumstances and emotional state, and also includes expiration date management.

[1556] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1557] In this invention, the server includes means for inputting the user's regional information, means for inputting the user's family composition information and physical information, means for assessing disaster risk based on the regional information input to the server, means for calculating the type and quantity of disaster preparedness supplies needed based on the disaster risk, means for learning stockpile data of similar users and proposing recommended stockpile items, means for analyzing the user's emotional state and adjusting the recommended stockpile items, means for managing the items stockpiled by the user and their expiration dates, means for detecting the user's anxiety and stress using an emotion engine, and means for proposing supplies. This makes it possible to propose and manage disaster preparedness supplies optimized for each user's situation.

[1558] "Regional information" is information about the area where the user lives, and is data about the local government, regional characteristics, and the like.

[1559] "Family composition information" is information about the composition of members in the user's household, including data such as the number of people, age groups, and health conditions.

[1560] "Physical information" refers to information about the physical health status of the user and their family members.

[1561] "Disaster risk" refers to the assessment results regarding the predicted probability of occurrence of disasters such as earthquakes, typhoons, and floods in a specific region, as well as the extent of their impact.

[1562] "Disaster preparedness supplies" are items such as food, drink, medical supplies, and daily necessities that are needed in the event of a disaster.

[1563] "Recommended stockpiles" are disaster preparedness stockpiles that are particularly recommended based on the user's situation and data on similar users.

[1564] "Emotional state" refers to the psychological state of the user, and is information relating to emotions such as anxiety, stress, and a sense of security.

[1565] The "emotion engine" is a system that recognizes and evaluates the user's emotional state by analyzing facial expressions, tone of voice, etc.

[1566] The "expiration date" is the end of the period during which the stockpiled goods can be used and the date by which their quality is guaranteed.

[1567] "Supplies" are items that should be stockpiled in addition as needed.

[1568] The present invention is a system that proposes and manages optimal disaster preparedness supplies by combining a user's regional information, family structure, physical information, and an emotion engine. Specific embodiments of the system are described below.

[1569] Registering user information

[1570] The user enters regional information, family composition information, and physical information. For example, the user opens the application and enters information such as "I live in Yokohama City, Kanagawa Prefecture, and my family consists of two adults and two children, one of whom has diabetes." The device (e.g., smartphone or tablet) then sends this data to the server.

[1571] Disaster risk assessment

[1572] The server refers to a hazard map based on regional information and calculates the risk of disasters such as earthquakes, typhoons, and floods in the relevant area. For example, the server evaluates the earthquake and typhoon risks in Yokohama City and sends the results of the risk evaluation to the terminal. The hardware used is a database server, and the software is a program that implements a risk evaluation algorithm.

[1573] Calculating necessary supplies

[1574] The server calculates the amount of food, drink, and disaster prevention supplies needed based on family composition and physical information. For example, a family of four (two adults and two children) will need 3 liters of water per person per day for seven days, for a total of 84 liters. A list is also generated that includes specific medications for diabetics. The server sends the calculation results to the terminal, which displays them to the user. The software used is a data calculation program written in Python.

[1575] Generating recommendations

[1576] The server takes in similar user data and learns from it. For example, it analyzes recommended additional stockpiles based on stockpiling data from users with similar family structures in the same area. It creates a list of recommended stockpiles, such as "cooling sheets" or "portable generators," and sends the results to the device. A machine learning model could be used.

[1577] Stockpile management function

[1578] The user inputs the items they have stockpiled and their expiration dates. For example, the user inputs information such as "I have stockpiled 15 bottles of water, the expiration date of which is October 2024," and the device sends this data to the server. The server then periodically checks the expiration dates and generates an alert when the expiration date approaches. This alert is sent to the device and notifies the user. The software used is a database and alert system.

[1579] Emotion engine integration

[1580] The system uses an emotion engine to recognize the user's emotional state. It analyzes facial expressions and tone of voice while the user is using the application to detect anxiety or stress. For example, if a user's expression becomes grim after viewing disaster information, the emotion engine will detect anxiety. This is done using an emotion analysis engine (API) and the camera and microphone of the smartphone or tablet.

