system

Abstract

We provide the system. [Solution] A means of collecting environmental data using an artificial intelligence agent installed in an autonomous machine designed to work in a radiation environment, A means for generating a work plan using the aforementioned artificial intelligence agent, Based on the aforementioned work plan, means for remotely operating or automatically controlling the autonomous machine device, Means for immediate response in the event of an anomaly or emergency, A means for providing feedback on work completion data obtained from the autonomous machine, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method 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 a chatbot 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 a high-radiation environment such as a nuclear power plant, direct work by human workers involves significant risks to health and safety. It is necessary to minimize the exposure of workers while simultaneously performing work effectively and efficiently. However, conventional technologies have limitations in substituting work with mechanically operating devices that can operate autonomously, and there has been a demand for immediate response to emergencies and generation of flexible work plans.

Means for Solving the Problems

[0005] This invention provides a system that replaces work in radiation environments by utilizing an artificial intelligence agent mounted on an autonomous machine. The artificial intelligence agent collects environmental data in real time and generates an optimal work plan based on that information. It also remotely operates or automatically controls the autonomous machine based on this plan. It has a function to respond immediately if an anomaly or emergency is detected, and a data feedback function after work completion is used to improve future work. In this way, it is possible to safely perform work in high-risk environments in place of human workers.

[0006] An "autonomous machine" is a machine equipped with the ability to operate based on its own judgment without external intervention, and is designed to perform a specific task.

[0007] An "artificial intelligence agent" is a software program that learns on its own through machine learning and data analysis, and makes optimal decisions in response to changes in the environment.

[0008] "Environmental data" refers to information that indicates the conditions of the work environment, and specifically includes radiation levels, temperature, humidity, etc.

[0009] A "work plan" is a planning document that outlines the processes and procedures for efficiently carrying out work under specific environmental conditions.

[0010] "Remote control" refers to a technique or method of operating an object from a distance without physically touching it.

[0011] "Automatic control" refers to a system's ability to automatically adjust its operation according to defined conditions and perform appropriate tasks.

[0012] An "abnormal or emergency situation" is an unexpected situation or event that deviates from normal working conditions and requires immediate action.

[0013] "Data feedback" is the process of analyzing information collected during work and returning it to the system to help improve future work. [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 a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a 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, a 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), and the like.

[0018] In the following embodiments, a 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, a 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] This invention provides a system for efficiently performing tasks in a radiation environment by equipping autonomous machinery with an artificial intelligence agent. The characteristics and operation of this system are illustrated below.

[0036] First, in high-radiation environments such as nuclear power plants, autonomous mechanical devices collect environmental data through sensors. This includes various data such as radiation levels, temperature, and humidity. This information is centrally managed by a server, and changes in the environment are analyzed by comparing it with past data.

[0037] Next, the server generates an optimal work plan with the help of an artificial intelligence agent based on environmental data. This plan includes a list of steps necessary to maximize work efficiency, as well as specific routes and tasks to be performed. For example, when performing decontamination work in a certain area, it calculates the optimal route to avoid high-radiation areas and the amount of decontamination agent to use.

[0038] Subsequently, the terminal sends specific control instructions to the autonomous machine based on the work plan transmitted from the server. This allows the machine to execute the planned actions and report its progress to the server in real time.

[0039] Furthermore, users can use a remote control terminal to monitor the operation of the entire system and modify the plan as needed. If the user determines that a particular task has not been completed, they can enter new instructions through the terminal, and the server will update the plan again.

[0040] In the event of an anomaly or sudden emergency, the terminal immediately switches the autonomous machine to safety mode to ensure safety. Based on subsequent analysis, the server generates new guidelines for safely resuming operations.

[0041] Thus, this invention utilizes autonomous mechanical devices and advanced artificial intelligence technology to efficiently and safely perform tasks in order to protect human workers from the dangers of radiation. In particular, it is characterized as a system that contributes to future work improvements by continuously providing data feedback on the work performed.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The server collects environmental data in real time from sensors installed within the nuclear power plant. This includes important parameters such as radiation levels, temperature, and humidity.

[0045] Step 2:

[0046] The server analyzes the collected environmental data and compares the current situation with past data. Based on the results of this analysis, an AI algorithm is used to evaluate anomalies and risks and set flags for emergency response.

[0047] Step 3:

[0048] The server utilizes an AI agent to generate an optimal work plan based on the obtained analytical data. This plan includes task details, execution order, required travel routes, and equipment to be used.

[0049] Step 4:

[0050] The terminal receives the work plan transmitted from the server and sends specific control signals to the autonomous machine. This causes the machine to start operating according to the plan, and its progress is monitored.

[0051] Step 5:

[0052] Users can monitor overall work progress and environmental data through the monitor. If necessary, they can modify instructions or temporarily suspend work via the terminal.

[0053] Step 6:

[0054] The terminal receives feedback data from the machine and transmits it to the server. This data is used to re-evaluate the level of work completion and the environment.

[0055] Step 7:

[0056] If an anomaly or emergency occurs, the terminal will immediately change its control signal and switch the machine to safety mode. This information is immediately reported to the server for further analysis.

[0057] Step 8:

[0058] After the task is completed, the server analyzes all collected data and extracts areas for improvement needed for the next work plan. This feedback loop results in improved work efficiency and safety.

[0059] (Example 1)

[0060] 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."

[0061] In high-radiation environments, it is essential to ensure the safety of human workers while performing tasks efficiently and flexibly. Furthermore, immediate response to emergencies and flexible adaptation to constantly changing work plans are necessary. In addition, utilizing feedback from work results to achieve continuous improvement is crucial.

[0062] 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.

[0063] In this invention, the server includes means for aggregating environmental information and analyzing it in comparison with past information, means for generating a work plan using artificial intelligence and instructing the machine to follow that plan, and means for controlling the autonomous machine using a remote control terminal based on the plan. This enables the safety of human workers in high-radiation environments and the efficient and flexible execution of work.

[0064] "Environmental information" refers to various physical information about the work environment, such as radiation levels, temperature, and humidity.

[0065] "Aggregation" refers to gathering dispersed data in one place and managing it centrally.

[0066] "Past information" refers to data collected previously, which forms the basis for analysis and comparison.

[0067] "Artificial intelligence" refers to a series of processes performed by computer systems that mimic human intelligent behavior.

[0068] A "work plan" refers to a list of specific procedures, routes, and tasks that are set in advance to improve the efficiency of a task.

[0069] "Mechanical equipment" refers to autonomous or semi-autonomous mechanical devices that perform specific tasks.

[0070] A "remote control terminal" refers to a device used to operate machinery from a physically distant location.

[0071] An "autonomous machine" refers to a machine that uses artificial intelligence to make its own decisions and perform specific tasks.

[0072] An "emergency situation" refers to a critical and urgent situation that prevents normal operations from continuing.

[0073] "Safety mode" refers to a state where operations are temporarily stopped or the system is temporarily maintained to ensure the safety of people and machinery.

[0074] "Work progress" refers to the state or stage of whether the assigned work is progressing according to plan.

[0075] "Feedback" refers to the process of evaluating the results of work and the information obtained, and incorporating that into future plans and execution.

[0076] This invention is an autonomous mechanical device system for achieving efficient work while ensuring the safety of human workers in high-radiation environments. The system mainly consists of three components: a server, a terminal, and a user.

[0077] The server's role is to aggregate environmental information and analyze it by comparing it with historical data. Specifically, the server receives environmental data such as radiation levels, temperature, and humidity transmitted from autonomous machinery. The server stores this data in a database and performs filtering of outliers and trend analysis. Furthermore, based on the collected data, it generates an optimal work plan using a generative AI model. This generated plan includes efficient work routes and task priorities.

[0078] The terminal receives work plans transmitted from the server and sends instructions to autonomous machinery. The terminal enables remote control and allows for real-time modification of instructions depending on the situation. Furthermore, the terminal has a function to automatically switch to safety mode in the event of an emergency.

[0079] The user's role is to monitor the entire system's operation via a terminal. The user can check the progress in real time and modify the work plan as needed. Furthermore, the user can input new instructions to the server using appropriate prompt messages.

[0080] As a concrete example, consider equipment inspection work at a nuclear facility. The server collects environmental data such as radiation levels using various sensors and generates a work plan accordingly. The terminal controls autonomous machinery based on this plan, and the user monitors the progress of the plan and makes adjustments as needed.

[0081] An example of a prompt message would be, "Please tell me how to perform inspection work within the facility using autonomous machinery." This system enables improved work efficiency and safety while minimizing the effects of radiation.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The server receives sensor information transmitted from autonomous mechanical devices. Input data includes radiation levels, temperature, and humidity. The server stores this data in a database and filters out abnormal values. Specifically, the server updates the data every minute and performs trend analysis by comparing it with past data.

[0085] Step 2:

[0086] The server uses an AI model based on analyzed environmental data to generate an optimal work plan. Inputs include collected environmental data and historical data. The server uses algorithms to calculate efficient work routes and task priorities, and outputs detailed work procedures. Specific operations include determining the minimum travel distance and optimal work points during decontamination work.

[0087] Step 3:

[0088] The terminal receives work plans sent from the server and transmits instructions to autonomous machinery. The input is the work plan from the server, which the terminal converts into a format the machine can understand and outputs. Specifically, it performs real-time routing control and work start instructions for the machine.

[0089] Step 4:

[0090] The user monitors ongoing work via a terminal and modifies the plan as needed. Real-time monitoring data on the terminal serves as input, and the user outputs instructions for plan changes. Specifically, the user uses an on-screen interface to decide whether to add or cancel certain tasks.

[0091] Step 5:

[0092] In the event of an emergency, the terminal immediately switches the autonomous machine to safety mode. Inputs include emergency alerts from sensors. The terminal processes these and outputs instructions for safety mode. Specific actions include stopping the machine and issuing emergency voice alerts.

[0093] Step 6:

[0094] After completing a task, the server analyzes all collected data and generates feedback for future improvements. The input is data from the completed task, and the output is a proposed improvement plan for the next task. Specifically, it performs statistical analysis of work efficiency and identifies areas that need improvement.

[0095] (Application Example 1)

[0096] 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."

[0097] In hazardous environments, including those involving radiation, there is a need to perform work efficiently and safely while mitigating human risks. Current technology lacks the means to adequately perform automated inspection and maintenance work in these environments. Therefore, the challenge is to provide a system that can collect environmental information in real time, develop optimal work plans, and respond quickly to abnormal situations.

[0098] 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.

[0099] In this invention, the server includes means for collecting environmental information by an intelligent agent mounted on an autonomous device for working in a radiation environment, means for creating a work plan using the intelligent agent, and means for remotely operating or automatically controlling the autonomous device based on the work plan. This enables safe and effective work to be carried out while correcting operations based on real-time information updates and minimizing human intervention.

