system

Abstract

We provide the system. [Solution] Observation methods for collecting environmental data, An analysis means for analyzing data collected by the observation means and determining the priority of household tasks, A command means that generates commands for performing household chores based on the priority determined by the analysis means, An execution means that performs household chores in accordance with the instructions generated by the command means, A system comprising progress reporting means for reporting the progress of the execution means.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, in the elderly and dual-income households, the burden of housework has become a major problem. Although conventional household appliances and housekeeping services can automate only specific tasks, it is difficult to comprehensively substitute all housework within the home, and users still require a great deal of time and effort. In response to such a situation, a self-regulating housework support system that can flexibly respond according to the situation is required.

Means for Solving the Problems

[0005] The present invention includes observation means for collecting environmental data and analysis means for analyzing this data to determine the priority of household tasks. Furthermore, it includes command means for generating commands to perform household tasks based on the determined priority. This system includes execution means for performing household tasks and progress reporting means for reporting the progress to the user. By providing correction means for adjusting priorities based on the user's preferences and past history, and notification means for checking progress, it becomes possible to support household chores efficiently and flexibly.

[0006] "Environmental data" refers to information such as the degree of dirtiness, temperature, humidity, and arrangement of objects in a room, which is obtained using observation methods.

[0007] "Observation means" refers to devices, including cameras and sensors, used to collect environmental data.

[0008] "Analysis means" refers to a data processing function that uses environmental data acquired by observation means to determine the priority of household chores.

[0009] The "command means" refers to the function that generates instructions for specific task execution based on the priority of household chores determined by the analysis means.

[0010] "Execution means" refers to mechanical or electrical devices used to actually perform household chores in accordance with instructions generated by the command means.

[0011] "Progress reporting means" refers to a function that monitors the progress of household chores performed by the execution means and reports it to the user.

[0012] "Correction measures" refer to a function that adaptively changes the priority of household chores determined by analysis measures, taking into account the user's preferences and past history.

[0013] "Notification means" refers to a function that transmits progress information collected through progress reporting means to the user's mobile device in real time. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiments for Carrying out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] The autonomous general-purpose home service robot system of this invention is designed to efficiently assist with various household chores. This system operates in a manner optimized for the user's home environment.

[0036] First, the system uses observation tools mounted on the robot to understand the current state of the room. The robot uses a camera to photograph the degree of dirtiness in the room and sensors to measure temperature and humidity, collecting the necessary environmental data. This data is then transmitted by the robot to a server.

[0037] The server uses analysis tools to determine the priority of household chores based on the received environmental data. In this process, the user's past behavioral history and preferences are also taken into account to adjust the priorities to match the user's needs. For example, multiple tasks such as cleaning, laundry, and cooking are listed in order of importance.

[0038] Next, the server uses a command mechanism to generate instructions for the robot regarding specific tasks to be performed. This allows the robot to sequentially perform various household chores. Because the robot, equipped with execution mechanisms, physically carries out the specified tasks, household chores are completed without the user having to touch them.

[0039] The server monitors the progress of household chores through progress reporting mechanisms and collects progress information in real time. The terminal notifies the user of this progress information via an application, and the user can easily check which chores have been completed and what the current progress is using a smartphone or other device. This allows the user to keep track of the progress of household chores step by step and adjust instructions as needed.

[0040] This system aims to improve the quality of life for users by efficiently automating household chores while they go about their normal daily lives. It is expected to particularly contribute to reducing the burden of housework for the elderly and dual-income households.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server receives environmental data collected by observation devices from the robot. This data includes information such as the cleanliness of the room, temperature, humidity, and the arrangement of objects. This data is recorded in a database before analysis, in preparation for subsequent processing.

[0044] Step 2:

[0045] Based on the received data, the server activates an analysis tool to determine the priority of current household chore needs. A machine learning algorithm references past data and takes into account user preferences and behaviors under similar conditions to efficiently allocate tasks.

[0046] Step 3:

[0047] The server utilizes command mechanisms to generate and send specific instructions for household tasks to the robot. These instructions include details of the task and execution timing based on priority. For example, they might include a specific command such as, "Start cleaning the living room at 10:00 AM."

[0048] Step 4:

[0049] The server receives feedback from the robot and monitors the progress of household chores through progress reporting mechanisms. It checks whether the tasks being performed are proceeding according to plan and adjusts the schedule as needed.

[0050] Step 5:

[0051] The terminal notifies the user's smart device of the latest task progress based on progress information received from the server. The user can check which tasks are completed or in progress through the app on their terminal. This allows the user to understand the progress of household chores in real time and confidently entrust the management to the system.

[0052] (Example 1)

[0053] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0054] In modern society, household chores are often not managed efficiently, placing a significant burden on the elderly and dual-income households. This problem leads to wasted time and effort, lowering the quality of life. There is a need for a system that efficiently handles household chores and provides users with appropriate information related to them.

[0055] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0056] In this invention, the server includes detection means for understanding the environment, processing means for analyzing the information acquired by the detection means and formulating work priorities, and instruction means for creating work instructions. This enables efficient and user-friendly work management and execution.

[0057] "Detection methods for understanding the environment" refers to devices and sensors used to observe conditions within a home and collect necessary data.

[0058] "Processing means" refers to devices or software used to analyze acquired information and determine the priority of tasks.

[0059] "Instruction means" refers to devices or programs that generate specific work instructions based on analyzed information.

[0060] An "execution device" refers to a robot or machine that executes instructions created by an instruction means and actually performs household tasks.

[0061] "Reporting means" refers to a system for monitoring the progress of work and communicating progress information to users.

[0062] "Correction measures" refer to devices or algorithms used to adjust the priority of tasks based on the user's preferences and past behavioral history.

[0063] "Notification means" refers to a function that uses mobile devices or similar devices to present work progress information to the user.

[0064] Modes for carrying out the invention

[0065] This invention is an autonomous system for efficiently managing and performing household tasks. The server uses detection means to understand the household environment. Specifically, it uses a robot equipped with cameras and sensors to collect indoor image data and environmental data. The collected data is transmitted to a server in the cloud.

[0066] The server analyzes the received data. It uses an AI model to analyze the collected data and automatically determines the priority of tasks. This involves using software such as Python and Python libraries (e.g., TENSORFLOW®, scikit-learn). During the analysis process, a database is utilized to consider the user's past behavior and preferences.

[0067] As a means of giving instructions, the server generates specific instructions for household chores based on determined priorities and sends them to the robot. This process utilizes communication protocols (e.g., MQTT, WebSocket). Based on these instructions, the robot performs tasks such as cleaning and laundry.

[0068] The server monitors the progress of the tasks being performed in real time. The terminal notifies the user of the progress via smartphone or tablet. Mobile applications are used for this notification method.

[0069] For example, if a user wants to clean their room and prepare a meal before returning home from work, the robot would first detect the dirt in the room, prioritize the cleaning tasks, and then begin simple cooking in the kitchen. Progress is notified to the user's smartphone in real time, and the user can adjust the instructions as needed.

[0070] Examples of prompts include, "Generate a natural language description to determine the priority of household tasks," and "Describe how an autonomous robotic system will perform tasks in the home."

[0071] This system is expected to significantly reduce the burden of household chores, especially for the elderly and dual-income households, and contribute to improving their quality of life.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The server receives environmental data transmitted from the robot. It receives image data captured by a camera and sensor data such as temperature and humidity as input. Based on this data, it initializes the current state of the home and saves it to a database. Specifically, the image data undergoes preprocessing to analyze color information and shape, and the sensor data is used to calculate the mean and standard deviation.

[0075] Step 2:

[0076] The server analyzes the input environmental data using an AI model. Specifically, it applies algorithms to quantify dirtiness and clutter levels from image data, and converts temperature and humidity data into indicators for evaluating comfort levels. The output generates a task list indicating whether cleaning or temperature adjustment is necessary. Specifically, it utilizes deep learning techniques for image analysis and statistical methods for sensor data.

[0077] Step 3:

[0078] The server determines task priorities based on analysis. It considers the user's past behavior history and preferences to determine the optimal work order. Its input includes user profile data, and its output is a prioritized list of work instructions. Specifically, a weighting algorithm calculates the importance of each task.

[0079] Step 4:

[0080] The server transmits specific work instructions to the robot through an instruction mechanism. The input includes a prioritized list of work instructions, and the output contains detailed procedural information for each task. In practice, instructions are transmitted in real time using a communication protocol.

[0081] Step 5:

[0082] The terminal receives progress data transmitted from the server via a progress reporting mechanism. Input includes progress logs, and output is a notification message to the user. Specifically, progress is notified via a smartphone app, which the user can view on the screen.

[0083] Step 6:

[0084] Users can modify instructions via the terminal as needed. Input includes user feedback, and the modified work instructions are sent to the server as output. Specifically, the system provides a function to edit and update instructions in real time on the user interface.

[0085] Throughout this entire process, household tasks are efficiently managed and executed, and users are provided with advanced work units tailored to their needs.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] To improve the efficiency of diverse tasks and achieve flexible task management in production environments, it is necessary to monitor progress in real time and appropriately adjust priorities. However, manual adjustments by workers are time-consuming and hinder productivity improvements. This is especially true in workplaces with a wide range of tasks, where efficient management is difficult.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes observation means for collecting environmental information, analysis means for analyzing the information collected by the observation means and determining the priority of business tasks, and command means for generating commands for executing tasks based on the priority determined by the analysis means. This enables automatic optimization and efficient management of business tasks in the production site.

[0091] "Environmental information" refers to physical data such as temperature, humidity, and light intensity observed within the work space, as well as information related to the progress and procedures of the work.

[0092] "Observation tools" refer to devices such as sensors and cameras used to collect environmental information in real time.

[0093] "Analysis tools" refer to software or algorithms used to analyze data collected by observation tools and determine the priority of business tasks.

[0094] A "command means" is a device or program that generates specific instructions for carrying out each business task based on the priority determined by the analysis means.

[0095] "Execution means" refers to robots or automated systems that perform actual tasks based on commands generated by command means.

[0096] A "progress reporting system" refers to a communication function or data management system used to record the progress of work performed by the execution system and report it to relevant parties.

[0097] "User" refers to an individual or organization that is in a position to supervise or manage the system.

[0098] "Device" refers to a device that a user carries or uses, and includes smartphones and tablets.

[0099] The system for implementing this invention comprises a series of processes for acquiring environmental information, analyzing it, setting priorities, and issuing commands. Specifically, it collects data within the workspace using observation means such as sensors and cameras, and the server analyzes this data. For analysis, it employs a generative AI model using, for example, Python libraries such as TensorFlow or PyTorch. Based on the priorities determined by the analysis means, the server generates commands for carrying out tasks.

[0100] This command is sent to the robot or automated system (execution mechanism), and the specific task begins. The server manages the progress of the task through a progress reporting mechanism. This information is transmitted in real time to the user's device (e.g., smartphone or tablet), allowing the user to monitor the situation. The user can modify the command or reset the task priority as needed.

[0101] As a concrete example, consider a system in an automotive parts factory where inventory management sensors and work robots work together to assemble parts and efficiently manage the production process. In this case, an example of a prompt message generated by the server would be: "Consider the machine operation data and production status data within the factory, and calculate the optimal process priority. Also, construct an algorithm that can issue real-time progress and efficiency improvement instructions." This would enable flexible production in response to demand while maintaining work efficiency.

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The server collects environmental information from observation devices. This information includes data such as temperature, humidity, light intensity, and operating status obtained from sensors and cameras. This data is transmitted to the server via the network and stored in a database.

[0105] Step 2:

[0106] The server processes accumulated environmental information using analytical tools. An AI model is applied using Python libraries such as TensorFlow and PyTorch to calculate the optimal priority of business tasks. Analysis based on input data enables real-time decision-making.

[0107] Step 3:

[0108] Based on the priorities calculated by the analysis tools, the server generates specific work instructions using the command tools. These instructions are generated as detailed information necessary for carrying out each work task, such as which machines to operate or which parts to use.

[0109] Step 4:

[0110] The server transmits the generated work instructions to the robots and automation systems that will execute them via the network. This ensures that each task is carried out accurately. The tasks are executed sequentially as specified, and the physical operations begin.

