System

Abstract

A system is provided.SOLUTION: This system is provided with a means for inputting the data of a user, a means for automatically generating a task document based on the inputted data of the user and a means for preserving and reporting the generated task document.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] The labor shortage in the nursing care industry is having a significant impact on facility operations and service provision. Furthermore, the tasks involved in nursing care are diverse, and efficiency is required. For example, manpower is required in a variety of areas, including administrative tasks, transporting users to and from the facility, nighttime supervision, rehabilitation support for elderly people, and providing companionship to prevent dementia. This increases the burden on nursing care staff, and risks reducing the quality of services. Therefore, resolving the labor shortage and streamlining operations are urgently needed. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means:

[0006] This system improves the efficiency of administrative work by including a means for inputting user data, a means for automatically generating business documents based on the input user data, and a means for saving and notifying the generated business documents. It also improves the efficiency of transportation operations by including a means for inputting user address information, a means for calculating the optimal transportation route based on the input address information, and a means for automatically generating and notifying a transportation plan including the optimal transportation route. Furthermore, it strengthens nighttime monitoring operations by including a camera for monitoring user movements in real time, a means for analyzing the monitored data to detect abnormalities, and a means for sending an alert when an abnormality is detected. Additionally, it supports rehabilitation follow-up and injury prevention by including a means for recording the elderly person's walking pattern, a means for analyzing the recorded walking pattern to detect abnormalities, and a means for generating and notifying a rehabilitation plan when an abnormality is detected. Finally, it includes a means for inputting user information, a means for generating a dialogue script based on the input information, a means for an AI robot to converse using the generated dialogue script, and a means for saving the dialogue log, thereby serving as a conversation partner for dementia prevention. In this way, this system utilizing AI technology alleviates labor shortages and improves operational efficiency.

[0007] "Users" refers to elderly people, disabled people, etc. who receive nursing care services.

[0008] "Data" refers to a collection of information about users and information related to care work, in a format that can be calculated, stored, and analyzed.

[0009] "Administrative documents" refers to official documents required in nursing care work, such as visit records and invoices.

[0010] "Automatic generation" refers to a process in which a computer automatically creates a document without human intervention.

[0011] "Storage" is the process of storing digital data in a storage device such as memory or disk.

[0012] "Notification" is a means of notifying a user of relevant information when a specific condition is met.

[0013] "Address information" means information that includes data about a user's place of residence.

[0014] "Pick-up route" refers to the route that is considered optimal for picking up and dropping off users.

[0015] A "transportation plan" refers to a detailed schedule that includes the transportation route, time, and order of users.

[0016] "Camera means" refers to any device or equipment capable of capturing and recording images.

[0017] "Monitoring" is the process of observing a specific object and recording and observing its condition and behavior in real time.

[0018] "Analysis" is the process of examining collected data to find patterns and anomalies.

[0019] "Abnormal" means an improper or dangerous condition that is different from normal conditions or operation.

[0020] An "alert" is a notification or warning intended to draw attention.

[0021] "Walking pattern" refers to the characteristics of movement such as movements, posture, and rhythm when walking.

[0022] A "rehabilitation plan" refers to a specific program or plan to help elderly or disabled people recover their functions.

[0023] "Dialogue script" refers to the scenario or template that an AI robot uses when interacting with a user.

[0024] An "AI robot" is a robot equipped with artificial intelligence and capable of interacting with humans.

[0025] A "dialogue log" is data that records the content of the dialogue between an AI robot and a user. [Brief explanation of the drawings]

[0026] [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

[0027] 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.

[0028] First, the terms used in the following description will be explained.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] [First embodiment]

[0035] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0036] 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.

[0037] 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).

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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."

[0047] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. This system has functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, analyzing elderly people's gait to provide rehabilitation support and injury prevention, and an AI robot that acts as a conversation partner to prevent dementia. Specific embodiments for implementing the present invention are described below.

[0048] 1. AI outsourcing of administrative tasks

[0049] The user first enters data such as care records and visit times into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the terminal. The user can check the generated documents through the terminal and print them as needed. For example, when the visit times and care contents of a certain user are entered, the server instantly creates accurate visit record sheets and invoices based on that information.

[0050] 2. Automating user transportation

[0051] When a new user registers at a nursing care facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal transportation route. The calculated route is automatically reflected in the transportation plan by the server and notified to the terminal. This allows for efficient transportation of multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan that is displayed on the terminal.

[0052] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0053] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the care worker in charge. For example, if it detects a movement that could lead to the user falling out of bed in the middle of the night, the device will issue an alert on the spot and notify the care worker via the server.

[0054] 4. Gait analysis and rehabilitation follow-up

[0055] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when carrying out rehabilitation. For example, if an elderly person is losing their balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device.

[0056] 5. AI robot conversation partner

[0057] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[0058] As described above, the present invention is a system that utilizes AI technology to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[0059] The processing flow will be explained below.

[0060] 1. AI outsourcing of administrative tasks

[0061] Processing Steps

[0062] Step 1:

[0063] Users input data such as care records, visit times, and care details into the system.

[0064] Step 2:

[0065] The server receives the entered data and stores it in a database.

[0066] Step 3:

[0067] The server runs algorithms that automatically generate the necessary business documents (e.g., visit logs, invoices) based on the stored data.

[0068] Step 4:

[0069] The server converts the generated business document into PDF format and saves it in a specified folder.

[0070] Step 5:

[0071] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[0072] 2. Automating user transportation

[0073] Processing Steps

[0074] Step 1:

[0075] The user enters the address information of the new user into the system.

[0076] Step 2:

[0077] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[0078] Step 3:

[0079] The server automatically generates a transportation plan based on the optimized transportation route.

[0080] Step 4:

[0081] The server transmits the generated transportation plan to the terminal.

[0082] Step 5:

[0083] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[0084] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0085] Processing Steps

[0086] Step 1:

[0087] The device monitors the user's movements in real time through a camera at night.

[0088] Step 2:

[0089] The device analyzes the collected video data using AI algorithms.

[0090] Step 3:

[0091] When the device detects abnormal activity, it sends alert data to the server.

[0092] Step 4:

[0093] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[0094] Step 5:

[0095] The device will display notifications on caregivers' smartphones, allowing them to respond quickly to any abnormalities.

[0096] 4. Gait analysis and rehabilitation follow-up

[0097] Processing Steps

[0098] Step 1:

[0099] The device uses a camera to record the elderly person's walking pattern.

[0100] Step 2:

[0101] The device analyzes the collected data in real time and detects abnormal walking patterns.

[0102] Step 3:

[0103] When an abnormality is detected, the terminal transfers the analysis results to the server.

[0104] Step 4:

[0105] The server determines the need for rehabilitation based on the analysis results and executes an algorithm to generate an optimal rehabilitation plan.

[0106] Step 5:

[0107] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[0108] 5. AI robot conversation partner

[0109] Processing Steps

[0110] Step 1:

[0111] Users input information into the system, such as their emotional state, preferences, and recent events.

[0112] Step 2:

[0113] The server executes an algorithm that generates a dialogue script based on the input information.

[0114] Step 3:

[0115] The server transfers the generated dialogue script to the AI ​​robot.

[0116] Step 4:

[0117] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[0118] Step 5:

[0119] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[0120] Example 1

[0121] 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."

[0122] Staff shortages are a serious problem in modern nursing care facilities, resulting in excessive workloads and concerns about a decline in the quality of services. Additionally, issues such as ensuring the safety of users, effective rehabilitation, and dementia prevention are also important. In particular, reducing the administrative burden, streamlining transportation plans, nighttime monitoring, rehabilitation follow-up through gait analysis, and dementia prevention through dialogue are all important issues that must be resolved independently. Conventional systems can only address these issues individually, so integrated and efficient solutions are needed.

[0123] 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.

[0124] In this invention, the server includes: means for inputting user data; means for automatically generating business documents based on the input user data; means for saving and notifying the generated business documents; means for inputting user address information; means for calculating an optimal shuttle route based on the input address information; means for automatically generating and notifying a shuttle plan including the optimal shuttle route; camera means for monitoring the user's movements in real time; means for analyzing the monitored data and detecting abnormalities; means for sending an alert when an abnormality is detected; means for recording and analyzing the user's walking pattern; means for generating and notifying a rehabilitation plan based on the analysis results; means for inputting data on emotional state and interests; means for generating dialogue content based on the input data and transferring it to the AI ​​robot; and means for saving the dialogue log and using it as a reference for the next dialogue. This enables a system that can simultaneously solve issues such as alleviating labor shortages in nursing care facilities, improving work efficiency, ensuring user safety, providing advanced rehabilitation support, and preventing dementia.

[0125] "Means for inputting user data" refers to an interface or device that allows care facility staff to input information about users, such as care records and visiting times.

[0126] "Means for automatically generating business documents" refers to algorithms or programs for automatically creating business documents such as nursing care records and invoices based on input user data.

[0127] The "means for storing and notifying business documents" is a system component for storing automatically generated business documents in electronic form and notifying appropriate parties of the same.

[0128] "Means for inputting address information" refers to an interface or device for inputting address information of a user's residence or facility into the system.

[0129] The "means for calculating a shuttle route" is an algorithm or program for calculating the optimal shuttle route based on the input address information.

[0130] The "means for automatically generating and notifying a transportation plan" is a system component for creating a transportation plan based on an optimized transportation route and notifying relevant parties of the plan.

[0131] "Camera Means" means camera devices and associated systems used to monitor user movements in real time.

[0132] "Means for analyzing data and detecting abnormalities" refers to algorithms or programs that analyze monitoring data collected by cameras and recognize abnormal conditions or movements when they occur.

[0133] An "alert sending means" is a system component that sends warnings or notifications to relevant parties when an abnormality is detected.

[0134] The "means for recording and analyzing walking patterns" refers to an algorithm or program that records the user's walking movements with a camera and analyzes the data to identify abnormalities or areas for improvement.

[0135] The "means for generating and notifying a rehabilitation plan" is a system component for creating an effective rehabilitation plan based on the analyzed walking data and notifying the relevant parties of the plan.

[0136] "Means for inputting emotional state and interest data" refers to an interface or device for inputting the user's current emotional state and interests into the system.

[0137] "Means for generating dialogue content and transmitting it to the AI ​​robot" refers to algorithms or programs that generate dialogue scripts for natural dialogue based on input emotional state and interest data, and transmit them to the AI ​​robot.

[0138] "Means for saving dialogue logs and using them as a reference for the next dialogue" refers to a system component that records the content of dialogue with an AI robot and saves it for reference during the next dialogue.

[0139] The present invention is a system that resolves the shortage of personnel in nursing care facilities, improves operational efficiency, and enhances services, and specific embodiments thereof will be described below.

[0140] 1. AI outsourcing of administrative tasks

[0141] Users first enter data such as care records and visit times into a dedicated interface or tablet device. This data is sent from the device to a server and stored in a central database. The server analyzes the received data and uses AI algorithms to automatically generate business documents such as care record sheets and invoices. The generated documents are converted to PDF format, and a notification is sent from the server to the device. The user can then view the generated documents through the device and print them if necessary.

[0142] For example, when the visit time and care details for user A are entered, the server instantly creates an accurate visit record and invoice based on that information. An example of a prompt would be, "Please enter the visit time and care details for the user into the system and generate a visit record and invoice."

[0143] 2. Automating user transportation

[0144] The user enters the address information of a new user into a dedicated interface. This information is sent from the device to the server and stored along with existing user data. The server calculates the optimal shuttle route based on the received address information. This calculation uses a geographic information system (GIS) and shortest distance algorithms. The optimized shuttle plan is automatically generated and sent to the device from the server. The user can then view and implement the plan through the device.

[0145] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan. An example of a prompt would be, "Please enter the address information of new user A into the system and calculate the optimal transportation route."

[0146] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0147] For nighttime monitoring, AI cameras installed in rooms and hallways are used. The device monitors the user's movements in real time through the camera and collects the data. This data is sent from the device to a server and analyzed using an AI algorithm. Incidentally, if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge.

[0148] For example, if a user falls out of bed in the middle of the night, the device will immediately issue an alert and notify the caregiver via the server. An example of a prompt would be, "Monitor the user's movements via the camera at night, and issue an alert if any abnormal movements are detected."

[0149] 4. Gait analysis and rehabilitation follow-up

[0150] During the day, the device uses an installed AI camera to record the elderly person's walking pattern. This data is collected in real time and sent from the device to a server. The server uses an AI algorithm to analyze the walking pattern, and if an abnormal walking pattern is detected, it automatically generates a rehabilitation plan based on that. The generated rehabilitation plan is then sent to the device, and caregivers use it as a reference when carrying out rehabilitation.

[0151] For example, if an elderly person loses balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. An example of a prompt would be, "Use a camera to record the elderly person's walking pattern, and if an abnormal pattern is detected, generate a rehabilitation plan."

[0152] 5. AI robot conversation partner

[0153] As part of dementia prevention, users input their emotional state and recent interests and concerns into a dedicated interface. This information is sent from the device to a server, which then uses a generative AI model to generate an appropriate dialogue script. This script is then transferred to an AI robot via the device, which then interacts with the user accordingly. The dialogue log is then sent from the device to the server and saved as a reference for the next dialogue.

[0154] For example, if a user is interested in flowers, the server will use that information to generate a script that will allow the AI ​​robot to continue the conversation on the topic of flowers. An example of a prompt would be, "Please generate a dialogue script based on the user's emotional state and interests, and transfer it to the AI ​​robot."

[0155] As described above, this invention utilizes AI technology to improve the efficiency of nursing care facility operations and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[0156] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0157] 1. AI outsourcing of administrative tasks

[0158] Step 1

[0159] Users input data such as care records and visit times into a dedicated interface or tablet device. The input data includes the date and time of the visit, the details of the visit, and user information. This information is then sent from the device to the server.

[0160] Step 2

[0161] The server stores the received data in a central database, which centrally manages each user's care records and visiting times, providing efficient data access.

[0162] Step 3

[0163] The server analyzes the stored data using AI algorithms (for example, natural language processing or machine learning models). The input data is analyzed and administrative documents such as nursing care records and invoices are generated. The analyzed data is sent to a document generation tool, which creates documents in PDF format.

[0164] Step 4

[0165] The server notifies the terminal of the generated PDF document, and the user can check the generated document through the terminal and print it if necessary.

[0166] 2. Automating user transportation

[0167] Step 1

[0168] The user enters the address information of the new user into a dedicated interface. The entered information includes the address of the user's residence or facility. This information is then sent from the terminal to the server.

[0169] Step 2

[0170] The server stores the received address information together with existing user data in a central database, which unifies address information management and provides efficient data access.

[0171] Step 3

[0172] The server calculates the optimal pickup route based on the stored address data. It uses a geographic information system (GIS) and shortest distance algorithms to optimize the pickup order and route for each passenger. The calculation results are sent to the transportation planning tool, which generates a transportation plan.

[0173] Step 4

[0174] The server notifies the terminal of the generated transportation plan, and the user can check and implement the plan through the terminal.

[0175] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0176] Step 1

[0177] The device monitors users' movements in real time through AI cameras installed in rooms and hallways, which continuously transmit high-resolution video to the device.

[0178] Step 2

[0179] The device temporarily stores the video data collected by the camera and periodically transmits it to the server, including time and location information.

[0180] Step 3

[0181] The server analyzes the received video data using an AI algorithm, which uses a pre-trained model (e.g., an anomaly detection model) to detect abnormal activity. If an anomaly is detected, the information is sent to an alert system.

[0182] Step 4

[0183] When an abnormality is detected, the server generates an alert and sends it to the caregiver's smartphone app. The alert includes information on the date, time, and location of the abnormality.

[0184] 4. Gait analysis and rehabilitation follow-up

[0185] Step 1

[0186] The device uses an AI camera installed in the device to record the elderly person's walking pattern in real time, and the camera transmits the walking movement data to the device.

[0187] Step 2

[0188] The device temporarily stores the recorded data and periodically transmits it to a server, which includes details of walking timing and movement.

[0189] Step 3

[0190] The server analyzes the transmitted walking data using an AI algorithm, and if an abnormal walking pattern is detected, the information is sent to a rehabilitation plan generation tool.

[0191] Step 4

[0192] The server automatically generates a rehabilitation plan based on the analysis results, which is then sent to the device, where caregivers can use it as a reference when carrying out rehabilitation.

[0193] 5. AI robot conversation partner

[0194] Step 1

[0195] Users input their emotional state and recent interests into a dedicated interface. The input data includes emotional state, interests, and user profile information. This information is then sent from the device to the server.

[0196] Step 2

[0197] The server uses a generative AI model to generate an appropriate dialogue script based on the received data. The generated script is based on the user's input data and the model's learning results.

[0198] Step 3

[0199] The server transfers the generated dialogue script to the terminal, which then sends it to the AI ​​robot, which then dialogues with the user according to the received script.

[0200] Step 4

[0201] The device records the conversation log and periodically sends it to the server, where it is saved as a reference for the next conversation.

[0202] (Application example 1)

[0203] 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."

[0204] Current factory operations involve a wide range of tasks, including production management, logistics management, and safety monitoring, and many labor-intensive tasks are required to perform them efficiently. These tasks are typically performed manually, which can lead to errors and reduced efficiency. Furthermore, monitoring to ensure worker safety is often performed manually, resulting in the risk of accidents. Therefore, there is a need for a system that can automate these tasks and improve efficiency and safety.

[0205] 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.

[0206] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, a means for collecting data, a means for analyzing the collected data, a means for generating technical proposals, and a means for displaying the generated proposals. This enables efficient production management and logistics management in factories and automation of safety monitoring. Furthermore, the anomaly detection and proposal generation functions can improve work efficiency in factories and ensure the safety of workers.

[0207] "Data collection means" refers to devices and functions that use various sensors and input devices to acquire production data, attendance information, logistics information, worker behavior data, and the like within a factory.

[0208] The "automatic business document generation means" refers to a device or function that automatically generates business documents such as daily reports, attendance sheets, and proposals based on input data.

[0209] The "storage and notification means" refers to a device or function that stores the generated business documents and analysis results and notifies the relevant staff and systems of their contents.

[0210] "Data analysis means" refers to devices or functions that analyze collected data, detect trends and anomalies in the data, and generate technical proposals and optimization plans.

[0211] The "technical proposal generation means" refers to a device or function that automatically generates technical proposals such as measures to improve the efficiency of factory operations, safety measures, etc., based on the analyzed data.

[0212] The "proposal display means" is a device or function for displaying the generated proposals and improvement measures in a format that is easy for factory staff to understand.

[0213] The "logistics route optimization means" is a device or function that calculates the optimal transportation route for materials and products based on input address information and logistics data, and generates an efficient logistics schedule.

[0214] "Camera means" refers to a device or function that monitors a specific area in a factory in real time and captures the operations of workers and machines.

[0215] An "abnormality detection means" is a device or function that analyzes monitored data, detects abnormal behavior or events, and notifies the user of such.

[0216] This invention is a comprehensive system aimed at improving efficiency and safety in factory operations. The system has the function of automatically generating, saving, and notifying business documents based on data input by users. It also has multiple automated functions such as optimizing logistics routes, safety monitoring, and analyzing worker movements and generating proposals.

[0217] The system includes the following major hardware and software components:

[0218] Cameras: Monitor specific areas of the factory in real time and capture activity.

[0219] RFID tag reader: Obtains location information for items and materials.

[0220] Server: Analyzes and stores data. Uses AI frameworks such as Python and TensorFlow.

[0221] Smartphone: Displays and notifies results.

[0222] 1. Data Collection

[0223] Users collect data from various sensors (cameras, RFID tags, etc.) and input devices. For example, they can obtain production data, attendance information, logistics information, and worker behavior data in a factory in real time.

[0224] 2. Data Analysis

[0225] The collected data is sent to a server and analyzed using AI models, using AI frameworks such as Python and TensorFlow to detect trends and anomalies in the data and generate technical recommendations and optimization plans.

[0226] 3. Notification and reflection of results

[0227] The analysis results and generated suggestions are sent to smartphones or other devices. For example, they may include suggestions regarding working hours and production efficiency, optimal logistics routes, and safety measures. This allows users to immediately check this information and take appropriate action.

[0228] Specific examples

[0229] During production line work in a factory, cameras detect when a worker's movements go outside the control range and send an immediate notification to prevent accidents. The system also analyzes production and attendance data from the past week to generate suggestions for improving efficiency. Furthermore, it recalculates optimal logistics routes and generates schedules based on the latest sensor information.

[0230] Prompt Sentence Examples

[0231] "Analyze production and attendance data from the past week and generate suggestions for improving efficiency."

[0232] "Based on the latest sensor information, recalculate the optimal logistics route and generate a schedule."

[0233] These prompts allow the system to provide optimal suggestions for efficient and safe factory operations.