[0100] An "autonomous device" is equipment that has the ability to operate on its own judgment without detailed instructions from an external source.

[0101] An "intelligent agent" is software that uses artificial intelligence technology to analyze data and make decisions.

[0102] "Environmental information" refers to data on physical and chemical conditions such as radiation levels, temperature, and humidity.

[0103] A "work plan" is a document that outlines the procedures and processes necessary to achieve a specific objective.

[0104] "Radiation environment" refers to a work area where radioactive materials are present or are affected by them.

[0105] "Remote control" refers to a method of controlling devices or equipment from a location away from the physical site.

[0106] An "abnormal situation" refers to an unexpected situation that deviates from the norm, or a problem that threatens the safety or operation of a system.

[0107] "Information processing" refers to a series of processes that involve collecting and analyzing data and deciding on appropriate actions based on the results.

[0108] "Maintenance work" refers to periodic inspections and repairs carried out to ensure the proper operation of equipment and devices.

[0109] The system realizing this invention combines autonomous equipment and intelligent agents to support work in radiation environments. A server operates the intelligent agents to collect and analyze environmental information. The intelligent agents use software such as Python and TENSORFLOW® to analyze the collected data and generate an optimal work plan. This plan clarifies the instructions necessary for remote operation or automated control.

[0110] The server also receives real-time feedback and adjusts its operations as needed. For this purpose, it uses ROS (Robot Operating System) to communicate with autonomous devices and controls written in Python to ensure safe operation. Hardware such as radiation sensors and temperature / humidity sensors are used to acquire environmental data.

[0111] Users monitor the work status using smart devices or computer terminals and send additional instructions to the server as needed. This allows for the immediate switching of autonomous equipment to safety mode in the event of an anomaly.

[0112] One practical example is a scenario in which a robot automatically inspects piping in a chemical plant. In this case, the robot continuously collects data using sensors, detects anomalies on the spot, and immediately reports them to the server. Correction instructions are then implemented in real time.

[0113] The following are examples of prompt statements used in the generative AI model.

[0114] "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please propose how to move the inspection robot to safely resume operations. Please also consider real-time correction instructions."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server collects environmental information through various sensors (such as radiation sensors and temperature / humidity sensors) installed in autonomous devices. This information is converted from analog signals from the sensors into digital data and recorded in the server's database.

[0118] Step 2:

[0119] The server analyzes the acquired environmental information using Python or TensorFlow. Here, it compares it with past data to determine if an anomaly exists. The input is the current environmental information, and the output is the anomaly detection result.

[0120] Step 3:

[0121] The server generates a work plan using an intelligent agent. Based on anomaly detection results and environmental information, it calculates the optimal work route and procedures, and generates work instructions. The output is a detailed work plan.

[0122] Step 4:

[0123] The server sends the generated work plan to the autonomous device. Using ROS (Robot Operating System), it runs the device's control script, and the device automatically starts the planned work. The input is the work plan, and the output is the execution of control commands.

[0124] Step 5:

[0125] The terminal monitors the progress of tasks received from the server in real time. Operators can check the status via the terminal and send additional instructions if an abnormal situation occurs. Input is task progress data, and output is corrective instructions as needed.

[0126] Step 6:

[0127] The server immediately switches autonomous equipment to safety mode if an anomaly or emergency is detected. This safely stops operations and collects data for subsequent investigation and recovery. Inputs are anomaly notifications, and outputs are safety control commands.

[0128] Step 7:

[0129] The user sends prompts to the generating AI model as needed and receives suggestions for a new work plan. An example prompt is: "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please suggest how to move the inspection robot to safely resume work. Please also consider real-time correction instructions." The input is the prompt, and the output is the new suggestion.

[0130] 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.

[0131] This invention is a system that efficiently manages work in a radiation environment while taking into account the user's emotional state, thereby achieving further improvements in safety and work efficiency. The autonomous machine incorporates an artificial intelligence agent and an emotion engine.

[0132] First, autonomous machinery uses advanced sensors to acquire environmental data such as radiation levels. This data is collected on a server and analyzed by AI algorithms. During this process, environmental safety is evaluated and reflected in the work plan.

[0133] Next, the emotion engine monitors the user's emotions in real time. This is done using multiple sensing technologies, such as the user's facial expressions, voice tone, and heart rate. This data is input to a server and analyzed by an emotion analysis algorithm.

[0134] The server integrates this emotional data into the AI-generated work plan. For example, if it determines that the user is experiencing extreme stress, the work plan is temporarily suspended, and alternative routes are searched for or tasks are prioritized. This ensures safety while reducing the user's psychological burden.

[0135] The terminal transmits the generated work plan to the autonomous machine and provides appropriate control instructions. It also monitors the progress of the work and responds immediately if any abnormalities or emergencies occur.

[0136] Users can view this information through the interface and fine-tune their work as needed. For example, they can issue new instructions to machinery to avoid specific high-radiation areas.

[0137] The combination of the emotion engine and AI in this invention enables efficient and flexible work management that takes both environmental and emotional data into consideration. This system is useful not only for providing a safe and secure work environment but also for maintaining the mental health of workers.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The server collects data from environmental sensors in real time, monitoring radiation levels, temperature, and other parameters. This data is immediately analyzed and forms the basis for assessing environmental safety.

[0141] Step 2:

[0142] The emotion engine collects emotional data from the user's facial recognition device and voice recognition system. It detects the user's emotional state from changes in facial expressions, voice tone, heart rate, etc. This data is sent to a server.

[0143] Step 3:

[0144] The server integrates environmental and emotional data and generates a work plan based on this. An AI algorithm determines the optimal work steps and sequence, and adjusts the work procedure if an increase in stress or anxiety is detected.

[0145] Step 4:

[0146] The terminal transmits the work plan received from the server to the autonomous machine and sends specific control signals. During this process, the starting position of the work and the movement path of the machine are set.

[0147] Step 5:

[0148] Users can monitor the progress of their work in real time via a monitor. If any ambiguities or problems arise, users can request changes to the plan through their terminal.

[0149] Step 6:

[0150] As the autonomous machine completes its task, the terminal reports progress data to the server. In particular, if an anomaly or emergency is detected, it immediately notifies the server and triggers a response that allows the system to take appropriate action.

[0151] Step 7:

[0152] After all tasks are completed, the server comprehensively analyzes the collected data and generates feedback to improve efficiency in future tasks. This feedback is used to improve the accuracy of future plans.

[0153] (Example 2)

[0154] 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".

[0155] Modern work environments requiring both safety and efficiency are essential. However, the lack of accurate environmental information collection and flexible work management that includes workers' emotional states leads to problems such as inability to respond quickly to work interruptions or unforeseen circumstances, resulting in reduced work efficiency. Furthermore, existing systems lack sufficient processes to alleviate the mental burden on workers.

[0156] 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.

[0157] In this invention, the server includes means for acquiring ambient environmental data, including radiation; means for generating a process plan; and means for evaluating the emotional state of on-site workers using an information analysis device and reflecting this in the work. This enables the generation and adjustment of plans that comprehensively consider environmental data and workers' emotional information, thereby improving safety, optimizing work efficiency, and reducing the psychological burden on workers.

[0158] "Autonomous mechanical devices" refer to robots and devices that perform tasks autonomously in a radiation environment, minimizing human intervention.

[0159] An "information processing device" refers to a computer system that collects and analyzes environmental data and worker sentiment data, and generates and adjusts process plans based on the results.

[0160] "Surrounding environment data" refers to data that provides detailed information about the work site, such as radiation levels, temperature and humidity, and air composition.

[0161] A "process plan" refers to a plan that outlines the procedures and routes for efficiently and safely carrying out a specific task.

[0162] An "information analysis device" refers to a device or system that analyzes data to extract useful information, enabling decision-making and adjustment of plans based on that information.

[0163] "Feedback" refers to the process of providing information about the next steps or areas for improvement based on data obtained after the completion of a task.

[0164] One embodiment of the present invention is a system for efficiently and safely performing work in a radiation environment. Specific embodiments thereof are described below.

[0165] First, the server collects ambient environmental data from autonomous mechanical devices. The hardware used includes devices equipped with high-performance sensors and communication modules. For software, libraries that execute AI algorithms such as TensorFlow and PyTorch are used for data analysis. This allows for the real-time acquisition of data such as radiation levels and temperature / humidity, enabling safety assessments.

[0166] Next, the information analysis device uses facial recognition and voice analysis technologies to evaluate the emotional state of workers. Data such as facial expressions, voice tone, and heart rate are processed using OpenCV and other emotion recognition software and reflected in the work plan. For example, if a worker is in a high-stress state, the work plan is dynamically adjusted and switched to a safety-first route. In this process, a generative AI model is used to automatically generate an efficient process plan.

[0167] The terminal transmits the work plan to the autonomous machine. The necessary hardware includes network-connected devices that use communication protocols to control the machine's operation. Furthermore, the terminal monitors the progress of the work and provides an interface for immediate response if any anomalies are detected.

[0168] Users verify the information obtained through this system via an interface. The interface is designed to provide the information necessary when the user performs manual operations. For example, it may be possible to issue new instructions to avoid high-radiation areas.

[0169] As a concrete example, consider the decontamination of a facility after a natural disaster. This system first monitors radiation levels and then provides the optimal work route based on the emotional state of the workers. An example of a prompt message would be, "Please tell me how to optimize the work while considering the user's emotional state."

[0170] Through the above process, a safe and efficient working environment is provided, and the psychological burden on workers is also reduced.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The server acquires ambient environmental data transmitted from autonomous machinery. This data includes radiation levels, temperature and humidity, and air composition. The acquired environmental data is input into an AI algorithm for data processing and analysis. Specifically, safety is evaluated using TensorFlow, the data is organized, and then output as basic information for process planning.

[0174] Step 2:

[0175] The server acquires emotional data from workers. This emotional data is collected based on facial expression data, voice tone, and heart rate entered by the user into a terminal. Face recognition is performed using image processing libraries such as OpenCV, and voice tone is analyzed using voice analysis software. The acquired emotional data is then analyzed, and stress levels and emotional states are quantified and output.

[0176] Step 3:

[0177] The server generates an optimal work plan using a generative AI model based on acquired environmental and emotional data. The generation process analyzes the input data and calculates steps that minimize radiation safety and worker psychological stress. The generated work plan is output in digital format and used as instructions for autonomous machinery.

[0178] Step 4:

[0179] The terminal transmits the work plan sent from the server to the autonomous machine. Using a communication protocol, it transmits the planned operation instructions to the machine. Upon receiving the instructions, the machine begins the specific actions based on the plan.