[0111] Step 5:

[0112] The server receives progress reports from the execution system through a progress reporting mechanism. Inputs include the completion status of each task and tasks currently in progress. Based on this, the server analyzes the current progress, records it in the database, and generates new instructions as needed.

[0113] Step 6:

[0114] The terminal notifies users of progress information. Through an application installed on a smartphone or tablet, users can see real-time progress and work instructions. This allows users to check the situation on-site and issue new instructions if necessary.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] The autonomous general-purpose home service robot system of the present invention, in addition to collecting and analyzing environmental data, determining the priority of household chores, generating and executing commands, and reporting progress, integrates an emotion engine to realize household assistance that is more optimized for the user.

[0117] This system uses a robot installed in the home to collect environmental data using observation tools. This includes taking pictures of the level of dirtiness in the room and measuring temperature and humidity. Simultaneously, an emotion engine estimates the user's emotions from their facial expressions, voice tone, and gestures, and sends this emotion data to a server.

[0118] The server analyzes the received data to determine the priority of household chores. By taking into account the user's past history and current emotions, more appropriate task scheduling becomes possible. For example, if the user is feeling stressed, adjustments will be made to prioritize quick and easy chores.

[0119] Once priorities are determined, the command system generates specific task instructions and sends them to the robot. The robot then performs household chores based on the instructions it receives. The content and method of the chores performed are adaptively modified according to emotional data.

[0120] Furthermore, the progress of ongoing tasks is reported to the server in real time, and users can check the progress through their terminals. In addition, messages such as encouragement and warnings tailored to the user's emotions are sent, providing support that is sensitive to the user's feelings.

[0121] In this way, the system provided by the present invention can realize household support tailored to the user's situation and emotions, thereby improving the quality of life and reducing the burden of household chores. However, data exchange and analysis functions between various modules are implemented by utilizing commonly available communication technologies and cloud computing technologies.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] The server receives environmental and emotional data transmitted from the robot. Environmental data includes room cleanliness, temperature, humidity, etc., while emotional data includes the user's emotional state analyzed through an emotion engine. This received data is recorded in a database.

[0125] Step 2:

[0126] The server uses analytical tools to determine the priority of household tasks based on the received environmental and emotional data. For example, if the user indicates fatigue, it prioritizes tasks that can be completed quickly, thus prioritizing tasks according to the user's emotions. This analysis result is then reflected in the generation of subsequent commands.

[0127] Step 3:

[0128] The server uses a command mechanism to generate specific task instructions based on priority. These instructions include details of the tasks to be performed and recommended procedures, and are sent to the robot. For example, an instruction might be, "The user wants to relax, so clean in silent mode."

[0129] Step 4:

[0130] Based on reports received from the robot, the server monitors the progress of ongoing tasks using a progress reporting mechanism. Based on the reported progress information, the server verifies the completion of tasks and prepares for the next task instruction.

[0131] Step 5:

[0132] The device sends progress updates received from the server, along with emotionally sensitive notifications, to the user. Through the device, the user can check the progress of household chores in real time and receive encouragement and reminders tailored to the situation. This allows the user to confidently entrust their daily chores to the system.

[0133] (Example 2)

[0134] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0135] In modern households, the burden of household chores is increasing due to various factors. In particular, emotional stress and time constraints make it difficult to efficiently prioritize household tasks. Furthermore, conventional systems cannot provide appropriate support based on the emotional state of individual users, making it difficult to improve the quality of life at home.

[0136] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0137] In this invention, the server includes an acquisition means for collecting environmental information, a calculation means for analyzing the information collected by the acquisition means and determining the priority of work tasks, and an emotion analysis means for estimating the emotional state and incorporating it into the analysis results. This allows for adaptive adjustment of work priorities based on the user's emotional state, enabling more efficient and personalized home support.

[0138] "Environmental information" refers to data that indicates the physical state and conditions within a home, including temperature, humidity, and pollution levels.

[0139] "Means of acquisition" refers to devices and sensors used to collect environmental information.

[0140] "Computational means" refers to a computing device or software used to analyze acquired information and determine the priority of household tasks.

[0141] "Emotional analysis means" refers to a technology or device that analyzes a user's facial expressions, voice, and actions to estimate their emotional state at that time.

[0142] "Instruction means" refers to a device or program that generates specific work instructions based on the priority of tasks determined by the calculation means.

[0143] An "execution device" is a device or robot that actually performs household tasks in response to generated commands.

[0144] A "reporting device" is a device or function that records the progress of a task in progress and reports it to a server or user terminal.

[0145] A "notification device" is a terminal or application used to communicate progress and other important information reported by a reporting device to the user.

[0146] This invention integrates various technological elements to provide a system that efficiently supports tasks within the home. This system collects information about the home environment, analyzes that information to derive the optimal work sequence, and provides work support tailored to each individual user.

[0147] The server collects physical data such as temperature, humidity, and pollution levels through environmental data acquisition methods that work in conjunction with sensors installed in the home. This makes it possible to understand the conditions of the room and the need for work.

[0148] Furthermore, the server uses emotion analysis tools, including facial expression recognition and voice analysis, to understand the user's emotions. This technology is supported by devices placed in the home, such as cameras and microphones. The analyzed emotion data plays an important role in determining task priorities.

[0149] The server integrates the above data and performs calculations using an AI model to determine the priority of household tasks. For example, if the user is feeling stressed, it will recommend simple tasks that can be completed quickly. Based on this analysis, the command system operates and generates specific work instructions. These instructions are sent to execution devices installed in the home, and the devices perform the tasks according to the instructions.

[0150] Users can check the progress of their ongoing tasks in real time using their terminals. Progress data from the reporting device is sent to the terminals via a server, and users receive notifications tailored to their emotions. For example, messages such as "Good job!" can be displayed to encourage relaxation.

[0151] For example, if the system suggests a simple cleaning task when the user is tired, the prompt message would be, "Please suggest a simple task to perform when the user's current emotion is 'tired'."

[0152] In this way, the present invention can improve the quality of life by providing personalized in-home support tailored to the user's emotions and circumstances.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] The user activates sensors installed in their home. The sensors detect indoor temperature, humidity, and air quality, acquiring environmental information. This information is sent to the server as input. The server receives this data and prepares it to be stored in a database. At this stage, the data is still in its raw, unprocessed state.

[0156] Step 2:

[0157] The server analyzes the received environmental information. Specifically, it performs data cleansing, correcting missing values ​​and outliers. Based on this clean data, it uses an AI model for analysis. The output is information analyzing the state of the room. The server then passes this information to the next emotion analysis tool.

[0158] Step 3:

[0159] When a user engages in activities within their home, the server utilizes emotion analysis tools to estimate their emotional state by analyzing their facial expressions and voice. Data from the camera and microphone serves as input. The analyzed emotion data is output as the user's emotional state and used in the next priority determination process.

[0160] Step 4:

[0161] The server integrates both environmental and emotional information and uses an AI model to determine the priority of household tasks. The input consists of previously analyzed environmental and emotional data. This calculation outputs instructions on "which tasks should be prioritized." The output is then sent to a command system.

[0162] Step 5:

[0163] The server sends instructions to the execution device (such as a home robot) through a command system. Specifically, a command is generated that describes a prioritized task in detail. The execution device receives this command and prepares to start the specified task. This causes the robot to perform actions such as cleaning or tidying up.

[0164] Step 6:

[0165] When the execution device performs a task, progress information related to that task is sent to the server via the reporting device. The input is progress data from the execution device. The server receives and analyzes this data and monitors the progress in real time. This information is then displayed on the user's terminal via the notification device.

[0166] Step 7:

[0167] Users check the progress of their tasks using their devices. Notifications displayed on the devices are based on the latest progress information from the server. This allows users to check the status of each task in a timely manner. Reminders and encouraging messages tailored to specific emotions may also be displayed.

[0168] (Application Example 2)

[0169] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0170] Conventional home work support systems lack the ability to provide optimal service based on the user's emotions. Furthermore, even in retail stores, services that take customer emotions into consideration are not adequately provided, making it necessary to improve customer satisfaction.

[0171] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0172] In this invention, the server includes an observation device for collecting environmental information, an analysis device for determining the priority of household tasks, and an emotion analysis device for analyzing customer emotion information and adjusting service provision priorities based on the analysis results. This enables the provision of optimized services based on the emotions of users and customers.

[0173] "Environmental information" refers to data that indicates the conditions and circumstances inside a room or store, and is acquired through various sensors such as temperature, humidity, and level of soiling.

[0174] An "observation device" is a device used to acquire environmental information, and it uses sensors, cameras, etc., to detect conditions inside homes or stores.

[0175] An "analysis device" is a device that processes information collected by observation devices and determines the priority of tasks and services.

[0176] A "command device" is a device that generates commands to perform specific tasks or services based on the priorities determined by the analysis device.

[0177] An "execution device" is a device that performs necessary tasks or services within a home or store in accordance with commands from a command device.

[0178] A "progress reporting device" is a device used to report the progress of the work and services performed by the execution device.

[0179] An "emotion analysis device" is a device that analyzes the emotions of users or customers from their facial expressions, tone of voice, etc., and adjusts the priority of services based on the results.

[0180] A "service management device" is a device used to manage service content, staff allocation, and other aspects in order to improve the customer experience within a store.

[0181] A "correction device" is a device that adjusts the priority of tasks and services based on the user's past history and preferences.

[0182] This invention optimizes various tasks within homes and stores according to the user's emotional state using an autonomous system. The server employs an observation device to collect environmental information and an emotion analysis device to analyze customer emotional information. This allows the system to determine the priority of tasks within the home and service provision within stores, providing users and customers with the optimal experience.

[0183] Specifically, observation devices capture environmental information, and emotion analysis devices analyze the facial expressions and tone of voice of users and customers in real time. Based on the analysis results, a command device generates commands through advanced algorithms, and a progress reporting device reports to users and store staff that the work or service is being executed and progressing smoothly. The server is integrated by programs and operates in conjunction with software such as Python, OpenCV, and emotion analysis libraries.

[0184] For example, if a customer is dissatisfied with a long queue in a store, an emotion analysis device can detect that emotion, and a service management device can automatically issue instructions to quickly reassign additional staff to the queue, thereby improving customer satisfaction. Analysis using a generative AI model makes it possible to respond to each user's emotions in the shortest possible time.

[0185] A concrete example of a prompt sentence for a generative AI model is: "Detect customer stress caused by long waiting times in store queues and suggest how store staff should address the issue."

[0186] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0187] Step 1:

[0188] The server collects environmental information using observation devices. Specifically, it acquires data such as temperature, humidity, and room cleanliness through various sensors. The input is raw data from the sensors, and the output is environmental data for processing. This data is stored in a database for subsequent analysis.

[0189] Step 2:

[0190] The server uses an emotion analysis device to acquire facial expression data from users and customers and performs emotion analysis. The input here is camera footage, and the output is the emotion analysis result. Using a generative AI model, it analyzes facial expressions, voice tone, gestures, etc., to grasp the emotional state of the situation in real time.

[0191] Step 3:

[0192] The analysis device takes the environmental information and sentiment analysis results obtained in steps 1 and 2 as input to determine high-priority tasks and services. The output is a priority list, which is sent to the command device. Specifically, the priority determination algorithm is executed using a programming language such as Python.

[0193] Step 4:

[0194] The command device generates specific task and service commands based on the priority list transmitted from the analysis device. The input is the priority list, and the output is the command to the execution device. This allows the system to automatically send commands to ensure the smooth delivery of necessary services within homes and stores.

[0195] Step 5:

[0196] The execution device performs tasks and services within a home or store based on commands received from the command device. The input is the command content, and the output is the completed state of the task. For example, it might rearrange the placement of store staff as needed, or initiate cleaning work within a home.

[0197] Step 6:

[0198] The progress reporting device monitors the progress of work and services in real time and reports the progress to users and store staff. The input is progress data from the execution device, and the output is a progress report. Users can check the progress via a terminal, and suggestions and feedback using a generated AI model are provided as needed.