[0234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0235] Step 1:

[0236] Users collect data in factories using sensors, cameras, RFID tag readers, etc. This collected data includes production data, logistics data, attendance information, worker behavior data, etc. Real-time data is obtained from sensors and cameras as input, and this data is sent to a server as output.

[0237] Step 2:

[0238] The server analyzes the received data. Python and AI frameworks such as TensorFlow are used for the analysis. Data processing includes preprocessing, normalization, and missing value completion. Data calculation involves applying anomaly detection and pattern recognition algorithms to detect abnormal behavior and opportunities for efficiency improvements. The collected data is read as input. Analysis results and suggestions are generated as output.

[0239] Step 3:

[0240] The server automatically generates optimal business documents based on the generated analysis results and proposals. These documents include daily production reports, attendance records, efficiency improvement proposals, logistics schedules, etc. The analysis results and proposals are used as inputs. The automatically generated business documents are obtained as output.

[0241] Step 4:

[0242] The server saves the generated business document in cloud storage or on a local disk. At the same time, it sends a notification to the relevant users and devices. The automatically generated business document is used as input. The saved document and notification are obtained as output.

[0243] Step 5:

[0244] The terminal displays the generated business documents, optimized routes, work suggestions, etc. to the user who received the notification. The user checks this and takes appropriate action if necessary. The notification and business documents from the server are used as inputs. The output is the display of information to the user.

[0245] Step 6:

[0246] The user inputs a prompt into the generative AI model in the system. For example, the user might input a prompt such as, "Please analyze the production data and attendance data from the past week and generate proposals for improving efficiency." Based on this prompt, the server analyzes the data again and generates new proposals. The prompt is used as input. The newly generated proposals are obtained as output.

[0247] Step 7:

[0248] The server notifies the user or terminal of the newly generated proposal and displays it again. This allows the user to operate the factory efficiently based on the latest information. The newly generated proposal is used as input. The output is a re-notification to the user and information display.

[0249] 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.

[0250] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. The system combines functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, providing rehabilitation support and injury prevention through gait analysis for elderly people, and an AI robot that acts as a conversation partner to prevent dementia, as well as an emotion engine. Specific embodiments for implementing the present invention are described below.

[0251] 1. AI outsourcing of administrative tasks

[0252] Users enter data such as care records, visit times, and care details into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the device. The user can check the generated documents through the device and print them as needed. For example, when a user's visit times and care details are entered, the server instantly creates an accurate visit record sheet and invoice based on that information. At this time, an emotion engine analyzes the user's emotions and can reflect them in the content of the documents as necessary.

[0253] 2. Automating user transportation

[0254] When a new user registers at a nursing facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal shuttle route. The calculated route is automatically reflected in the shuttle plan by the server and notified to the terminal. This allows for efficient shuttle service for multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall shuttle plan that is displayed on the terminal. In this case, the emotion engine considers the user's stress level and physical condition to select a comfortable shuttle route.

[0255] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0256] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, the device sends an alert to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge. For example, if the device detects movements that suggest the user has fallen out of bed in the middle of the night, it will immediately issue an alert and notify the caregiver via the server. This process includes a function in which an emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[0257] 4. Gait analysis and rehabilitation follow-up

[0258] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when implementing rehabilitation. For example, if an elderly person is increasingly losing their balance while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. At this time, the emotion engine also takes into account the user's level of anxiety and depression, and provides a rehabilitation plan that incorporates psychological support.

[0259] 5. AI robot conversation partner

[0260] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue and adjusts the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[0261] As described above, this invention is a system that utilizes AI technology and an emotion engine to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[0262] The processing flow will be explained below.

[0263] 1. AI outsourcing of administrative tasks

[0264] Processing Steps

[0265] Step 1:

[0266] Users input data such as care records, visit times, and care details into the system.

[0267] Step 2:

[0268] The server receives the entered data and stores it in a database.

[0269] Step 3:

[0270] The server uses an emotion engine to analyze the user's emotional state and executes algorithms to adjust the content of business documents based on that analysis.

[0271] Step 4:

[0272] The server automatically generates business documents such as nursing care records and invoices.

[0273] Step 5:

[0274] The server converts the generated business document into PDF format and saves it in a specified folder.

[0275] Step 6:

[0276] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[0277] 2. Automating user transportation

[0278] Processing Steps

[0279] Step 1:

[0280] The user enters the address information of the new user into the system.

[0281] Step 2:

[0282] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[0283] Step 3:

[0284] The server uses an emotion engine to consider the user's emotional state and adjust the optimal pick-up route and time.

[0285] Step 4:

[0286] The server automatically generates a transportation plan based on the optimized transportation route.

[0287] Step 5:

[0288] The server transmits the generated transportation plan to the terminal.

[0289] Step 6:

[0290] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[0291] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0292] Processing Steps

[0293] Step 1:

[0294] The device monitors the user's movements in real time through a camera at night.

[0295] Step 2:

[0296] The device analyzes the collected video data using AI algorithms.

[0297] Step 3:

[0298] When the device detects abnormal activity, it sends alert data to the server.

[0299] Step 4:

[0300] The server also analyzes the user's emotional state using an emotion engine to determine whether stress or anxiety is increasing.

[0301] Step 5:

[0302] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[0303] Step 6:

[0304] The device will display notifications on caregivers' smartphones, allowing them to respond quickly.

[0305] 4. Gait analysis and rehabilitation follow-up

[0306] Processing Steps

[0307] Step 1:

[0308] The device uses a camera to record the elderly person's walking pattern.

[0309] Step 2:

[0310] The device analyzes the collected data in real time and detects abnormal walking patterns.

[0311] Step 3:

[0312] When an abnormality is detected, the terminal transfers the analysis results to the server.

[0313] Step 4:

[0314] The server also analyzes the user's emotional state and anxiety level using an emotion engine.

[0315] Step 5:

[0316] The server executes an algorithm that determines the need for rehabilitation based on the analysis results and generates an appropriate rehabilitation plan.

[0317] Step 6:

[0318] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[0319] 5. AI robot conversation partner

[0320] Processing Steps

[0321] Step 1:

[0322] Users input information such as their emotional state and interests into the system.

[0323] Step 2:

[0324] The server runs an algorithm that generates a dialogue script based on the input information.

[0325] Step 3:

[0326] The server transfers the generated dialogue script to the AI ​​robot.

[0327] Step 4:

[0328] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[0329] Step 5:

[0330] The device uses an emotion engine to analyze the user's facial expressions and tone of voice during a conversation and adjusts the content and tone of the conversation as appropriate.

[0331] Step 6:

[0332] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[0333] Example 2

[0334] 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."

[0335] The present invention aims to provide a system that can address the shortage of personnel and the increasing workload in nursing care facilities and provide efficient and advanced services. In particular, the present invention focuses on streamlining specific tasks such as automating administrative tasks, optimizing transportation plans for users, detecting abnormalities at night, following up on rehabilitation through gait analysis, and preventing dementia through dialogue with users.

[0336] 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.

[0337] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, and a means for analyzing the user's emotional state and reflecting it in the generated documents, thereby enabling the automatic generation of care records and invoices and the reflection of the emotional state.

[0338] The system also includes a means for inputting the user's address information, a means for calculating the optimal shuttle route based on the input address information, a means for automatically generating and notifying a shuttle plan including the optimal shuttle route, and a means for selecting a shuttle route taking into consideration the user's stress level and physical condition, thereby enabling the creation of an efficient shuttle plan that takes into consideration the user.

[0339] Furthermore, the system includes a camera means for monitoring the user's movements in real time, a means for analyzing the monitored data and detecting abnormalities, a means for sending an alert when an abnormality is detected, and a means for analyzing the user's facial expressions and voice and responding quickly when emotional stress increases. This improves the accuracy of nighttime monitoring and abnormality detection, enabling a quick response.

[0340] "Client data" refers to information such as records about clients of care facilities, visit times, and care provided.

[0341] "Business documents" refer to documents related to nursing care work, such as nursing care records and invoices.

[0342] "Server" refers to a central computer that manages the overall processing of the system, including receiving, storing, analyzing, and notifying data.

[0343] "Terminal" refers to an input device or output device used by a user, and includes devices for inputting data and displaying notifications.

[0344] "Means for inputting data" refers to the interface that users and care staff use to input information such as care records and visit times into the system.

[0345] "Means for analyzing data" refers to software or algorithms that the server uses to perform the necessary processing based on the information entered.

[0346] "Means for automatically generating documents" refers to technology that automatically creates documents such as nursing care records and invoices based on input data.

[0347] "Means of notification" refers to a mechanism for informing users of generated documents, transportation plans, abnormality detection information, etc.

[0348] "Means for analyzing emotional state" refers to technology that analyzes a user's facial expressions and tone of voice to determine their emotions.

[0349] "Address information" refers to information about the user's base of residence, and is used to calculate the shuttle route.

[0350] "Means for calculating optimal shuttle routes" refers to an algorithm for calculating efficient shuttle routes based on the address information of existing and new users.

[0351] "Means that take stress levels and physical condition into consideration" refers to a system that analyzes the user's emotions and health condition and selects the optimal route accordingly.

[0352] "Camera means" refers to a photographic device installed in a room or corridor for monitoring the movements of users in real time.

[0353] "Means for detecting anomalies" refers to programs or algorithms that analyze collected data and identify unusual behavior or conditions.

[0354] "Means for sending alerts" refers to a mechanism for sending immediate notifications to relevant parties when an abnormality is detected.

[0355] A "dialogue script" refers to a document that describes a predefined conversation flow that an AI robot uses when interacting with a user.

[0356] This invention is a system that solves the labor shortage in nursing care facilities, improves operational efficiency, and enhances services. This system provides specific functions such as generating nursing care records and invoices, automating transportation plans for users, detecting abnormalities at night, providing rehabilitation follow-up, and preventing dementia through dialogue with users using an AI robot.

[0357] AI-powered administrative work

[0358] Users input data such as care records, visiting times, and care details into the system. This data is sent to the server via the terminal. The server saves the input data in a database and analyzes it using Python scripts. A template engine generates care records and invoices, which are then converted into PDF format using the PDFKit library. The generated documents are sent to the terminal, where the user can check them and print them if necessary. The emotion engine can analyze the user's emotional state and reflect it in the document content.

[0359] For example, when a user's visit time and care details are entered, the server instantly creates an accurate visit record and invoice based on that information. The emotion engine analyzes the user's emotions and reflects them in the data.

[0360] Example prompt sentence:

[0361] Visiting time: October 1, 2023, 14:00-15:00, Care content: Bathing assistance. User A's emotional state: Relaxed.

[0362] Automated transportation for users

[0363] When a new user registers at a care facility, the user enters their address information into the system. The device sends the input data to the server. The server combines the existing user data with the new data and calculates the optimal shuttle route using the Google Maps API. The calculated route is reflected in the shuttle plan by the template engine, converted into PDF format, and notified to the device. The emotion engine selects the shuttle route taking into account the user's stress level and physical condition.

[0364] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route for existing users B and C and displays the transportation plan on the terminal.

[0365] Example prompt sentence:

[0366] New user X's address: 1-1-1 Nishi-Shinjuku, Shinjuku-ku, Tokyo. Existing user Y's address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo, and user Z's address: 1-4-5 Yurakucho, Chiyoda-ku, Tokyo. User Y's emotional state: stress.

[0367] Nighttime monitoring with AI cameras to detect abnormalities

[0368] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is sent to a server, which analyzes it using AI libraries such as TensorFlow. If abnormal movements are detected, an alert is sent immediately to the caregiver's smartphone app. The emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[0369] As a specific example, if the device detects a user falling out of bed in the middle of the night, it will issue an alert on the spot and notify caregivers via the server.

[0370] Example prompt sentence:

[0371] The nighttime surveillance camera detects abnormal movement. User A is seen falling out of bed. Emotional state: High stress.

[0372] Gait analysis and rehabilitation follow-up

[0373] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is sent to a server, which analyzes the data using AI libraries such as TensorFlow. If an abnormal walking pattern is detected, the server automatically generates a rehabilitation plan and documents it using a template engine. The generated rehabilitation plan is converted to PDF format and sent to the device. The emotion engine provides a rehabilitation plan taking into account the user's level of anxiety and depression.

[0374] As a specific example, if an elderly person is losing their balance while walking more frequently, the server will analyze the data, create a rehabilitation plan, and notify the device.

[0375] Example prompt sentence:

[0376] Elderly person B loses balance while walking three times per hour. Emotional state: high anxiety.

[0377] AI robot conversation partner

[0378] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. The input information is sent to a server, which uses a natural language processing engine to generate a dialogue script. The generated script is transferred to the AI ​​robot, which then converses with the user via the device. The dialogue log is sent to the server and saved as reference for the next dialogue. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue, adjusting the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[0379] As a specific example, if a user is interested in flowers, the server will use that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[0380] Example prompt sentence:

[0381] User C's interest: flowers. Emotional state: joy.

[0382] The above is an embodiment of the present invention, which can improve the efficiency of operations at nursing care facilities and provide advanced services.

[0383] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0384] 1. AI outsourcing of administrative tasks

[0385] Processing Steps

[0386] Step 1:

[0387] The user opens the system's web form and enters data such as care records, visit times, and care details.

[0388] Input: Care records, visiting time, care contents

[0389] Output: Formatted data to terminal

[0390] Step 2:

[0391] The terminal formats the input data and sends it to the server.

[0392] Input: Formatted data

[0393] Output: Data sent to the server

[0394] Step 3:

[0395] The server stores the received data in a MySQL database.

[0396] Input: Received data

[0397] Output: Data stored in the database

[0398] Step 4:

[0399] The server analyzes the stored data using Python scripts.

[0400] Input: Data in the database

[0401] Output: Analysis results

[0402] Step 5:

[0403] The server uses a template engine to generate care records and bills.

[0404] Input: Analysis results

[0405] Output: The generated document

[0406] Step 6:

[0407] The server converts the generated document into PDF format using the PDFKit library and sends a notification to the device.

[0408] Input: Generated document

[0409] Output: Converted document as PDF, notification to device

[0410] Step 7:

[0411] The device displays the notification to the user as a pop-up message.

[0412] Input: Notification to device

[0413] Output: Display notification to the user

[0414] Step 8:

[0415] The user checks the generated document and prints it out on a printer if necessary.

[0416] Input: Popup message

[0417] Output: Printed document

[0418] 2. Automating user transportation

[0419] Processing Steps

[0420] Step 1:

[0421] A user logs into the system and enters the address information for a new user.

[0422] Input: New user's address information

[0423] Output: Formatted data to terminal

[0424] Step 2:

[0425] The terminal formats the address data and sends it to the server.

[0426] Input: Formatted address data

[0427] Output: Data sent to the server

[0428] Step 3:

[0429] The server uses Python and the Google Maps API to integrate the address information of new and old users and calculate the optimal shuttle route.

[0430] Input: Integrated address data

[0431] Output: Calculated pickup route

[0432] Step 4:

[0433] The server creates a transportation plan using a template engine based on the route calculation results.

[0434] Input: Calculated pickup route

[0435] Output: Transportation plan

[0436] Step 5:

[0437] The server converts the generated transportation plan into PDF format using the PDFKit library and sends a notification to the terminal.

[0438] Input: Transportation Plan

[0439] Output: Converted plan as PDF, notification to device

[0440] Step 6:

[0441] The terminal displays a notification of the transportation plan to the user as a pop-up message.

[0442] Input: Notification to device

[0443] Output: Display notification to the user

[0444] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0445] Processing Steps

[0446] Step 1:

[0447] The device streams footage from cameras installed in rooms and hallways and analyzes it in real time.

[0448] Input: Camera image

[0449] Output: Real-time analytics data

[0450] Step 2:

[0451] The terminal transmits the analysis results to the server as appropriate.

[0452] Input: Parsed data

[0453] Output: Data sent to the server

[0454] Step 3:

[0455] The server analyzes the data using AI libraries such as TensorFlow to identify abnormal behavior.

[0456] Input: Parsed data

[0457] Output: Anomaly detection information

[0458] Step 4:

[0459] If the server detects an abnormality, it will notify the caregiver's smartphone app using a real-time database such as Firebase.

[0460] Input: Anomaly detection information

[0461] Output: Notification to care staff

[0462] 4. Gait analysis and rehabilitation follow-up

[0463] Processing Steps

[0464] Step 1:

[0465] The device collects footage from cameras installed in rooms and hallways and records the elderly person's walking patterns.

[0466] Input: Camera image

[0467] Output: Recorded walking data

[0468] Step 2:

[0469] The terminal transmits the collected data to the server as appropriate.

[0470] Input: Gait data

[0471] Output: Data sent to the server

[0472] Step 3:

[0473] The server analyzes the data using AI libraries such as TensorFlow to detect any abnormal walking patterns.

[0474] Input: Collected data

[0475] Output: Analysis results

[0476] Step 4:

[0477] If the server detects an abnormality, it automatically generates a rehabilitation plan and documents it using a template engine.

[0478] Input: Analysis results

[0479] Output: Rehabilitation plan

[0480] Step 5:

[0481] The server converts the generated rehabilitation plan into PDF format and sends a notification to the terminal.

[0482] Input: Rehabilitation plan

[0483] Output: Converted plan as PDF, notification to device

[0484] Step 6:

[0485] The device displays the rehabilitation plan to the caregiver as a pop-up message.

[0486] Input: Notification to device

[0487] Output: Notification to be displayed to care staff

[0488] 5. AI robot conversation partner

[0489] Processing Steps

[0490] Step 1:

[0491] The user enters their emotional state and recent interests and concerns on the system's input screen.

[0492] Input: User's emotional state and interests

[0493] Output: Formatted data to terminal

[0494] Step 2:

[0495] The terminal formats the input data and sends it to the server.

[0496] Input: Formatted data

[0497] Output: Data sent to the server

[0498] Step 3:

[0499] The server uses a natural language processing engine (e.g., GPT-3) to generate an appropriate dialogue script.

[0500] Input: Data sent

[0501] Output: Generated dialogue script

[0502] Step 4:

[0503] The server transfers the generated script to the terminal and conveys the dialogue content to the AI ​​robot.

[0504] Input: Interactive script

[0505] Output: The transferred script

[0506] Step 5:

[0507] The device controls the AI ​​robot and engages in a dialogue with the user, processing what the robot is saying and the user's responses in real time.

[0508] Input: Transferred script, user response

[0509] Output: Interactions performed

[0510] Step 6:

[0511] The terminal generates a dialogue log and transmits it to the server as appropriate.

[0512] Input: Interaction log data

[0513] Output: Log data sent to the server

[0514] Step 7:

[0515] The server saves the dialogue log and uses it as a reference for generating the next dialogue script.

[0516] Input: Log data sent

[0517] Output: Saved log data

[0518] (Application example 2)

[0519] 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."

[0520] Currently, nighttime monitoring in factories still relies on human labor, making it difficult to respond quickly when an abnormality occurs. Furthermore, machine failures and employee stress cannot be detected in real time, often delaying effective countermeasures. This results in problems such as reduced work efficiency and an increased risk of accidents. Therefore, there is a need to automate nighttime factory monitoring and detect abnormalities and stress conditions early.

[0521] 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.

[0522] In this invention, the server includes means for monitoring user movements in real time using a camera, means for analyzing the monitored data to detect abnormalities, means for notifying when an abnormality is detected, means for analyzing emotions and improving responses to detected abnormalities, and means for sending notifications to smartphones. This automates nighttime monitoring in factories, enabling early detection of abnormalities and stress states and prompt responses.

[0523] "Means for inputting user data" refers to a device or interface that allows input of information about people to be monitored in the factory and their work status.

[0524] "Means for automatically generating business documents" refers to a system that automatically creates necessary reports and notification documents based on input user data.

[0525] "Means for storing and notifying generated business documents" refers to a system that stores created documents and reports in a database and sends notifications to appropriate terminals when necessary.

[0526] "Means for monitoring user movements in real time using cameras" refers to a device or system that uses cameras installed in a factory to monitor the movements of the person being monitored in real time.

[0527] "Means for analyzing monitoring data and detecting abnormalities" refers to algorithms or systems that analyze monitoring data collected by cameras and detect unnatural movements or abnormal conditions.

[0528] "Means for notifying when an abnormality is detected" refers to a system that sends an alert to a person in charge or a manager when an abnormal situation is detected.

[0529] The "means of analyzing emotions and improving responses to detected abnormalities" refers to a system that analyzes the facial expressions and movements of the person being monitored, evaluates their stress level and changes in emotions, and suggests appropriate responses based on that.

[0530] "Means for sending notifications to smartphones" is a system for sending important alerts and information directly to the smartphones of responsible personnel.

[0531] This invention is a system that automates nighttime monitoring in factory environments, detects abnormalities and stress levels early, and enables rapid response. The system analyzes camera footage in real time, detects abnormal behavior and emotional states, and sends notifications to smartphones.