[0180] Step 5:

[0181] The terminal monitors the progress of the work in real time. It analyzes feedback from sensors and immediately notifies the server if any abnormalities or emergencies occur. This information is automatically recorded and used as data input for the next step.

[0182] Step 6:

[0183] Users can view work plans and progress information through the interface and add manual instructions as needed. Specifically, they can create new routes to avoid high-radiation areas. The results of this process are sent to the server and referenced within the system.

[0184] This series of processing steps enables work management that balances safety and efficiency.

[0185] (Application Example 2)

[0186] 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".

[0187] Working in a radiation-affected environment is highly stressful for workers, and this psychological burden can negatively impact work efficiency and safety. Furthermore, existing systems only provide work plans based on environmental data, failing to implement flexible and safe work management that considers the emotional state of workers. Against this backdrop, there is a need for a new system that simultaneously ensures the safety of the work environment and the mental well-being of workers.

[0188] 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.

[0189] In this invention, the server includes means for collecting and analyzing environmental data, means for collecting and analyzing worker emotional data using an emotional analysis function, and means for flexibly adjusting and generating work plans based on the emotional state of the workers. This makes it possible to reduce the psychological burden on workers even in a radiation environment and to manage work in a way that combines safety and efficiency.

[0190] An "autonomous machine" is a machine equipped with artificial intelligence that automatically performs tasks according to set environmental conditions.

[0191] An "artificial intelligence agent" is a program that analyzes environmental data and emotional data to generate work plans and optimize work efficiency.

[0192] "Environmental data" refers to information about the work environment, such as radiation levels, temperature, and humidity.

[0193] "Emotion analysis function" is a technology that uses the worker's facial expressions, tone of voice, heart rate, etc., to determine their emotional state in real time.

[0194] A "work plan" refers to a specific process and procedure generated based on environmental and emotional data to ensure that work is carried out efficiently and safely.

[0195] "Emotional data" refers to information that reflects the emotional state of a worker, and includes heart rate, facial expressions, and vocal characteristics.

[0196] An "abnormal or emergency situation" refers to a situation or event that makes it difficult to continue normal operations and requires a swift response.

[0197] "Feedback" is a procedure for analyzing data and results obtained after a task is completed and using that information to inform future work plans.

[0198] To implement this invention, a system is required in which a server, terminal, and user work together.

[0199] The server first collects environmental data such as radiation levels, temperature, and humidity from environmental sensors and stores it in a database. Based on this data, an artificial intelligence agent performs analysis and generates a safe work plan. The server also processes emotional data obtained from workers using emotion analysis capabilities. For example, it monitors the emotional state of workers in real time using cameras and heart rate monitors, and analyzes this data to understand their emotional state.

[0200] The terminal issues control instructions to autonomous machine devices based on work plans and sentiment analysis results sent from the server. These instructions control the devices to select the optimal route and perform tasks safely and efficiently. In the event of an anomaly or emergency, an alarm is immediately issued from the server, enabling a rapid response.

[0201] Users can monitor their work progress and emotional state in real time through the terminal interface. They can fine-tune their work as needed, further improving safety and efficiency. Specifically, the system can issue new instructions to help users avoid high-radiation areas. Utilizing a generative AI model, an example of a prompt might be: "Analyze the user's emotions while working in this environment and restructure the work plan. If the user is experiencing significant stress, suggest a new work route and provide an optimal work environment."

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The server receives data from environmental sensors, including environmental data such as radiation levels, temperature, and humidity. This data is then stored and managed in a database. An AI algorithm is used to analyze this environmental data and extract the fundamental values ​​and conditions necessary to generate safe work plans.

[0205] Step 2:

[0206] The server performs sentiment analysis using data obtained from cameras and heart rate monitors as input. This includes the worker's facial expressions, voice tone, and heart rate. Using sentiment analysis algorithms, the server quantifies the worker's stress and emotional state, monitoring it in real time. This result is fed back to the server and expressed as metrics indicating the emotional state.

[0207] Step 3:

[0208] The server integrates the results of environmental data analysis and emotional data analysis, and uses a generative AI model to create a flexible work plan. If the user's emotional state is determined to be excessively stressed, it generates a prompt message and suggests temporarily changing the work plan. For example, it might introduce a specific prompt message such as, "If the user is feeling very stressed, suggest a new work route and provide an optimal work environment."

[0209] Step 4:

[0210] The terminal controls the autonomous machinery based on the work plan and control instructions sent from the server. Specifically, it selects the optimal work path and performs the work using automatic control functions. Furthermore, the terminal monitors the operation of the machinery and sends a warning to the server if an abnormal situation occurs, enabling a rapid response.

[0211] Step 5:

[0212] Users can use the interface provided by the terminal to check the progress of their work and the results of sentiment analysis. Based on this, they can fine-tune work instructions and change the control settings of machinery and equipment as needed. For example, a user might instruct a new route to avoid high-radiation areas.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention provides a system for efficiently performing tasks in a radiation environment by equipping autonomous machinery with an artificial intelligence agent. The characteristics and operation of this system are illustrated below.

[0230] First, in high-radiation environments such as nuclear power plants, autonomous mechanical devices collect environmental data through sensors. This includes various data such as radiation levels, temperature, and humidity. This information is centrally managed by a server, and changes in the environment are analyzed by comparing it with past data.

[0231] Next, the server generates an optimal work plan with the help of an artificial intelligence agent based on environmental data. This plan includes a list of steps necessary to maximize work efficiency, as well as specific routes and tasks to be performed. For example, when performing decontamination work in a certain area, it calculates the optimal route to avoid high-radiation areas and the amount of decontamination agent to use.

[0232] Subsequently, the terminal sends specific control instructions to the autonomous machine based on the work plan transmitted from the server. This allows the machine to execute the planned actions and report its progress to the server in real time.

[0233] Furthermore, users can use a remote control terminal to monitor the operation of the entire system and modify the plan as needed. If the user determines that a particular task has not been completed, they can enter new instructions through the terminal, and the server will update the plan again.

[0234] In the event of an anomaly or sudden emergency, the terminal immediately switches the autonomous machine to safety mode to ensure safety. Based on subsequent analysis, the server generates new guidelines for safely resuming operations.

[0235] Thus, this invention utilizes autonomous mechanical devices and advanced artificial intelligence technology to efficiently and safely perform tasks in order to protect human workers from the dangers of radiation. In particular, it is characterized as a system that contributes to future work improvements by continuously providing data feedback on the work performed.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] The server collects environmental data in real time from sensors installed within the nuclear power plant. This includes important parameters such as radiation levels, temperature, and humidity.

[0239] Step 2:

[0240] The server analyzes the collected environmental data and compares the current situation with past data. Based on the results of this analysis, an AI algorithm is used to evaluate anomalies and risks and set flags for emergency response.

[0241] Step 3:

[0242] The server utilizes an AI agent to generate an optimal work plan based on the obtained analytical data. This plan includes task details, execution order, required travel routes, and equipment to be used.

[0243] Step 4:

[0244] The terminal receives the work plan transmitted from the server and sends specific control signals to the autonomous machine. This causes the machine to start operating according to the plan, and its progress is monitored.

[0245] Step 5:

[0246] Users can monitor overall work progress and environmental data through the monitor. If necessary, they can modify instructions or temporarily suspend work via the terminal.

[0247] Step 6:

[0248] The terminal receives feedback data from the machine and transmits it to the server. This data is used to re-evaluate the level of work completion and the environment.

[0249] Step 7:

[0250] If an anomaly or emergency occurs, the terminal will immediately change its control signal and switch the machine to safety mode. This information is immediately reported to the server for further analysis.

[0251] Step 8:

[0252] After the task is completed, the server analyzes all collected data and extracts areas for improvement needed for the next work plan. This feedback loop results in improved work efficiency and safety.

[0253] (Example 1)

[0254] 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."

[0255] In high-radiation environments, it is essential to ensure the safety of human workers while performing tasks efficiently and flexibly. Furthermore, immediate response to emergencies and flexible adaptation to constantly changing work plans are necessary. In addition, utilizing feedback from work results to achieve continuous improvement is crucial.

[0256] 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.

[0257] In this invention, the server includes means for aggregating environmental information and analyzing it in comparison with past information, means for generating a work plan using artificial intelligence and instructing the machine to follow that plan, and means for controlling the autonomous machine using a remote control terminal based on the plan. This enables the safety of human workers in high-radiation environments and the efficient and flexible execution of work.

[0258] "Environmental information" refers to various physical information about the work environment, such as radiation levels, temperature, and humidity.

[0259] "Aggregation" refers to gathering dispersed data in one place and managing it centrally.

[0260] "Past information" refers to data collected previously, which forms the basis for analysis and comparison.

[0261] "Artificial intelligence" refers to a series of processes performed by computer systems that mimic human intelligent behavior.

[0262] A "work plan" refers to a list of specific procedures, routes, and tasks that are set in advance to improve the efficiency of a task.

[0263] "Mechanical equipment" refers to autonomous or semi-autonomous mechanical devices that perform specific tasks.

[0264] A "remote control terminal" refers to a device used to operate machinery from a physically distant location.

[0265] An "autonomous machine" refers to a machine that uses artificial intelligence to make its own decisions and perform specific tasks.

[0266] An "emergency situation" refers to a critical and urgent situation that prevents normal operations from continuing.

[0267] "Safety mode" refers to a state where operations are temporarily stopped or the system is temporarily maintained to ensure the safety of people and machinery.

[0268] "Work progress" refers to the state or stage of whether the assigned work is progressing according to plan.

[0269] "Feedback" refers to the process of evaluating the results of work and the information obtained, and incorporating that into future plans and execution.

[0270] This invention is an autonomous mechanical device system for achieving efficient work while ensuring the safety of human workers in high-radiation environments. The system mainly consists of three components: a server, a terminal, and a user.

[0271] The server's role is to aggregate environmental information and analyze it by comparing it with historical data. Specifically, the server receives environmental data such as radiation levels, temperature, and humidity transmitted from autonomous machinery. The server stores this data in a database and performs filtering of outliers and trend analysis. Furthermore, based on the collected data, it generates an optimal work plan using a generative AI model. This generated plan includes efficient work routes and task priorities.

[0272] The terminal receives work plans transmitted from the server and sends instructions to autonomous machinery. The terminal enables remote control and allows for real-time modification of instructions depending on the situation. Furthermore, the terminal has a function to automatically switch to safety mode in the event of an emergency.

[0273] The user's role is to monitor the entire system's operation via a terminal. The user can check the progress in real time and modify the work plan as needed. Furthermore, the user can input new instructions to the server using appropriate prompt messages.

[0274] As a concrete example, consider equipment inspection work at a nuclear facility. The server collects environmental data such as radiation levels using various sensors and generates a work plan accordingly. The terminal controls autonomous machinery based on this plan, and the user monitors the progress of the plan and makes adjustments as needed.