[0199] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0200] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0201] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0202] [Second Embodiment]

[0203] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0204] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0205] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0206] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0207] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0208] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0209] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0210] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0211] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0212] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0213] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0214] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0215] The autonomous general-purpose home service robot system of this invention is designed to efficiently assist with various household chores. This system operates in a manner optimized for the user's home environment.

[0216] First, the system uses observation tools mounted on the robot to understand the current state of the room. The robot uses a camera to photograph the degree of dirtiness in the room and sensors to measure temperature and humidity, collecting the necessary environmental data. This data is then transmitted by the robot to a server.

[0217] The server uses analysis tools to determine the priority of household chores based on the received environmental data. In this process, the user's past behavioral history and preferences are also taken into account to adjust the priorities to match the user's needs. For example, multiple tasks such as cleaning, laundry, and cooking are listed in order of importance.

[0218] Next, the server uses a command mechanism to generate instructions for the robot regarding specific tasks to be performed. This allows the robot to sequentially perform various household chores. Because the robot, equipped with execution mechanisms, physically carries out the specified tasks, household chores are completed without the user having to touch them.

[0219] The server monitors the progress of household chores through progress reporting mechanisms and collects progress information in real time. The terminal notifies the user of this progress information via an application, and the user can easily check which chores have been completed and what the current progress is using a smartphone or other device. This allows the user to keep track of the progress of household chores step by step and adjust instructions as needed.

[0220] This system aims to improve the quality of life for users by efficiently automating household chores while they go about their normal daily lives. It is expected to particularly contribute to reducing the burden of housework for the elderly and dual-income households.

[0221] The following describes the processing flow.

[0222] Step 1:

[0223] The server receives environmental data collected by the robot using observation tools. This data includes information such as the cleanliness of the room, temperature, humidity, and the arrangement of objects. This data is recorded in a database before analysis, in preparation for subsequent processing.

[0224] Step 2:

[0225] Based on the received data, the server activates an analysis tool to determine the priority of current household chore needs. A machine learning algorithm references past data and takes into account user preferences and behaviors under similar conditions to efficiently allocate tasks.

[0226] Step 3:

[0227] The server utilizes command mechanisms to generate and send specific instructions for household tasks to the robot. These instructions include details of the task and execution timing based on priority. For example, they might include a specific command such as, "Start cleaning the living room at 10:00 AM."

[0228] Step 4:

[0229] The server receives feedback from the robot and monitors the progress of household chores through progress reporting mechanisms. It checks whether the tasks being performed are proceeding according to plan and adjusts the schedule as needed.

[0230] Step 5:

[0231] The terminal notifies the user's smart device of the latest task progress based on progress information received from the server. The user can check which tasks are completed or in progress through the app on their terminal. This allows the user to understand the progress of household chores in real time and confidently entrust the management to the system.

[0232] (Example 1)

[0233] Next, we will describe Example 1. 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."

[0234] In modern society, household chores are often not managed efficiently, placing a significant burden on the elderly and dual-income households. This problem leads to wasted time and effort, lowering the quality of life. There is a need for a system that efficiently handles household chores and provides users with appropriate information related to them.

[0235] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0236] In this invention, the server includes detection means for understanding the environment, processing means for analyzing the information acquired by the detection means and formulating work priorities, and instruction means for creating work instructions. This enables efficient and user-friendly work management and execution.

[0237] "Detection methods for understanding the environment" refers to devices and sensors used to observe conditions within a home and collect necessary data.

[0238] "Processing means" refers to devices or software used to analyze acquired information and determine the priority of tasks.

[0239] "Instruction means" refers to devices or programs that generate specific work instructions based on analyzed information.

[0240] An "execution device" refers to a robot or machine that executes instructions created by an instruction means and actually performs household tasks.

[0241] "Reporting means" refers to a system for monitoring the progress of work and communicating progress information to users.

[0242] "Correction measures" refer to devices or algorithms used to adjust the priority of tasks based on the user's preferences and past behavioral history.

[0243] "Notification means" refers to a function that uses mobile devices or similar devices to present work progress information to the user.

[0244] Modes for carrying out the invention

[0245] This invention is an autonomous system for efficiently managing and performing household tasks. The server uses detection means to understand the household environment. Specifically, it uses a robot equipped with cameras and sensors to collect indoor image data and environmental data. The collected data is transmitted to a server in the cloud.

[0246] The server analyzes the received data. It uses an AI model to analyze the collected data and automatically determines the priority of tasks. This involves using software such as Python and Python libraries (e.g., TensorFlow, scikit-learn). During the analysis process, a database is utilized to consider the user's past behavior and preferences.

[0247] As a means of giving instructions, the server generates specific instructions for household chores based on determined priorities and sends them to the robot. This process utilizes communication protocols (e.g., MQTT, WebSocket). Based on these instructions, the robot performs tasks such as cleaning and laundry.

[0248] The server monitors the progress of the tasks being performed in real time. The terminal notifies the user of the progress via smartphone or tablet. Mobile applications are used for this notification method.

[0249] For example, if a user wants to clean their room and prepare a meal before returning home from work, the robot would first detect the dirt in the room, prioritize the cleaning tasks, and then begin simple cooking in the kitchen. Progress is notified to the user's smartphone in real time, and the user can adjust the instructions as needed.

[0250] Examples of prompts include, "Generate a natural language description to determine the priority of household tasks," and "Describe how an autonomous robotic system will perform tasks in the home."

[0251] This system is expected to significantly reduce the burden of household chores, especially for the elderly and dual-income households, and contribute to improving their quality of life.

[0252] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0253] Step 1:

[0254] The server receives environmental data transmitted from the robot. It receives image data captured by a camera and sensor data such as temperature and humidity as input. Based on this data, it initializes the current state of the home and saves it to a database. Specifically, the image data undergoes preprocessing to analyze color information and shape, and the sensor data is used to calculate the mean and standard deviation.

[0255] Step 2:

[0256] The server analyzes the input environmental data using an AI model. Specifically, it applies algorithms to quantify dirtiness and clutter levels from image data, and converts temperature and humidity data into indicators for evaluating comfort levels. The output generates a task list indicating whether cleaning or temperature adjustment is necessary. Specifically, it utilizes deep learning techniques for image analysis and statistical methods for sensor data.

[0257] Step 3:

[0258] The server determines task priorities based on analysis. It considers the user's past behavior history and preferences to determine the optimal work order. Its input includes user profile data, and its output is a prioritized list of work instructions. Specifically, a weighting algorithm calculates the importance of each task.

[0259] Step 4:

[0260] The server transmits specific work instructions to the robot through an instruction mechanism. The input includes a prioritized list of work instructions, and the output contains detailed procedural information for each task. In practice, instructions are transmitted in real time using a communication protocol.

[0261] Step 5:

[0262] The terminal receives progress data transmitted from the server via a progress reporting mechanism. Input includes progress logs, and output is a notification message to the user. Specifically, progress is notified via a smartphone app, which the user can view on the screen.

[0263] Step 6:

[0264] Users can modify instructions via the terminal as needed. Input includes user feedback, and the modified work instructions are sent to the server as output. Specifically, the system provides a function to edit and update instructions in real time on the user interface.

[0265] Throughout this entire process, household tasks are efficiently managed and executed, and users are provided with advanced work units tailored to their needs.

[0266] (Application Example 1)

[0267] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0268] To improve the efficiency of diverse tasks and achieve flexible task management in production environments, it is necessary to monitor progress in real time and appropriately adjust priorities. However, manual adjustments by workers are time-consuming and hinder productivity improvements. This is especially true in workplaces with a wide range of tasks, where efficient management is difficult.

[0269] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0270] In this invention, the server includes observation means for collecting environmental information, analysis means for analyzing the information collected by the observation means and determining the priority of business tasks, and command means for generating commands for executing tasks based on the priority determined by the analysis means. This enables automatic optimization and efficient management of business tasks in the production site.

[0271] "Environmental information" refers to physical data such as temperature, humidity, and light intensity observed within the work space, as well as information related to the progress and procedures of the work.

[0272] "Observation tools" refer to devices such as sensors and cameras used to collect environmental information in real time.

[0273] "Analysis tools" refer to software or algorithms used to analyze data collected by observation tools and determine the priority of business tasks.

[0274] A "command means" is a device or program that generates specific instructions for carrying out each business task based on the priority determined by the analysis means.

[0275] "Execution means" refers to robots or automated systems that perform actual tasks based on commands generated by command means.

[0276] A "progress reporting system" refers to a communication function or data management system used to record the progress of work performed by the execution system and report it to relevant parties.

[0277] "User" refers to an individual or organization that is in a position to supervise or manage the system.

[0278] "Device" refers to a device that a user carries or uses, and includes smartphones and tablets.

[0279] The system for implementing this invention comprises a series of processes for acquiring environmental information, analyzing it, setting priorities, and issuing commands. Specifically, it collects data within the workspace using observation means such as sensors and cameras, and the server analyzes this data. For analysis, it employs a generative AI model using, for example, Python libraries such as TensorFlow or PyTorch. Based on the priorities determined by the analysis means, the server generates commands for carrying out tasks.

[0280] This command is sent to the robot or automated system (execution mechanism), and the specific task begins. The server manages the progress of the task through a progress reporting mechanism. This information is transmitted in real time to the user's device (e.g., smartphone or tablet), allowing the user to monitor the situation. The user can modify the command or reset the task priority as needed.

[0281] As a concrete example, consider a system in an automotive parts factory where inventory management sensors and work robots work together to assemble parts and efficiently manage the production process. In this case, an example of a prompt message generated by the server would be: "Consider the machine operation data and production status data within the factory, and calculate the optimal process priority. Also, construct an algorithm that can issue real-time progress and efficiency improvement instructions." This would enable flexible production in response to demand while maintaining work efficiency.

[0282] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0283] Step 1:

[0284] The server collects environmental information from the observation means. This information includes data such as temperature, humidity, light intensity, and operating status obtained from sensors and cameras. These are transmitted to the server via the network and stored in the database.

[0285] Step 2:

[0286] The server processes the accumulated environmental information using the analysis means. An AI model generated using libraries such as TensorFlow and PyTorch in Python is applied to calculate the optimal priority of business tasks. Real-time judgment becomes possible through analysis based on the input data.

[0287] Step 3:

[0288] Based on the priority calculated by the analysis means, the server generates specific business instructions using the command means. This instruction is generated as detailed information necessary for the implementation of each business task. For example, which machine to operate and which parts to use.

[0289] Step 4:

[0290] The server transmits the generated business instructions to robots or automation systems serving as execution means via the network. As a result, each operation is accurately performed. The operations are sequentially executed as specified, and physical operations are started.

[0291] Step 5:

[0292] The server receives progress reports from the execution system through a progress reporting mechanism. Inputs include the completion status of each task and tasks currently in progress. Based on this, the server analyzes the current progress, records it in the database, and generates new instructions as needed.

[0293] Step 6:

[0294] The terminal notifies users of progress information. Through an application installed on a smartphone or tablet, users can see real-time progress and work instructions. This allows users to check the situation on-site and issue new instructions if necessary.

[0295] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0296] The autonomous general-purpose home service robot system of the present invention, in addition to collecting and analyzing environmental data, determining the priority of household chores, generating and executing commands, and reporting progress, integrates an emotion engine to realize household assistance that is more optimized for the user.

[0297] This system uses a robot installed in the home to collect environmental data using observation tools. This includes taking pictures of the level of dirtiness in the room and measuring temperature and humidity. Simultaneously, an emotion engine estimates the user's emotions from their facial expressions, voice tone, and gestures, and sends this emotion data to a server.

[0298] The server analyzes the received data to determine the priority of household chores. By taking into account the user's past history and current emotions, more appropriate task scheduling becomes possible. For example, if the user is feeling stressed, adjustments will be made to prioritize quick and easy chores.

[0299] Once the priority is determined, the command means generates a specific task instruction and sends it to the robot. Based on the received instruction, the robot performs housework. The content and method of the housework to be performed are adaptively changed according to the emotional data.

[0300] Also, the progress of the task being executed is reported to the server in real time, and the user can check the progress through the terminal. Furthermore, messages such as encouragement and attention according to the emotion are notified, and support considering the user's emotion is provided.