[0532] First, the user inputs information about the workers and equipment to be monitored in the factory. This data is then sent to the server and stored in a database.

[0533] For real-time video monitoring, multiple cameras are installed, and the device acquires video data from these cameras. This video data is sent to a server and analyzed using a specific algorithm. Specifically, OpenCV is used to process the images and detect abnormal movements and situations.

[0534] Furthermore, the server uses an emotion analysis model powered by TensorFlow to analyze the facial expressions and movements of the monitored subject, assessing their stress level, and if a change in emotion is detected, taking this into account when responding to an anomaly.

[0535] When an anomaly is detected, the server uses a notification service such as Twilio to instantly send an alert to the agent's smartphone, including details about the anomaly and the detected emotional state, allowing the agent to respond quickly and appropriately.

[0536] As a concrete example, imagine a factory where surveillance cameras are installed during the night shift. The cameras monitor the work area in real time at night, detecting any abnormal activity or equipment malfunctions. They also analyze employees' faces and behavior to assess whether they are showing signs of stress or anxiety. This information is sent to a server in real time, and the analysis results are sent to the person in charge's smartphone. The person in charge can then immediately go to the site and resolve the problem quickly.

[0537] Below are some example prompts for a generative AI model:

[0538] "Please create a program that analyzes the stress levels of factory workers in real time and notifies their smartphones if an abnormality is detected. The hardware required will be cameras and servers, the software will be OpenCV and TensorFlow, and the notification service will be Twilio."

[0539] In this way, the system of the present invention highly automates nighttime monitoring work within a factory, enabling rapid response to problems.

[0540] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0541] Step 1:

[0542] The user inputs information about the workers and equipment to be monitored. Data input is performed using a dedicated interface, and this information is sent to the server and stored in a database. The input for this step is detailed information about the workers and equipment, and the output is the data stored on the server.

[0543] Step 2:

[0544] The terminal acquires images in real time from cameras installed in the factory. The cameras are in operation 24 hours a day, and the image data sent is transmitted to the server in real time. The input of this step is the camera image, and the output is the image data sent to the server.

[0545] Step 3:

[0546] To analyze the video data received by the server, image processing is performed using OpenCV. Specifically, the video frames are converted to grayscale and analyzed to detect abnormal movements or situations. The input of this step is real-time video data, and the output is a judgment result on whether there is an abnormality.

[0547] Step 4:

[0548] The server uses TensorFlow to perform emotion analysis on the received video data. It detects the target's face, evaluates their facial expressions and movements in real time, and measures changes in stress and emotion. The input for this step is the analyzed video frames, and the output is data on stress levels and emotional states.

[0549] Step 5:

[0550] If the server detects an anomaly or stress state, it immediately generates a notification message using Twilio and sends it to the person in charge's smartphone. This message includes details of the anomaly and information about the person's emotional state. The input of this step is the anomaly detection result and the emotion analysis result, and the output is the sent notification message.

[0551] Step 6:

[0552] The person in charge checks the notification message received on their smartphone and quickly heads to the site. Upon receiving this notification, they decide on a specific response method and quickly implement the necessary measures. The input of this step is the notification message, and the output is the implementation of the problem response at the site.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] [Second embodiment]

[0557] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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).

[0563] 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.

[0564] 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.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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."

[0569] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. This system has functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, analyzing elderly people's gait to provide rehabilitation support and injury prevention, and an AI robot that acts as a conversation partner to prevent dementia. Specific embodiments for implementing the present invention are described below.

[0570] 1. AI outsourcing of administrative tasks

[0571] The user first enters data such as care records and visit times into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the terminal. The user can check the generated documents through the terminal and print them as needed. For example, when the visit times and care contents of a certain user are entered, the server instantly creates accurate visit record sheets and invoices based on that information.

[0572] 2. Automating user transportation

[0573] When a new user registers at a nursing care facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal transportation route. The calculated route is automatically reflected in the transportation plan by the server and notified to the terminal. This allows for efficient transportation of multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan that is displayed on the terminal.

[0574] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0575] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the care worker in charge. For example, if it detects a movement that could lead to the user falling out of bed in the middle of the night, the device will issue an alert on the spot and notify the care worker via the server.

[0576] 4. Gait analysis and rehabilitation follow-up

[0577] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when carrying out rehabilitation. For example, if an elderly person is losing their balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device.

[0578] 5. AI robot conversation partner

[0579] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[0580] As described above, the present invention is a system that utilizes AI technology to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[0581] The processing flow will be explained below.

[0582] 1. AI outsourcing of administrative tasks

[0583] Processing Steps

[0584] Step 1:

[0585] Users input data such as care records, visit times, and care details into the system.

[0586] Step 2:

[0587] The server receives the entered data and stores it in a database.

[0588] Step 3:

[0589] The server runs algorithms that automatically generate the necessary business documents (e.g., visit logs, invoices) based on the stored data.

[0590] Step 4:

[0591] The server converts the generated business document into PDF format and saves it in a specified folder.

[0592] Step 5:

[0593] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[0594] 2. Automating user transportation

[0595] Processing Steps

[0596] Step 1:

[0597] The user enters the address information of the new user into the system.

[0598] Step 2:

[0599] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[0600] Step 3:

[0601] The server automatically generates a transportation plan based on the optimized transportation route.

[0602] Step 4:

[0603] The server transmits the generated transportation plan to the terminal.

[0604] Step 5:

[0605] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[0606] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0607] Processing Steps

[0608] Step 1:

[0609] The device monitors the user's movements in real time through a camera at night.

[0610] Step 2:

[0611] The device analyzes the collected video data using AI algorithms.

[0612] Step 3:

[0613] When the device detects abnormal activity, it sends alert data to the server.

[0614] Step 4:

[0615] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[0616] Step 5:

[0617] The device will display notifications on caregivers' smartphones, allowing them to respond quickly to any abnormalities.

[0618] 4. Gait analysis and rehabilitation follow-up

[0619] Processing Steps

[0620] Step 1:

[0621] The device uses a camera to record the elderly person's walking pattern.

[0622] Step 2:

[0623] The device analyzes the collected data in real time and detects abnormal walking patterns.

[0624] Step 3:

[0625] When an abnormality is detected, the terminal transfers the analysis results to the server.

[0626] Step 4:

[0627] The server determines the need for rehabilitation based on the analysis results and executes an algorithm to generate an optimal rehabilitation plan.

[0628] Step 5:

[0629] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[0630] 5. AI robot conversation partner

[0631] Processing Steps

[0632] Step 1:

[0633] Users input information into the system, such as their emotional state, preferences, and recent events.

[0634] Step 2:

[0635] The server executes an algorithm that generates a dialogue script based on the input information.

[0636] Step 3:

[0637] The server transfers the generated dialogue script to the AI ​​robot.

[0638] Step 4:

[0639] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[0640] Step 5:

[0641] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[0642] Example 1

[0643] 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."

[0644] Staff shortages are a serious problem in modern nursing care facilities, resulting in excessive workloads and concerns about a decline in the quality of services. Additionally, issues such as ensuring the safety of users, effective rehabilitation, and dementia prevention are also important. In particular, reducing the administrative burden, streamlining transportation plans, nighttime monitoring, rehabilitation follow-up through gait analysis, and dementia prevention through dialogue are all important issues that must be resolved independently. Conventional systems can only address these issues individually, so integrated and efficient solutions are needed.

[0645] 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.

[0646] In this invention, the server includes: means for inputting user data; means for automatically generating business documents based on the input user data; means for saving and notifying the generated business documents; means for inputting user address information; means for calculating an optimal shuttle route based on the input address information; means for automatically generating and notifying a shuttle plan including the optimal shuttle route; camera means for monitoring the user's movements in real time; means for analyzing the monitored data and detecting abnormalities; means for sending an alert when an abnormality is detected; means for recording and analyzing the user's walking pattern; means for generating and notifying a rehabilitation plan based on the analysis results; means for inputting data on emotional state and interests; means for generating dialogue content based on the input data and transferring it to the AI ​​robot; and means for saving the dialogue log and using it as a reference for the next dialogue. This enables a system that can simultaneously solve issues such as alleviating labor shortages in nursing care facilities, improving work efficiency, ensuring user safety, providing advanced rehabilitation support, and preventing dementia.

[0647] "Means for inputting user data" refers to an interface or device that allows care facility staff to input information about users, such as care records and visiting times.

[0648] "Means for automatically generating business documents" refers to algorithms or programs for automatically creating business documents such as nursing care records and invoices based on input user data.

[0649] The "means for storing and notifying business documents" is a system component for storing automatically generated business documents in electronic form and notifying appropriate parties of the same.

[0650] "Means for inputting address information" refers to an interface or device for inputting address information of a user's residence or facility into the system.

[0651] The "means for calculating a shuttle route" is an algorithm or program for calculating the optimal shuttle route based on the input address information.

[0652] The "means for automatically generating and notifying a transportation plan" is a system component for creating a transportation plan based on an optimized transportation route and notifying relevant parties of the plan.

[0653] "Camera Means" means camera devices and associated systems used to monitor user movements in real time.

[0654] "Means for analyzing data and detecting abnormalities" refers to algorithms or programs that analyze monitoring data collected by cameras and recognize abnormal conditions or movements when they occur.

[0655] An "alert sending means" is a system component that sends warnings or notifications to relevant parties when an abnormality is detected.

[0656] The "means for recording and analyzing walking patterns" refers to an algorithm or program that records the user's walking movements with a camera and analyzes the data to identify abnormalities or areas for improvement.

[0657] The "means for generating and notifying a rehabilitation plan" is a system component for creating an effective rehabilitation plan based on the analyzed walking data and notifying the relevant parties of the plan.

[0658] "Means for inputting emotional state and interest data" refers to an interface or device for inputting the user's current emotional state and interests into the system.

[0659] "Means for generating dialogue content and transmitting it to the AI ​​robot" refers to algorithms or programs that generate dialogue scripts for natural dialogue based on input emotional state and interest data, and transmit them to the AI ​​robot.

[0660] "Means for saving dialogue logs and using them as a reference for the next dialogue" refers to a system component that records the content of dialogue with an AI robot and saves it for reference during the next dialogue.

[0661] The present invention is a system that resolves the shortage of personnel in nursing care facilities, improves operational efficiency, and enhances services, and specific embodiments thereof will be described below.

[0662] 1. AI outsourcing of administrative tasks

[0663] Users first enter data such as care records and visit times into a dedicated interface or tablet device. This data is sent from the device to a server and stored in a central database. The server analyzes the received data and uses AI algorithms to automatically generate business documents such as care record sheets and invoices. The generated documents are converted to PDF format, and a notification is sent from the server to the device. The user can then view the generated documents through the device and print them if necessary.

[0664] For example, when the visit time and care details for user A are entered, the server instantly creates an accurate visit record and invoice based on that information. An example of a prompt would be, "Please enter the visit time and care details for the user into the system and generate a visit record and invoice."

[0665] 2. Automating user transportation

[0666] The user enters the address information of a new user into a dedicated interface. This information is sent from the device to the server and stored along with existing user data. The server calculates the optimal shuttle route based on the received address information. This calculation uses a geographic information system (GIS) and shortest distance algorithms. The optimized shuttle plan is automatically generated and sent to the device from the server. The user can then view and implement the plan through the device.

[0667] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan. An example of a prompt would be, "Please enter the address information of new user A into the system and calculate the optimal transportation route."

[0668] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0669] For nighttime monitoring, AI cameras installed in rooms and hallways are used. The device monitors the user's movements in real time through the camera and collects the data. This data is sent from the device to a server and analyzed using an AI algorithm. Incidentally, if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge.

[0670] For example, if a user falls out of bed in the middle of the night, the device will immediately issue an alert and notify the caregiver via the server. An example of a prompt would be, "Monitor the user's movements via the camera at night, and issue an alert if any abnormal movements are detected."

[0671] 4. Gait analysis and rehabilitation follow-up

[0672] During the day, the device uses an installed AI camera to record the elderly person's walking pattern. This data is collected in real time and sent from the device to a server. The server uses an AI algorithm to analyze the walking pattern, and if an abnormal walking pattern is detected, it automatically generates a rehabilitation plan based on that. The generated rehabilitation plan is then sent to the device, and caregivers use it as a reference when carrying out rehabilitation.

[0673] For example, if an elderly person loses balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. An example of a prompt would be, "Use a camera to record the elderly person's walking pattern, and if an abnormal pattern is detected, generate a rehabilitation plan."

[0674] 5. AI robot conversation partner

[0675] As part of dementia prevention, users input their emotional state and recent interests and concerns into a dedicated interface. This information is sent from the device to a server, which then uses a generative AI model to generate an appropriate dialogue script. This script is then transferred to an AI robot via the device, which then interacts with the user accordingly. The dialogue log is then sent from the device to the server and saved as a reference for the next dialogue.

[0676] For example, if a user is interested in flowers, the server will use that information to generate a script that will allow the AI ​​robot to continue the conversation on the topic of flowers. An example of a prompt would be, "Please generate a dialogue script based on the user's emotional state and interests, and transfer it to the AI ​​robot."

[0677] As described above, this invention utilizes AI technology to improve the efficiency of nursing care facility operations and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[0678] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0679] 1. AI outsourcing of administrative tasks

[0680] Step 1

[0681] Users input data such as care records and visit times into a dedicated interface or tablet device. The input data includes the date and time of the visit, the details of the visit, and user information. This information is then sent from the device to the server.

[0682] Step 2

[0683] The server stores the received data in a central database, which centrally manages each user's care records and visiting times, providing efficient data access.

[0684] Step 3

[0685] The server analyzes the stored data using AI algorithms (for example, natural language processing or machine learning models). The input data is analyzed and administrative documents such as nursing care records and invoices are generated. The analyzed data is sent to a document generation tool, which creates documents in PDF format.

[0686] Step 4

[0687] The server notifies the terminal of the generated PDF document, and the user can check the generated document through the terminal and print it if necessary.

[0688] 2. Automating user transportation

[0689] Step 1

[0690] The user enters the address information of the new user into a dedicated interface. The entered information includes the address of the user's residence or facility. This information is then sent from the terminal to the server.

[0691] Step 2

[0692] The server stores the received address information together with existing user data in a central database, which unifies address information management and provides efficient data access.

[0693] Step 3

[0694] The server calculates the optimal pickup route based on the stored address data. It uses a geographic information system (GIS) and shortest distance algorithms to optimize the pickup order and route for each passenger. The calculation results are sent to the transportation planning tool, which generates a transportation plan.

[0695] Step 4

[0696] The server notifies the terminal of the generated transportation plan, and the user can check and implement the plan through the terminal.

[0697] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0698] Step 1

[0699] The device monitors users' movements in real time through AI cameras installed in rooms and hallways, which continuously transmit high-resolution video to the device.

[0700] Step 2

[0701] The device temporarily stores the video data collected by the camera and periodically transmits it to the server, including time and location information.

[0702] Step 3

[0703] The server analyzes the received video data using an AI algorithm, which uses a pre-trained model (e.g., an anomaly detection model) to detect abnormal activity. If an anomaly is detected, the information is sent to an alert system.

[0704] Step 4

[0705] When an abnormality is detected, the server generates an alert and sends it to the caregiver's smartphone app. The alert includes information on the date, time, and location of the abnormality.

[0706] 4. Gait analysis and rehabilitation follow-up

[0707] Step 1

[0708] The device uses an AI camera installed in the device to record the elderly person's walking pattern in real time, and the camera transmits the walking movement data to the device.

[0709] Step 2

[0710] The device temporarily stores the recorded data and periodically transmits it to a server, which includes details of walking timing and movement.

[0711] Step 3

[0712] The server analyzes the transmitted walking data using an AI algorithm, and if an abnormal walking pattern is detected, the information is sent to a rehabilitation plan generation tool.

[0713] Step 4

[0714] The server automatically generates a rehabilitation plan based on the analysis results, which is then sent to the device, where caregivers can use it as a reference when carrying out rehabilitation.

[0715] 5. AI robot conversation partner

[0716] Step 1

[0717] Users input their emotional state and recent interests into a dedicated interface. The input data includes emotional state, interests, and user profile information. This information is then sent from the device to the server.

[0718] Step 2

[0719] The server uses a generative AI model to generate an appropriate dialogue script based on the received data. The generated script is based on the user's input data and the model's learning results.

[0720] Step 3

[0721] The server transfers the generated dialogue script to the terminal, which then sends it to the AI ​​robot, which then dialogues with the user according to the received script.

[0722] Step 4

[0723] The device records the conversation log and periodically sends it to the server, where it is saved as a reference for the next conversation.

[0724] (Application example 1)

[0725] 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."

[0726] Current factory operations involve a wide range of tasks, including production management, logistics management, and safety monitoring, and many labor-intensive tasks are required to perform them efficiently. These tasks are typically performed manually, which can lead to errors and reduced efficiency. Furthermore, monitoring to ensure worker safety is often performed manually, resulting in the risk of accidents. Therefore, there is a need for a system that can automate these tasks and improve efficiency and safety.

[0727] 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.

[0728] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, a means for collecting data, a means for analyzing the collected data, a means for generating technical proposals, and a means for displaying the generated proposals. This enables efficient production management and logistics management in factories and automation of safety monitoring. Furthermore, the anomaly detection and proposal generation functions can improve work efficiency in factories and ensure the safety of workers.

[0729] "Data collection means" refers to devices and functions that use various sensors and input devices to acquire production data, attendance information, logistics information, worker behavior data, and the like within a factory.

[0730] The "automatic business document generation means" refers to a device or function that automatically generates business documents such as daily reports, attendance sheets, and proposals based on input data.

[0731] The "storage and notification means" refers to a device or function that stores the generated business documents and analysis results and notifies the relevant staff and systems of their contents.

[0732] "Data analysis means" refers to devices or functions that analyze collected data, detect trends and anomalies in the data, and generate technical proposals and optimization plans.

[0733] The "technical proposal generation means" refers to a device or function that automatically generates technical proposals such as measures to improve the efficiency of factory operations, safety measures, etc., based on the analyzed data.

[0734] The "proposal display means" is a device or function for displaying the generated proposals and improvement measures in a format that is easy for factory staff to understand.

[0735] The "logistics route optimization means" is a device or function that calculates the optimal transportation route for materials and products based on input address information and logistics data, and generates an efficient logistics schedule.

[0736] "Camera means" refers to a device or function that monitors a specific area in a factory in real time and captures the operations of workers and machines.

[0737] An "abnormality detection means" is a device or function that analyzes monitored data, detects abnormal behavior or events, and notifies the user of such.

[0738] This invention is a comprehensive system aimed at improving efficiency and safety in factory operations. The system has the function of automatically generating, saving, and notifying business documents based on data input by users. It also has multiple automated functions such as optimizing logistics routes, safety monitoring, and analyzing worker movements and generating proposals.

[0739] The system includes the following major hardware and software components:

[0740] Cameras: Monitor specific areas of the factory in real time and capture activity.

[0741] RFID tag reader: Obtains location information for items and materials.

[0742] Server: Analyzes and stores data. Uses AI frameworks such as Python and TensorFlow.

[0743] Smartphone: Displays and notifies results.

[0744] 1. Data Collection

[0745] Users collect data from various sensors (cameras, RFID tags, etc.) and input devices. For example, they can obtain production data, attendance information, logistics information, and worker behavior data in a factory in real time.

[0746] 2. Data Analysis

[0747] The collected data is sent to a server and analyzed using AI models, using AI frameworks such as Python and TensorFlow to detect trends and anomalies in the data and generate technical recommendations and optimization plans.

[0748] 3. Notification and reflection of results

[0749] The analysis results and generated suggestions are sent to smartphones or other devices. For example, they may include suggestions regarding working hours and production efficiency, optimal logistics routes, and safety measures. This allows users to immediately check this information and take appropriate action.

[0750] Specific examples

[0751] During production line work in a factory, cameras detect when a worker's movements go outside the control range and send an immediate notification to prevent accidents. The system also analyzes production and attendance data from the past week to generate suggestions for improving efficiency. Furthermore, it recalculates optimal logistics routes and generates schedules based on the latest sensor information.

[0752] Prompt Sentence Examples

[0753] "Analyze production and attendance data from the past week and generate suggestions for improving efficiency."

[0754] "Based on the latest sensor information, recalculate the optimal logistics route and generate a schedule."

[0755] These prompts allow the system to provide optimal suggestions for efficient and safe factory operations.

[0756] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0757] Step 1:

[0758] Users collect data in factories using sensors, cameras, RFID tag readers, etc. This collected data includes production data, logistics data, attendance information, worker behavior data, etc. Real-time data is obtained from sensors and cameras as input, and this data is sent to a server as output.