[0275] An example of a prompt message would be, "Please tell me how to perform inspection work within the facility using autonomous machinery." This system enables improved work efficiency and safety while minimizing the effects of radiation.

[0276] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0277] Step 1:

[0278] The server receives sensor information transmitted from autonomous mechanical devices. The input data includes radiation levels, temperature, and humidity. The server stores this data in a database and filters out abnormal values. As a specific operation, the server updates the data every minute and performs trend analysis while comparing it with past data.

[0279] Step 2:

[0280] The server utilizes an AI model generated based on the analyzed environmental data to generate an optimal work plan. The inputs include the collected environmental data and past history data. The server calculates efficient work routes and task priorities through an algorithm and creates detailed work procedures as output. As a specific operation, it includes the process of determining the minimum movement distance and optimal work points in decontamination operations.

[0281] Step 3:

[0282] The terminal receives the work plan transmitted from the server and sends instructions to the autonomous mechanical device. The input is the work plan from the server, and the terminal converts it into a format that the device can understand and outputs it. As a specific operation, it performs real-time path control of the device and starts work instructions.

[0283] Step 4:

[0284] The user monitors the ongoing work via the terminal and changes the plan as needed. The input is the real-time monitoring data on the terminal, and the user outputs an instruction to change the plan. As a specific operation, it uses the interface on the screen to determine whether to add or cancel a specific task.

[0285] Step 5:

[0286] In case of an emergency, the terminal immediately switches the autonomous mechanical device to the safe mode. As an input, there is an emergency alert from the sensor. The terminal processes this and outputs an instruction for the safe mode. Specific operations include stopping the operation of the machine and issuing an emergency voice alert.

[0287] Step 6:

[0288] After the work is completed, the server analyzes all the collected data and generates feedback for improvement in subsequent operations. The input is the data of the completed work, and the output is a proposal for improving the next work plan. Specific operations include performing statistical analysis of work efficiency and identifying areas that need improvement.

[0289] (Application Example 1)

[0290] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0291] In a harmful environment including radiation, it is required to perform work efficiently and safely while reducing human risks. With the current technology, there is a lack of means to appropriately perform automated inspections and maintenance work in these environments. Therefore, it is an issue to provide a system that can collect environmental information in real time, formulate an optimal work plan, and respond quickly to abnormal situations.

[0292] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0293] In this invention, the server includes means for collecting environmental information by an intelligent agent installed in an autonomous device for working in a radiation environment, means for creating a work plan using the intelligent agent, and means for remotely operating or automatically controlling the autonomous device based on the work plan. Thereby, it becomes possible to modify the operation based on real-time information update and implement safe and effective work while minimizing human intervention.

[0294] An "autonomous device" is equipment that has the ability to operate on its own judgment without detailed instructions from an external source.

[0295] An "intelligent agent" is software that uses artificial intelligence technology to analyze data and make decisions.

[0296] "Environmental information" refers to data on physical and chemical conditions such as radiation levels, temperature, and humidity.

[0297] A "work plan" is a document that outlines the procedures and processes necessary to achieve a specific objective.

[0298] "Radiation environment" refers to a work area where radioactive materials are present or are affected by them.

[0299] "Remote control" refers to a method of controlling devices or equipment from a location away from the physical site.

[0300] An "abnormal situation" refers to an unexpected situation that deviates from the norm, or a problem that threatens the safety or operation of a system.

[0301] "Information processing" refers to a series of processes that involve collecting and analyzing data and deciding on appropriate actions based on the results.

[0302] "Maintenance work" refers to periodic inspections and repairs carried out to ensure the proper operation of equipment and devices.

[0303] The system realizing this invention combines autonomous equipment and intelligent agents to support work in radiation environments. A server operates the intelligent agents to collect and analyze environmental information. The intelligent agents use software such as Python or TensorFlow to analyze the collected data and generate an optimal work plan. This plan clarifies the instructions necessary for remote operation or automated control.

[0304] The server also receives real-time feedback and adjusts the work as needed. For this purpose, ROS (Robot Operating System) is used to communicate with autonomous devices, and a control script written in Python is used to ensure the safe operation of the devices. Hardware such as radiation sensors and temperature and humidity sensors is used to obtain environmental data.

[0305] The user monitors the work status using a smart device or a computer terminal and sends additional instructions to the server as needed. Through this, when an abnormal situation occurs, the autonomous device can be immediately switched to the safe mode.

[0306] As an actual operation example, a scenario where a robot automatically inspects pipes in a chemical plant can be cited. In this case, the robot continuously collects data using sensors, detects abnormalities on the spot, and immediately reports them to the server. The correction instructions are reflected in real time.

[0307] The following are examples of prompt texts used in the generative AI model.

[0308] "Based on the current environmental data, an abnormality has been detected by the radiation sensor. Please propose how to move the inspection robot to resume work safely. Also, consider real-time correction instructions."

[0309] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0310] Step 1:

[0311] The server collects environmental information through various sensors (such as radiation sensors and temperature and humidity sensors) installed on the autonomous device. This information is converted from analog signals from the sensors into digital data and recorded in the server's database.

[0312] Step 2:

[0313] The server analyzes the acquired environmental information using Python or TensorFlow. Here, it compares it with past data to determine if an anomaly exists. The input is the current environmental information, and the output is the anomaly detection result.

[0314] Step 3:

[0315] The server generates a work plan using an intelligent agent. Based on anomaly detection results and environmental information, it calculates the optimal work route and procedures, and generates work instructions. The output is a detailed work plan.

[0316] Step 4:

[0317] The server sends the generated work plan to the autonomous device. Using ROS (Robot Operating System), it runs the device's control script, and the device automatically starts the planned work. The input is the work plan, and the output is the execution of control commands.

[0318] Step 5:

[0319] The terminal monitors the progress of tasks received from the server in real time. Operators can check the status via the terminal and send additional instructions if an abnormal situation occurs. Input is task progress data, and output is corrective instructions as needed.

[0320] Step 6:

[0321] The server immediately switches autonomous equipment to safety mode if an anomaly or emergency is detected. This safely stops operations and collects data for subsequent investigation and recovery. Inputs are anomaly notifications, and outputs are safety control commands.

[0322] Step 7:

[0323] The user sends prompts to the generating AI model as needed and receives suggestions for a new work plan. An example prompt is: "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please suggest how to move the inspection robot to safely resume work. Please also consider real-time correction instructions." The input is the prompt, and the output is the new suggestion.

[0324] 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.

[0325] This invention is a system that efficiently manages work in a radiation environment while taking into account the user's emotional state, thereby achieving further improvements in safety and work efficiency. The autonomous machine incorporates an artificial intelligence agent and an emotion engine.

[0326] First, autonomous machinery uses advanced sensors to acquire environmental data such as radiation levels. This data is collected on a server and analyzed by AI algorithms. During this process, environmental safety is evaluated and reflected in the work plan.

[0327] Next, the emotion engine monitors the user's emotions in real time. This is done using multiple sensing technologies, such as the user's facial expressions, voice tone, and heart rate. This data is input to a server and analyzed by an emotion analysis algorithm.

[0328] The server integrates this emotional data into the AI-generated work plan. For example, if it determines that the user is experiencing extreme stress, the work plan is temporarily suspended, and alternative routes are searched for or tasks are prioritized. This ensures safety while reducing the user's psychological burden.

[0329] The terminal transmits the generated work plan to the autonomous machine and provides appropriate control instructions. It also monitors the progress of the work and responds immediately if any abnormalities or emergencies occur.

[0330] Users can view this information through the interface and fine-tune their work as needed. For example, they can issue new instructions to machinery to avoid specific high-radiation areas.

[0331] The combination of the emotion engine and AI in this invention enables efficient and flexible work management that takes both environmental and emotional data into consideration. This system is useful not only for providing a safe and secure work environment but also for maintaining the mental health of workers.

[0332] The following describes the processing flow.

[0333] Step 1:

[0334] The server collects data from environmental sensors in real time, monitoring radiation levels, temperature, and other parameters. This data is immediately analyzed and forms the basis for assessing environmental safety.

[0335] Step 2:

[0336] The emotion engine collects emotional data from the user's facial recognition device and voice recognition system. It detects the user's emotional state from changes in facial expressions, voice tone, heart rate, etc. This data is sent to a server.

[0337] Step 3:

[0338] The server integrates environmental and emotional data and generates a work plan based on this. An AI algorithm determines the optimal work steps and sequence, and adjusts the work procedure if an increase in stress or anxiety is detected.

[0339] Step 4:

[0340] The terminal transmits the work plan received from the server to the autonomous machine and sends specific control signals. During this process, the starting position of the work and the movement path of the machine are set.

[0341] Step 5:

[0342] Users can monitor the progress of their work in real time via a monitor. If any ambiguities or problems arise, users can request changes to the plan through their terminal.

[0343] Step 6:

[0344] As the autonomous machine completes its task, the terminal reports progress data to the server. In particular, if an anomaly or emergency is detected, it immediately notifies the server and triggers a response that allows the system to take appropriate action.

[0345] Step 7:

[0346] After all tasks are completed, the server comprehensively analyzes the collected data and generates feedback to improve efficiency in future tasks. This feedback is used to improve the accuracy of future plans.

[0347] (Example 2)

[0348] 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".

[0349] Modern work environments requiring both safety and efficiency are essential. However, the lack of accurate environmental information collection and flexible work management that includes workers' emotional states leads to problems such as inability to respond quickly to work interruptions or unforeseen circumstances, resulting in reduced work efficiency. Furthermore, existing systems lack sufficient processes to alleviate the mental burden on workers.

[0350] 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.

[0351] In this invention, the server includes means for acquiring ambient environmental data, including radiation; means for generating a process plan; and means for evaluating the emotional state of on-site workers using an information analysis device and reflecting this in the work. This enables the generation and adjustment of plans that comprehensively consider environmental data and workers' emotional information, thereby improving safety, optimizing work efficiency, and reducing the psychological burden on workers.

[0352] "Autonomous mechanical devices" refer to robots and devices that perform tasks autonomously in a radiation environment, minimizing human intervention.

[0353] An "information processing device" refers to a computer system that collects and analyzes environmental data and worker sentiment data, and generates and adjusts process plans based on the results.

[0354] "Surrounding environment data" refers to data that provides detailed information about the work site, such as radiation levels, temperature and humidity, and air composition.

[0355] A "process plan" refers to a plan that outlines the procedures and routes for efficiently and safely carrying out a specific task.

[0356] An "information analysis device" refers to a device or system that analyzes data to extract useful information, enabling decision-making and adjustment of plans based on that information.

[0357] "Feedback" refers to the process of providing information about the next steps or areas for improvement based on data obtained after the completion of a task.