[0301] In this way, the system provided by the present invention can realize housework support according to the user's situation and emotion, improve the quality of life, and reduce the burden of housework. However, the data exchange and analysis functions between various modules are implemented by utilizing the generally popular communication technology and cloud computing technology.

[0302] The following describes the processing flow.

[0303] I Step 1:

[0304] The server receives the environmental data and emotional data sent from the robot. The environmental data includes the dirt, temperature, humidity, etc. of the room, and the emotional data includes the user's emotional state analyzed through the emotion engine. These received data are recorded in the database.

[0305] Step 2:

[0306] <H Based on the received environmental data and emotional data, the server determines the priority of the housework task using the analysis means. When the user shows fatigue, prioritize tasks that can be completed in a short time, etc., and perform prioritization according to the user's emotion. This analysis result is reflected in the next command generation.

[0307] Step 3:

[0308] The server uses a command mechanism to generate specific task instructions based on priority. These instructions include details of the tasks to be performed and recommended procedures, and are sent to the robot. For example, an instruction might be, "The user wants to relax, so clean in silent mode."

[0309] Step 4:

[0310] Based on reports received from the robot, the server monitors the progress of ongoing tasks using a progress reporting mechanism. Based on the reported progress information, the server verifies task completion and prepares for the next task instruction.

[0311] Step 5:

[0312] The device sends progress updates received from the server, along with emotionally sensitive notifications, to the user. Through the device, the user can check the progress of household chores in real time and receive encouragement and reminders tailored to the situation. This allows the user to confidently entrust their daily chores to the system.

[0313] (Example 2)

[0314] Next, we will describe Example 2. 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".

[0315] In modern households, the burden of household chores is increasing due to various factors. In particular, emotional stress and time constraints make it difficult to efficiently prioritize household tasks. Furthermore, conventional systems cannot provide appropriate support based on the emotional state of individual users, making it difficult to improve the quality of life at home.

[0316] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0317] In this invention, the server includes an acquisition means for collecting environmental information, a calculation means for analyzing the information collected by the acquisition means and determining the priority of work tasks, and an emotion analysis means for estimating the emotional state and incorporating it into the analysis results. This allows for adaptive adjustment of work priorities based on the user's emotional state, enabling more efficient and personalized home support.

[0318] "Environmental information" refers to data that indicates the physical state and conditions within a home, including temperature, humidity, and pollution levels.

[0319] "Means of acquisition" refers to devices and sensors used to collect environmental information.

[0320] "Computational means" refers to a computing device or software used to analyze acquired information and determine the priority of household tasks.

[0321] "Emotional analysis means" refers to a technology or device that analyzes a user's facial expressions, voice, and actions to estimate their emotional state at that time.

[0322] "Instruction means" refers to a device or program that generates specific work instructions based on the priority of tasks determined by the calculation means.

[0323] An "execution device" is a device or robot that actually performs household tasks in response to generated commands.

[0324] A "reporting device" is a device or function that records the progress of a task in progress and reports it to a server or user terminal.

[0325] A "notification device" is a terminal or application used to communicate progress and other important information reported by a reporting device to the user.

[0326] This invention integrates various technological elements to provide a system that efficiently supports tasks within the home. This system collects information about the home environment, analyzes that information to derive the optimal work sequence, and provides work support tailored to each individual user.

[0327] The server collects physical data such as temperature, humidity, and pollution levels through environmental data acquisition methods that work in conjunction with sensors installed in the home. This makes it possible to understand the conditions of the room and the need for work.

[0328] Furthermore, the server uses emotion analysis tools, including facial expression recognition and voice analysis, to understand the user's emotions. This technology is supported by devices placed in the home, such as cameras and microphones. The analyzed emotion data plays an important role in determining task priorities.

[0329] The server integrates the above data and performs calculations using an AI model to determine the priority of household tasks. For example, if the user is feeling stressed, it will recommend simple tasks that can be completed quickly. Based on this analysis, the command system operates and generates specific work instructions. These instructions are sent to execution devices installed in the home, and the devices perform the tasks according to the instructions.

[0330] Users can check the progress of their ongoing tasks in real time using their terminals. Progress data from the reporting device is sent to the terminals via a server, and users receive notifications tailored to their emotions. For example, messages such as "Good job!" can be displayed to encourage relaxation.

[0331] For example, if the system suggests a simple cleaning task when the user is tired, the prompt message would be, "Please suggest a simple task to perform when the user's current emotion is 'tired'."

[0332] In this way, the present invention can improve the quality of life by providing personalized in-home support tailored to the user's emotions and circumstances.

[0333] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0334] Step 1:

[0335] The user activates sensors installed in their home. The sensors detect indoor temperature, humidity, and air quality, acquiring environmental information. This information is sent to the server as input. The server receives this data and prepares it to be stored in a database. At this stage, the data is still in its raw, unprocessed state.

[0336] Step 2:

[0337] The server analyzes the received environmental information. Specifically, it performs data cleansing, correcting missing values ​​and outliers. Based on this clean data, it uses an AI model for analysis. The output is information analyzing the state of the room. The server then passes this information to the next emotion analysis tool.

[0338] Step 3:

[0339] When a user engages in activities within their home, the server utilizes emotion analysis tools to estimate their emotional state by analyzing their facial expressions and voice. Data from the camera and microphone serves as input. The analyzed emotion data is output as the user's emotional state and used in the next priority determination process.

[0340] Step 4:

[0341] The server integrates both environmental and emotional information and uses an AI model to determine the priority of household tasks. The input consists of previously analyzed environmental and emotional data. This calculation outputs instructions on "which tasks should be prioritized." The output is then sent to a command system.

[0342] Step 5:

[0343] The server sends instructions to the execution device (such as a home robot) through a command system. Specifically, a command is generated that describes a prioritized task in detail. The execution device receives this command and prepares to start the specified task. This causes the robot to perform actions such as cleaning or tidying up.

[0344] Step 6:

[0345] When the execution device performs a task, progress information related to that task is sent to the server via the reporting device. The input is progress data from the execution device. The server receives and analyzes this data and monitors the progress in real time. This information is then displayed on the user's terminal via the notification device.

[0346] Step 7:

[0347] Users check the progress of their tasks using their devices. Notifications displayed on the devices are based on the latest progress information from the server. This allows users to check the status of each task in a timely manner. Reminders and encouraging messages tailored to specific emotions may also be displayed.

[0348] (Application Example 2)

[0349] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0350] Conventional home work support systems lack the ability to provide optimal service based on the user's emotions. Furthermore, even in retail stores, services that take customer emotions into consideration are not adequately provided, making it necessary to improve customer satisfaction.

[0351] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0352] In this invention, the server includes an observation device for collecting environmental information, an analysis device for determining the priority of household tasks, and an emotion analysis device for analyzing customer emotion information and adjusting service provision priorities based on the analysis results. This enables the provision of optimized services based on the emotions of users and customers.

[0353] "Environmental information" refers to data that indicates the conditions and circumstances inside a room or store, and is acquired through various sensors such as temperature, humidity, and level of soiling.

[0354] An "observation device" is a device used to acquire environmental information, and it uses sensors, cameras, etc., to detect conditions inside homes or stores.

[0355] An "analysis device" is a device that processes information collected by observation devices and determines the priority of tasks and services.

[0356] A "command device" is a device that generates commands to perform specific tasks or services based on the priorities determined by the analysis device.

[0357] An "execution device" is a device that performs necessary tasks or services within a home or store in accordance with commands from a command device.

[0358] A "progress reporting device" is a device used to report the progress of the work and services performed by the execution device.

[0359] An "emotion analysis device" is a device that analyzes the emotions of users or customers from their facial expressions, tone of voice, etc., and adjusts the priority of services based on the results.

[0360] A "service management device" is a device used to manage service content, staff allocation, and other aspects in order to improve the customer experience within a store.

[0361] A "correction device" is a device that adjusts the priority of tasks and services based on the user's past history and preferences.

[0362] This invention optimizes various tasks within homes and stores according to the user's emotional state using an autonomous system. The server employs an observation device to collect environmental information and an emotion analysis device to analyze customer emotional information. This allows the system to determine the priority of tasks within the home and service provision within stores, providing users and customers with the optimal experience.

[0363] Specifically, observation devices capture environmental information, and emotion analysis devices analyze the facial expressions and tone of voice of users and customers in real time. Based on the analysis results, a command device generates commands through advanced algorithms, and a progress reporting device reports to users and store staff that the work or service is being executed and progressing smoothly. The server is integrated by programs and operates in conjunction with software such as Python, OpenCV, and emotion analysis libraries.

[0364] For example, if a customer is dissatisfied with a long queue in a store, an emotion analysis device can detect that emotion, and a service management device can automatically issue instructions to quickly reassign additional staff to the queue, thereby improving customer satisfaction. Analysis using a generative AI model makes it possible to respond to each user's emotions in the shortest possible time.

[0365] A concrete example of a prompt sentence for a generative AI model is: "Detect customer stress caused by long waiting times in store queues and suggest how store staff should address the issue."

[0366] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0367] Step 1:

[0368] The server collects environmental information using observation devices. Specifically, it acquires data such as temperature, humidity, and room cleanliness through various sensors. The input is raw data from the sensors, and the output is environmental data for processing. This data is stored in a database for subsequent analysis.

[0369] Step 2:

[0370] The server uses an emotion analysis device to acquire facial expression data from users and customers and performs emotion analysis. The input here is camera footage, and the output is the emotion analysis result. Using a generative AI model, it analyzes facial expressions, voice tone, gestures, etc., to grasp the emotional state of the situation in real time.

[0371] Step 3:

[0372] The analysis device takes the environmental information and sentiment analysis results obtained in steps 1 and 2 as input to determine high-priority tasks and services. The output is a priority list, which is sent to the command device. Specifically, the priority determination algorithm is executed using a programming language such as Python.

[0373] Step 4:

[0374] The command device generates specific task and service commands based on the priority list transmitted from the analysis device. The input is the priority list, and the output is the command to the execution device. This allows the system to automatically send commands to ensure the smooth delivery of necessary services within homes and stores.

[0375] Step 5:

[0376] The execution device performs tasks and services within a home or store based on commands received from the command device. The input is the command content, and the output is the completed state of the task. For example, it might rearrange the placement of store staff as needed, or initiate cleaning work within a home.

[0377] Step 6:

[0378] The progress reporting device monitors the progress of work and services in real time and reports the progress to users and store staff. The input is progress data from the execution device, and the output is a progress report. Users can check the progress via a terminal, and suggestions and feedback using a generated AI model are provided as needed.

[0379] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0380] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0381] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0382] [Third Embodiment]

[0383] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0384] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0385] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0386] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0387] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0388] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0389] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0390] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0391] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0392] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0393] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0394] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0395] The autonomous general-purpose home service robot system of this invention is designed to efficiently assist with various household chores. This system operates in a manner optimized for the user's home environment.

[0396] First, the system uses observation tools mounted on the robot to understand the current state of the room. The robot uses a camera to photograph the degree of dirtiness in the room and sensors to measure temperature and humidity, collecting the necessary environmental data. This data is then transmitted by the robot to a server.

[0397] The server uses analysis tools to determine the priority of household chores based on the received environmental data. In this process, the user's past behavioral history and preferences are also taken into account to adjust the priorities to match the user's needs. For example, multiple tasks such as cleaning, laundry, and cooking are listed in order of importance.

[0398] Next, the server uses a command mechanism to generate instructions for the robot regarding specific tasks to be performed. This allows the robot to sequentially perform various household chores. Because the robot, equipped with execution mechanisms, physically carries out the specified tasks, household chores are completed without the user having to touch them.

[0399] The server monitors the progress of household chores through progress reporting mechanisms and collects progress information in real time. The terminal notifies the user of this progress information via an application, and the user can easily check which chores have been completed and what the current progress is using a smartphone or other device. This allows the user to keep track of the progress of household chores step by step and adjust instructions as needed.

[0400] This system aims to improve the quality of life for users by efficiently automating household chores while they go about their normal daily lives. It is expected to particularly contribute to reducing the burden of housework for the elderly and dual-income households.

[0401] The following describes the processing flow.