[0759] Step 2:

[0760] The server analyzes the received data. Python and AI frameworks such as TensorFlow are used for the analysis. Data processing includes preprocessing, normalization, and missing value completion. Data calculation involves applying anomaly detection and pattern recognition algorithms to detect abnormal behavior and opportunities for efficiency improvements. The collected data is read as input. Analysis results and suggestions are generated as output.

[0761] Step 3:

[0762] The server automatically generates optimal business documents based on the generated analysis results and proposals. These documents include daily production reports, attendance records, efficiency improvement proposals, logistics schedules, etc. The analysis results and proposals are used as inputs. The automatically generated business documents are obtained as output.

[0763] Step 4:

[0764] The server saves the generated business document in cloud storage or on a local disk. At the same time, it sends a notification to the relevant users and devices. The automatically generated business document is used as input. The saved document and notification are obtained as output.

[0765] Step 5:

[0766] The terminal displays the generated business documents, optimized routes, work suggestions, etc. to the user who received the notification. The user checks this and takes appropriate action if necessary. The notification and business documents from the server are used as inputs. The output is the display of information to the user.

[0767] Step 6:

[0768] The user inputs a prompt into the generative AI model in the system. For example, the user might input a prompt such as, "Please analyze the production data and attendance data from the past week and generate proposals for improving efficiency." Based on this prompt, the server analyzes the data again and generates new proposals. The prompt is used as input. The newly generated proposals are obtained as output.

[0769] Step 7:

[0770] The server notifies the user or terminal of the newly generated proposal and displays it again. This allows the user to operate the factory efficiently based on the latest information. The newly generated proposal is used as input. The output is a re-notification to the user and information display.

[0771] 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.

[0772] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. The system combines functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, providing rehabilitation support and injury prevention through gait analysis for elderly people, and an AI robot that acts as a conversation partner to prevent dementia, as well as an emotion engine. Specific embodiments for implementing the present invention are described below.

[0773] 1. AI outsourcing of administrative tasks

[0774] Users enter data such as care records, visit times, and care details into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the device. The user can check the generated documents through the device and print them as needed. For example, when a user's visit times and care details are entered, the server instantly creates an accurate visit record sheet and invoice based on that information. At this time, an emotion engine analyzes the user's emotions and can reflect them in the content of the documents as necessary.

[0775] 2. Automating user transportation

[0776] When a new user registers at a nursing facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal shuttle route. The calculated route is automatically reflected in the shuttle plan by the server and notified to the terminal. This allows for efficient shuttle service for multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall shuttle plan that is displayed on the terminal. In this case, the emotion engine considers the user's stress level and physical condition to select a comfortable shuttle route.

[0777] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0778] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, the device sends an alert to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge. For example, if the device detects movements that suggest the user has fallen out of bed in the middle of the night, it will immediately issue an alert and notify the caregiver via the server. This process includes a function in which an emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[0779] 4. Gait analysis and rehabilitation follow-up

[0780] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when implementing rehabilitation. For example, if an elderly person is increasingly losing their balance while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. At this time, the emotion engine also takes into account the user's level of anxiety and depression, and provides a rehabilitation plan that incorporates psychological support.

[0781] 5. AI robot conversation partner

[0782] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue and adjusts the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[0783] As described above, this invention is a system that utilizes AI technology and an emotion engine to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[0784] The processing flow will be explained below.

[0785] 1. AI outsourcing of administrative tasks

[0786] Processing Steps

[0787] Step 1:

[0788] Users input data such as care records, visit times, and care details into the system.

[0789] Step 2:

[0790] The server receives the entered data and stores it in a database.

[0791] Step 3:

[0792] The server uses an emotion engine to analyze the user's emotional state and executes algorithms to adjust the content of business documents based on that analysis.

[0793] Step 4:

[0794] The server automatically generates business documents such as nursing care records and invoices.

[0795] Step 5:

[0796] The server converts the generated business document into PDF format and saves it in a specified folder.

[0797] Step 6:

[0798] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[0799] 2. Automating user transportation

[0800] Processing Steps

[0801] Step 1:

[0802] The user enters the address information of the new user into the system.

[0803] Step 2:

[0804] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[0805] Step 3:

[0806] The server uses an emotion engine to consider the user's emotional state and adjust the optimal pick-up route and time.

[0807] Step 4:

[0808] The server automatically generates a transportation plan based on the optimized transportation route.

[0809] Step 5:

[0810] The server transmits the generated transportation plan to the terminal.

[0811] Step 6:

[0812] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[0813] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0814] Processing Steps

[0815] Step 1:

[0816] The device monitors the user's movements in real time through a camera at night.

[0817] Step 2:

[0818] The device analyzes the collected video data using AI algorithms.

[0819] Step 3:

[0820] When the device detects abnormal activity, it sends alert data to the server.

[0821] Step 4:

[0822] The server also analyzes the user's emotional state using an emotion engine to determine whether stress or anxiety is increasing.

[0823] Step 5:

[0824] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[0825] Step 6:

[0826] The device will display notifications on caregivers' smartphones, allowing them to respond quickly.

[0827] 4. Gait analysis and rehabilitation follow-up

[0828] Processing Steps

[0829] Step 1:

[0830] The device uses a camera to record the elderly person's walking pattern.

[0831] Step 2:

[0832] The device analyzes the collected data in real time and detects abnormal walking patterns.

[0833] Step 3:

[0834] When an abnormality is detected, the terminal transfers the analysis results to the server.

[0835] Step 4:

[0836] The server also analyzes the user's emotional state and anxiety level using an emotion engine.

[0837] Step 5:

[0838] The server executes an algorithm that determines the need for rehabilitation based on the analysis results and generates an appropriate rehabilitation plan.

[0839] Step 6:

[0840] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[0841] 5. AI robot conversation partner

[0842] Processing Steps

[0843] Step 1:

[0844] Users input information such as their emotional state and interests into the system.

[0845] Step 2:

[0846] The server runs an algorithm that generates a dialogue script based on the input information.

[0847] Step 3:

[0848] The server transfers the generated dialogue script to the AI ​​robot.

[0849] Step 4:

[0850] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[0851] Step 5:

[0852] The device uses an emotion engine to analyze the user's facial expressions and tone of voice during a conversation and adjusts the content and tone of the conversation as appropriate.

[0853] Step 6:

[0854] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[0855] Example 2

[0856] 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."

[0857] The present invention aims to provide a system that can address the shortage of personnel and the increasing workload in nursing care facilities and provide efficient and advanced services. In particular, the present invention focuses on streamlining specific tasks such as automating administrative tasks, optimizing transportation plans for users, detecting abnormalities at night, following up on rehabilitation through gait analysis, and preventing dementia through dialogue with users.

[0858] 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.

[0859] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, and a means for analyzing the user's emotional state and reflecting it in the generated documents, thereby enabling the automatic generation of care records and invoices and the reflection of the emotional state.

[0860] The system also includes a means for inputting the user's address information, a means for calculating the optimal shuttle route based on the input address information, a means for automatically generating and notifying a shuttle plan including the optimal shuttle route, and a means for selecting a shuttle route taking into consideration the user's stress level and physical condition, thereby enabling the creation of an efficient shuttle plan that takes into consideration the user.

[0861] Furthermore, the system includes a camera means for monitoring the user's movements in real time, a means for analyzing the monitored data and detecting abnormalities, a means for sending an alert when an abnormality is detected, and a means for analyzing the user's facial expressions and voice and responding quickly when emotional stress increases. This improves the accuracy of nighttime monitoring and abnormality detection, enabling a quick response.

[0862] "Client data" refers to information such as records about clients of care facilities, visit times, and care provided.

[0863] "Business documents" refer to documents related to nursing care work, such as nursing care records and invoices.

[0864] "Server" refers to a central computer that manages the overall processing of the system, including receiving, storing, analyzing, and notifying data.

[0865] "Terminal" refers to an input device or output device used by a user, and includes devices for inputting data and displaying notifications.

[0866] "Means for inputting data" refers to the interface that users and care staff use to input information such as care records and visit times into the system.

[0867] "Means for analyzing data" refers to software or algorithms that the server uses to perform the necessary processing based on the information entered.

[0868] "Means for automatically generating documents" refers to technology that automatically creates documents such as nursing care records and invoices based on input data.

[0869] "Means of notification" refers to a mechanism for informing users of generated documents, transportation plans, abnormality detection information, etc.

[0870] "Means for analyzing emotional state" refers to technology that analyzes a user's facial expressions and tone of voice to determine their emotions.

[0871] "Address information" refers to information about the user's base of residence, and is used to calculate the shuttle route.

[0872] "Means for calculating optimal shuttle routes" refers to an algorithm for calculating efficient shuttle routes based on the address information of existing and new users.

[0873] "Means that take stress levels and physical condition into consideration" refers to a system that analyzes the user's emotions and health condition and selects the optimal route accordingly.

[0874] "Camera means" refers to a photographic device installed in a room or corridor for monitoring the movements of users in real time.

[0875] "Means for detecting anomalies" refers to programs or algorithms that analyze collected data and identify unusual behavior or conditions.

[0876] "Means for sending alerts" refers to a mechanism for sending immediate notifications to relevant parties when an abnormality is detected.

[0877] A "dialogue script" refers to a document that describes a predefined conversation flow that an AI robot uses when interacting with a user.

[0878] This invention is a system that solves the labor shortage in nursing care facilities, improves operational efficiency, and enhances services. This system provides specific functions such as generating nursing care records and invoices, automating transportation plans for users, detecting abnormalities at night, providing rehabilitation follow-up, and preventing dementia through dialogue with users using an AI robot.

[0879] AI-powered administrative work

[0880] Users input data such as care records, visiting times, and care details into the system. This data is sent to the server via the terminal. The server saves the input data in a database and analyzes it using Python scripts. A template engine generates care records and invoices, which are then converted into PDF format using the PDFKit library. The generated documents are sent to the terminal, where the user can check them and print them if necessary. The emotion engine can analyze the user's emotional state and reflect it in the document content.

[0881] For example, when a user's visit time and care details are entered, the server instantly creates an accurate visit record and invoice based on that information. The emotion engine analyzes the user's emotions and reflects them in the data.

[0882] Example prompt sentence:

[0883] Visiting time: October 1, 2023, 14:00-15:00, Care content: Bathing assistance. User A's emotional state: Relaxed.

[0884] Automated transportation for users

[0885] When a new user registers at a care facility, the user enters their address information into the system. The device sends the input data to the server. The server combines the existing user data with the new data and calculates the optimal shuttle route using the Google Maps API. The calculated route is reflected in the shuttle plan by the template engine, converted into PDF format, and notified to the device. The emotion engine selects the shuttle route taking into account the user's stress level and physical condition.

[0886] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route for existing users B and C and displays the transportation plan on the terminal.

[0887] Example prompt sentence:

[0888] New user X's address: 1-1-1 Nishi-Shinjuku, Shinjuku-ku, Tokyo. Existing user Y's address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo, and user Z's address: 1-4-5 Yurakucho, Chiyoda-ku, Tokyo. User Y's emotional state: stress.

[0889] Nighttime monitoring with AI cameras to detect abnormalities

[0890] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is sent to a server, which analyzes it using AI libraries such as TensorFlow. If abnormal movements are detected, an alert is sent immediately to the caregiver's smartphone app. The emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[0891] As a specific example, if the device detects a user falling out of bed in the middle of the night, it will issue an alert on the spot and notify caregivers via the server.

[0892] Example prompt sentence:

[0893] The nighttime surveillance camera detects abnormal movement. User A is seen falling out of bed. Emotional state: High stress.

[0894] Gait analysis and rehabilitation follow-up

[0895] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is sent to a server, which analyzes the data using AI libraries such as TensorFlow. If an abnormal walking pattern is detected, the server automatically generates a rehabilitation plan and documents it using a template engine. The generated rehabilitation plan is converted to PDF format and sent to the device. The emotion engine provides a rehabilitation plan taking into account the user's level of anxiety and depression.

[0896] As a specific example, if an elderly person is losing their balance while walking more frequently, the server will analyze the data, create a rehabilitation plan, and notify the device.

[0897] Example prompt sentence:

[0898] Elderly person B loses balance while walking three times per hour. Emotional state: high anxiety.

[0899] AI robot conversation partner

[0900] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. The input information is sent to a server, which uses a natural language processing engine to generate a dialogue script. The generated script is transferred to the AI ​​robot, which then converses with the user via the device. The dialogue log is sent to the server and saved as reference for the next dialogue. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue, adjusting the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[0901] As a specific example, if a user is interested in flowers, the server will use that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[0902] Example prompt sentence:

[0903] User C's interest: flowers. Emotional state: joy.

[0904] The above is an embodiment of the present invention, which can improve the efficiency of operations at nursing care facilities and provide advanced services.

[0905] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0906] 1. AI outsourcing of administrative tasks

[0907] Processing Steps

[0908] Step 1:

[0909] The user opens the system's web form and enters data such as care records, visit times, and care details.

[0910] Input: Care records, visiting time, care contents

[0911] Output: Formatted data to terminal

[0912] Step 2:

[0913] The terminal formats the input data and sends it to the server.

[0914] Input: Formatted data

[0915] Output: Data sent to the server

[0916] Step 3:

[0917] The server stores the received data in a MySQL database.

[0918] Input: Received data

[0919] Output: Data stored in the database

[0920] Step 4:

[0921] The server analyzes the stored data using Python scripts.

[0922] Input: Data in the database

[0923] Output: Analysis results

[0924] Step 5:

[0925] The server uses a template engine to generate care records and bills.

[0926] Input: Analysis results

[0927] Output: The generated document

[0928] Step 6:

[0929] The server converts the generated document into PDF format using the PDFKit library and sends a notification to the device.

[0930] Input: Generated document

[0931] Output: Converted document as PDF, notification to device

[0932] Step 7:

[0933] The device displays the notification to the user as a pop-up message.

[0934] Input: Notification to device

[0935] Output: Display notification to the user

[0936] Step 8:

[0937] The user checks the generated document and prints it out on a printer if necessary.

[0938] Input: Popup message

[0939] Output: Printed document

[0940] 2. Automating user transportation

[0941] Processing Steps

[0942] Step 1:

[0943] A user logs into the system and enters the address information for a new user.

[0944] Input: New user's address information

[0945] Output: Formatted data to terminal

[0946] Step 2:

[0947] The terminal formats the address data and sends it to the server.

[0948] Input: Formatted address data

[0949] Output: Data sent to the server

[0950] Step 3:

[0951] The server uses Python and the Google Maps API to integrate the address information of new and old users and calculate the optimal shuttle route.

[0952] Input: Integrated address data

[0953] Output: Calculated pickup route

[0954] Step 4:

[0955] The server creates a transportation plan using a template engine based on the route calculation results.

[0956] Input: Calculated pickup route

[0957] Output: Transportation plan

[0958] Step 5:

[0959] The server converts the generated transportation plan into PDF format using the PDFKit library and sends a notification to the terminal.

[0960] Input: Transportation Plan

[0961] Output: Converted plan as PDF, notification to device

[0962] Step 6:

[0963] The terminal displays a notification of the transportation plan to the user as a pop-up message.

[0964] Input: Notification to device

[0965] Output: Display notification to the user

[0966] 3. Nighttime monitoring with AI cameras for detecting anomalies

[0967] Processing Steps

[0968] Step 1:

[0969] The device streams footage from cameras installed in rooms and hallways and analyzes it in real time.

[0970] Input: Camera image

[0971] Output: Real-time analytics data

[0972] Step 2:

[0973] The terminal transmits the analysis results to the server as appropriate.

[0974] Input: Parsed data

[0975] Output: Data sent to the server

[0976] Step 3:

[0977] The server analyzes the data using AI libraries such as TensorFlow to identify abnormal behavior.

[0978] Input: Parsed data

[0979] Output: Anomaly detection information

[0980] Step 4:

[0981] If the server detects an abnormality, it will notify the caregiver's smartphone app using a real-time database such as Firebase.

[0982] Input: Anomaly detection information

[0983] Output: Notification to care staff

[0984] 4. Gait analysis and rehabilitation follow-up

[0985] Processing Steps

[0986] Step 1:

[0987] The device collects footage from cameras installed in rooms and hallways and records the elderly person's walking patterns.

[0988] Input: Camera image

[0989] Output: Recorded walking data

[0990] Step 2:

[0991] The terminal transmits the collected data to the server as appropriate.

[0992] Input: Gait data

[0993] Output: Data sent to the server

[0994] Step 3:

[0995] The server analyzes the data using AI libraries such as TensorFlow to detect any abnormal walking patterns.

[0996] Input: Collected data

[0997] Output: Analysis results

[0998] Step 4:

[0999] If the server detects an abnormality, it automatically generates a rehabilitation plan and documents it using a template engine.

[1000] Input: Analysis results

[1001] Output: Rehabilitation plan

[1002] Step 5:

[1003] The server converts the generated rehabilitation plan into PDF format and sends a notification to the terminal.

[1004] Input: Rehabilitation plan

[1005] Output: Converted plan as PDF, notification to device

[1006] Step 6:

[1007] The device displays the rehabilitation plan to the caregiver as a pop-up message.

[1008] Input: Notification to device

[1009] Output: Notification to be displayed to care staff

[1010] 5. AI robot conversation partner

[1011] Processing Steps

[1012] Step 1:

[1013] The user enters their emotional state and recent interests and concerns on the system's input screen.

[1014] Input: User's emotional state and interests

[1015] Output: Formatted data to terminal

[1016] Step 2:

[1017] The terminal formats the input data and sends it to the server.

[1018] Input: Formatted data

[1019] Output: Data sent to the server

[1020] Step 3:

[1021] The server uses a natural language processing engine (e.g., GPT-3) to generate an appropriate dialogue script.

[1022] Input: Data sent

[1023] Output: Generated dialogue script

[1024] Step 4:

[1025] The server transfers the generated script to the terminal and conveys the dialogue content to the AI ​​robot.

[1026] Input: Interactive script

[1027] Output: The transferred script

[1028] Step 5:

[1029] The device controls the AI ​​robot and engages in a dialogue with the user, processing what the robot is saying and the user's responses in real time.

[1030] Input: Transferred script, user response

[1031] Output: Interactions performed

[1032] Step 6:

[1033] The terminal generates a dialogue log and transmits it to the server as appropriate.

[1034] Input: Interaction log data

[1035] Output: Log data sent to the server

[1036] Step 7:

[1037] The server saves the dialogue log and uses it as a reference for generating the next dialogue script.

[1038] Input: Log data sent

[1039] Output: Saved log data

[1040] (Application example 2)

[1041] 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."

[1042] Currently, nighttime monitoring in factories still relies on human labor, making it difficult to respond quickly when an abnormality occurs. Furthermore, machine failures and employee stress cannot be detected in real time, often delaying effective countermeasures. This results in problems such as reduced work efficiency and an increased risk of accidents. Therefore, there is a need to automate nighttime factory monitoring and detect abnormalities and stress conditions early.

[1043] 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.

[1044] In this invention, the server includes means for monitoring user movements in real time using a camera, means for analyzing the monitored data to detect abnormalities, means for notifying when an abnormality is detected, means for analyzing emotions and improving responses to detected abnormalities, and means for sending notifications to smartphones. This automates nighttime monitoring in factories, enabling early detection of abnormalities and stress states and prompt responses.

[1045] "Means for inputting user data" refers to a device or interface that allows input of information about people to be monitored in the factory and their work status.

[1046] "Means for automatically generating business documents" refers to a system that automatically creates necessary reports and notification documents based on input user data.

[1047] "Means for storing and notifying generated business documents" refers to a system that stores created documents and reports in a database and sends notifications to appropriate terminals when necessary.

[1048] "Means for monitoring user movements in real time using cameras" refers to a device or system that uses cameras installed in a factory to monitor the movements of the person being monitored in real time.

[1049] "Means for analyzing monitoring data and detecting abnormalities" refers to algorithms or systems that analyze monitoring data collected by cameras and detect unnatural movements or abnormal conditions.

[1050] "Means for notifying when an abnormality is detected" refers to a system that sends an alert to a person in charge or a manager when an abnormal situation is detected.

[1051] The "means of analyzing emotions and improving responses to detected abnormalities" refers to a system that analyzes the facial expressions and movements of the person being monitored, evaluates their stress level and changes in emotions, and suggests appropriate responses based on that.

[1052] "Means for sending notifications to smartphones" is a system for sending important alerts and information directly to the smartphones of responsible personnel.

[1053] This invention is a system that automates nighttime monitoring in factory environments, detects abnormalities and stress levels early, and enables rapid response. The system analyzes camera footage in real time, detects abnormal behavior and emotional states, and sends notifications to smartphones.

[1054] First, the user inputs information about the workers and equipment to be monitored in the factory. This data is then sent to the server and stored in a database.

[1055] For real-time video monitoring, multiple cameras are installed, and the device acquires video data from these cameras. This video data is sent to a server and analyzed using a specific algorithm. Specifically, OpenCV is used to process the images and detect abnormal movements and situations.