[0358] One embodiment of the present invention is a system for efficiently and safely performing work in a radiation environment. Specific embodiments thereof are described below.

[0359] First, the server collects ambient environmental data from autonomous mechanical devices. The hardware used includes devices equipped with high-performance sensors and communication modules. For software, libraries that execute AI algorithms such as TensorFlow and PyTorch are used for data analysis. This allows for the real-time acquisition of data such as radiation levels and temperature / humidity, enabling safety assessments.

[0360] Next, the information analysis device uses facial recognition and voice analysis technologies to evaluate the emotional state of workers. Data such as facial expressions, voice tone, and heart rate are processed using OpenCV and other emotion recognition software and reflected in the work plan. For example, if a worker is in a high-stress state, the work plan is dynamically adjusted and switched to a safety-first route. In this process, a generative AI model is used to automatically generate an efficient process plan.

[0361] The terminal transmits the work plan to the autonomous machine. The necessary hardware includes network-connected devices that use communication protocols to control the machine's operation. Furthermore, the terminal monitors the progress of the work and provides an interface for immediate response if any anomalies are detected.

[0362] Users verify the information obtained through this system via an interface. The interface is designed to provide the information necessary when the user performs manual operations. For example, it may be possible to issue new instructions to avoid high-radiation areas.

[0363] As a concrete example, consider the decontamination of a facility after a natural disaster. This system first monitors radiation levels and then provides the optimal work route based on the emotional state of the workers. An example of a prompt message would be, "Please tell me how to optimize the work while considering the user's emotional state."

[0364] Through the above process, a safe and efficient working environment is provided, and the psychological burden on workers is also reduced.

[0365] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0366] Step 1:

[0367] The server acquires ambient environmental data transmitted from autonomous machinery. This data includes radiation levels, temperature and humidity, and air composition. The acquired environmental data is input into an AI algorithm for data processing and analysis. Specifically, safety is evaluated using TensorFlow, the data is organized, and then output as basic information for process planning.

[0368] Step 2:

[0369] The server acquires emotional data from workers. This emotional data is collected based on facial expression data, voice tone, and heart rate entered by the user into a terminal. Face recognition is performed using image processing libraries such as OpenCV, and voice tone is analyzed using voice analysis software. The acquired emotional data is then analyzed, and stress levels and emotional states are quantified and output.

[0370] Step 3:

[0371] The server generates an optimal work plan using a generative AI model based on acquired environmental and emotional data. The generation process analyzes the input data and calculates steps that minimize radiation safety and worker psychological stress. The generated work plan is output in digital format and used as instructions for autonomous machinery.

[0372] Step 4:

[0373] The terminal transmits the work plan sent from the server to the autonomous machine. Using a communication protocol, it transmits the planned operation instructions to the machine. Upon receiving the instructions, the machine begins the specific actions based on the plan.

[0374] Step 5:

[0375] The terminal monitors the progress of the work in real time. It analyzes feedback from sensors and immediately notifies the server if any abnormalities or emergencies occur. This information is automatically recorded and used as data input for the next step.

[0376] Step 6:

[0377] Users can view work plans and progress information through the interface and add manual instructions as needed. Specifically, they can create new routes to avoid high-radiation areas. The results of this process are sent to the server and referenced within the system.

[0378] This series of processing steps enables work management that balances safety and efficiency.

[0379] (Application Example 2)

[0380] 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."

[0381] Working in a radiation-affected environment is highly stressful for workers, and this psychological burden can negatively impact work efficiency and safety. Furthermore, existing systems only provide work plans based on environmental data, failing to implement flexible and safe work management that considers the emotional state of workers. Against this backdrop, there is a need for a new system that simultaneously ensures the safety of the work environment and the mental well-being of workers.

[0382] 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.

[0383] In this invention, the server includes means for collecting and analyzing environmental data, means for collecting and analyzing worker emotional data using an emotional analysis function, and means for flexibly adjusting and generating work plans based on the emotional state of the workers. This makes it possible to reduce the psychological burden on workers even in a radiation environment and to manage work in a way that combines safety and efficiency.

[0384] An "autonomous machine" is a machine equipped with artificial intelligence that automatically performs tasks according to set environmental conditions.

[0385] An "artificial intelligence agent" is a program that analyzes environmental data and emotional data to generate work plans and optimize work efficiency.

[0386] "Environmental data" refers to information about the work environment, such as radiation levels, temperature, and humidity.

[0387] "Emotion analysis function" is a technology that uses the worker's facial expressions, tone of voice, heart rate, etc., to determine their emotional state in real time.

[0388] A "work plan" refers to a specific process and procedure generated based on environmental and emotional data to ensure that work is carried out efficiently and safely.

[0389] "Emotional data" refers to information that reflects the emotional state of a worker, and includes heart rate, facial expressions, and vocal characteristics.

[0390] An "abnormal or emergency situation" refers to a situation or event that makes it difficult to continue normal operations and requires a swift response.

[0391] "Feedback" is a procedure for analyzing data and results obtained after a task is completed and using that information to inform future work plans.

[0392] To implement this invention, a system is required in which a server, terminal, and user work together.

[0393] The server first collects environmental data such as radiation levels, temperature, and humidity from environmental sensors and stores it in a database. Based on this data, an artificial intelligence agent performs analysis and generates a safe work plan. The server also processes emotional data obtained from workers using emotion analysis capabilities. For example, it monitors the emotional state of workers in real time using cameras and heart rate monitors, and analyzes this data to understand their emotional state.

[0394] The terminal issues control instructions to autonomous machine devices based on work plans and sentiment analysis results sent from the server. These instructions control the devices to select the optimal route and perform tasks safely and efficiently. In the event of an anomaly or emergency, an alarm is immediately issued from the server, enabling a rapid response.

[0395] Users can monitor their work progress and emotional state in real time through the terminal interface. They can fine-tune their work as needed, further improving safety and efficiency. Specifically, the system can issue new instructions to help users avoid high-radiation areas. Utilizing a generative AI model, an example of a prompt might be: "Analyze the user's emotions while working in this environment and restructure the work plan. If the user is experiencing significant stress, suggest a new work route and provide an optimal work environment."

[0396] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0397] Step 1:

[0398] The server receives data from environmental sensors, including environmental data such as radiation levels, temperature, and humidity. This data is then stored and managed in a database. An AI algorithm is used to analyze this environmental data and extract the fundamental values ​​and conditions necessary to generate safe work plans.

[0399] Step 2:

[0400] The server performs sentiment analysis using data obtained from cameras and heart rate monitors as input. This includes the worker's facial expressions, voice tone, and heart rate. Using sentiment analysis algorithms, the server quantifies the worker's stress and emotional state, monitoring it in real time. This result is fed back to the server and expressed as metrics indicating the emotional state.

[0401] Step 3:

[0402] The server integrates the results of environmental data analysis and emotional data analysis, and uses a generative AI model to create a flexible work plan. If the user's emotional state is determined to be excessively stressed, it generates a prompt message and suggests temporarily changing the work plan. For example, it might introduce a specific prompt message such as, "If the user is feeling very stressed, suggest a new work route and provide an optimal work environment."

[0403] Step 4:

[0404] The terminal controls the autonomous machinery based on the work plan and control instructions sent from the server. Specifically, it selects the optimal work path and performs the work using automatic control functions. Furthermore, the terminal monitors the operation of the machinery and sends a warning to the server if an abnormal situation occurs, enabling a rapid response.

[0405] Step 5:

[0406] Users can use the interface provided by the terminal to check the progress of their work and the results of sentiment analysis. Based on this, they can fine-tune work instructions and change the control settings of machinery and equipment as needed. For example, a user might instruct a new route to avoid high-radiation areas.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] [Third Embodiment]

[0411] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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".

[0423] This invention provides a system for efficiently performing tasks in a radiation environment by equipping autonomous machinery with an artificial intelligence agent. The characteristics and operation of this system are illustrated below.

[0424] First, in high-radiation environments such as nuclear power plants, autonomous mechanical devices collect environmental data through sensors. This includes various data such as radiation levels, temperature, and humidity. This information is centrally managed by a server, and changes in the environment are analyzed by comparing it with past data.

[0425] Next, the server generates an optimal work plan with the help of an artificial intelligence agent based on environmental data. This plan includes a list of steps necessary to maximize work efficiency, as well as specific routes and tasks to be performed. For example, when performing decontamination work in a certain area, it calculates the optimal route to avoid high-radiation areas and the amount of decontamination agent to use.

[0426] Subsequently, the terminal sends specific control instructions to the autonomous machine based on the work plan transmitted from the server. This allows the machine to execute the planned actions and report its progress to the server in real time.

[0427] Furthermore, users can use a remote control terminal to monitor the operation of the entire system and modify the plan as needed. If the user determines that a particular task has not been completed, they can enter new instructions through the terminal, and the server will update the plan again.

[0428] In the event of an anomaly or sudden emergency, the terminal immediately switches the autonomous machine to safety mode to ensure safety. Based on subsequent analysis, the server generates new guidelines for safely resuming operations.

[0429] Thus, this invention utilizes autonomous mechanical devices and advanced artificial intelligence technology to efficiently and safely perform tasks in order to protect human workers from the dangers of radiation. In particular, it is characterized as a system that contributes to future work improvements by continuously providing data feedback on the work performed.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] The server collects environmental data in real time from sensors installed within the nuclear power plant. This includes important parameters such as radiation levels, temperature, and humidity.

[0433] Step 2:

[0434] The server analyzes the collected environmental data and compares the current situation with past data. Based on the results of this analysis, an AI algorithm is used to evaluate anomalies and risks and set flags for emergency response.

[0435] Step 3:

[0436] The server utilizes an AI agent to generate an optimal work plan based on the obtained analytical data. This plan includes task details, execution order, required travel routes, and equipment to be used.

[0437] Step 4:

[0438] The terminal receives the work plan transmitted from the server and sends specific control signals to the autonomous machine. This causes the machine to start operating according to the plan, and its progress is monitored.

[0439] Step 5:

[0440] Users can monitor overall work progress and environmental data through the monitor. If necessary, they can modify instructions or temporarily suspend work via the terminal.

[0441] Step 6:

[0442] The terminal receives feedback data from the machine and transmits it to the server. This data is used to re-evaluate the level of work completion and the environment.

[0443] Step 7:

[0444] If an anomaly or emergency occurs, the terminal will immediately change its control signal and switch the machine to safety mode. This information is immediately reported to the server for further analysis.

[0445] Step 8:

[0446] After the task is completed, the server analyzes all collected data and extracts areas for improvement needed for the next work plan. This feedback loop results in improved work efficiency and safety.

[0447] (Example 1)

[0448] 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."