[0402] Step 1:

[0403] The server receives environmental data collected by the robot using observation tools. This data includes information such as the cleanliness of the room, temperature, humidity, and the arrangement of objects. This data is recorded in a database before analysis, in preparation for subsequent processing.

[0404] Step 2:

[0405] Based on the received data, the server activates an analysis tool to determine the priority of current household chore needs. A machine learning algorithm references past data and takes into account user preferences and behaviors under similar conditions to efficiently allocate tasks.

[0406] Step 3:

[0407] The server utilizes command mechanisms to generate and send specific instructions for household tasks to the robot. These instructions include details of the task and execution timing based on priority. For example, they might include a specific command such as, "Start cleaning the living room at 10:00 AM."

[0408] Step 4:

[0409] The server receives feedback from the robot and monitors the progress of household chores through progress reporting mechanisms. It checks whether the tasks being performed are proceeding according to plan and adjusts the schedule as needed.

[0410] Step 5:

[0411] The terminal notifies the user's smart device of the latest task progress based on progress information received from the server. The user can check which tasks are completed or in progress through the app on their terminal. This allows the user to understand the progress of household chores in real time and confidently entrust the management to the system.

[0412] (Example 1)

[0413] Next, we will describe Example 1. 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."

[0414] In modern society, household chores are often not managed efficiently, placing a significant burden on the elderly and dual-income households. This problem leads to wasted time and effort, lowering the quality of life. There is a need for a system that efficiently handles household chores and provides users with appropriate information related to them.

[0415] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0416] In this invention, the server includes detection means for understanding the environment, processing means for analyzing the information acquired by the detection means and formulating work priorities, and instruction means for creating work instructions. This enables efficient and user-friendly work management and execution.

[0417] "Detection methods for understanding the environment" refers to devices and sensors used to observe conditions within a home and collect necessary data.

[0418] "Processing means" refers to devices or software used to analyze acquired information and determine the priority of tasks.

[0419] "Instruction means" refers to devices or programs that generate specific work instructions based on analyzed information.

[0420] An "execution device" refers to a robot or machine that executes instructions created by an instruction means and actually performs household tasks.

[0421] "Reporting means" refers to a system for monitoring the progress of work and communicating progress information to users.

[0422] "Correction measures" refer to devices or algorithms used to adjust the priority of tasks based on the user's preferences and past behavioral history.

[0423] "Notification means" refers to a function that uses mobile devices or similar devices to present work progress information to the user.

[0424] Modes for carrying out the invention

[0425] This invention is an autonomous system for efficiently managing and performing household tasks. The server uses detection means to understand the household environment. Specifically, it uses a robot equipped with cameras and sensors to collect indoor image data and environmental data. The collected data is transmitted to a server in the cloud.

[0426] The server analyzes the received data. It uses an AI model to analyze the collected data and automatically determines the priority of tasks. This involves using software such as Python and Python libraries (e.g., TensorFlow, scikit-learn). During the analysis process, a database is utilized to consider the user's past behavior and preferences.

[0427] As a means of giving instructions, the server generates specific instructions for household chores based on determined priorities and sends them to the robot. This process utilizes communication protocols (e.g., MQTT, WebSocket). Based on these instructions, the robot performs tasks such as cleaning and laundry.

[0428] The server monitors the progress of the tasks being performed in real time. The terminal notifies the user of the progress via smartphone or tablet. Mobile applications are used for this notification method.

[0429] For example, if a user wants to clean their room and prepare a meal before returning home from work, the robot would first detect the dirt in the room, prioritize the cleaning tasks, and then begin simple cooking in the kitchen. Progress is notified to the user's smartphone in real time, and the user can adjust the instructions as needed.

[0430] Examples of prompts include, "Generate a natural language description to determine the priority of household tasks," and "Describe how an autonomous robotic system will perform tasks in the home."

[0431] This system is expected to significantly reduce the burden of household chores, especially for the elderly and dual-income households, and contribute to improving their quality of life.

[0432] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0433] Step 1:

[0434] The server receives environmental data transmitted from the robot. It receives image data captured by a camera and sensor data such as temperature and humidity as input. Based on this data, it initializes the current state of the home and saves it to a database. Specifically, the image data undergoes preprocessing to analyze color information and shape, and the sensor data is used to calculate the mean and standard deviation.

[0435] Step 2:

[0436] The server analyzes the input environmental data using an AI model. Specifically, it applies algorithms to quantify dirtiness and clutter levels from image data, and converts temperature and humidity data into indicators for evaluating comfort levels. The output generates a task list indicating whether cleaning or temperature adjustment is necessary. Specifically, it utilizes deep learning techniques for image analysis and statistical methods for sensor data.

[0437] Step 3:

[0438] The server determines task priorities based on analysis. It considers the user's past behavior history and preferences to determine the optimal work order. Its input includes user profile data, and its output is a prioritized list of work instructions. Specifically, a weighting algorithm calculates the importance of each task.

[0439] Step 4:

[0440] The server transmits specific work instructions to the robot through an instruction mechanism. The input includes a prioritized list of work instructions, and the output contains detailed procedural information for each task. In practice, instructions are transmitted in real time using a communication protocol.

[0441] Step 5:

[0442] The terminal receives progress data transmitted from the server via a progress reporting mechanism. Input includes progress logs, and output is a notification message to the user. Specifically, progress is notified via a smartphone app, which the user can view on the screen.

[0443] Step 6:

[0444] Users can modify instructions via the terminal as needed. Input includes user feedback, and the modified work instructions are sent to the server as output. Specifically, the system provides a function to edit and update instructions in real time on the user interface.

[0445] Throughout this entire process, household tasks are efficiently managed and executed, and users are provided with advanced work units tailored to their needs.

[0446] (Application Example 1)

[0447] Next, we will explain Application Example 1. In the following explanation, 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."

[0448] To improve the efficiency of diverse tasks and achieve flexible task management in production environments, it is necessary to monitor progress in real time and appropriately adjust priorities. However, manual adjustments by workers are time-consuming and hinder productivity improvements. This is especially true in workplaces with a wide range of tasks, where efficient management is difficult.

[0449] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0450] In this invention, the server includes observation means for collecting environmental information, analysis means for analyzing the information collected by the observation means and determining the priority of business tasks, and command means for generating commands for executing tasks based on the priority determined by the analysis means. This enables automatic optimization and efficient management of business tasks in the production site.

[0451] "Environmental information" refers to physical data such as temperature, humidity, and light intensity observed within the work space, as well as information related to the progress and procedures of the work.

[0452] "Observation tools" refer to devices such as sensors and cameras used to collect environmental information in real time.

[0453] "Analysis tools" refer to software or algorithms used to analyze data collected by observation tools and determine the priority of business tasks.

[0454] A "command means" is a device or program that generates specific instructions for carrying out each business task based on the priority determined by the analysis means.

[0455] "Execution means" refers to robots or automated systems that perform actual tasks based on commands generated by command means.

[0456] A "progress reporting system" refers to a communication function or data management system used to record the progress of work performed by the execution system and report it to relevant parties.

[0457] "User" refers to an individual or organization that is in a position to supervise or manage the system.

[0458] "Device" refers to a device that a user carries or uses, and includes smartphones and tablets.

[0459] The system for implementing this invention comprises a series of processes for acquiring environmental information, analyzing it, setting priorities, and issuing commands. Specifically, it collects data within the workspace using observation means such as sensors and cameras, and the server analyzes this data. For analysis, it employs a generative AI model using, for example, Python libraries such as TensorFlow or PyTorch. Based on the priorities determined by the analysis means, the server generates commands for carrying out tasks.

[0460] This command is sent to the robot or automated system (execution mechanism), and the specific task begins. The server manages the progress of the task through a progress reporting mechanism. This information is transmitted in real time to the user's device (e.g., smartphone or tablet), allowing the user to monitor the situation. The user can modify the command or reset the task priority as needed.

[0461] As a concrete example, consider a system in an automotive parts factory where inventory management sensors and work robots work together to assemble parts and efficiently manage the production process. In this case, an example of a prompt message generated by the server would be: "Consider the machine operation data and production status data within the factory, and calculate the optimal process priority. Also, construct an algorithm that can issue real-time progress and efficiency improvement instructions." This would enable flexible production in response to demand while maintaining work efficiency.

[0462] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0463] Step 1:

[0464] The server collects environmental information from observation devices. This information includes data such as temperature, humidity, light intensity, and operating status obtained from sensors and cameras. This data is transmitted to the server via the network and stored in a database.

[0465] Step 2:

[0466] The server processes accumulated environmental information using analytical tools. An AI model is applied using Python libraries such as TensorFlow and PyTorch to calculate the optimal priority of business tasks. Analysis based on input data enables real-time decision-making.

[0467] Step 3:

[0468] Based on the priorities calculated by the analysis tools, the server generates specific work instructions using the command tools. These instructions are generated as detailed information necessary for carrying out each work task, such as which machines to operate or which parts to use.

[0469] Step 4:

[0470] The server transmits the generated work instructions to the robots and automation systems that will execute them via the network. This ensures that each task is carried out accurately. The tasks are executed sequentially as specified, and the physical operations begin.

[0471] Step 5:

[0472] The server receives progress reports from the execution system through a progress reporting mechanism. Inputs include the completion status of each task and tasks currently in progress. Based on this, the server analyzes the current progress, records it in the database, and generates new instructions as needed.

[0473] Step 6:

[0474] The terminal notifies users of progress information. Through an application installed on a smartphone or tablet, users can see real-time progress and work instructions. This allows users to check the situation on-site and issue new instructions if necessary.

[0475] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0476] The autonomous general-purpose home service robot system of the present invention, in addition to collecting and analyzing environmental data, determining the priority of household chores, generating and executing commands, and reporting progress, integrates an emotion engine to realize household assistance that is more optimized for the user.

[0477] This system uses a robot installed in the home to collect environmental data using observation tools. This includes taking pictures of the level of dirtiness in the room and measuring temperature and humidity. Simultaneously, an emotion engine estimates the user's emotions from their facial expressions, voice tone, and gestures, and sends this emotion data to a server.

[0478] The server analyzes the received data to determine the priority of household chores. By taking into account the user's past history and current emotions, more appropriate task scheduling becomes possible. For example, if the user is feeling stressed, adjustments will be made to prioritize quick and easy chores.

[0479] Once priorities are determined, the command system generates specific task instructions and sends them to the robot. The robot then performs household chores based on the received instructions. The content and method of the chores performed are adaptively modified according to emotional data.

[0480] Furthermore, the progress of ongoing tasks is reported to the server in real time, and users can check the progress through their terminals. In addition, messages such as encouragement and warnings tailored to the user's emotions are sent, providing support that is sensitive to the user's feelings.

[0481] In this way, the system provided by the present invention can realize household support tailored to the user's situation and emotions, thereby improving the quality of life and reducing the burden of household chores. However, data exchange and analysis functions between various modules are implemented by utilizing commonly available communication technologies and cloud computing technologies.

[0482] The following describes the processing flow.

[0483] Step 1:

[0484] The server receives environmental and emotional data transmitted from the robot. Environmental data includes room cleanliness, temperature, humidity, etc., while emotional data includes the user's emotional state analyzed through an emotion engine. This received data is recorded in a database.

[0485] Step 2:

[0486] The server uses analytical tools to determine the priority of household tasks based on the received environmental and emotional data. If the user indicates fatigue, it prioritizes tasks that can be completed quickly, thus prioritizing tasks according to the user's emotions. This analysis result is then reflected in the generation of subsequent commands.

[0487] Step 3:

[0488] The server uses a command mechanism to generate specific task instructions based on priority. These instructions include details of the tasks to be performed and recommended procedures, and are sent to the robot. For example, an instruction might be, "The user wants to relax, so clean in silent mode."

[0489] Step 4:

[0490] Based on reports received from the robot, the server monitors the progress of ongoing tasks using a progress reporting mechanism. Based on the reported progress information, the server verifies task completion and prepares for the next task instruction.

[0491] Step 5:

[0492] The device sends progress updates received from the server, along with emotionally sensitive notifications, to the user. Through the device, the user can check the progress of household chores in real time and receive encouragement and reminders tailored to the situation. This allows the user to confidently entrust their daily chores to the system.