[1056] Furthermore, the server uses an emotion analysis model powered by TensorFlow to analyze the facial expressions and movements of the monitored subject, assessing their stress level, and if a change in emotion is detected, taking this into account when responding to an anomaly.

[1057] When an anomaly is detected, the server uses a notification service such as Twilio to instantly send an alert to the agent's smartphone, including details about the anomaly and the detected emotional state, allowing the agent to respond quickly and appropriately.

[1058] As a concrete example, imagine a factory where surveillance cameras are installed during the night shift. The cameras monitor the work area in real time at night, detecting any abnormal activity or equipment malfunctions. They also analyze employees' faces and behavior to assess whether they are showing signs of stress or anxiety. This information is sent to a server in real time, and the analysis results are sent to the person in charge's smartphone. The person in charge can then immediately go to the site and resolve the problem quickly.

[1059] Below are some example prompts for a generative AI model:

[1060] "Please create a program that analyzes the stress levels of factory workers in real time and notifies their smartphones if an abnormality is detected. The hardware required will be cameras and servers, the software will be OpenCV and TensorFlow, and the notification service will be Twilio."

[1061] In this way, the system of the present invention highly automates nighttime monitoring work within a factory, enabling rapid response to problems.

[1062] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1063] Step 1:

[1064] The user inputs information about the workers and equipment to be monitored. Data input is performed using a dedicated interface, and this information is sent to the server and stored in a database. The input for this step is detailed information about the workers and equipment, and the output is the data stored on the server.

[1065] Step 2:

[1066] The terminal acquires images in real time from cameras installed in the factory. The cameras are in operation 24 hours a day, and the image data sent is transmitted to the server in real time. The input of this step is the camera image, and the output is the image data sent to the server.

[1067] Step 3:

[1068] To analyze the video data received by the server, image processing is performed using OpenCV. Specifically, the video frames are converted to grayscale and analyzed to detect abnormal movements or situations. The input of this step is real-time video data, and the output is a judgment result on whether there is an abnormality.

[1069] Step 4:

[1070] The server uses TensorFlow to perform emotion analysis on the received video data. It detects the target's face, evaluates their facial expressions and movements in real time, and measures changes in stress and emotion. The input for this step is the analyzed video frames, and the output is data on stress levels and emotional states.

[1071] Step 5:

[1072] If the server detects an anomaly or stress state, it immediately generates a notification message using Twilio and sends it to the person in charge's smartphone. This message includes details of the anomaly and information about the person's emotional state. The input of this step is the anomaly detection result and the emotion analysis result, and the output is the sent notification message.

[1073] Step 6:

[1074] The person in charge checks the notification message received on their smartphone and quickly heads to the site. Upon receiving this notification, they decide on a specific response method and quickly implement the necessary measures. The input of this step is the notification message, and the output is the implementation of the problem response at the site.

[1075] 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.

[1076] 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.

[1077] 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.

[1078] [Third embodiment]

[1079] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1080] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1081] 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).

[1082] 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.

[1083] 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.

[1084] 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).

[1085] 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.

[1086] 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.

[1087] 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.

[1088] 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.

[1089] 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.

[1090] 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."

[1091] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. This system has functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, analyzing elderly people's gait to provide rehabilitation support and injury prevention, and an AI robot that acts as a conversation partner to prevent dementia. Specific embodiments for implementing the present invention are described below.

[1092] 1. AI outsourcing of administrative tasks

[1093] The user first enters data such as care records and visit times into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the terminal. The user can check the generated documents through the terminal and print them as needed. For example, when the visit times and care contents of a certain user are entered, the server instantly creates accurate visit record sheets and invoices based on that information.

[1094] 2. Automating user transportation

[1095] When a new user registers at a nursing care facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal transportation route. The calculated route is automatically reflected in the transportation plan by the server and notified to the terminal. This allows for efficient transportation of multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan that is displayed on the terminal.

[1096] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1097] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the care worker in charge. For example, if it detects a movement that could lead to the user falling out of bed in the middle of the night, the device will issue an alert on the spot and notify the care worker via the server.

[1098] 4. Gait analysis and rehabilitation follow-up

[1099] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when carrying out rehabilitation. For example, if an elderly person is losing their balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device.

[1100] 5. AI robot conversation partner

[1101] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[1102] As described above, the present invention is a system that utilizes AI technology to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[1103] The processing flow will be explained below.

[1104] 1. AI outsourcing of administrative tasks

[1105] Processing Steps

[1106] Step 1:

[1107] Users input data such as care records, visit times, and care details into the system.

[1108] Step 2:

[1109] The server receives the entered data and stores it in a database.

[1110] Step 3:

[1111] The server runs algorithms that automatically generate the necessary business documents (e.g., visit logs, invoices) based on the stored data.

[1112] Step 4:

[1113] The server converts the generated business document into PDF format and saves it in a specified folder.

[1114] Step 5:

[1115] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[1116] 2. Automating user transportation

[1117] Processing Steps

[1118] Step 1:

[1119] The user enters the address information of the new user into the system.

[1120] Step 2:

[1121] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[1122] Step 3:

[1123] The server automatically generates a transportation plan based on the optimized transportation route.

[1124] Step 4:

[1125] The server transmits the generated transportation plan to the terminal.

[1126] Step 5:

[1127] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[1128] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1129] Processing Steps

[1130] Step 1:

[1131] The device monitors the user's movements in real time through a camera at night.

[1132] Step 2:

[1133] The device analyzes the collected video data using AI algorithms.

[1134] Step 3:

[1135] When the device detects abnormal activity, it sends alert data to the server.

[1136] Step 4:

[1137] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[1138] Step 5:

[1139] The device will display notifications on caregivers' smartphones, allowing them to respond quickly to any abnormalities.

[1140] 4. Gait analysis and rehabilitation follow-up

[1141] Processing Steps

[1142] Step 1:

[1143] The device uses a camera to record the elderly person's walking pattern.

[1144] Step 2:

[1145] The device analyzes the collected data in real time and detects abnormal walking patterns.

[1146] Step 3:

[1147] When an abnormality is detected, the terminal transfers the analysis results to the server.

[1148] Step 4:

[1149] The server determines the need for rehabilitation based on the analysis results and executes an algorithm to generate an optimal rehabilitation plan.

[1150] Step 5:

[1151] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[1152] 5. AI robot conversation partner

[1153] Processing Steps

[1154] Step 1:

[1155] Users input information into the system, such as their emotional state, preferences, and recent events.

[1156] Step 2:

[1157] The server executes an algorithm that generates a dialogue script based on the input information.

[1158] Step 3:

[1159] The server transfers the generated dialogue script to the AI ​​robot.

[1160] Step 4:

[1161] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[1162] Step 5:

[1163] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[1164] Example 1

[1165] 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."

[1166] Staff shortages are a serious problem in modern nursing care facilities, resulting in excessive workloads and concerns about a decline in the quality of services. Additionally, issues such as ensuring the safety of users, effective rehabilitation, and dementia prevention are also important. In particular, reducing the administrative burden, streamlining transportation plans, nighttime monitoring, rehabilitation follow-up through gait analysis, and dementia prevention through dialogue are all important issues that must be resolved independently. Conventional systems can only address these issues individually, so integrated and efficient solutions are needed.

[1167] 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.

[1168] In this invention, the server includes: means for inputting user data; means for automatically generating business documents based on the input user data; means for saving and notifying the generated business documents; means for inputting user address information; means for calculating an optimal shuttle route based on the input address information; means for automatically generating and notifying a shuttle plan including the optimal shuttle route; camera means for monitoring the user's movements in real time; means for analyzing the monitored data and detecting abnormalities; means for sending an alert when an abnormality is detected; means for recording and analyzing the user's walking pattern; means for generating and notifying a rehabilitation plan based on the analysis results; means for inputting data on emotional state and interests; means for generating dialogue content based on the input data and transferring it to the AI ​​robot; and means for saving the dialogue log and using it as a reference for the next dialogue. This enables a system that can simultaneously solve issues such as alleviating labor shortages in nursing care facilities, improving work efficiency, ensuring user safety, providing advanced rehabilitation support, and preventing dementia.

[1169] "Means for inputting user data" refers to an interface or device that allows care facility staff to input information about users, such as care records and visiting times.

[1170] "Means for automatically generating business documents" refers to algorithms or programs for automatically creating business documents such as nursing care records and invoices based on input user data.

[1171] The "means for storing and notifying business documents" is a system component for storing automatically generated business documents in electronic form and notifying appropriate parties of the same.

[1172] "Means for inputting address information" refers to an interface or device for inputting address information of a user's residence or facility into the system.

[1173] The "means for calculating a shuttle route" is an algorithm or program for calculating the optimal shuttle route based on the input address information.

[1174] The "means for automatically generating and notifying a transportation plan" is a system component for creating a transportation plan based on an optimized transportation route and notifying relevant parties of the plan.

[1175] "Camera Means" means camera devices and associated systems used to monitor user movements in real time.

[1176] "Means for analyzing data and detecting abnormalities" refers to algorithms or programs that analyze monitoring data collected by cameras and recognize abnormal conditions or movements when they occur.

[1177] An "alert sending means" is a system component that sends warnings or notifications to relevant parties when an abnormality is detected.

[1178] The "means for recording and analyzing walking patterns" refers to an algorithm or program that records the user's walking movements with a camera and analyzes the data to identify abnormalities or areas for improvement.

[1179] The "means for generating and notifying a rehabilitation plan" is a system component for creating an effective rehabilitation plan based on the analyzed walking data and notifying the relevant parties of the plan.

[1180] "Means for inputting emotional state and interest data" refers to an interface or device for inputting the user's current emotional state and interests into the system.

[1181] "Means for generating dialogue content and transmitting it to the AI ​​robot" refers to algorithms or programs that generate dialogue scripts for natural dialogue based on input emotional state and interest data, and transmit them to the AI ​​robot.

[1182] "Means for saving dialogue logs and using them as a reference for the next dialogue" refers to a system component that records the content of dialogue with an AI robot and saves it for reference during the next dialogue.

[1183] The present invention is a system that resolves the shortage of personnel in nursing care facilities, improves operational efficiency, and enhances services, and specific embodiments thereof will be described below.

[1184] 1. AI outsourcing of administrative tasks

[1185] Users first enter data such as care records and visit times into a dedicated interface or tablet device. This data is sent from the device to a server and stored in a central database. The server analyzes the received data and uses AI algorithms to automatically generate business documents such as care record sheets and invoices. The generated documents are converted to PDF format, and a notification is sent from the server to the device. The user can then view the generated documents through the device and print them if necessary.

[1186] For example, when the visit time and care details for user A are entered, the server instantly creates an accurate visit record and invoice based on that information. An example of a prompt would be, "Please enter the visit time and care details for the user into the system and generate a visit record and invoice."

[1187] 2. Automating user transportation

[1188] The user enters the address information of a new user into a dedicated interface. This information is sent from the device to the server and stored along with existing user data. The server calculates the optimal shuttle route based on the received address information. This calculation uses a geographic information system (GIS) and shortest distance algorithms. The optimized shuttle plan is automatically generated and sent to the device from the server. The user can then view and implement the plan through the device.

[1189] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan. An example of a prompt would be, "Please enter the address information of new user A into the system and calculate the optimal transportation route."

[1190] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1191] For nighttime monitoring, AI cameras installed in rooms and hallways are used. The device monitors the user's movements in real time through the camera and collects the data. This data is sent from the device to a server and analyzed using an AI algorithm. Incidentally, if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge.

[1192] For example, if a user falls out of bed in the middle of the night, the device will immediately issue an alert and notify the caregiver via the server. An example of a prompt would be, "Monitor the user's movements via the camera at night, and issue an alert if any abnormal movements are detected."

[1193] 4. Gait analysis and rehabilitation follow-up

[1194] During the day, the device uses an installed AI camera to record the elderly person's walking pattern. This data is collected in real time and sent from the device to a server. The server uses an AI algorithm to analyze the walking pattern, and if an abnormal walking pattern is detected, it automatically generates a rehabilitation plan based on that. The generated rehabilitation plan is then sent to the device, and caregivers use it as a reference when carrying out rehabilitation.

[1195] For example, if an elderly person loses balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. An example of a prompt would be, "Use a camera to record the elderly person's walking pattern, and if an abnormal pattern is detected, generate a rehabilitation plan."

[1196] 5. AI robot conversation partner

[1197] As part of dementia prevention, users input their emotional state and recent interests and concerns into a dedicated interface. This information is sent from the device to a server, which then uses a generative AI model to generate an appropriate dialogue script. This script is then transferred to an AI robot via the device, which then interacts with the user accordingly. The dialogue log is then sent from the device to the server and saved as a reference for the next dialogue.

[1198] For example, if a user is interested in flowers, the server will use that information to generate a script that will allow the AI ​​robot to continue the conversation on the topic of flowers. An example of a prompt would be, "Please generate a dialogue script based on the user's emotional state and interests, and transfer it to the AI ​​robot."

[1199] As described above, this invention utilizes AI technology to improve the efficiency of nursing care facility operations and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[1200] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1201] 1. AI outsourcing of administrative tasks

[1202] Step 1

[1203] Users input data such as care records and visit times into a dedicated interface or tablet device. The input data includes the date and time of the visit, the details of the visit, and user information. This information is then sent from the device to the server.

[1204] Step 2

[1205] The server stores the received data in a central database, which centrally manages each user's care records and visiting times, providing efficient data access.

[1206] Step 3

[1207] The server analyzes the stored data using AI algorithms (for example, natural language processing or machine learning models). The input data is analyzed and administrative documents such as nursing care records and invoices are generated. The analyzed data is sent to a document generation tool, which creates documents in PDF format.

[1208] Step 4

[1209] The server notifies the terminal of the generated PDF document, and the user can check the generated document through the terminal and print it if necessary.

[1210] 2. Automating user transportation

[1211] Step 1

[1212] The user enters the address information of the new user into a dedicated interface. The entered information includes the address of the user's residence or facility. This information is then sent from the terminal to the server.

[1213] Step 2

[1214] The server stores the received address information together with existing user data in a central database, which unifies address information management and provides efficient data access.

[1215] Step 3

[1216] The server calculates the optimal pickup route based on the stored address data. It uses a geographic information system (GIS) and shortest distance algorithms to optimize the pickup order and route for each passenger. The calculation results are sent to the transportation planning tool, which generates a transportation plan.

[1217] Step 4

[1218] The server notifies the terminal of the generated transportation plan, and the user can check and implement the plan through the terminal.

[1219] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1220] Step 1

[1221] The device monitors users' movements in real time through AI cameras installed in rooms and hallways, which continuously transmit high-resolution video to the device.

[1222] Step 2

[1223] The device temporarily stores the video data collected by the camera and periodically transmits it to the server, including time and location information.

[1224] Step 3

[1225] The server analyzes the received video data using an AI algorithm, which uses a pre-trained model (e.g., an anomaly detection model) to detect abnormal activity. If an anomaly is detected, the information is sent to an alert system.

[1226] Step 4

[1227] When an abnormality is detected, the server generates an alert and sends it to the caregiver's smartphone app. The alert includes information on the date, time, and location of the abnormality.

[1228] 4. Gait analysis and rehabilitation follow-up

[1229] Step 1

[1230] The device uses an AI camera installed in the device to record the elderly person's walking pattern in real time, and the camera transmits the walking movement data to the device.

[1231] Step 2

[1232] The device temporarily stores the recorded data and periodically transmits it to a server, which includes details of walking timing and movement.

[1233] Step 3

[1234] The server analyzes the transmitted walking data using an AI algorithm, and if an abnormal walking pattern is detected, the information is sent to a rehabilitation plan generation tool.

[1235] Step 4

[1236] The server automatically generates a rehabilitation plan based on the analysis results, which is then sent to the device, where caregivers can use it as a reference when carrying out rehabilitation.

[1237] 5. AI robot conversation partner

[1238] Step 1

[1239] Users input their emotional state and recent interests into a dedicated interface. The input data includes emotional state, interests, and user profile information. This information is then sent from the device to the server.

[1240] Step 2

[1241] The server uses a generative AI model to generate an appropriate dialogue script based on the received data. The generated script is based on the user's input data and the model's learning results.

[1242] Step 3

[1243] The server transfers the generated dialogue script to the terminal, which then sends it to the AI ​​robot, which then dialogues with the user according to the received script.

[1244] Step 4

[1245] The device records the conversation log and periodically sends it to the server, where it is saved as a reference for the next conversation.

[1246] (Application example 1)

[1247] 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."

[1248] Current factory operations involve a wide range of tasks, including production management, logistics management, and safety monitoring, and many labor-intensive tasks are required to perform them efficiently. These tasks are typically performed manually, which can lead to errors and reduced efficiency. Furthermore, monitoring to ensure worker safety is often performed manually, resulting in the risk of accidents. Therefore, there is a need for a system that can automate these tasks and improve efficiency and safety.

[1249] 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.

[1250] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, a means for collecting data, a means for analyzing the collected data, a means for generating technical proposals, and a means for displaying the generated proposals. This enables efficient production management and logistics management in factories and automation of safety monitoring. Furthermore, the anomaly detection and proposal generation functions can improve work efficiency in factories and ensure the safety of workers.

[1251] "Data collection means" refers to devices and functions that use various sensors and input devices to acquire production data, attendance information, logistics information, worker behavior data, and the like within a factory.

[1252] The "automatic business document generation means" refers to a device or function that automatically generates business documents such as daily reports, attendance sheets, and proposals based on input data.

[1253] The "storage and notification means" refers to a device or function that stores the generated business documents and analysis results and notifies the relevant staff and systems of their contents.

[1254] "Data analysis means" refers to devices or functions that analyze collected data, detect trends and anomalies in the data, and generate technical proposals and optimization plans.

[1255] The "technical proposal generation means" refers to a device or function that automatically generates technical proposals such as measures to improve the efficiency of factory operations, safety measures, etc., based on the analyzed data.

[1256] The "proposal display means" is a device or function for displaying the generated proposals and improvement measures in a format that is easy for factory staff to understand.

[1257] The "logistics route optimization means" is a device or function that calculates the optimal transportation route for materials and products based on input address information and logistics data, and generates an efficient logistics schedule.

[1258] "Camera means" refers to a device or function that monitors a specific area in a factory in real time and captures the operations of workers and machines.

[1259] An "abnormality detection means" is a device or function that analyzes monitored data, detects abnormal behavior or events, and notifies the user of such.

[1260] This invention is a comprehensive system aimed at improving efficiency and safety in factory operations. The system has the function of automatically generating, saving, and notifying business documents based on data input by users. It also has multiple automated functions such as optimizing logistics routes, safety monitoring, and analyzing worker movements and generating proposals.

[1261] The system includes the following major hardware and software components:

[1262] Cameras: Monitor specific areas of the factory in real time and capture activity.

[1263] RFID tag reader: Obtains location information for items and materials.

[1264] Server: Analyzes and stores data. Uses AI frameworks such as Python and TensorFlow.

[1265] Smartphone: Displays and notifies results.

[1266] 1. Data Collection

[1267] Users collect data from various sensors (cameras, RFID tags, etc.) and input devices. For example, they can obtain production data, attendance information, logistics information, and worker behavior data in a factory in real time.

[1268] 2. Data Analysis

[1269] The collected data is sent to a server and analyzed using AI models, using AI frameworks such as Python and TensorFlow to detect trends and anomalies in the data and generate technical recommendations and optimization plans.

[1270] 3. Notification and reflection of results

[1271] The analysis results and generated suggestions are sent to smartphones or other devices. For example, they may include suggestions regarding working hours and production efficiency, optimal logistics routes, and safety measures. This allows users to immediately check this information and take appropriate action.

[1272] Specific examples

[1273] During production line work in a factory, cameras detect when a worker's movements go outside the control range and send an immediate notification to prevent accidents. The system also analyzes production and attendance data from the past week to generate suggestions for improving efficiency. Furthermore, it recalculates optimal logistics routes and generates schedules based on the latest sensor information.

[1274] Prompt Sentence Examples

[1275] "Analyze production and attendance data from the past week and generate suggestions for improving efficiency."

[1276] "Based on the latest sensor information, recalculate the optimal logistics route and generate a schedule."

[1277] These prompts allow the system to provide optimal suggestions for efficient and safe factory operations.

[1278] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1279] Step 1:

[1280] Users collect data in factories using sensors, cameras, RFID tag readers, etc. This collected data includes production data, logistics data, attendance information, worker behavior data, etc. Real-time data is obtained from sensors and cameras as input, and this data is sent to a server as output.

[1281] Step 2:

[1282] The server analyzes the received data. Python and AI frameworks such as TensorFlow are used for the analysis. Data processing includes preprocessing, normalization, and missing value completion. Data calculation involves applying anomaly detection and pattern recognition algorithms to detect abnormal behavior and opportunities for efficiency improvements. The collected data is read as input. Analysis results and suggestions are generated as output.