[1581] Tailoring recommendations based on sentiment

[1582] The emotion engine analyzes the user's emotional state and adjusts the recommended items as needed. If anxiety or stress levels are high, it suggests items with a relaxing effect (such as aroma oils or stress relief products). For users in a positive emotional state, it reinforces reminders to regularly manage and update their inventory. The program implements logic to list recommended items based on the results of emotion analysis.

[1583] Specific examples

[1584] If the user is a "family of four (two adults, two children, one diabetic) living in Yokohama City, Kanagawa Prefecture," all of the above processes will be carried out, and a list of necessary stockpiles, expiration date alerts, and emotion-based recommendations will be provided.

[1585] Prompt Sentence Examples

[1586] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's area information, family composition, and physical information, and suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state.

[1587] Please use "Yokohama, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[1588] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1589] Step 1:

[1590] The user enters regional information, family composition information, and physical information. The user opens the application and enters information such as "A family of two adults and two children living in Yokohama City, Kanagawa Prefecture, one of whom has diabetes." The device sends this data to the server. The input data is sent in JSON format and is analyzed by the server.

[1591] Step 2:

[1592] The server refers to a hazard map based on regional information and assesses the disaster risk of the relevant region. The server uses a disaster risk assessment algorithm to assess the risks of earthquakes, typhoons, floods, etc. and calculates the results. The server generates earthquake and typhoon risk assessment results for Yokohama City and sends them to the terminal. The input is regional information and the output is the risk assessment results.

[1593] Step 3:

[1594] The server calculates the amount of food, drink, and disaster preparedness supplies needed based on family composition and physical information. For example, it calculates that a family of four needs 3 liters of water per person per day for seven days. It also calculates the amount of specific medications needed for diabetics. The server lists the calculation results and sends them to the terminal. The input is family composition and physical information, and the output is a list of the necessary supplies.

[1595] Step 4:

[1596] The server uses similar user data to suggest recommended stockpiles. The server uses a machine learning model to analyze stockpiles data from users with similar family structures in the same area and lists additional recommended stockpiles. Items such as "cooling sheets" and "portable generators" may be included in the list. The input is existing user data, and the output is a list of recommended stockpiles.

[1597] Step 5:

[1598] The user inputs the stockpiled items and their expiration dates. For example, they input information such as "I have 15 bottles of water in stock, and the expiration date is October 2024." The device sends this data to the server. The server stores it in a database, periodically checks the expiration date, and generates an alert when the expiration date approaches and sends it to the device. The input is stockpiled item information and expiration date, and the output is alert information.

[1599] Step 6:

[1600] The system uses an emotion engine to recognize the user's emotional state. It uses a camera and microphone to collect facial expressions and tone of voice while the user is using the application, and detects anxiety and stress. The emotion engine then sends the analysis results to a server. The input is facial expressions and tone of voice, and the output is an evaluation of the user's emotional state.

[1601] Step 7:

[1602] The emotion engine analyzes the user's emotional state and adjusts recommended stockpiles as needed. If anxiety or stress is high, it suggests stockpiles with a relaxing effect (such as aroma oils or stress relief products). If the emotional state is positive, it reinforces reminders to regularly manage and update stockpiles. The input is the emotion analysis results, and the output is recommended stockpiles or reminder information.

[1603] Example prompt sentence:

[1604] Based on the system outline of the invention, write a Python program that evaluates disaster risk by inputting the user's region, family composition, and physical information, and then suggests optimal disaster preparedness supplies. Also, use an emotion engine to adjust the recommended products based on the user's emotional state. Use "Yokohama City, Kanagawa Prefecture, 2 adults, 2 children, 1 diabetic" as an example user input.

[1605] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1606] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1607] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1608] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1609] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1610] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1611] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1612] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1613] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1614] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1615] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1616] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1617] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1618] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1619] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1620] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1621] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1622] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1623] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1624] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, act...

Claims

1. a means for inputting user region information; A means for inputting family composition information and physical information of a user; A means for assessing disaster risk based on regional information input into a server; A means for calculating the type and quantity of disaster preparedness supplies required based on disaster risk; A means for learning stockpiling data of similar users and proposing recommended stockpiles; A means for managing items stockpiled by the user and their expiration dates; A system including:

2. The system of claim 1 further comprising means for recommending a particular medication if the user's physical information includes a particular health condition.

3. 10. The system of claim 1, further comprising means for providing alerts to a user about stockpiles approaching their expiration date.

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