[0493] (Example 2)

[0494] Next, we will describe Example 2. 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."

[0495] In modern households, the burden of household chores is increasing due to various factors. In particular, emotional stress and time constraints make it difficult to efficiently prioritize household tasks. Furthermore, conventional systems cannot provide appropriate support based on the emotional state of individual users, making it difficult to improve the quality of life at home.

[0496] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0497] In this invention, the server includes an acquisition means for collecting environmental information, a calculation means for analyzing the information collected by the acquisition means and determining the priority of work tasks, and an emotion analysis means for estimating the emotional state and incorporating it into the analysis results. This allows for adaptive adjustment of work priorities based on the user's emotional state, enabling more efficient and personalized home support.

[0498] "Environmental information" refers to data that indicates the physical state and conditions within a home, including temperature, humidity, and pollution levels.

[0499] "Means of acquisition" refers to devices and sensors used to collect environmental information.

[0500] "Computational means" refers to a computing device or software used to analyze acquired information and determine the priority of household tasks.

[0501] "Emotional analysis means" refers to a technology or device that analyzes a user's facial expressions, voice, and actions to estimate their emotional state at that time.

[0502] "Instruction means" refers to a device or program that generates specific work instructions based on the priority of tasks determined by the calculation means.

[0503] An "execution device" is a device or robot that actually performs household tasks in response to generated commands.

[0504] A "reporting device" is a device or function that records the progress of a task in progress and reports it to a server or user terminal.

[0505] A "notification device" is a terminal or application used to communicate progress and other important information reported by a reporting device to the user.

[0506] This invention integrates various technological elements to provide a system that efficiently supports tasks within the home. This system collects information about the home environment, analyzes that information to derive the optimal work sequence, and provides work support tailored to each individual user.

[0507] The server collects physical data such as temperature, humidity, and pollution levels through environmental data acquisition methods that work in conjunction with sensors installed in the home. This makes it possible to understand the conditions of the room and the need for work.

[0508] Furthermore, the server uses emotion analysis tools, including facial expression recognition and voice analysis, to understand the user's emotions. This technology is supported by devices placed in the home, such as cameras and microphones. The analyzed emotion data plays an important role in determining task priorities.

[0509] The server integrates the above data and performs calculations using an AI model to determine the priority of household tasks. For example, if the user is feeling stressed, it will recommend simple tasks that can be completed quickly. Based on this analysis, the command system operates and generates specific work instructions. These instructions are sent to execution devices installed in the home, and the devices perform the tasks according to the instructions.

[0510] Users can check the progress of their ongoing tasks in real time using their terminals. Progress data from the reporting device is sent to the terminals via a server, and users receive notifications tailored to their emotions. For example, messages such as "Good job!" can be displayed to encourage relaxation.

[0511] For example, if the system suggests a simple cleaning task when the user is tired, the prompt message would be, "Please suggest a simple task to perform when the user's current emotion is 'tired'."

[0512] In this way, the present invention can improve the quality of life by providing personalized in-home support tailored to the user's emotions and circumstances.

[0513] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0514] Step 1:

[0515] The user activates sensors installed in their home. The sensors detect indoor temperature, humidity, and air quality, acquiring environmental information. This information is sent to the server as input. The server receives this data and prepares it to be stored in a database. At this stage, the data is still in its raw, unprocessed state.

[0516] Step 2:

[0517] The server analyzes the received environmental information. Specifically, it performs data cleansing, correcting missing values ​​and outliers. Based on this clean data, it uses an AI model for analysis. The output is information analyzing the state of the room. The server then passes this information to the next emotion analysis tool.

[0518] Step 3:

[0519] When a user engages in activities within their home, the server utilizes emotion analysis tools to estimate their emotional state by analyzing their facial expressions and voice. Data from the camera and microphone serves as input. The analyzed emotion data is output as the user's emotional state and used in the next priority determination process.

[0520] Step 4:

[0521] The server integrates both environmental and emotional information and uses an AI model to determine the priority of household tasks. The input consists of previously analyzed environmental and emotional data. This calculation outputs instructions on "which tasks should be prioritized." The output is then sent to a command system.

[0522] Step 5:

[0523] The server sends instructions to the execution device (such as a home robot) through a command system. Specifically, a command is generated that describes a prioritized task in detail. The execution device receives this command and prepares to start the specified task. This causes the robot to perform actions such as cleaning or tidying up.

[0524] Step 6:

[0525] When the execution device performs a task, progress information related to that task is sent to the server via the reporting device. The input is progress data from the execution device. The server receives and analyzes this data and monitors the progress in real time. This information is then displayed on the user's terminal via the notification device.

[0526] Step 7:

[0527] Users check the progress of their tasks using their devices. Notifications displayed on the devices are based on the latest progress information from the server. This allows users to check the status of each task in a timely manner. Reminders and encouraging messages tailored to specific emotions may also be displayed.

[0528] (Application Example 2)

[0529] Next, we will explain application example 2. In the following explanation, 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."

[0530] Conventional home work support systems lack the ability to provide optimal service based on the user's emotions. Furthermore, even in retail stores, services that take customer emotions into consideration are not adequately provided, making it necessary to improve customer satisfaction.

[0531] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0532] In this invention, the server includes an observation device for collecting environmental information, an analysis device for determining the priority of household tasks, and an emotion analysis device for analyzing customer emotion information and adjusting service provision priorities based on the analysis results. This enables the provision of optimized services based on the emotions of users and customers.

[0533] "Environmental information" refers to data that indicates the conditions and circumstances inside a room or store, and is acquired through various sensors such as temperature, humidity, and level of soiling.

[0534] An "observation device" is a device used to acquire environmental information, and it uses sensors, cameras, etc., to detect conditions inside homes or stores.

[0535] An "analysis device" is a device that processes information collected by observation devices and determines the priority of tasks and services.

[0536] A "command device" is a device that generates commands to perform specific tasks or services based on the priorities determined by the analysis device.

[0537] An "execution device" is a device that performs necessary tasks or services within a home or store in accordance with commands from a command device.

[0538] A "progress reporting device" is a device used to report the progress of the work and services performed by the execution device.

[0539] An "emotion analysis device" is a device that analyzes the emotions of users or customers from their facial expressions, tone of voice, etc., and adjusts the priority of services based on the results.

[0540] A "service management device" is a device used to manage service content, staff allocation, and other aspects in order to improve the customer experience within a store.

[0541] A "correction device" is a device that adjusts the priority of tasks and services based on the user's past history and preferences.

[0542] This invention optimizes various tasks within homes and stores according to the user's emotional state using an autonomous system. The server employs an observation device to collect environmental information and an emotion analysis device to analyze customer emotional information. This allows the system to determine the priority of tasks within the home and service provision within stores, providing users and customers with the optimal experience.

[0543] Specifically, observation devices capture environmental information, and emotion analysis devices analyze the facial expressions and tone of voice of users and customers in real time. Based on the analysis results, a command device generates commands through advanced algorithms, and a progress reporting device reports to users and store staff that the work or service is being executed and progressing smoothly. The server is integrated by programs and operates in conjunction with software such as Python, OpenCV, and emotion analysis libraries.

[0544] For example, if a customer is dissatisfied with a long queue in a store, an emotion analysis device can detect that emotion, and a service management device can automatically issue instructions to quickly reassign additional staff to the queue, thereby improving customer satisfaction. Analysis using a generative AI model makes it possible to respond to each user's emotions in the shortest possible time.

[0545] A concrete example of a prompt sentence for a generative AI model is: "Detect customer stress caused by long waiting times in store queues and suggest how store staff should address the issue."

[0546] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0547] Step 1:

[0548] The server collects environmental information using observation devices. Specifically, it acquires data such as temperature, humidity, and room cleanliness through various sensors. The input is raw data from the sensors, and the output is environmental data for processing. This data is stored in a database for subsequent analysis.

[0549] Step 2:

[0550] The server uses an emotion analysis device to acquire facial expression data from users and customers and performs emotion analysis. The input here is camera footage, and the output is the emotion analysis result. Using a generative AI model, it analyzes facial expressions, voice tone, gestures, etc., to grasp the emotional state of the situation in real time.

[0551] Step 3:

[0552] The analysis device takes the environmental information and sentiment analysis results obtained in steps 1 and 2 as input to determine high-priority tasks and services. The output is a priority list, which is sent to the command device. Specifically, the priority determination algorithm is executed using a programming language such as Python.

[0553] Step 4:

[0554] The command device generates specific task and service commands based on the priority list transmitted from the analysis device. The input is the priority list, and the output is the command to the execution device. This allows the system to automatically send commands to ensure the smooth delivery of necessary services within homes and stores.

[0555] Step 5:

[0556] The execution device performs tasks and services within a home or store based on commands received from the command device. The input is the command content, and the output is the completed state of the task. For example, it might rearrange the placement of store staff as needed, or initiate cleaning work within a home.

[0557] Step 6:

[0558] The progress reporting device monitors the progress of work and services in real time and reports the progress to users and store staff. The input is progress data from the execution device, and the output is a progress report. Users can check the progress via a terminal, and suggestions and feedback using a generated AI model are provided as needed.

[0559] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0560] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0561] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0562] [Fourth Embodiment]

[0563] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0564] As shown in Figure 7, the 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.

[0565] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0566] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0567] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0568] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0569] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0570] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0571] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0572] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0573] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0574] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0575] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0576] The autonomous general-purpose home service robot system of this invention is designed to efficiently assist with various household chores. This system operates in a manner optimized for the user's home environment.

[0577] First, the system uses observation tools mounted on the robot to understand the current state of the room. The robot uses a camera to photograph the degree of dirtiness in the room and sensors to measure temperature and humidity, collecting the necessary environmental data. This data is then transmitted by the robot to a server.

[0578] The server uses analysis tools to determine the priority of household chores based on the received environmental data. In this process, the user's past behavioral history and preferences are also taken into account to adjust the priorities to match the user's needs. For example, multiple tasks such as cleaning, laundry, and cooking are listed in order of importance.

[0579] Next, the server uses a command mechanism to generate instructions for the robot regarding specific tasks to be performed. This allows the robot to sequentially perform various household chores. Because the robot, equipped with execution mechanisms, physically carries out the specified tasks, household chores are completed without the user having to touch them.

[0580] The server monitors the progress of household chores through progress reporting mechanisms and collects progress information in real time. The terminal notifies the user of this progress information via an application, and the user can easily check which chores have been completed and what the current progress is using a smartphone or other device. This allows the user to keep track of the progress of household chores step by step and adjust instructions as needed.

[0581] This system aims to improve the quality of life for users by efficiently automating household chores while they go about their normal daily lives. It is expected to particularly contribute to reducing the burden of housework for the elderly and dual-income households.

[0582] The following describes the processing flow.

[0583] Step 1:

[0584] The server receives environmental data collected by the robot using observation tools. This data includes information such as the cleanliness of the room, temperature, humidity, and the arrangement of objects. This data is recorded in a database before analysis, in preparation for subsequent processing.

[0585] Step 2:

[0586] Based on the received data, the server activates an analysis tool to determine the priority of current household chore needs. A machine learning algorithm references past data and takes into account user preferences and behaviors under similar conditions to efficiently allocate tasks.

[0587] Step 3:

[0588] The server utilizes command mechanisms to generate and send specific instructions for household tasks to the robot. These instructions include details of the task and execution timing based on priority. For example, they might include a specific command such as, "Start cleaning the living room at 10:00 AM."

[0589] Step 4:

[0590] The server receives feedback from the robot and monitors the progress of household chores through progress reporting mechanisms. It checks whether the tasks being performed are proceeding according to plan and adjusts the schedule as needed.

[0591] Step 5:

[0592] The terminal notifies the user's smart device of the latest task progress based on progress information received from the server. The user can check which tasks are completed or in progress through the app on their terminal. This allows the user to understand the progress of household chores in real time and confidently entrust the management to the system.

[0593] (Example 1)

[0594] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0595] In modern society, household chores are often not managed efficiently, placing a significant burden on the elderly and dual-income households. This problem leads to wasted time and effort, lowering the quality of life. There is a need for a system that efficiently handles household chores and provides users with appropriate information related to them.