[0449] In high-radiation environments, it is essential to ensure the safety of human workers while performing tasks efficiently and flexibly. Furthermore, immediate response to emergencies and flexible adaptation to constantly changing work plans are necessary. In addition, utilizing feedback from work results to achieve continuous improvement is crucial.

[0450] 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.

[0451] In this invention, the server includes means for aggregating environmental information and analyzing it in comparison with past information, means for generating a work plan using artificial intelligence and instructing the machine to follow that plan, and means for controlling the autonomous machine using a remote control terminal based on the plan. This enables the safety of human workers in high-radiation environments and the efficient and flexible execution of work.

[0452] "Environmental information" refers to various physical information about the work environment, such as radiation levels, temperature, and humidity.

[0453] "Aggregation" refers to gathering dispersed data in one place and managing it centrally.

[0454] "Past information" refers to data collected previously, which forms the basis for analysis and comparison.

[0455] "Artificial intelligence" refers to a series of processes performed by computer systems that mimic human intelligent behavior.

[0456] A "work plan" refers to a list of specific procedures, routes, and tasks that are set in advance to improve the efficiency of a task.

[0457] "Mechanical equipment" refers to autonomous or semi-autonomous mechanical devices that perform specific tasks.

[0458] A "remote control terminal" refers to a device used to operate machinery from a physically distant location.

[0459] An "autonomous machine" refers to a machine that uses artificial intelligence to make its own decisions and perform specific tasks.

[0460] An "emergency situation" refers to a critical and urgent situation that prevents normal operations from continuing.

[0461] "Safety mode" refers to a state where operations are temporarily stopped or the system is temporarily maintained to ensure the safety of people and machinery.

[0462] "Work progress" refers to the state or stage of whether the assigned work is progressing according to plan.

[0463] "Feedback" refers to the process of evaluating the results of work and the information obtained, and incorporating that into future plans and execution.

[0464] This invention is an autonomous mechanical device system for achieving efficient work while ensuring the safety of human workers in high-radiation environments. The system mainly consists of three components: a server, a terminal, and a user.

[0465] The server's role is to aggregate environmental information and analyze it by comparing it with historical data. Specifically, the server receives environmental data such as radiation levels, temperature, and humidity transmitted from autonomous machinery. The server stores this data in a database and performs filtering of outliers and trend analysis. Furthermore, based on the collected data, it generates an optimal work plan using a generative AI model. This generated plan includes efficient work routes and task priorities.

[0466] The terminal receives work plans transmitted from the server and sends instructions to autonomous machinery. The terminal enables remote control and allows for real-time modification of instructions depending on the situation. Furthermore, the terminal has a function to automatically switch to safety mode in the event of an emergency.

[0467] The user's role is to monitor the entire system's operation via a terminal. The user can check the progress in real time and modify the work plan as needed. Furthermore, the user can input new instructions to the server using appropriate prompt messages.

[0468] As a concrete example, consider equipment inspection work at a nuclear facility. The server collects environmental data such as radiation levels using various sensors and generates a work plan accordingly. The terminal controls autonomous machinery based on this plan, and the user monitors the progress of the plan and makes adjustments as needed.

[0469] An example of a prompt message would be, "Please tell me how to perform inspection work within the facility using autonomous machinery." This system enables improved work efficiency and safety while minimizing the effects of radiation.

[0470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0471] Step 1:

[0472] The server receives sensor information transmitted from autonomous mechanical devices. Input data includes radiation levels, temperature, and humidity. The server stores this data in a database and filters out abnormal values. Specifically, the server updates the data every minute and performs trend analysis by comparing it with past data.

[0473] Step 2:

[0474] The server uses an AI model based on analyzed environmental data to generate an optimal work plan. Inputs include collected environmental data and historical data. The server uses algorithms to calculate efficient work routes and task priorities, and outputs detailed work procedures. Specific operations include determining the minimum travel distance and optimal work points during decontamination work.

[0475] Step 3:

[0476] The terminal receives work plans sent from the server and transmits instructions to autonomous machinery. The input is the work plan from the server, which the terminal converts into a format the machine can understand and outputs. Specifically, it performs real-time routing control and work start instructions for the machine.

[0477] Step 4:

[0478] The user monitors ongoing work via a terminal and modifies the plan as needed. Real-time monitoring data on the terminal serves as input, and the user outputs instructions for plan changes. Specifically, the user uses an on-screen interface to decide whether to add or cancel certain tasks.

[0479] Step 5:

[0480] In the event of an emergency, the terminal immediately switches the autonomous machine to safety mode. Inputs include emergency alerts from sensors. The terminal processes these and outputs instructions for safety mode. Specific actions include stopping the machine and issuing emergency voice alerts.

[0481] Step 6:

[0482] After completing a task, the server analyzes all collected data and generates feedback for future improvements. The input is data from the completed task, and the output is a proposed improvement plan for the next task. Specifically, it performs statistical analysis of work efficiency and identifies areas that need improvement.

[0483] (Application Example 1)

[0484] 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."

[0485] In hazardous environments, including those involving radiation, there is a need to perform work efficiently and safely while mitigating human risks. Current technology lacks the means to adequately perform automated inspection and maintenance work in these environments. Therefore, the challenge is to provide a system that can collect environmental information in real time, develop optimal work plans, and respond quickly to abnormal situations.

[0486] 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.

[0487] In this invention, the server includes means for collecting environmental information by an intelligent agent mounted on an autonomous device for working in a radiation environment, means for creating a work plan using the intelligent agent, and means for remotely operating or automatically controlling the autonomous device based on the work plan. This enables safe and effective work to be carried out while correcting operations based on real-time information updates and minimizing human intervention.

[0488] An "autonomous device" is equipment that has the ability to operate on its own judgment without detailed instructions from an external source.

[0489] An "intelligent agent" is software that uses artificial intelligence technology to analyze data and make decisions.

[0490] "Environmental information" refers to data on physical and chemical conditions such as radiation levels, temperature, and humidity.

[0491] A "work plan" is a document that outlines the procedures and processes necessary to achieve a specific objective.

[0492] "Radiation environment" refers to a work area where radioactive materials are present or are affected by them.

[0493] "Remote control" refers to a method of controlling devices or equipment from a location away from the physical site.

[0494] An "abnormal situation" refers to an unexpected situation that deviates from the norm, or a problem that threatens the safety or operation of a system.

[0495] "Information processing" refers to a series of processes that involve collecting and analyzing data and deciding on appropriate actions based on the results.

[0496] "Maintenance work" refers to periodic inspections and repairs carried out to ensure the proper operation of equipment and devices.

[0497] The system realizing this invention combines autonomous equipment and intelligent agents to support work in radiation environments. A server operates the intelligent agents to collect and analyze environmental information. The intelligent agents use software such as Python or TensorFlow to analyze the collected data and generate an optimal work plan. This plan clarifies the instructions necessary for remote operation or automated control.

[0498] The server also receives real-time feedback and adjusts its operations as needed. For this purpose, it uses ROS (Robot Operating System) to communicate with autonomous devices and controls written in Python to ensure safe operation. Hardware such as radiation sensors and temperature / humidity sensors are used to acquire environmental data.

[0499] Users monitor the work status using smart devices or computer terminals and send additional instructions to the server as needed. This allows for the immediate switching of autonomous equipment to safety mode in the event of an anomaly.

[0500] One practical example is a scenario in which a robot automatically inspects piping in a chemical plant. In this case, the robot continuously collects data using sensors, detects anomalies on the spot, and immediately reports them to the server. Correction instructions are then implemented in real time.

[0501] The following are examples of prompt statements used in the generative AI model.

[0502] "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please propose how to move the inspection robot to safely resume operations. Please also consider real-time correction instructions."

[0503] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0504] Step 1:

[0505] The server collects environmental information through various sensors (such as radiation sensors and temperature / humidity sensors) installed in autonomous devices. This information is converted from analog signals from the sensors into digital data and recorded in the server's database.

[0506] Step 2:

[0507] The server analyzes the acquired environmental information using Python or TensorFlow. Here, it compares it with past data to determine if an anomaly exists. The input is the current environmental information, and the output is the anomaly detection result.

[0508] Step 3:

[0509] The server generates a work plan using an intelligent agent. Based on anomaly detection results and environmental information, it calculates the optimal work route and procedures, and generates work instructions. The output is a detailed work plan.

[0510] Step 4:

[0511] The server sends the generated work plan to the autonomous device. Using ROS (Robot Operating System), it runs the device's control script, and the device automatically starts the planned work. The input is the work plan, and the output is the execution of control commands.

[0512] Step 5:

[0513] The terminal monitors the progress of tasks received from the server in real time. Operators can check the status via the terminal and send additional instructions if an abnormal situation occurs. Input is task progress data, and output is corrective instructions as needed.

[0514] Step 6:

[0515] The server immediately switches autonomous equipment to safety mode if an anomaly or emergency is detected. This safely stops operations and collects data for subsequent investigation and recovery. Inputs are anomaly notifications, and outputs are safety control commands.

[0516] Step 7:

[0517] The user sends prompts to the generating AI model as needed and receives suggestions for a new work plan. An example prompt is: "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please suggest how to move the inspection robot to safely resume work. Please also consider real-time correction instructions." The input is the prompt, and the output is the new suggestion.

[0518] 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.

[0519] This invention is a system that efficiently manages work in a radiation environment while taking into account the user's emotional state, thereby achieving further improvements in safety and work efficiency. The autonomous machine incorporates an artificial intelligence agent and an emotion engine.

[0520] First, autonomous machinery uses advanced sensors to acquire environmental data such as radiation levels. This data is collected on a server and analyzed by AI algorithms. During this process, environmental safety is evaluated and reflected in the work plan.

[0521] Next, the emotion engine monitors the user's emotions in real time. This is done using multiple sensing technologies, such as the user's facial expressions, voice tone, and heart rate. This data is input to a server and analyzed by an emotion analysis algorithm.

[0522] The server integrates this emotional data into the AI-generated work plan. For example, if it determines that the user is experiencing extreme stress, the work plan is temporarily suspended, and alternative routes are searched for or tasks are prioritized. This ensures safety while reducing the user's psychological burden.

[0523] The terminal transmits the generated work plan to the autonomous machine and provides appropriate control instructions. It also monitors the progress of the work and responds immediately if any abnormalities or emergencies occur.

[0524] Users can view this information through the interface and fine-tune their work as needed. For example, they can issue new instructions to machinery to avoid specific high-radiation areas.

[0525] The combination of the emotion engine and AI in this invention enables efficient and flexible work management that takes both environmental and emotional data into consideration. This system is useful not only for providing a safe and secure work environment but also for maintaining the mental health of workers.

[0526] The following describes the processing flow.

[0527] Step 1:

[0528] The server collects data from environmental sensors in real time, monitoring radiation levels, temperature, and other parameters. This data is immediately analyzed and forms the basis for assessing environmental safety.