[1283] Step 3:

[1284] The server automatically generates optimal business documents based on the generated analysis results and proposals. These documents include daily production reports, attendance records, efficiency improvement proposals, logistics schedules, etc. The analysis results and proposals are used as inputs. The automatically generated business documents are obtained as output.

[1285] Step 4:

[1286] The server saves the generated business document in cloud storage or on a local disk. At the same time, it sends a notification to the relevant users and devices. The automatically generated business document is used as input. The saved document and notification are obtained as output.

[1287] Step 5:

[1288] The terminal displays the generated business documents, optimized routes, work suggestions, etc. to the user who received the notification. The user checks this and takes appropriate action if necessary. The notification and business documents from the server are used as inputs. The output is the display of information to the user.

[1289] Step 6:

[1290] The user inputs a prompt into the generative AI model in the system. For example, the user might input a prompt such as, "Please analyze the production data and attendance data from the past week and generate proposals for improving efficiency." Based on this prompt, the server analyzes the data again and generates new proposals. The prompt is used as input. The newly generated proposals are obtained as output.

[1291] Step 7:

[1292] The server notifies the user or terminal of the newly generated proposal and displays it again. This allows the user to operate the factory efficiently based on the latest information. The newly generated proposal is used as input. The output is a re-notification to the user and information display.

[1293] 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.

[1294] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. The system combines functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, providing rehabilitation support and injury prevention through gait analysis for elderly people, and an AI robot that acts as a conversation partner to prevent dementia, as well as an emotion engine. Specific embodiments for implementing the present invention are described below.

[1295] 1. AI outsourcing of administrative tasks

[1296] Users enter data such as care records, visit times, and care details into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the device. The user can check the generated documents through the device and print them as needed. For example, when a user's visit times and care details are entered, the server instantly creates an accurate visit record sheet and invoice based on that information. At this time, an emotion engine analyzes the user's emotions and can reflect them in the content of the documents as necessary.

[1297] 2. Automating user transportation

[1298] When a new user registers at a nursing facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal shuttle route. The calculated route is automatically reflected in the shuttle plan by the server and notified to the terminal. This allows for efficient shuttle service for multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall shuttle plan that is displayed on the terminal. In this case, the emotion engine considers the user's stress level and physical condition to select a comfortable shuttle route.

[1299] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1300] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, the device sends an alert to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge. For example, if the device detects movements that suggest the user has fallen out of bed in the middle of the night, it will immediately issue an alert and notify the caregiver via the server. This process includes a function in which an emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[1301] 4. Gait analysis and rehabilitation follow-up

[1302] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when implementing rehabilitation. For example, if an elderly person is increasingly losing their balance while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. At this time, the emotion engine also takes into account the user's level of anxiety and depression, and provides a rehabilitation plan that incorporates psychological support.

[1303] 5. AI robot conversation partner

[1304] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue and adjusts the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[1305] As described above, this invention is a system that utilizes AI technology and an emotion engine to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[1306] The processing flow will be explained below.

[1307] 1. AI outsourcing of administrative tasks

[1308] Processing Steps

[1309] Step 1:

[1310] Users input data such as care records, visit times, and care details into the system.

[1311] Step 2:

[1312] The server receives the entered data and stores it in a database.

[1313] Step 3:

[1314] The server uses an emotion engine to analyze the user's emotional state and executes algorithms to adjust the content of business documents based on that analysis.

[1315] Step 4:

[1316] The server automatically generates business documents such as nursing care records and invoices.

[1317] Step 5:

[1318] The server converts the generated business document into PDF format and saves it in a specified folder.

[1319] Step 6:

[1320] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[1321] 2. Automating user transportation

[1322] Processing Steps

[1323] Step 1:

[1324] The user enters the address information of the new user into the system.

[1325] Step 2:

[1326] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[1327] Step 3:

[1328] The server uses an emotion engine to consider the user's emotional state and adjust the optimal pick-up route and time.

[1329] Step 4:

[1330] The server automatically generates a transportation plan based on the optimized transportation route.

[1331] Step 5:

[1332] The server transmits the generated transportation plan to the terminal.

[1333] Step 6:

[1334] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[1335] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1336] Processing Steps

[1337] Step 1:

[1338] The device monitors the user's movements in real time through a camera at night.

[1339] Step 2:

[1340] The device analyzes the collected video data using AI algorithms.

[1341] Step 3:

[1342] When the device detects abnormal activity, it sends alert data to the server.

[1343] Step 4:

[1344] The server also analyzes the user's emotional state using an emotion engine to determine whether stress or anxiety is increasing.

[1345] Step 5:

[1346] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[1347] Step 6:

[1348] The device will display notifications on caregivers' smartphones, allowing them to respond quickly.

[1349] 4. Gait analysis and rehabilitation follow-up

[1350] Processing Steps

[1351] Step 1:

[1352] The device uses a camera to record the elderly person's walking pattern.

[1353] Step 2:

[1354] The device analyzes the collected data in real time and detects abnormal walking patterns.

[1355] Step 3:

[1356] When an abnormality is detected, the terminal transfers the analysis results to the server.

[1357] Step 4:

[1358] The server also analyzes the user's emotional state and anxiety level using an emotion engine.

[1359] Step 5:

[1360] The server executes an algorithm that determines the need for rehabilitation based on the analysis results and generates an appropriate rehabilitation plan.

[1361] Step 6:

[1362] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[1363] 5. AI robot conversation partner

[1364] Processing Steps

[1365] Step 1:

[1366] Users input information such as their emotional state and interests into the system.

[1367] Step 2:

[1368] The server runs an algorithm that generates a dialogue script based on the input information.

[1369] Step 3:

[1370] The server transfers the generated dialogue script to the AI ​​robot.

[1371] Step 4:

[1372] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[1373] Step 5:

[1374] The device uses an emotion engine to analyze the user's facial expressions and tone of voice during a conversation and adjusts the content and tone of the conversation as appropriate.

[1375] Step 6:

[1376] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[1377] Example 2

[1378] 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."

[1379] The present invention aims to provide a system that can address the shortage of personnel and the increasing workload in nursing care facilities and provide efficient and advanced services. In particular, the present invention focuses on streamlining specific tasks such as automating administrative tasks, optimizing transportation plans for users, detecting abnormalities at night, following up on rehabilitation through gait analysis, and preventing dementia through dialogue with users.

[1380] 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.

[1381] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, and a means for analyzing the user's emotional state and reflecting it in the generated documents, thereby enabling the automatic generation of care records and invoices and the reflection of the emotional state.

[1382] The system also includes a means for inputting the user's address information, a means for calculating the optimal shuttle route based on the input address information, a means for automatically generating and notifying a shuttle plan including the optimal shuttle route, and a means for selecting a shuttle route taking into consideration the user's stress level and physical condition, thereby enabling the creation of an efficient shuttle plan that takes into consideration the user.

[1383] Furthermore, the system includes a camera means for monitoring the user's movements in real time, a means for analyzing the monitored data and detecting abnormalities, a means for sending an alert when an abnormality is detected, and a means for analyzing the user's facial expressions and voice and responding quickly when emotional stress increases. This improves the accuracy of nighttime monitoring and abnormality detection, enabling a quick response.

[1384] "Client data" refers to information such as records about clients of care facilities, visit times, and care provided.

[1385] "Business documents" refer to documents related to nursing care work, such as nursing care records and invoices.

[1386] "Server" refers to a central computer that manages the overall processing of the system, including receiving, storing, analyzing, and notifying data.

[1387] "Terminal" refers to an input device or output device used by a user, and includes devices for inputting data and displaying notifications.

[1388] "Means for inputting data" refers to the interface that users and care staff use to input information such as care records and visit times into the system.

[1389] "Means for analyzing data" refers to software or algorithms that the server uses to perform the necessary processing based on the information entered.

[1390] "Means for automatically generating documents" refers to technology that automatically creates documents such as nursing care records and invoices based on input data.

[1391] "Means of notification" refers to a mechanism for informing users of generated documents, transportation plans, abnormality detection information, etc.

[1392] "Means for analyzing emotional state" refers to technology that analyzes a user's facial expressions and tone of voice to determine their emotions.

[1393] "Address information" refers to information about the user's base of residence, and is used to calculate the shuttle route.

[1394] "Means for calculating optimal shuttle routes" refers to an algorithm for calculating efficient shuttle routes based on the address information of existing and new users.

[1395] "Means that take stress levels and physical condition into consideration" refers to a system that analyzes the user's emotions and health condition and selects the optimal route accordingly.

[1396] "Camera means" refers to a photographic device installed in a room or corridor for monitoring the movements of users in real time.

[1397] "Means for detecting anomalies" refers to programs or algorithms that analyze collected data and identify unusual behavior or conditions.

[1398] "Means for sending alerts" refers to a mechanism for sending immediate notifications to relevant parties when an abnormality is detected.

[1399] A "dialogue script" refers to a document that describes a predefined conversation flow that an AI robot uses when interacting with a user.

[1400] This invention is a system that solves the labor shortage in nursing care facilities, improves operational efficiency, and enhances services. This system provides specific functions such as generating nursing care records and invoices, automating transportation plans for users, detecting abnormalities at night, providing rehabilitation follow-up, and preventing dementia through dialogue with users using an AI robot.

[1401] AI-powered administrative work

[1402] Users input data such as care records, visiting times, and care details into the system. This data is sent to the server via the terminal. The server saves the input data in a database and analyzes it using Python scripts. A template engine generates care records and invoices, which are then converted into PDF format using the PDFKit library. The generated documents are sent to the terminal, where the user can check them and print them if necessary. The emotion engine can analyze the user's emotional state and reflect it in the document content.

[1403] For example, when a user's visit time and care details are entered, the server instantly creates an accurate visit record and invoice based on that information. The emotion engine analyzes the user's emotions and reflects them in the data.

[1404] Example prompt sentence:

[1405] Visiting time: October 1, 2023, 14:00-15:00, Care content: Bathing assistance. User A's emotional state: Relaxed.

[1406] Automated transportation for users

[1407] When a new user registers at a care facility, the user enters their address information into the system. The device sends the input data to the server. The server combines the existing user data with the new data and calculates the optimal shuttle route using the Google Maps API. The calculated route is reflected in the shuttle plan by the template engine, converted into PDF format, and notified to the device. The emotion engine selects the shuttle route taking into account the user's stress level and physical condition.

[1408] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route for existing users B and C and displays the transportation plan on the terminal.

[1409] Example prompt sentence:

[1410] New user X's address: 1-1-1 Nishi-Shinjuku, Shinjuku-ku, Tokyo. Existing user Y's address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo, and user Z's address: 1-4-5 Yurakucho, Chiyoda-ku, Tokyo. User Y's emotional state: stress.

[1411] Nighttime monitoring with AI cameras to detect abnormalities

[1412] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is sent to a server, which analyzes it using AI libraries such as TensorFlow. If abnormal movements are detected, an alert is sent immediately to the caregiver's smartphone app. The emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[1413] As a specific example, if the device detects a user falling out of bed in the middle of the night, it will issue an alert on the spot and notify caregivers via the server.

[1414] Example prompt sentence:

[1415] The nighttime surveillance camera detects abnormal movement. User A is seen falling out of bed. Emotional state: High stress.

[1416] Gait analysis and rehabilitation follow-up

[1417] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is sent to a server, which analyzes the data using AI libraries such as TensorFlow. If an abnormal walking pattern is detected, the server automatically generates a rehabilitation plan and documents it using a template engine. The generated rehabilitation plan is converted to PDF format and sent to the device. The emotion engine provides a rehabilitation plan taking into account the user's level of anxiety and depression.

[1418] As a specific example, if an elderly person is losing their balance while walking more frequently, the server will analyze the data, create a rehabilitation plan, and notify the device.

[1419] Example prompt sentence:

[1420] Elderly person B loses balance while walking three times per hour. Emotional state: high anxiety.

[1421] AI robot conversation partner

[1422] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. The input information is sent to a server, which uses a natural language processing engine to generate a dialogue script. The generated script is transferred to the AI ​​robot, which then converses with the user via the device. The dialogue log is sent to the server and saved as reference for the next dialogue. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue, adjusting the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[1423] As a specific example, if a user is interested in flowers, the server will use that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[1424] Example prompt sentence:

[1425] User C's interest: flowers. Emotional state: joy.

[1426] The above is an embodiment of the present invention, which can improve the efficiency of operations at nursing care facilities and provide advanced services.

[1427] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1428] 1. AI outsourcing of administrative tasks

[1429] Processing Steps

[1430] Step 1:

[1431] The user opens the system's web form and enters data such as care records, visit times, and care details.

[1432] Input: Care records, visiting time, care contents

[1433] Output: Formatted data to terminal

[1434] Step 2:

[1435] The terminal formats the input data and sends it to the server.

[1436] Input: Formatted data

[1437] Output: Data sent to the server

[1438] Step 3:

[1439] The server stores the received data in a MySQL database.

[1440] Input: Received data

[1441] Output: Data stored in the database

[1442] Step 4:

[1443] The server analyzes the stored data using Python scripts.

[1444] Input: Data in the database

[1445] Output: Analysis results

[1446] Step 5:

[1447] The server uses a template engine to generate care records and bills.

[1448] Input: Analysis results

[1449] Output: The generated document

[1450] Step 6:

[1451] The server converts the generated document into PDF format using the PDFKit library and sends a notification to the device.

[1452] Input: Generated document

[1453] Output: Converted document as PDF, notification to device

[1454] Step 7:

[1455] The device displays the notification to the user as a pop-up message.

[1456] Input: Notification to device

[1457] Output: Display notification to the user

[1458] Step 8:

[1459] The user checks the generated document and prints it out on a printer if necessary.

[1460] Input: Popup message

[1461] Output: Printed document

[1462] 2. Automating user transportation

[1463] Processing Steps

[1464] Step 1:

[1465] A user logs into the system and enters the address information for a new user.

[1466] Input: New user's address information

[1467] Output: Formatted data to terminal

[1468] Step 2:

[1469] The terminal formats the address data and sends it to the server.

[1470] Input: Formatted address data

[1471] Output: Data sent to the server

[1472] Step 3:

[1473] The server uses Python and the Google Maps API to integrate the address information of new and old users and calculate the optimal shuttle route.

[1474] Input: Integrated address data

[1475] Output: Calculated pickup route

[1476] Step 4:

[1477] The server creates a transportation plan using a template engine based on the route calculation results.

[1478] Input: Calculated pickup route

[1479] Output: Transportation plan

[1480] Step 5:

[1481] The server converts the generated transportation plan into PDF format using the PDFKit library and sends a notification to the terminal.

[1482] Input: Transportation Plan

[1483] Output: Converted plan as PDF, notification to device

[1484] Step 6:

[1485] The terminal displays a notification of the transportation plan to the user as a pop-up message.

[1486] Input: Notification to device

[1487] Output: Display notification to the user

[1488] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1489] Processing Steps

[1490] Step 1:

[1491] The device streams footage from cameras installed in rooms and hallways and analyzes it in real time.

[1492] Input: Camera image

[1493] Output: Real-time analytics data

[1494] Step 2:

[1495] The terminal transmits the analysis results to the server as appropriate.

[1496] Input: Parsed data

[1497] Output: Data sent to the server

[1498] Step 3:

[1499] The server analyzes the data using AI libraries such as TensorFlow to identify abnormal behavior.

[1500] Input: Parsed data

[1501] Output: Anomaly detection information

[1502] Step 4:

[1503] If the server detects an abnormality, it will notify the caregiver's smartphone app using a real-time database such as Firebase.

[1504] Input: Anomaly detection information

[1505] Output: Notification to care staff

[1506] 4. Gait analysis and rehabilitation follow-up

[1507] Processing Steps

[1508] Step 1:

[1509] The device collects footage from cameras installed in rooms and hallways and records the elderly person's walking patterns.

[1510] Input: Camera image

[1511] Output: Recorded walking data

[1512] Step 2:

[1513] The terminal transmits the collected data to the server as appropriate.

[1514] Input: Gait data

[1515] Output: Data sent to the server

[1516] Step 3:

[1517] The server analyzes the data using AI libraries such as TensorFlow to detect any abnormal walking patterns.

[1518] Input: Collected data

[1519] Output: Analysis results

[1520] Step 4:

[1521] If the server detects an abnormality, it automatically generates a rehabilitation plan and documents it using a template engine.

[1522] Input: Analysis results

[1523] Output: Rehabilitation plan

[1524] Step 5:

[1525] The server converts the generated rehabilitation plan into PDF format and sends a notification to the terminal.

[1526] Input: Rehabilitation plan

[1527] Output: Converted plan as PDF, notification to device

[1528] Step 6:

[1529] The device displays the rehabilitation plan to the caregiver as a pop-up message.

[1530] Input: Notification to device

[1531] Output: Notification to be displayed to care staff

[1532] 5. AI robot conversation partner

[1533] Processing Steps

[1534] Step 1:

[1535] The user enters their emotional state and recent interests and concerns on the system's input screen.

[1536] Input: User's emotional state and interests

[1537] Output: Formatted data to terminal

[1538] Step 2:

[1539] The terminal formats the input data and sends it to the server.

[1540] Input: Formatted data

[1541] Output: Data sent to the server

[1542] Step 3:

[1543] The server uses a natural language processing engine (e.g., GPT-3) to generate an appropriate dialogue script.

[1544] Input: Data sent

[1545] Output: Generated dialogue script

[1546] Step 4:

[1547] The server transfers the generated script to the terminal and conveys the dialogue content to the AI ​​robot.

[1548] Input: Interactive script

[1549] Output: The transferred script

[1550] Step 5:

[1551] The device controls the AI ​​robot and engages in a dialogue with the user, processing what the robot is saying and the user's responses in real time.

[1552] Input: Transferred script, user response

[1553] Output: Interactions performed

[1554] Step 6:

[1555] The terminal generates a dialogue log and transmits it to the server as appropriate.

[1556] Input: Interaction log data

[1557] Output: Log data sent to the server

[1558] Step 7:

[1559] The server saves the dialogue log and uses it as a reference for generating the next dialogue script.

[1560] Input: Log data sent

[1561] Output: Saved log data

[1562] (Application example 2)

[1563] 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."

[1564] Currently, nighttime monitoring in factories still relies on human labor, making it difficult to respond quickly when an abnormality occurs. Furthermore, machine failures and employee stress cannot be detected in real time, often delaying effective countermeasures. This results in problems such as reduced work efficiency and an increased risk of accidents. Therefore, there is a need to automate nighttime factory monitoring and detect abnormalities and stress conditions early.

[1565] 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.

[1566] In this invention, the server includes means for monitoring user movements in real time using a camera, means for analyzing the monitored data to detect abnormalities, means for notifying when an abnormality is detected, means for analyzing emotions and improving responses to detected abnormalities, and means for sending notifications to smartphones. This automates nighttime monitoring in factories, enabling early detection of abnormalities and stress states and prompt responses.

[1567] "Means for inputting user data" refers to a device or interface that allows input of information about people to be monitored in the factory and their work status.

[1568] "Means for automatically generating business documents" refers to a system that automatically creates necessary reports and notification documents based on input user data.

[1569] "Means for storing and notifying generated business documents" refers to a system that stores created documents and reports in a database and sends notifications to appropriate terminals when necessary.

[1570] "Means for monitoring user movements in real time using cameras" refers to a device or system that uses cameras installed in a factory to monitor the movements of the person being monitored in real time.

[1571] "Means for analyzing monitoring data and detecting abnormalities" refers to algorithms or systems that analyze monitoring data collected by cameras and detect unnatural movements or abnormal conditions.

[1572] "Means for notifying when an abnormality is detected" refers to a system that sends an alert to a person in charge or a manager when an abnormal situation is detected.

[1573] The "means of analyzing emotions and improving responses to detected abnormalities" refers to a system that analyzes the facial expressions and movements of the person being monitored, evaluates their stress level and changes in emotions, and suggests appropriate responses based on that.

[1574] "Means for sending notifications to smartphones" is a system for sending important alerts and information directly to the smartphones of responsible personnel.

[1575] This invention is a system that automates nighttime monitoring in factory environments, detects abnormalities and stress levels early, and enables rapid response. The system analyzes camera footage in real time, detects abnormal behavior and emotional states, and sends notifications to smartphones.

[1576] First, the user inputs information about the workers and equipment to be monitored in the factory. This data is then sent to the server and stored in a database.

[1577] For real-time video monitoring, multiple cameras are installed, and the device acquires video data from these cameras. This video data is sent to a server and analyzed using a specific algorithm. Specifically, OpenCV is used to process the images and detect abnormal movements and situations.

[1578] Furthermore, the server uses an emotion analysis model powered by TensorFlow to analyze the facial expressions and movements of the monitored subject, assessing their stress level, and if a change in emotion is detected, taking this into account when responding to an anomaly.