[0596] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0597] In this invention, the server includes detection means for understanding the environment, processing means for analyzing the information acquired by the detection means and formulating work priorities, and instruction means for creating work instructions. This enables efficient and user-friendly work management and execution.

[0598] "Detection methods for understanding the environment" refers to devices and sensors used to observe conditions within a home and collect necessary data.

[0599] "Processing means" refers to devices or software used to analyze acquired information and determine the priority of tasks.

[0600] "Instruction means" refers to devices or programs that generate specific work instructions based on analyzed information.

[0601] An "execution device" refers to a robot or machine that executes instructions created by an instruction means and actually performs household tasks.

[0602] "Reporting means" refers to a system for monitoring the progress of work and communicating progress information to users.

[0603] "Correction measures" refer to devices or algorithms used to adjust the priority of tasks based on the user's preferences and past behavioral history.

[0604] "Notification means" refers to a function that uses mobile devices or similar devices to present work progress information to the user.

[0605] Modes for carrying out the invention

[0606] This invention is an autonomous system for efficiently managing and performing household tasks. The server uses detection means to understand the household environment. Specifically, it uses a robot equipped with cameras and sensors to collect indoor image data and environmental data. The collected data is transmitted to a server in the cloud.

[0607] The server analyzes the received data. It uses an AI model to analyze the collected data and automatically determines the priority of tasks. This involves using software such as Python and Python libraries (e.g., TensorFlow, scikit-learn). During the analysis process, a database is utilized to consider the user's past behavior and preferences.

[0608] As a means of giving instructions, the server generates specific instructions for household chores based on determined priorities and sends them to the robot. This process utilizes communication protocols (e.g., MQTT, WebSocket). Based on these instructions, the robot performs tasks such as cleaning and laundry.

[0609] The server monitors the progress of the tasks being performed in real time. The terminal notifies the user of the progress via smartphone or tablet. Mobile applications are used for this notification method.

[0610] For example, if a user wants to clean their room and prepare a meal before returning home from work, the robot would first detect the dirt in the room, prioritize the cleaning tasks, and then begin simple cooking in the kitchen. Progress is notified to the user's smartphone in real time, and the user can adjust the instructions as needed.

[0611] Examples of prompts include, "Generate a natural language description to determine the priority of household tasks," and "Describe how an autonomous robotic system will perform tasks in the home."

[0612] This system is expected to significantly reduce the burden of household chores, especially for the elderly and dual-income households, and contribute to improving their quality of life.

[0613] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0614] Step 1:

[0615] The server receives environmental data transmitted from the robot. It receives image data captured by a camera and sensor data such as temperature and humidity as input. Based on this data, it initializes the current state of the home and saves it to a database. Specifically, the image data undergoes preprocessing to analyze color information and shape, and the sensor data is used to calculate the mean and standard deviation.

[0616] Step 2:

[0617] The server analyzes the input environmental data using an AI model. Specifically, it applies algorithms to quantify dirtiness and clutter levels from image data, and converts temperature and humidity data into indicators for evaluating comfort levels. The output generates a task list indicating whether cleaning or temperature adjustment is necessary. Specifically, it utilizes deep learning techniques for image analysis and statistical methods for sensor data.

[0618] Step 3:

[0619] The server determines task priorities based on analysis. It considers the user's past behavior history and preferences to determine the optimal work order. Its input includes user profile data, and its output is a prioritized list of work instructions. Specifically, a weighting algorithm calculates the importance of each task.

[0620] Step 4:

[0621] The server transmits specific work instructions to the robot through an instruction mechanism. The input includes a prioritized list of work instructions, and the output contains detailed procedural information for each task. In practice, instructions are transmitted in real time using a communication protocol.

[0622] Step 5:

[0623] The terminal receives progress data transmitted from the server via a progress reporting mechanism. Input includes progress logs, and output is a notification message to the user. Specifically, progress is notified via a smartphone app, which the user can view on the screen.

[0624] Step 6:

[0625] Users can modify instructions via the terminal as needed. Input includes user feedback, and the modified work instructions are sent to the server as output. Specifically, the system provides a function to edit and update instructions in real time on the user interface.

[0626] Throughout this entire process, household tasks are efficiently managed and executed, and users are provided with advanced work units tailored to their needs.

[0627] (Application Example 1)

[0628] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0629] To improve the efficiency of diverse tasks and achieve flexible task management in production environments, it is necessary to monitor progress in real time and appropriately adjust priorities. However, manual adjustments by workers are time-consuming and hinder productivity improvements. This is especially true in workplaces with a wide range of tasks, where efficient management is difficult.

[0630] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0631] In this invention, the server includes observation means for collecting environmental information, analysis means for analyzing the information collected by the observation means and determining the priority of business tasks, and command means for generating commands for executing tasks based on the priority determined by the analysis means. This enables automatic optimization and efficient management of business tasks in the production site.

[0632] "Environmental information" refers to physical data such as temperature, humidity, and light intensity observed within the work space, as well as information related to the progress and procedures of the work.

[0633] "Observation tools" refer to devices such as sensors and cameras used to collect environmental information in real time.

[0634] "Analysis tools" refer to software or algorithms used to analyze data collected by observation tools and determine the priority of business tasks.

[0635] A "command means" is a device or program that generates specific instructions for carrying out each business task based on the priority determined by the analysis means.

[0636] "Execution means" refers to robots or automated systems that perform actual tasks based on commands generated by command means.

[0637] A "progress reporting system" refers to a communication function or data management system used to record the progress of work performed by the execution system and report it to relevant parties.

[0638] "User" refers to an individual or organization that is in a position to supervise or manage the system.

[0639] "Device" refers to a device that a user carries or uses, and includes smartphones and tablets.

[0640] The system for implementing this invention comprises a series of processes for acquiring environmental information, analyzing it, setting priorities, and issuing commands. Specifically, it collects data within the workspace using observation means such as sensors and cameras, and the server analyzes this data. For analysis, it employs a generative AI model using, for example, Python libraries such as TensorFlow or PyTorch. Based on the priorities determined by the analysis means, the server generates commands for carrying out tasks.

[0641] This command is sent to the robot or automated system (execution mechanism), and the specific task begins. The server manages the progress of the task through a progress reporting mechanism. This information is transmitted in real time to the user's device (e.g., smartphone or tablet), allowing the user to monitor the situation. The user can modify the command or reset the task priority as needed.

[0642] As a concrete example, consider a system in an automotive parts factory where inventory management sensors and work robots work together to assemble parts and efficiently manage the production process. In this case, an example of a prompt message generated by the server would be: "Consider the machine operation data and production status data within the factory, and calculate the optimal process priority. Also, construct an algorithm that can issue real-time progress and efficiency improvement instructions." This would enable flexible production in response to demand while maintaining work efficiency.

[0643] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0644] Step 1:

[0645] The server collects environmental information from observation devices. This information includes data such as temperature, humidity, light intensity, and operating status obtained from sensors and cameras. This data is transmitted to the server via the network and stored in a database.

[0646] Step 2:

[0647] The server processes accumulated environmental information using analytical tools. An AI model is applied using Python libraries such as TensorFlow and PyTorch to calculate the optimal priority of business tasks. Analysis based on input data enables real-time decision-making.

[0648] Step 3:

[0649] Based on the priorities calculated by the analysis tools, the server generates specific work instructions using the command tools. These instructions are generated as detailed information necessary for carrying out each work task, such as which machines to operate or which parts to use.

[0650] Step 4:

[0651] The server transmits the generated work instructions to the robots and automation systems that will execute them via the network. This ensures that each task is carried out accurately. The tasks are executed sequentially as specified, and the physical operations begin.

[0652] Step 5:

[0653] The server receives progress reports from the execution system through a progress reporting mechanism. Inputs include the completion status of each task and tasks currently in progress. Based on this, the server analyzes the current progress, records it in the database, and generates new instructions as needed.

[0654] Step 6:

[0655] The terminal notifies users of progress information. Through an application installed on a smartphone or tablet, users can see real-time progress and work instructions. This allows users to check the situation on-site and issue new instructions if necessary.

[0656] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0657] The autonomous general-purpose home service robot system of the present invention, in addition to collecting and analyzing environmental data, determining the priority of household chores, generating and executing commands, and reporting progress, integrates an emotion engine to realize household assistance that is more optimized for the user.

[0658] This system uses a robot installed in the home to collect environmental data using observation tools. This includes taking pictures of the level of dirtiness in the room and measuring temperature and humidity. Simultaneously, an emotion engine estimates the user's emotions from their facial expressions, voice tone, and gestures, and sends this emotion data to a server.

[0659] The server analyzes the received data to determine the priority of household chores. By taking into account the user's past history and current emotions, more appropriate task scheduling becomes possible. For example, if the user is feeling stressed, adjustments will be made to prioritize quick and easy chores.

[0660] Once priorities are determined, the command system generates specific task instructions and sends them to the robot. The robot then performs household chores based on the received instructions. The content and method of the chores performed are adaptively modified according to emotional data.

[0661] Furthermore, the progress of ongoing tasks is reported to the server in real time, and users can check the progress through their terminals. In addition, messages such as encouragement and warnings tailored to the user's emotions are sent, providing support that is sensitive to the user's feelings.

[0662] In this way, the system provided by the present invention can realize household support tailored to the user's situation and emotions, thereby improving the quality of life and reducing the burden of household chores. However, data exchange and analysis functions between various modules are implemented by utilizing commonly available communication technologies and cloud computing technologies.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] The server receives environmental and emotional data transmitted from the robot. Environmental data includes room cleanliness, temperature, humidity, etc., while emotional data includes the user's emotional state analyzed through an emotion engine. This received data is recorded in a database.

[0666] Step 2:

[0667] The server uses analytical tools to determine the priority of household tasks based on the received environmental and emotional data. If the user indicates fatigue, it prioritizes tasks that can be completed quickly, thus prioritizing tasks according to the user's emotions. This analysis result is then reflected in the generation of subsequent commands.

[0668] Step 3:

[0669] The server uses a command mechanism to generate specific task instructions based on priority. These instructions include details of the tasks to be performed and recommended procedures, and are sent to the robot. For example, an instruction might be, "The user wants to relax, so clean in silent mode."

[0670] Step 4:

[0671] Based on reports received from the robot, the server monitors the progress of ongoing tasks using a progress reporting mechanism. Based on the reported progress information, the server verifies task completion and prepares for the next task instruction.

[0672] Step 5:

[0673] The device sends progress updates received from the server, along with emotionally sensitive notifications, to the user. Through the device, the user can check the progress of household chores in real time and receive encouragement and reminders tailored to the situation. This allows the user to confidently entrust their daily chores to the system.

[0674] (Example 2)

[0675] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] In modern households, the burden of household chores is increasing due to various factors. In particular, emotional stress and time constraints make it difficult to efficiently prioritize household tasks. Furthermore, conventional systems cannot provide appropriate support based on the emotional state of individual users, making it difficult to improve the quality of life at home.

[0677] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0678] In this invention, the server includes an acquisition means for collecting environmental information, a calculation means for analyzing the information collected by the acquisition means and determining the priority of work tasks, and an emotion analysis means for estimating the emotional state and incorporating it into the analysis results. This allows for adaptive adjustment of work priorities based on the user's emotional state, enabling more efficient and personalized home support.

[0679] "Environmental information" refers to data that indicates the physical state and conditions within a home, including temperature, humidity, and pollution levels.

[0680] "Means of acquisition" refers to devices and sensors used to collect environmental information.

[0681] "Computational means" refers to a computing device or software used to analyze acquired information and determine the priority of household tasks.

[0682] "Emotional analysis means" refers to a technology or device that analyzes a user's facial expressions, voice, and actions to estimate their emotional state at that time.

[0683] "Instruction means" refers to a device or program that generates specific work instructions based on the priority of tasks determined by the calculation means.

[0684] An "execution device" is a device or robot that actually performs household tasks in response to generated commands.

[0685] A "reporting device" is a device or function that records the progress of a task in progress and reports it to a server or user terminal.

[0686] A "notification device" is a terminal or application used to communicate progress and other important information reported by a reporting device to the user.