[0529] Step 2:

[0530] The emotion engine collects emotional data from the user's facial recognition device and voice recognition system. It detects the user's emotional state from changes in facial expressions, voice tone, heart rate, etc. This data is sent to a server.

[0531] Step 3:

[0532] The server integrates environmental and emotional data and generates a work plan based on this. An AI algorithm determines the optimal work steps and sequence, and adjusts the work procedure if an increase in stress or anxiety is detected.

[0533] Step 4:

[0534] The terminal transmits the work plan received from the server to the autonomous machine and sends specific control signals. During this process, the starting position of the work and the movement path of the machine are set.

[0535] Step 5:

[0536] Users can monitor the progress of their work in real time via a monitor. If any ambiguities or problems arise, users can request changes to the plan through their terminal.

[0537] Step 6:

[0538] As the autonomous machine completes its task, the terminal reports progress data to the server. In particular, if an anomaly or emergency is detected, it immediately notifies the server and triggers a response that allows the system to take appropriate action.

[0539] Step 7:

[0540] After all tasks are completed, the server comprehensively analyzes the collected data and generates feedback to improve efficiency in future tasks. This feedback is used to improve the accuracy of future plans.

[0541] (Example 2)

[0542] 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."

[0543] Modern work environments requiring both safety and efficiency are essential. However, the lack of accurate environmental information collection and flexible work management that includes workers' emotional states leads to problems such as inability to respond quickly to work interruptions or unforeseen circumstances, resulting in reduced work efficiency. Furthermore, existing systems lack sufficient processes to alleviate the mental burden on workers.

[0544] 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.

[0545] In this invention, the server includes means for acquiring ambient environmental data, including radiation; means for generating a process plan; and means for evaluating the emotional state of on-site workers using an information analysis device and reflecting this in the work. This enables the generation and adjustment of plans that comprehensively consider environmental data and workers' emotional information, thereby improving safety, optimizing work efficiency, and reducing the psychological burden on workers.

[0546] "Autonomous mechanical devices" refer to robots and devices that perform tasks autonomously in a radiation environment, minimizing human intervention.

[0547] An "information processing device" refers to a computer system that collects and analyzes environmental data and worker sentiment data, and generates and adjusts process plans based on the results.

[0548] "Surrounding environment data" refers to data that provides detailed information about the work site, such as radiation levels, temperature and humidity, and air composition.

[0549] A "process plan" refers to a plan that outlines the procedures and routes for efficiently and safely carrying out a specific task.

[0550] An "information analysis device" refers to a device or system that analyzes data to extract useful information, enabling decision-making and adjustment of plans based on that information.

[0551] "Feedback" refers to the process of providing information about the next steps or areas for improvement based on data obtained after the completion of a task.

[0552] One embodiment of the present invention is a system for efficiently and safely performing work in a radiation environment. Specific embodiments thereof are described below.

[0553] First, the server collects ambient environmental data from autonomous mechanical devices. The hardware used includes devices equipped with high-performance sensors and communication modules. For software, libraries that execute AI algorithms such as TensorFlow and PyTorch are used for data analysis. This allows for the real-time acquisition of data such as radiation levels and temperature / humidity, enabling safety assessments.

[0554] Next, the information analysis device uses facial recognition and voice analysis technologies to evaluate the emotional state of workers. Data such as facial expressions, voice tone, and heart rate are processed using OpenCV and other emotion recognition software and reflected in the work plan. For example, if a worker is in a high-stress state, the work plan is dynamically adjusted and switched to a safety-first route. In this process, a generative AI model is used to automatically generate an efficient process plan.

[0555] The terminal transmits the work plan to the autonomous machine. The necessary hardware includes network-connected devices that use communication protocols to control the machine's operation. Furthermore, the terminal monitors the progress of the work and provides an interface for immediate response if any anomalies are detected.

[0556] Users verify the information obtained through this system via an interface. The interface is designed to provide the information necessary when the user performs manual operations. For example, it may be possible to issue new instructions to avoid high-radiation areas.

[0557] As a concrete example, consider the decontamination of a facility after a natural disaster. This system first monitors radiation levels and then provides the optimal work route based on the emotional state of the workers. An example of a prompt message would be, "Please tell me how to optimize the work while considering the user's emotional state."

[0558] Through the above process, a safe and efficient working environment is provided, and the psychological burden on workers is also reduced.

[0559] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0560] Step 1:

[0561] The server acquires ambient environmental data transmitted from autonomous machinery. This data includes radiation levels, temperature and humidity, and air composition. The acquired environmental data is input into an AI algorithm for data processing and analysis. Specifically, safety is evaluated using TensorFlow, the data is organized, and then output as basic information for process planning.

[0562] Step 2:

[0563] The server acquires emotional data from workers. This emotional data is collected based on facial expression data, voice tone, and heart rate entered by the user into a terminal. Face recognition is performed using image processing libraries such as OpenCV, and voice tone is analyzed using voice analysis software. The acquired emotional data is then analyzed, and stress levels and emotional states are quantified and output.

[0564] Step 3:

[0565] The server generates an optimal work plan using a generative AI model based on acquired environmental and emotional data. The generation process analyzes the input data and calculates steps that minimize radiation safety and worker psychological stress. The generated work plan is output in digital format and used as instructions for autonomous machinery.

[0566] Step 4:

[0567] The terminal transmits the work plan sent from the server to the autonomous machine. Using a communication protocol, it transmits the planned operation instructions to the machine. Upon receiving the instructions, the machine begins the specific actions based on the plan.

[0568] Step 5:

[0569] The terminal monitors the progress of the work in real time. It analyzes feedback from sensors and immediately notifies the server if any abnormalities or emergencies occur. This information is automatically recorded and used as data input for the next step.

[0570] Step 6:

[0571] Users can view work plans and progress information through the interface and add manual instructions as needed. Specifically, they can create new routes to avoid high-radiation areas. The results of this process are sent to the server and referenced within the system.

[0572] This series of processing steps enables work management that balances safety and efficiency.

[0573] (Application Example 2)

[0574] 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."

[0575] Working in a radiation-affected environment is highly stressful for workers, and this psychological burden can negatively impact work efficiency and safety. Furthermore, existing systems only provide work plans based on environmental data, failing to implement flexible and safe work management that considers the emotional state of workers. Against this backdrop, there is a need for a new system that simultaneously ensures the safety of the work environment and the mental well-being of workers.

[0576] 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.

[0577] In this invention, the server includes means for collecting and analyzing environmental data, means for collecting and analyzing worker emotional data using an emotional analysis function, and means for flexibly adjusting and generating work plans based on the emotional state of the workers. This makes it possible to reduce the psychological burden on workers even in a radiation environment and to manage work in a way that combines safety and efficiency.

[0578] An "autonomous machine" is a machine equipped with artificial intelligence that automatically performs tasks according to set environmental conditions.

[0579] An "artificial intelligence agent" is a program that analyzes environmental data and emotional data to generate work plans and optimize work efficiency.

[0580] "Environmental data" refers to information about the work environment, such as radiation levels, temperature, and humidity.

[0581] "Emotion analysis function" is a technology that uses the worker's facial expressions, tone of voice, heart rate, etc., to determine their emotional state in real time.

[0582] A "work plan" refers to a specific process and procedure generated based on environmental and emotional data to ensure that work is carried out efficiently and safely.

[0583] "Emotional data" refers to information that reflects the emotional state of a worker, and includes heart rate, facial expressions, and vocal characteristics.

[0584] An "abnormal or emergency situation" refers to a situation or event that makes it difficult to continue normal operations and requires a swift response.

[0585] "Feedback" is a procedure for analyzing data and results obtained after a task is completed and using that information to inform future work plans.

[0586] To implement this invention, a system is required in which a server, terminal, and user work together.

[0587] The server first collects environmental data such as radiation levels, temperature, and humidity from environmental sensors and stores it in a database. Based on this data, an artificial intelligence agent performs analysis and generates a safe work plan. The server also processes emotional data obtained from workers using emotion analysis capabilities. For example, it monitors the emotional state of workers in real time using cameras and heart rate monitors, and analyzes this data to understand their emotional state.

[0588] The terminal issues control instructions to autonomous machine devices based on work plans and sentiment analysis results sent from the server. These instructions control the devices to select the optimal route and perform tasks safely and efficiently. In the event of an anomaly or emergency, an alarm is immediately issued from the server, enabling a rapid response.

[0589] Users can monitor their work progress and emotional state in real time through the terminal interface. They can fine-tune their work as needed, further improving safety and efficiency. Specifically, the system can issue new instructions to help users avoid high-radiation areas. Utilizing a generative AI model, an example of a prompt might be: "Analyze the user's emotions while working in this environment and restructure the work plan. If the user is experiencing significant stress, suggest a new work route and provide an optimal work environment."

[0590] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0591] Step 1:

[0592] The server receives data from environmental sensors, including environmental data such as radiation levels, temperature, and humidity. This data is then stored and managed in a database. An AI algorithm is used to analyze this environmental data and extract the fundamental values ​​and conditions necessary to generate safe work plans.

[0593] Step 2:

[0594] The server performs sentiment analysis using data obtained from cameras and heart rate monitors as input. This includes the worker's facial expressions, voice tone, and heart rate. Using sentiment analysis algorithms, the server quantifies the worker's stress and emotional state, monitoring it in real time. This result is fed back to the server and expressed as metrics indicating the emotional state.

[0595] Step 3:

[0596] The server integrates the results of environmental data analysis and emotional data analysis, and uses a generative AI model to create a flexible work plan. If the user's emotional state is determined to be excessively stressed, it generates a prompt message and suggests temporarily changing the work plan. For example, it might introduce a specific prompt message such as, "If the user is feeling very stressed, suggest a new work route and provide an optimal work environment."

[0597] Step 4:

[0598] The terminal controls the autonomous machinery based on the work plan and control instructions sent from the server. Specifically, it selects the optimal work path and performs the work using automatic control functions. Furthermore, the terminal monitors the operation of the machinery and sends a warning to the server if an abnormal situation occurs, enabling a rapid response.

[0599] Step 5:

[0600] Users can use the interface provided by the terminal to check the progress of their work and the results of sentiment analysis. Based on this, they can fine-tune work instructions and change the control settings of machinery and equipment as needed. For example, a user might instruct a new route to avoid high-radiation areas.

[0601] 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.

[0602] 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.

[0603] 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.

[0604] [Fourth Embodiment]

[0605] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0606] 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.

[0607] 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).

[0608] 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.

[0609] 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.

[0610] 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).

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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".

[0618] This invention provides a system for efficiently performing tasks in a radiation environment by equipping autonomous machinery with an artificial intelligence agent. The characteristics and operation of this system are illustrated below.