[1579] When an anomaly is detected, the server uses a notification service such as Twilio to instantly send an alert to the agent's smartphone, including details about the anomaly and the detected emotional state, allowing the agent to respond quickly and appropriately.

[1580] As a concrete example, imagine a factory where surveillance cameras are installed during the night shift. The cameras monitor the work area in real time at night, detecting any abnormal activity or equipment malfunctions. They also analyze employees' faces and behavior to assess whether they are showing signs of stress or anxiety. This information is sent to a server in real time, and the analysis results are sent to the person in charge's smartphone. The person in charge can then immediately go to the site and resolve the problem quickly.

[1581] Below are some example prompts for a generative AI model:

[1582] "Please create a program that analyzes the stress levels of factory workers in real time and notifies their smartphones if an abnormality is detected. The hardware required will be cameras and servers, the software will be OpenCV and TensorFlow, and the notification service will be Twilio."

[1583] In this way, the system of the present invention highly automates nighttime monitoring work within a factory, enabling rapid response to problems.

[1584] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1585] Step 1:

[1586] The user inputs information about the workers and equipment to be monitored. Data input is performed using a dedicated interface, and this information is sent to the server and stored in a database. The input for this step is detailed information about the workers and equipment, and the output is the data stored on the server.

[1587] Step 2:

[1588] The terminal acquires images in real time from cameras installed in the factory. The cameras are in operation 24 hours a day, and the image data sent is transmitted to the server in real time. The input of this step is the camera image, and the output is the image data sent to the server.

[1589] Step 3:

[1590] To analyze the video data received by the server, image processing is performed using OpenCV. Specifically, the video frames are converted to grayscale and analyzed to detect abnormal movements or situations. The input of this step is real-time video data, and the output is a judgment result on whether there is an abnormality.

[1591] Step 4:

[1592] The server uses TensorFlow to perform emotion analysis on the received video data. It detects the target's face, evaluates their facial expressions and movements in real time, and measures changes in stress and emotion. The input for this step is the analyzed video frames, and the output is data on stress levels and emotional states.

[1593] Step 5:

[1594] If the server detects an anomaly or stress state, it immediately generates a notification message using Twilio and sends it to the person in charge's smartphone. This message includes details of the anomaly and information about the person's emotional state. The input of this step is the anomaly detection result and the emotion analysis result, and the output is the sent notification message.

[1595] Step 6:

[1596] The person in charge checks the notification message received on their smartphone and quickly heads to the site. Upon receiving this notification, they decide on a specific response method and quickly implement the necessary measures. The input of this step is the notification message, and the output is the implementation of the problem response at the site.

[1597] 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.

[1598] 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.

[1599] 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.

[1600] [Fourth embodiment]

[1601] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1602] 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.

[1603] 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).

[1604] 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.

[1605] 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.

[1606] 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).

[1607] 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.

[1608] 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.

[1609] 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.

[1610] 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.

[1611] 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.

[1612] 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.

[1613] 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."

[1614] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. This system has functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, analyzing elderly people's gait to provide rehabilitation support and injury prevention, and an AI robot that acts as a conversation partner to prevent dementia. Specific embodiments for implementing the present invention are described below.

[1615] 1. AI outsourcing of administrative tasks

[1616] The user first enters data such as care records and visit times into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the terminal. The user can check the generated documents through the terminal and print them as needed. For example, when the visit times and care contents of a certain user are entered, the server instantly creates accurate visit record sheets and invoices based on that information.

[1617] 2. Automating user transportation

[1618] When a new user registers at a nursing care facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal transportation route. The calculated route is automatically reflected in the transportation plan by the server and notified to the terminal. This allows for efficient transportation of multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan that is displayed on the terminal.

[1619] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1620] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the care worker in charge. For example, if it detects a movement that could lead to the user falling out of bed in the middle of the night, the device will issue an alert on the spot and notify the care worker via the server.

[1621] 4. Gait analysis and rehabilitation follow-up

[1622] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when carrying out rehabilitation. For example, if an elderly person is losing their balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device.

[1623] 5. AI robot conversation partner

[1624] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[1625] As described above, the present invention is a system that utilizes AI technology to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[1626] The processing flow will be explained below.

[1627] 1. AI outsourcing of administrative tasks

[1628] Processing Steps

[1629] Step 1:

[1630] Users input data such as care records, visit times, and care details into the system.

[1631] Step 2:

[1632] The server receives the entered data and stores it in a database.

[1633] Step 3:

[1634] The server runs algorithms that automatically generate the necessary business documents (e.g., visit logs, invoices) based on the stored data.

[1635] Step 4:

[1636] The server converts the generated business document into PDF format and saves it in a specified folder.

[1637] Step 5:

[1638] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[1639] 2. Automating user transportation

[1640] Processing Steps

[1641] Step 1:

[1642] The user enters the address information of the new user into the system.

[1643] Step 2:

[1644] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[1645] Step 3:

[1646] The server automatically generates a transportation plan based on the optimized transportation route.

[1647] Step 4:

[1648] The server transmits the generated transportation plan to the terminal.

[1649] Step 5:

[1650] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[1651] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1652] Processing Steps

[1653] Step 1:

[1654] The device monitors the user's movements in real time through a camera at night.

[1655] Step 2:

[1656] The device analyzes the collected video data using AI algorithms.

[1657] Step 3:

[1658] When the device detects abnormal activity, it sends alert data to the server.

[1659] Step 4:

[1660] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[1661] Step 5:

[1662] The device will display notifications on caregivers' smartphones, allowing them to respond quickly to any abnormalities.

[1663] 4. Gait analysis and rehabilitation follow-up

[1664] Processing Steps

[1665] Step 1:

[1666] The device uses a camera to record the elderly person's walking pattern.

[1667] Step 2:

[1668] The device analyzes the collected data in real time and detects abnormal walking patterns.

[1669] Step 3:

[1670] When an abnormality is detected, the terminal transfers the analysis results to the server.

[1671] Step 4:

[1672] The server determines the need for rehabilitation based on the analysis results and executes an algorithm to generate an optimal rehabilitation plan.

[1673] Step 5:

[1674] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[1675] 5. AI robot conversation partner

[1676] Processing Steps

[1677] Step 1:

[1678] Users input information into the system, such as their emotional state, preferences, and recent events.

[1679] Step 2:

[1680] The server executes an algorithm that generates a dialogue script based on the input information.

[1681] Step 3:

[1682] The server transfers the generated dialogue script to the AI ​​robot.

[1683] Step 4:

[1684] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[1685] Step 5:

[1686] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[1687] Example 1

[1688] 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."

[1689] Staff shortages are a serious problem in modern nursing care facilities, resulting in excessive workloads and concerns about a decline in the quality of services. Additionally, issues such as ensuring the safety of users, effective rehabilitation, and dementia prevention are also important. In particular, reducing the administrative burden, streamlining transportation plans, nighttime monitoring, rehabilitation follow-up through gait analysis, and dementia prevention through dialogue are all important issues that must be resolved independently. Conventional systems can only address these issues individually, so integrated and efficient solutions are needed.

[1690] 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.

[1691] In this invention, the server includes: means for inputting user data; means for automatically generating business documents based on the input user data; means for saving and notifying the generated business documents; means for inputting user address information; means for calculating an optimal shuttle route based on the input address information; means for automatically generating and notifying a shuttle plan including the optimal shuttle route; camera means for monitoring the user's movements in real time; means for analyzing the monitored data and detecting abnormalities; means for sending an alert when an abnormality is detected; means for recording and analyzing the user's walking pattern; means for generating and notifying a rehabilitation plan based on the analysis results; means for inputting data on emotional state and interests; means for generating dialogue content based on the input data and transferring it to the AI ​​robot; and means for saving the dialogue log and using it as a reference for the next dialogue. This enables a system that can simultaneously solve issues such as alleviating labor shortages in nursing care facilities, improving work efficiency, ensuring user safety, providing advanced rehabilitation support, and preventing dementia.

[1692] "Means for inputting user data" refers to an interface or device that allows care facility staff to input information about users, such as care records and visiting times.

[1693] "Means for automatically generating business documents" refers to algorithms or programs for automatically creating business documents such as nursing care records and invoices based on input user data.

[1694] The "means for storing and notifying business documents" is a system component for storing automatically generated business documents in electronic form and notifying appropriate parties of the same.

[1695] "Means for inputting address information" refers to an interface or device for inputting address information of a user's residence or facility into the system.

[1696] The "means for calculating a shuttle route" is an algorithm or program for calculating the optimal shuttle route based on the input address information.

[1697] The "means for automatically generating and notifying a transportation plan" is a system component for creating a transportation plan based on an optimized transportation route and notifying relevant parties of the plan.

[1698] "Camera Means" means camera devices and associated systems used to monitor user movements in real time.

[1699] "Means for analyzing data and detecting abnormalities" refers to algorithms or programs that analyze monitoring data collected by cameras and recognize abnormal conditions or movements when they occur.

[1700] An "alert sending means" is a system component that sends warnings or notifications to relevant parties when an abnormality is detected.

[1701] The "means for recording and analyzing walking patterns" refers to an algorithm or program that records the user's walking movements with a camera and analyzes the data to identify abnormalities or areas for improvement.

[1702] The "means for generating and notifying a rehabilitation plan" is a system component for creating an effective rehabilitation plan based on the analyzed walking data and notifying the relevant parties of the plan.

[1703] "Means for inputting emotional state and interest data" refers to an interface or device for inputting the user's current emotional state and interests into the system.

[1704] "Means for generating dialogue content and transmitting it to the AI ​​robot" refers to algorithms or programs that generate dialogue scripts for natural dialogue based on input emotional state and interest data, and transmit them to the AI ​​robot.

[1705] "Means for saving dialogue logs and using them as a reference for the next dialogue" refers to a system component that records the content of dialogue with an AI robot and saves it for reference during the next dialogue.

[1706] The present invention is a system that resolves the shortage of personnel in nursing care facilities, improves operational efficiency, and enhances services, and specific embodiments thereof will be described below.

[1707] 1. AI outsourcing of administrative tasks

[1708] Users first enter data such as care records and visit times into a dedicated interface or tablet device. This data is sent from the device to a server and stored in a central database. The server analyzes the received data and uses AI algorithms to automatically generate business documents such as care record sheets and invoices. The generated documents are converted to PDF format, and a notification is sent from the server to the device. The user can then view the generated documents through the device and print them if necessary.

[1709] For example, when the visit time and care details for user A are entered, the server instantly creates an accurate visit record and invoice based on that information. An example of a prompt would be, "Please enter the visit time and care details for the user into the system and generate a visit record and invoice."

[1710] 2. Automating user transportation

[1711] The user enters the address information of a new user into a dedicated interface. This information is sent from the device to the server and stored along with existing user data. The server calculates the optimal shuttle route based on the received address information. This calculation uses a geographic information system (GIS) and shortest distance algorithms. The optimized shuttle plan is automatically generated and sent to the device from the server. The user can then view and implement the plan through the device.

[1712] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall transportation plan. An example of a prompt would be, "Please enter the address information of new user A into the system and calculate the optimal transportation route."

[1713] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1714] For nighttime monitoring, AI cameras installed in rooms and hallways are used. The device monitors the user's movements in real time through the camera and collects the data. This data is sent from the device to a server and analyzed using an AI algorithm. Incidentally, if any abnormal movements are detected, an alert is sent from the device to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge.

[1715] For example, if a user falls out of bed in the middle of the night, the device will immediately issue an alert and notify the caregiver via the server. An example of a prompt would be, "Monitor the user's movements via the camera at night, and issue an alert if any abnormal movements are detected."

[1716] 4. Gait analysis and rehabilitation follow-up

[1717] During the day, the device uses an installed AI camera to record the elderly person's walking pattern. This data is collected in real time and sent from the device to a server. The server uses an AI algorithm to analyze the walking pattern, and if an abnormal walking pattern is detected, it automatically generates a rehabilitation plan based on that. The generated rehabilitation plan is then sent to the device, and caregivers use it as a reference when carrying out rehabilitation.

[1718] For example, if an elderly person loses balance more frequently while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. An example of a prompt would be, "Use a camera to record the elderly person's walking pattern, and if an abnormal pattern is detected, generate a rehabilitation plan."

[1719] 5. AI robot conversation partner

[1720] As part of dementia prevention, users input their emotional state and recent interests and concerns into a dedicated interface. This information is sent from the device to a server, which then uses a generative AI model to generate an appropriate dialogue script. This script is then transferred to an AI robot via the device, which then interacts with the user accordingly. The dialogue log is then sent from the device to the server and saved as a reference for the next dialogue.

[1721] For example, if a user is interested in flowers, the server will use that information to generate a script that will allow the AI ​​robot to continue the conversation on the topic of flowers. An example of a prompt would be, "Please generate a dialogue script based on the user's emotional state and interests, and transfer it to the AI ​​robot."

[1722] As described above, this invention utilizes AI technology to improve the efficiency of nursing care facility operations and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[1723] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1724] 1. AI outsourcing of administrative tasks

[1725] Step 1

[1726] Users input data such as care records and visit times into a dedicated interface or tablet device. The input data includes the date and time of the visit, the details of the visit, and user information. This information is then sent from the device to the server.

[1727] Step 2

[1728] The server stores the received data in a central database, which centrally manages each user's care records and visiting times, providing efficient data access.

[1729] Step 3

[1730] The server analyzes the stored data using AI algorithms (for example, natural language processing or machine learning models). The input data is analyzed and administrative documents such as nursing care records and invoices are generated. The analyzed data is sent to a document generation tool, which creates documents in PDF format.

[1731] Step 4

[1732] The server notifies the terminal of the generated PDF document, and the user can check the generated document through the terminal and print it if necessary.

[1733] 2. Automating user transportation

[1734] Step 1

[1735] The user enters the address information of the new user into a dedicated interface. The entered information includes the address of the user's residence or facility. This information is then sent from the terminal to the server.

[1736] Step 2

[1737] The server stores the received address information together with existing user data in a central database, which unifies address information management and provides efficient data access.

[1738] Step 3

[1739] The server calculates the optimal pickup route based on the stored address data. It uses a geographic information system (GIS) and shortest distance algorithms to optimize the pickup order and route for each passenger. The calculation results are sent to the transportation planning tool, which generates a transportation plan.

[1740] Step 4

[1741] The server notifies the terminal of the generated transportation plan, and the user can check and implement the plan through the terminal.

[1742] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1743] Step 1

[1744] The device monitors users' movements in real time through AI cameras installed in rooms and hallways, which continuously transmit high-resolution video to the device.

[1745] Step 2

[1746] The device temporarily stores the video data collected by the camera and periodically transmits it to the server, including time and location information.

[1747] Step 3

[1748] The server analyzes the received video data using an AI algorithm, which uses a pre-trained model (e.g., an anomaly detection model) to detect abnormal activity. If an anomaly is detected, the information is sent to an alert system.

[1749] Step 4

[1750] When an abnormality is detected, the server generates an alert and sends it to the caregiver's smartphone app. The alert includes information on the date, time, and location of the abnormality.

[1751] 4. Gait analysis and rehabilitation follow-up

[1752] Step 1

[1753] The device uses an AI camera installed in the device to record the elderly person's walking pattern in real time, and the camera transmits the walking movement data to the device.

[1754] Step 2

[1755] The device temporarily stores the recorded data and periodically transmits it to a server, which includes details of walking timing and movement.

[1756] Step 3

[1757] The server analyzes the transmitted walking data using an AI algorithm, and if an abnormal walking pattern is detected, the information is sent to a rehabilitation plan generation tool.

[1758] Step 4

[1759] The server automatically generates a rehabilitation plan based on the analysis results, which is then sent to the device, where caregivers can use it as a reference when carrying out rehabilitation.

[1760] 5. AI robot conversation partner

[1761] Step 1

[1762] Users input their emotional state and recent interests into a dedicated interface. The input data includes emotional state, interests, and user profile information. This information is then sent from the device to the server.

[1763] Step 2

[1764] The server uses a generative AI model to generate an appropriate dialogue script based on the received data. The generated script is based on the user's input data and the model's learning results.

[1765] Step 3

[1766] The server transfers the generated dialogue script to the terminal, which then sends it to the AI ​​robot, which then dialogues with the user according to the received script.

[1767] Step 4

[1768] The device records the conversation log and periodically sends it to the server, where it is saved as a reference for the next conversation.

[1769] (Application example 1)

[1770] 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."

[1771] Current factory operations involve a wide range of tasks, including production management, logistics management, and safety monitoring, and many labor-intensive tasks are required to perform them efficiently. These tasks are typically performed manually, which can lead to errors and reduced efficiency. Furthermore, monitoring to ensure worker safety is often performed manually, resulting in the risk of accidents. Therefore, there is a need for a system that can automate these tasks and improve efficiency and safety.

[1772] 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.

[1773] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, a means for collecting data, a means for analyzing the collected data, a means for generating technical proposals, and a means for displaying the generated proposals. This enables efficient production management and logistics management in factories and automation of safety monitoring. Furthermore, the anomaly detection and proposal generation functions can improve work efficiency in factories and ensure the safety of workers.

[1774] "Data collection means" refers to devices and functions that use various sensors and input devices to acquire production data, attendance information, logistics information, worker behavior data, and the like within a factory.

[1775] The "automatic business document generation means" refers to a device or function that automatically generates business documents such as daily reports, attendance sheets, and proposals based on input data.

[1776] The "storage and notification means" refers to a device or function that stores the generated business documents and analysis results and notifies the relevant staff and systems of their contents.

[1777] "Data analysis means" refers to devices or functions that analyze collected data, detect trends and anomalies in the data, and generate technical proposals and optimization plans.

[1778] The "technical proposal generation means" refers to a device or function that automatically generates technical proposals such as measures to improve the efficiency of factory operations, safety measures, etc., based on the analyzed data.

[1779] The "proposal display means" is a device or function for displaying the generated proposals and improvement measures in a format that is easy for factory staff to understand.

[1780] The "logistics route optimization means" is a device or function that calculates the optimal transportation route for materials and products based on input address information and logistics data, and generates an efficient logistics schedule.

[1781] "Camera means" refers to a device or function that monitors a specific area in a factory in real time and captures the operations of workers and machines.

[1782] An "abnormality detection means" is a device or function that analyzes monitored data, detects abnormal behavior or events, and notifies the user of such.

[1783] This invention is a comprehensive system aimed at improving efficiency and safety in factory operations. The system has the function of automatically generating, saving, and notifying business documents based on data input by users. It also has multiple automated functions such as optimizing logistics routes, safety monitoring, and analyzing worker movements and generating proposals.

[1784] The system includes the following major hardware and software components:

[1785] Cameras: Monitor specific areas of the factory in real time and capture activity.

[1786] RFID tag reader: Obtains location information for items and materials.

[1787] Server: Analyzes and stores data. Uses AI frameworks such as Python and TensorFlow.

[1788] Smartphone: Displays and notifies results.

[1789] 1. Data Collection

[1790] Users collect data from various sensors (cameras, RFID tags, etc.) and input devices. For example, they can obtain production data, attendance information, logistics information, and worker behavior data in a factory in real time.

[1791] 2. Data Analysis

[1792] The collected data is sent to a server and analyzed using AI models, using AI frameworks such as Python and TensorFlow to detect trends and anomalies in the data and generate technical recommendations and optimization plans.

[1793] 3. Notification and reflection of results

[1794] The analysis results and generated suggestions are sent to smartphones or other devices. For example, they may include suggestions regarding working hours and production efficiency, optimal logistics routes, and safety measures. This allows users to immediately check this information and take appropriate action.

[1795] Specific examples

[1796] During production line work in a factory, cameras detect when a worker's movements go outside the control range and send an immediate notification to prevent accidents. The system also analyzes production and attendance data from the past week to generate suggestions for improving efficiency. Furthermore, it recalculates optimal logistics routes and generates schedules based on the latest sensor information.

[1797] Prompt Sentence Examples

[1798] "Analyze production and attendance data from the past week and generate suggestions for improving efficiency."

[1799] "Based on the latest sensor information, recalculate the optimal logistics route and generate a schedule."

[1800] These prompts allow the system to provide optimal suggestions for efficient and safe factory operations.

[1801] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1802] Step 1:

[1803] Users collect data in factories using sensors, cameras, RFID tag readers, etc. This collected data includes production data, logistics data, attendance information, worker behavior data, etc. Real-time data is obtained from sensors and cameras as input, and this data is sent to a server as output.

[1804] Step 2:

[1805] The server analyzes the received data. Python and AI frameworks such as TensorFlow are used for the analysis. Data processing includes preprocessing, normalization, and missing value completion. Data calculation involves applying anomaly detection and pattern recognition algorithms to detect abnormal behavior and opportunities for efficiency improvements. The collected data is read as input. Analysis results and suggestions are generated as output.