[0687] This invention integrates various technological elements to provide a system that efficiently supports tasks within the home. This system collects information about the home environment, analyzes that information to derive the optimal work sequence, and provides work support tailored to each individual user.

[0688] The server collects physical data such as temperature, humidity, and pollution levels through environmental data acquisition methods that work in conjunction with sensors installed in the home. This makes it possible to understand the conditions of the room and the need for work.

[0689] Furthermore, the server uses emotion analysis tools, including facial expression recognition and voice analysis, to understand the user's emotions. This technology is supported by devices placed in the home, such as cameras and microphones. The analyzed emotion data plays an important role in determining task priorities.

[0690] The server integrates the above data and performs calculations using an AI model to determine the priority of household tasks. For example, if the user is feeling stressed, it will recommend simple tasks that can be completed quickly. Based on this analysis, the command system operates and generates specific work instructions. These instructions are sent to execution devices installed in the home, and the devices perform the tasks according to the instructions.

[0691] Users can check the progress of their ongoing tasks in real time using their terminals. Progress data from the reporting device is sent to the terminals via a server, and users receive notifications tailored to their emotions. For example, messages such as "Good job!" can be displayed to encourage relaxation.

[0692] For example, if the system suggests a simple cleaning task when the user is tired, the prompt message would be, "Please suggest a simple task to perform when the user's current emotion is 'tired'."

[0693] In this way, the present invention can improve the quality of life by providing personalized in-home support tailored to the user's emotions and circumstances.

[0694] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0695] Step 1:

[0696] The user activates sensors installed in their home. The sensors detect indoor temperature, humidity, and air quality, acquiring environmental information. This information is sent to the server as input. The server receives this data and prepares it to be stored in a database. At this stage, the data is still in its raw, unprocessed state.

[0697] Step 2:

[0698] The server analyzes the received environmental information. Specifically, it performs data cleansing, correcting missing values ​​and outliers. Based on this clean data, it uses an AI model for analysis. The output is information analyzing the state of the room. The server then passes this information to the next emotion analysis tool.

[0699] Step 3:

[0700] When a user engages in activities within their home, the server utilizes emotion analysis tools to estimate their emotional state by analyzing their facial expressions and voice. Data from the camera and microphone serves as input. The analyzed emotion data is output as the user's emotional state and used in the next priority determination process.

[0701] Step 4:

[0702] The server integrates both environmental and emotional information and uses an AI model to determine the priority of household tasks. The input consists of previously analyzed environmental and emotional data. This calculation outputs instructions on "which tasks should be prioritized." The output is then sent to a command system.

[0703] Step 5:

[0704] The server sends instructions to the execution device (such as a home robot) through a command system. Specifically, a command is generated that describes a prioritized task in detail. The execution device receives this command and prepares to start the specified task. This causes the robot to perform actions such as cleaning or tidying up.

[0705] Step 6:

[0706] When the execution device performs a task, progress information related to that task is sent to the server via the reporting device. The input is progress data from the execution device. The server receives and analyzes this data and monitors the progress in real time. This information is then displayed on the user's terminal via the notification device.

[0707] Step 7:

[0708] Users check the progress of their tasks using their devices. Notifications displayed on the devices are based on the latest progress information from the server. This allows users to check the status of each task in a timely manner. Reminders and encouraging messages tailored to specific emotions may also be displayed.

[0709] (Application Example 2)

[0710] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] Conventional home work support systems lack the ability to provide optimal service based on the user's emotions. Furthermore, even in retail stores, services that take customer emotions into consideration are not adequately provided, making it necessary to improve customer satisfaction.

[0712] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0713] In this invention, the server includes an observation device for collecting environmental information, an analysis device for determining the priority of household tasks, and an emotion analysis device for analyzing customer emotion information and adjusting service provision priorities based on the analysis results. This enables the provision of optimized services based on the emotions of users and customers.

[0714] "Environmental information" refers to data that indicates the conditions and circumstances inside a room or store, and is acquired through various sensors such as temperature, humidity, and level of soiling.

[0715] An "observation device" is a device used to acquire environmental information, and it uses sensors, cameras, etc., to detect conditions inside homes or stores.

[0716] An "analysis device" is a device that processes information collected by observation devices and determines the priority of tasks and services.

[0717] A "command device" is a device that generates commands to perform specific tasks or services based on the priorities determined by the analysis device.

[0718] An "execution device" is a device that performs necessary tasks or services within a home or store in accordance with commands from a command device.

[0719] A "progress reporting device" is a device used to report the progress of the work and services performed by the execution device.

[0720] An "emotion analysis device" is a device that analyzes the emotions of users or customers from their facial expressions, tone of voice, etc., and adjusts the priority of services based on the results.

[0721] A "service management device" is a device used to manage service content, staff allocation, and other aspects in order to improve the customer experience within a store.

[0722] A "correction device" is a device that adjusts the priority of tasks and services based on the user's past history and preferences.

[0723] This invention optimizes various tasks within homes and stores according to the user's emotional state using an autonomous system. The server employs an observation device to collect environmental information and an emotion analysis device to analyze customer emotional information. This allows the system to determine the priority of tasks within the home and service provision within stores, providing users and customers with the optimal experience.

[0724] Specifically, observation devices capture environmental information, and emotion analysis devices analyze the facial expressions and tone of voice of users and customers in real time. Based on the analysis results, a command device generates commands through advanced algorithms, and a progress reporting device reports to users and store staff that the work or service is being executed and progressing smoothly. The server is integrated by programs and operates in conjunction with software such as Python, OpenCV, and emotion analysis libraries.

[0725] For example, if a customer is dissatisfied with a long queue in a store, an emotion analysis device can detect that emotion, and a service management device can automatically issue instructions to quickly reassign additional staff to the queue, thereby improving customer satisfaction. Analysis using a generative AI model makes it possible to respond to each user's emotions in the shortest possible time.

[0726] A concrete example of a prompt sentence for a generative AI model is: "Detect customer stress caused by long waiting times in store queues and suggest how store staff should address the issue."

[0727] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0728] Step 1:

[0729] The server collects environmental information using observation devices. Specifically, it acquires data such as temperature, humidity, and room cleanliness through various sensors. The input is raw data from the sensors, and the output is environmental data for processing. This data is stored in a database for subsequent analysis.

[0730] Step 2:

[0731] The server uses an emotion analysis device to acquire facial expression data from users and customers and performs emotion analysis. The input here is camera footage, and the output is the emotion analysis result. Using a generative AI model, it analyzes facial expressions, voice tone, gestures, etc., to grasp the emotional state of the situation in real time.

[0732] Step 3:

[0733] The analysis device takes the environmental information and sentiment analysis results obtained in steps 1 and 2 as input to determine high-priority tasks and services. The output is a priority list, which is sent to the command device. Specifically, the priority determination algorithm is executed using a programming language such as Python.

[0734] Step 4:

[0735] The command device generates specific task and service commands based on the priority list transmitted from the analysis device. The input is the priority list, and the output is the command to the execution device. This allows the system to automatically send commands to ensure the smooth delivery of necessary services within homes and stores.

[0736] Step 5:

[0737] The execution device performs tasks and services within a home or store based on commands received from the command device. The input is the command content, and the output is the completed state of the task. For example, it might rearrange the placement of store staff as needed, or initiate cleaning work within a home.

[0738] Step 6:

[0739] The progress reporting device monitors the progress of work and services in real time and reports the progress to users and store staff. The input is progress data from the execution device, and the output is a progress report. Users can check the progress via a terminal, and suggestions and feedback using a generated AI model are provided as needed.

[0740] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0741] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0742] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0743] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0744] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0745] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0746] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0747] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0748] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0749] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0750] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0751] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0752] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0753] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0754] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0755] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0756] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0757] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0758] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0759] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0760] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0761] The following is further disclosed regarding the embodiments described above.

[0762] (Claim 1)

[0763] Observation methods for collecting environmental data,

[0764] An analysis means for analyzing data collected by the observation means and determining the priority of household tasks,

[0765] A command means that generates commands for performing household chores based on the priority determined by the analysis means,

[0766] An execution means that performs household chores in accordance with the instructions generated by the command means,

[0767] A system comprising progress reporting means for reporting the progress of the execution means.

[0768] (Claim 2)

[0769] The system according to claim 1, further comprising a corrective means for adjusting the priority of household chores based on the user's preferences and past history.

[0770] (Claim 3)

[0771] The system according to claim 1, further comprising a notification means that allows the user to check the progress reported by the progress reporting means using a device carried by the user.

[0772] "Example 1"

[0773] (Claim 1)

[0774] Detection means for understanding the environment,

[0775] A processing means for analyzing the information acquired by the detection means and formulating work priorities,

[0776] An instruction means for creating work instructions based on the priority set by the processing means,

[0777] An execution device that performs a predetermined task in accordance with instructions created by the aforementioned instruction means,

[0778] A system that monitors the working status of the execution device and includes a reporting means for communicating progress.

[0779] (Claim 2)

[0780] The system according to claim 1, further comprising a modification means for adjusting the priority of tasks based on user preferences and past history.

[0781] (Claim 3)

[0782] The system according to claim 1, further comprising a notification means for displaying the work progress communicated by the reporting means via the user's mobile device.

[0783] "Application Example 1"

[0784] (Claim 1)

[0785] Observation methods for collecting environmental information,

[0786] An analysis means for analyzing information collected by the observation means and determining the priority of business tasks,

[0787] A command means that generates commands for executing tasks based on the priority determined by the analysis means,

[0788] An execution means that performs tasks within the workspace in accordance with the commands generated by the command means,

[0789] A system comprising progress reporting means for reporting the progress of the execution means.

[0790] (Claim 2)

[0791] The system according to claim 1, further comprising a corrective means for adjusting the priority of tasks based on the user's preferences and past history.

[0792] (Claim 3)

[0793] The system according to claim 1, further comprising a notification means that allows the user to confirm the progress reported by the progress reporting means using a device carried by the user.

[0794] "Example 2 of combining an emotion engine"

[0795] (Claim 1)

[0796] Means of acquiring environmental information,

[0797] A calculation means that analyzes the information collected by the acquisition means and determines the priority of work tasks,

[0798] An instruction means that generates a command based on the priority determined by the calculation means,

[0799] An execution device that performs household tasks in accordance with the commands generated by the command means,

[0800] A reporting device that reports the progress of the execution device,

[0801] A system that includes emotion analysis means for estimating emotional states and incorporating them into the analysis results.

[0802] (Claim 2)

[0803] The system according to claim 1, further comprising a corrective means for adjusting the priority of tasks based on the emotional state of the user.

[0804] (Claim 3)

[0805] The system according to claim 1, further comprising a notification device that allows the user to check the progress reported by the reporting device using an information terminal carried by the user.

[0806] "Application example 2 when combining with an emotional engine"

[0807] (Claim 1)

[0808] Observation equipment for collecting environmental information,

[0809] An analysis device that analyzes the information collected by the observation device and determines the priority of household tasks,

[0810] A command device that generates commands for performing household tasks based on the priority determined by the analysis device,

[0811] An execution device that performs household tasks according to commands generated by the command device,

[0812] A progress reporting device that reports the progress of the execution device,

[0813] An emotion analysis device that analyzes customer emotional information and adjusts service provision priorities based on the analysis results,

[0814] A system including a service management device for optimizing the customer experience within a store.

[0815] (Claim 2)

[0816] The system according to claim 1, further comprising a correction device that adjusts the priority of tasks based on the user's preferences and past history.

[0817] (Claim 3)

[0818] The system according to claim 1, further comprising a notification device that allows the user to check the progress reported by the progress reporting device using a device carried by the user. [Explanation of Symbols]

[0819] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Observation methods for collecting environmental data, An analysis means for analyzing data collected by the observation means and determining the priority of household tasks, A command means that generates commands for performing household chores based on the priority determined by the analysis means, An execution means that performs household chores in accordance with the instructions generated by the command means, A system comprising progress reporting means for reporting the progress of the execution means.

2. The system according to claim 1, further comprising a corrective means for adjusting the priority of household chores based on the user's preferences and past history.

3. The system according to claim 1, further comprising a notification means that allows the user to check the progress reported by the progress reporting means using a device carried by the user.

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