[1806] Step 3:

[1807] The server automatically generates optimal business documents based on the generated analysis results and proposals. These documents include daily production reports, attendance records, efficiency improvement proposals, logistics schedules, etc. The analysis results and proposals are used as inputs. The automatically generated business documents are obtained as output.

[1808] Step 4:

[1809] The server saves the generated business document in cloud storage or on a local disk. At the same time, it sends a notification to the relevant users and devices. The automatically generated business document is used as input. The saved document and notification are obtained as output.

[1810] Step 5:

[1811] The terminal displays the generated business documents, optimized routes, work suggestions, etc. to the user who received the notification. The user checks this and takes appropriate action if necessary. The notification and business documents from the server are used as inputs. The output is the display of information to the user.

[1812] Step 6:

[1813] The user inputs a prompt into the generative AI model in the system. For example, the user might input a prompt such as, "Please analyze the production data and attendance data from the past week and generate proposals for improving efficiency." Based on this prompt, the server analyzes the data again and generates new proposals. The prompt is used as input. The newly generated proposals are obtained as output.

[1814] Step 7:

[1815] The server notifies the user or terminal of the newly generated proposal and displays it again. This allows the user to operate the factory efficiently based on the latest information. The newly generated proposal is used as input. The output is a re-notification to the user and information display.

[1816] 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.

[1817] The present invention is a system for resolving the labor shortage in nursing care facilities, improving operational efficiency, and enhancing services. The system combines functions such as taking over administrative tasks, automatically creating user transportation plans, detecting abnormalities using nighttime surveillance cameras, providing rehabilitation support and injury prevention through gait analysis for elderly people, and an AI robot that acts as a conversation partner to prevent dementia, as well as an emotion engine. Specific embodiments for implementing the present invention are described below.

[1818] 1. AI outsourcing of administrative tasks

[1819] Users enter data such as care records, visit times, and care details into the system. This data is sent to the server and stored in a database. The server analyzes the entered data and automatically generates administrative documents such as care record sheets and invoices. The generated documents are converted to PDF format and a notification is sent to the device. The user can check the generated documents through the device and print them as needed. For example, when a user's visit times and care details are entered, the server instantly creates an accurate visit record sheet and invoice based on that information. At this time, an emotion engine analyzes the user's emotions and can reflect them in the content of the documents as necessary.

[1820] 2. Automating user transportation

[1821] When a new user registers at a nursing facility, the user enters their address information into the system. The server combines the new user data with existing user data to calculate the optimal shuttle route. The calculated route is automatically reflected in the shuttle plan by the server and notified to the terminal. This allows for efficient shuttle service for multiple users. As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route with existing users B and C, and automatically generates an overall shuttle plan that is displayed on the terminal. In this case, the emotion engine considers the user's stress level and physical condition to select a comfortable shuttle route.

[1822] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1823] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is analyzed using an AI algorithm, and if any abnormal movements are detected, the device sends an alert to the server. When the server receives this alert information, it immediately sends a notification to the smartphone app of the caregiver in charge. For example, if the device detects movements that suggest the user has fallen out of bed in the middle of the night, it will immediately issue an alert and notify the caregiver via the server. This process includes a function in which an emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[1824] 4. Gait analysis and rehabilitation follow-up

[1825] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is analyzed on the spot, and if an abnormal walking pattern is detected, the results are sent to a server. Based on the analysis results, the server determines whether rehabilitation is necessary and automatically generates an appropriate rehabilitation plan. This plan is notified to the device, and caregivers use it as a reference when implementing rehabilitation. For example, if an elderly person is increasingly losing their balance while walking, the server analyzes the data, creates a rehabilitation plan, and notifies the device. At this time, the emotion engine also takes into account the user's level of anxiety and depression, and provides a rehabilitation plan that incorporates psychological support.

[1826] 5. AI robot conversation partner

[1827] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. Based on this information, the server generates an appropriate dialogue script and transmits it to the AI ​​robot. The AI ​​robot installed on the device then converses with the user according to the generated script. The dialogue log is sent from the device to the server and saved as reference for the next dialogue. For example, if the user is interested in flowers, the server uses that information to generate a script that will lead the AI ​​robot into a conversation about flowers. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue and adjusts the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[1828] As described above, this invention is a system that utilizes AI technology and an emotion engine to streamline operations at nursing care facilities and provide advanced services, thereby resolving the problem of labor shortages and enabling better services to be provided to users.

[1829] The processing flow will be explained below.

[1830] 1. AI outsourcing of administrative tasks

[1831] Processing Steps

[1832] Step 1:

[1833] Users input data such as care records, visit times, and care details into the system.

[1834] Step 2:

[1835] The server receives the entered data and stores it in a database.

[1836] Step 3:

[1837] The server uses an emotion engine to analyze the user's emotional state and executes algorithms to adjust the content of business documents based on that analysis.

[1838] Step 4:

[1839] The server automatically generates business documents such as nursing care records and invoices.

[1840] Step 5:

[1841] The server converts the generated business document into PDF format and saves it in a specified folder.

[1842] Step 6:

[1843] The terminal displays a notification on the user's terminal to inform the user that a business document has been created. The user can check the created document and print it if necessary.

[1844] 2. Automating user transportation

[1845] Processing Steps

[1846] Step 1:

[1847] The user enters the address information of the new user into the system.

[1848] Step 2:

[1849] The server runs an algorithm that combines existing user data with new data to calculate the optimal shuttle route.

[1850] Step 3:

[1851] The server uses an emotion engine to consider the user's emotional state and adjust the optimal pick-up route and time.

[1852] Step 4:

[1853] The server automatically generates a transportation plan based on the optimized transportation route.

[1854] Step 5:

[1855] The server transmits the generated transportation plan to the terminal.

[1856] Step 6:

[1857] The terminal displays the transportation plan on the user's terminal so that the user can check it.

[1858] 3. Nighttime monitoring with AI cameras for detecting anomalies

[1859] Processing Steps

[1860] Step 1:

[1861] The device monitors the user's movements in real time through a camera at night.

[1862] Step 2:

[1863] The device analyzes the collected video data using AI algorithms.

[1864] Step 3:

[1865] When the device detects abnormal activity, it sends alert data to the server.

[1866] Step 4:

[1867] The server also analyzes the user's emotional state using an emotion engine to determine whether stress or anxiety is increasing.

[1868] Step 5:

[1869] The server receives the alert data and sends a notification to the smartphone app of the designated care worker.

[1870] Step 6:

[1871] The device will display notifications on caregivers' smartphones, allowing them to respond quickly.

[1872] 4. Gait analysis and rehabilitation follow-up

[1873] Processing Steps

[1874] Step 1:

[1875] The device uses a camera to record the elderly person's walking pattern.

[1876] Step 2:

[1877] The device analyzes the collected data in real time and detects abnormal walking patterns.

[1878] Step 3:

[1879] When an abnormality is detected, the terminal transfers the analysis results to the server.

[1880] Step 4:

[1881] The server also analyzes the user's emotional state and anxiety level using an emotion engine.

[1882] Step 5:

[1883] The server executes an algorithm that determines the need for rehabilitation based on the analysis results and generates an appropriate rehabilitation plan.

[1884] Step 6:

[1885] The terminal transmits the generated rehabilitation plan to the caregiver's terminal and provides follow-up instructions.

[1886] 5. AI robot conversation partner

[1887] Processing Steps

[1888] Step 1:

[1889] Users input information such as their emotional state and interests into the system.

[1890] Step 2:

[1891] The server runs an algorithm that generates a dialogue script based on the input information.

[1892] Step 3:

[1893] The server transfers the generated dialogue script to the AI ​​robot.

[1894] Step 4:

[1895] The terminal begins a dialogue with the user using an AI robot according to a dialogue script.

[1896] Step 5:

[1897] The device uses an emotion engine to analyze the user's facial expressions and tone of voice during a conversation and adjusts the content and tone of the conversation as appropriate.

[1898] Step 6:

[1899] The device sends the conversation log to the server in real time and saves it as a reference for the next conversation.

[1900] Example 2

[1901] 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."

[1902] The present invention aims to provide a system that can address the shortage of personnel and the increasing workload in nursing care facilities and provide efficient and advanced services. In particular, the present invention focuses on streamlining specific tasks such as automating administrative tasks, optimizing transportation plans for users, detecting abnormalities at night, following up on rehabilitation through gait analysis, and preventing dementia through dialogue with users.

[1903] 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.

[1904] In this invention, the server includes a means for inputting user data, a means for automatically generating business documents based on the input user data, a means for saving and notifying the generated business documents, and a means for analyzing the user's emotional state and reflecting it in the generated documents, thereby enabling the automatic generation of care records and invoices and the reflection of the emotional state.

[1905] The system also includes a means for inputting the user's address information, a means for calculating the optimal shuttle route based on the input address information, a means for automatically generating and notifying a shuttle plan including the optimal shuttle route, and a means for selecting a shuttle route taking into consideration the user's stress level and physical condition, thereby enabling the creation of an efficient shuttle plan that takes into consideration the user.

[1906] Furthermore, the system includes a camera means for monitoring the user's movements in real time, a means for analyzing the monitored data and detecting abnormalities, a means for sending an alert when an abnormality is detected, and a means for analyzing the user's facial expressions and voice and responding quickly when emotional stress increases. This improves the accuracy of nighttime monitoring and abnormality detection, enabling a quick response.

[1907] "Client data" refers to information such as records about clients of care facilities, visit times, and care provided.

[1908] "Business documents" refer to documents related to nursing care work, such as nursing care records and invoices.

[1909] "Server" refers to a central computer that manages the overall processing of the system, including receiving, storing, analyzing, and notifying data.

[1910] "Terminal" refers to an input device or output device used by a user, and includes devices for inputting data and displaying notifications.

[1911] "Means for inputting data" refers to the interface that users and care staff use to input information such as care records and visit times into the system.

[1912] "Means for analyzing data" refers to software or algorithms that the server uses to perform the necessary processing based on the information entered.

[1913] "Means for automatically generating documents" refers to technology that automatically creates documents such as nursing care records and invoices based on input data.

[1914] "Means of notification" refers to a mechanism for informing users of generated documents, transportation plans, abnormality detection information, etc.

[1915] "Means for analyzing emotional state" refers to technology that analyzes a user's facial expressions and tone of voice to determine their emotions.

[1916] "Address information" refers to information about the user's base of residence, and is used to calculate the shuttle route.

[1917] "Means for calculating optimal shuttle routes" refers to an algorithm for calculating efficient shuttle routes based on the address information of existing and new users.

[1918] "Means that take stress levels and physical condition into consideration" refers to a system that analyzes the user's emotions and health condition and selects the optimal route accordingly.

[1919] "Camera means" refers to a photographic device installed in a room or corridor for monitoring the movements of users in real time.

[1920] "Means for detecting anomalies" refers to programs or algorithms that analyze collected data and identify unusual behavior or conditions.

[1921] "Means for sending alerts" refers to a mechanism for sending immediate notifications to relevant parties when an abnormality is detected.

[1922] A "dialogue script" refers to a document that describes a predefined conversation flow that an AI robot uses when interacting with a user.

[1923] This invention is a system that solves the labor shortage in nursing care facilities, improves operational efficiency, and enhances services. This system provides specific functions such as generating nursing care records and invoices, automating transportation plans for users, detecting abnormalities at night, providing rehabilitation follow-up, and preventing dementia through dialogue with users using an AI robot.

[1924] AI-powered administrative work

[1925] Users input data such as care records, visiting times, and care details into the system. This data is sent to the server via the terminal. The server saves the input data in a database and analyzes it using Python scripts. A template engine generates care records and invoices, which are then converted into PDF format using the PDFKit library. The generated documents are sent to the terminal, where the user can check them and print them if necessary. The emotion engine can analyze the user's emotional state and reflect it in the document content.

[1926] For example, when a user's visit time and care details are entered, the server instantly creates an accurate visit record and invoice based on that information. The emotion engine analyzes the user's emotions and reflects them in the data.

[1927] Example prompt sentence:

[1928] Visiting time: October 1, 2023, 14:00-15:00, Care content: Bathing assistance. User A's emotional state: Relaxed.

[1929] Automated transportation for users

[1930] When a new user registers at a care facility, the user enters their address information into the system. The device sends the input data to the server. The server combines the existing user data with the new data and calculates the optimal shuttle route using the Google Maps API. The calculated route is reflected in the shuttle plan by the template engine, converted into PDF format, and notified to the device. The emotion engine selects the shuttle route taking into account the user's stress level and physical condition.

[1931] As a specific example, when the address information of new user A is entered, the server calculates the optimal order and route for existing users B and C and displays the transportation plan on the terminal.

[1932] Example prompt sentence:

[1933] New user X's address: 1-1-1 Nishi-Shinjuku, Shinjuku-ku, Tokyo. Existing user Y's address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo, and user Z's address: 1-4-5 Yurakucho, Chiyoda-ku, Tokyo. User Y's emotional state: stress.

[1934] Nighttime monitoring with AI cameras to detect abnormalities

[1935] Cameras installed in rooms and hallways are used for nighttime monitoring. The device monitors the user's movements in real time through the cameras and collects data. The collected data is sent to a server, which analyzes it using AI libraries such as TensorFlow. If abnormal movements are detected, an alert is sent immediately to the caregiver's smartphone app. The emotion engine analyzes changes in the user's facial expressions and voice, and responds quickly if emotional stress is increasing.

[1936] As a specific example, if the device detects a user falling out of bed in the middle of the night, it will issue an alert on the spot and notify caregivers via the server.

[1937] Example prompt sentence:

[1938] The nighttime surveillance camera detects abnormal movement. User A is seen falling out of bed. Emotional state: High stress.

[1939] Gait analysis and rehabilitation follow-up

[1940] During the day, the device uses an installed camera to record the elderly person's walking pattern. The collected data is sent to a server, which analyzes the data using AI libraries such as TensorFlow. If an abnormal walking pattern is detected, the server automatically generates a rehabilitation plan and documents it using a template engine. The generated rehabilitation plan is converted to PDF format and sent to the device. The emotion engine provides a rehabilitation plan taking into account the user's level of anxiety and depression.

[1941] As a specific example, if an elderly person is losing their balance while walking more frequently, the server will analyze the data, create a rehabilitation plan, and notify the device.

[1942] Example prompt sentence:

[1943] Elderly person B loses balance while walking three times per hour. Emotional state: high anxiety.

[1944] AI robot conversation partner

[1945] As part of dementia prevention, users input their emotional state and recent interests and concerns into the system. The input information is sent to a server, which uses a natural language processing engine to generate a dialogue script. The generated script is transferred to the AI ​​robot, which then converses with the user via the device. The dialogue log is sent to the server and saved as reference for the next dialogue. The emotion engine analyzes the user's facial expressions and tone of voice during the dialogue, adjusting the content and tone of the conversation as appropriate, enabling more natural and in-depth communication.

[1946] As a specific example, if a user is interested in flowers, the server will use that information to generate a script that will lead the AI ​​robot into a conversation about flowers.

[1947] Example prompt sentence:

[1948] User C's interest: flowers. Emotional state: joy.

[1949] The above is an embodiment of the present invention, which can improve the efficiency of operations at nursing care facilities and provide advanced services.

[1950] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1951] 1. AI outsourcing of administrative tasks

[1952] Processing Steps

[1953] Step 1:

[1954] The user opens the system's web form and enters data such as care records, visit times, and care details.

[1955] Input: Care records, visiting time, care contents

[1956] Output: Formatted data to terminal

[1957] Step 2:

[1958] The terminal formats the input data and sends it to the server.

[1959] Input: Formatted data

[1960] Output: Data sent to the server

[1961] Step 3:

[1962] The server stores the received data in a MySQL database.

[1963] Input: Received data

[1964] Output: Data stored in the database

[1965] Step 4:

[1966] The server analyzes the stored data using Python scripts.

[1967] Input: Data in the database

[1968] Output: Analysis results

[1969] Step 5:

[1970] The server uses a template engine to generate care records and bills.

[1971] Input: Analysis results

[1972] Output: The generated document

[1973] Step 6:

[1974] The server converts the generated document into PDF format using the PDFKit library and sends a notification to the device.

[1975] Input: Generated document

[1976] Output: Converted document as PDF, notification to device

[1977] Step 7:

[1978] The device displays the notification to the user as a pop-up message.

[1979] Input: Notification to device

[1980] Output: Display notification to the user

[1981] Step 8:

[1982] The user checks the generated document and prints it out on a printer if necessary.

[1983] Input: Popup message

[1984] Output: Printed document

[1985] 2. Automating user transportation

[1986] Processing Steps

[1987] Step 1:

[1988] A user logs into the system and enters the address information for a new user.

[1989] Input: New user's address information

[1990] Output: Formatted data to terminal

[1991] Step 2:

[1992] The terminal formats the address data and sends it to the server.

[1993] Input: Formatted address data

[1994] Output: Data sent to the server

[1995] Step 3:

[1996] The server uses Python and the Google Maps API to integrate the address information of new and old users and calculate the optimal shuttle route.

[1997] Input: Integrated address data

[1998] Output: Calculated pickup route

[1999] Step 4:

[2000] The server creates a transportation plan using a template engine based on the route calculation results.

[2001] Input: Calculated pickup route

[2002] Output: Transportation plan

[2003] Step 5:

[2004] The server converts the generated transportation plan into PDF format using the PDFKit library and sends a notification to the terminal.

[2005] Input: Transportation Plan

[2006] Output: Converted plan as PDF, notification to device

[2007] Step 6:

[2008] The terminal displays a notification of the transportation plan to the user as a pop-up message.

[2009] Input: Notification to device

[2010] Output: Display notification to the user

[2011] 3. Nighttime monitoring with AI cameras for detecting anomalies

[2012] Processing Steps

[2013] Step 1:

[2014] The device streams footage from cameras installed in rooms and hallways and analyzes it in real time.

[2015] Input: Camera image

[2016] Output: Real-time analytics data

[2017] Step 2:

[2018] The terminal transmits the analysis results to the server as appropriate.

[2019] Input: Parsed data

[2020] Output: Data sent to the server

[2021] Step 3:

[2022] The server analyzes the data using AI libraries such as TensorFlow to identify abnormal behavior.

[2023] Input: Parsed data

[2024] Output: Anomaly detection information

[2025] Step 4:

[2026] If the server detects an abnormality, it will notify the caregiver's smartphone app using a real-time database such as Firebase.

[2027] Input: Anomaly detection information

[2028] Output: Notification to care staff

[2029] 4. Gait analysis and rehabilitation follow-up

[2030] Processing Steps

[2031] Step 1:

[2032] The device collects footage from cameras installed in rooms and hallways and records the elderly person's walking patterns.

[2033] Input: Camera image

[2034] Output: Recorded walking data

[2035] Step 2:

[2036] The terminal transmits the collected data to the server as appropriate.

[2037] Input: Gait data

[2038] Output: Data sent to the server

[2039] Step 3:

[2040] The server analyzes the data using AI libraries such as TensorFlow to detect any abnormal walking patterns.

[2041] Input: Collected data

[2042] Output: Analysis results

[2043] Step 4:

[2044] If the server detects an abnormality, it automatically generates a rehabilitation plan and documents it using a template engine.

[2045] Input: Analysis results

[2046] Output: Rehabilitation plan

[2047] Step 5:

[2048] The server converts the generated rehabilitation plan into PDF format and sends a notification to the terminal.

[2049] Input: Rehabilitation plan

[2050] Output: Converted plan as PDF, notification to device

[2051] Step 6:

[2052] The device displays the rehabilitation plan to the caregiver as a pop-up message.

[2053] Input: Notification to device

[2054] Output: Notification to be displayed to care staff

[2055] 5. AI robot conversation partner

[2056] Processing Steps

[2057] Step 1:

[2058] The user enters their emotional state and recent interests and concerns on the system's input screen.

[2059] Input: User's emotional s...

Claims

1. means for inputting user data; A means for automatically generating business documents based on input user data; A means for storing and notifying the generated business document; A system including:

2. a means for inputting user address information; A means for calculating the optimal pick-up route based on the input address information; A means for automatically generating and notifying a transportation plan including an optimal transportation route; The system of claim 1 , comprising:

3. a camera means for monitoring user movements in real time; A means for analyzing the monitored data and detecting abnormalities; A means of sending an alert when an anomaly is detected; The system of claim 1 , comprising:

4. a means for recording the walking pattern of an elderly person; A means for analyzing the recorded walking pattern and detecting abnormalities; A means for generating and notifying a rehabilitation plan when an abnormality is detected; The system of claim 1 , comprising:

5. a means for inputting user information; A means for generating an interaction script based on input information; A means for the AI ​​robot to have a conversation using the generated conversation script; a means for storing dialogue logs; The system of claim 1 , comprising:

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