[0619] First, in high-radiation environments such as nuclear power plants, autonomous mechanical devices collect environmental data through sensors. This includes various data such as radiation levels, temperature, and humidity. This information is centrally managed by a server, and changes in the environment are analyzed by comparing it with past data.

[0620] Next, the server generates an optimal work plan with the help of an artificial intelligence agent based on environmental data. This plan includes a list of steps necessary to maximize work efficiency, as well as specific routes and tasks to be performed. For example, when performing decontamination work in a certain area, it calculates the optimal route to avoid high-radiation areas and the amount of decontamination agent to use.

[0621] Subsequently, the terminal sends specific control instructions to the autonomous machine based on the work plan transmitted from the server. This allows the machine to execute the planned actions and report its progress to the server in real time.

[0622] Furthermore, users can use a remote control terminal to monitor the operation of the entire system and modify the plan as needed. If the user determines that a particular task has not been completed, they can enter new instructions through the terminal, and the server will update the plan again.

[0623] In the event of an anomaly or sudden emergency, the terminal immediately switches the autonomous machine to safety mode to ensure safety. Based on subsequent analysis, the server generates new guidelines for safely resuming operations.

[0624] Thus, this invention utilizes autonomous mechanical devices and advanced artificial intelligence technology to efficiently and safely perform tasks in order to protect human workers from the dangers of radiation. In particular, it is characterized as a system that contributes to future work improvements by continuously providing data feedback on the work performed.

[0625] The following describes the processing flow.

[0626] Step 1:

[0627] The server collects environmental data in real time from sensors installed within the nuclear power plant. This includes important parameters such as radiation levels, temperature, and humidity.

[0628] Step 2:

[0629] The server analyzes the collected environmental data and compares the current situation with past data. Based on the results of this analysis, an AI algorithm is used to evaluate anomalies and risks and set flags for emergency response.

[0630] Step 3:

[0631] The server utilizes an AI agent to generate an optimal work plan based on the obtained analytical data. This plan includes task details, execution order, required travel routes, and equipment to be used.

[0632] Step 4:

[0633] The terminal receives the work plan transmitted from the server and sends specific control signals to the autonomous machine. This causes the machine to start operating according to the plan, and its progress is monitored.

[0634] Step 5:

[0635] Users can monitor overall work progress and environmental data through the monitor. If necessary, they can modify instructions or temporarily suspend work via the terminal.

[0636] Step 6:

[0637] The terminal receives feedback data from the machine and transmits it to the server. This data is used to re-evaluate the level of work completion and the environment.

[0638] Step 7:

[0639] If an anomaly or emergency occurs, the terminal will immediately change its control signal and switch the machine to safety mode. This information is immediately reported to the server for further analysis.

[0640] Step 8:

[0641] After the task is completed, the server analyzes all collected data and extracts areas for improvement needed for the next work plan. This feedback loop results in improved work efficiency and safety.

[0642] (Example 1)

[0643] 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".

[0644] In high-radiation environments, it is essential to ensure the safety of human workers while performing tasks efficiently and flexibly. Furthermore, immediate response to emergencies and flexible adaptation to constantly changing work plans are necessary. In addition, utilizing feedback from work results to achieve continuous improvement is crucial.

[0645] 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.

[0646] In this invention, the server includes means for aggregating environmental information and analyzing it in comparison with past information, means for generating a work plan using artificial intelligence and instructing the machine to follow that plan, and means for controlling the autonomous machine using a remote control terminal based on the plan. This enables the safety of human workers in high-radiation environments and the efficient and flexible execution of work.

[0647] "Environmental information" refers to various physical information about the work environment, such as radiation levels, temperature, and humidity.

[0648] "Aggregation" refers to gathering dispersed data in one place and managing it centrally.

[0649] "Past information" refers to data collected previously, which forms the basis for analysis and comparison.

[0650] "Artificial intelligence" refers to a series of processes performed by computer systems that mimic human intelligent behavior.

[0651] A "work plan" refers to a list of specific procedures, routes, and tasks that are set in advance to improve the efficiency of a task.

[0652] "Mechanical equipment" refers to autonomous or semi-autonomous mechanical devices that perform specific tasks.

[0653] A "remote control terminal" refers to a device used to operate machinery from a physically distant location.

[0654] An "autonomous machine" refers to a machine that uses artificial intelligence to make its own decisions and perform specific tasks.

[0655] An "emergency situation" refers to a critical and urgent situation that prevents normal operations from continuing.

[0656] "Safety mode" refers to a state where operations are temporarily stopped or the system is temporarily maintained to ensure the safety of people and machinery.

[0657] "Work progress" refers to the state or stage of whether the assigned work is progressing according to plan.

[0658] "Feedback" refers to the process of evaluating the results of work and the information obtained, and incorporating that into future plans and execution.

[0659] This invention is an autonomous mechanical device system for achieving efficient work while ensuring the safety of human workers in high-radiation environments. The system mainly consists of three components: a server, a terminal, and a user.

[0660] The server's role is to aggregate environmental information and analyze it by comparing it with historical data. Specifically, the server receives environmental data such as radiation levels, temperature, and humidity transmitted from autonomous machinery. The server stores this data in a database and performs filtering of outliers and trend analysis. Furthermore, based on the collected data, it generates an optimal work plan using a generative AI model. This generated plan includes efficient work routes and task priorities.

[0661] The terminal receives work plans transmitted from the server and sends instructions to autonomous machinery. The terminal enables remote control and allows for real-time modification of instructions depending on the situation. Furthermore, the terminal has a function to automatically switch to safety mode in the event of an emergency.

[0662] The user's role is to monitor the entire system's operation via a terminal. The user can check the progress in real time and modify the work plan as needed. Furthermore, the user can input new instructions to the server using appropriate prompt messages.

[0663] As a concrete example, consider equipment inspection work at a nuclear facility. The server collects environmental data such as radiation levels using various sensors and generates a work plan accordingly. The terminal controls autonomous machinery based on this plan, and the user monitors the progress of the plan and makes adjustments as needed.

[0664] An example of a prompt message would be, "Please tell me how to perform inspection work within the facility using autonomous machinery." This system enables improved work efficiency and safety while minimizing the effects of radiation.

[0665] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0666] Step 1:

[0667] The server receives sensor information transmitted from autonomous mechanical devices. Input data includes radiation levels, temperature, and humidity. The server stores this data in a database and filters out abnormal values. Specifically, the server updates the data every minute and performs trend analysis by comparing it with past data.

[0668] Step 2:

[0669] The server uses an AI model based on analyzed environmental data to generate an optimal work plan. Inputs include collected environmental data and historical data. The server uses algorithms to calculate efficient work routes and task priorities, and outputs detailed work procedures. Specific operations include determining the minimum travel distance and optimal work points during decontamination work.

[0670] Step 3:

[0671] The terminal receives work plans sent from the server and transmits instructions to autonomous machinery. The input is the work plan from the server, which the terminal converts into a format the machine can understand and outputs. Specifically, it performs real-time routing control and work start instructions for the machine.

[0672] Step 4:

[0673] The user monitors ongoing work via a terminal and modifies the plan as needed. Real-time monitoring data on the terminal serves as input, and the user outputs instructions for plan changes. Specifically, the user uses an on-screen interface to decide whether to add or cancel certain tasks.

[0674] Step 5:

[0675] In the event of an emergency, the terminal immediately switches the autonomous machine to safety mode. Inputs include emergency alerts from sensors. The terminal processes these and outputs instructions for safety mode. Specific actions include stopping the machine and issuing emergency voice alerts.

[0676] Step 6:

[0677] After completing a task, the server analyzes all collected data and generates feedback for future improvements. The input is data from the completed task, and the output is a proposed improvement plan for the next task. Specifically, it performs statistical analysis of work efficiency and identifies areas that need improvement.

[0678] (Application Example 1)

[0679] 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".

[0680] In hazardous environments, including those involving radiation, there is a need to perform work efficiently and safely while mitigating human risks. Current technology lacks the means to adequately perform automated inspection and maintenance work in these environments. Therefore, the challenge is to provide a system that can collect environmental information in real time, develop optimal work plans, and respond quickly to abnormal situations.

[0681] 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.

[0682] In this invention, the server includes means for collecting environmental information by an intelligent agent mounted on an autonomous device for working in a radiation environment, means for creating a work plan using the intelligent agent, and means for remotely operating or automatically controlling the autonomous device based on the work plan. This enables safe and effective work to be carried out while correcting operations based on real-time information updates and minimizing human intervention.

[0683] An "autonomous device" is equipment that has the ability to operate on its own judgment without detailed instructions from an external source.

[0684] An "intelligent agent" is software that uses artificial intelligence technology to analyze data and make decisions.

[0685] "Environmental information" refers to data on physical and chemical conditions such as radiation levels, temperature, and humidity.

[0686] A "work plan" is a document that outlines the procedures and processes necessary to achieve a specific objective.

[0687] "Radiation environment" refers to a work area where radioactive materials are present or are affected by them.

[0688] "Remote control" refers to a method of controlling devices or equipment from a location away from the physical site.

[0689] An "abnormal situation" refers to an unexpected situation that deviates from the norm, or a problem that threatens the safety or operation of a system.

[0690] "Information processing" refers to a series of processes that involve collecting and analyzing data and deciding on appropriate actions based on the results.

[0691] "Maintenance work" refers to periodic inspections and repairs carried out to ensure the proper operation of equipment and devices.

[0692] The system realizing this invention combines autonomous equipment and intelligent agents to support work in radiation environments. A server operates the intelligent agents to collect and analyze environmental information. The intelligent agents use software such as Python or TensorFlow to analyze the collected data and generate an optimal work plan. This plan clarifies the instructions necessary for remote operation or automated control.

[0693] The server also receives real-time feedback and adjusts its operations as needed. For this purpose, it uses ROS (Robot Operating System) to communicate with autonomous devices and controls written in Python to ensure safe operation. Hardware such as radiation sensors and temperature / humidity sensors are used to acquire environmental data.

[0694] Users monitor the work status using smart devices or computer terminals and send additional instructions to the server as needed. This allows for the immediate switching of autonomous equipment to safety mode in the event of an anomaly.

[0695] One practical example is a scenario in which a robot automatically inspects piping in a chemical plant. In this case, the robot continuously collects data using sensors, detects anomalies on the spot, and immediately reports them to the server. Correction instructions are then implemented in real time.

[0696] The following are examples of prompt statements used in the generative AI model.

[0697] "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please propose how to move the inspection robot to safely resume operations. Please also consider real-time correction instructions."

[0698] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0699] Step 1:

[0700] The server collects environmental information through various sensors (such as radiation sensors and temperature / humidity sensors) installed in autonomous devices. This information is converted from analog signals from the sensors into digital data and recorded in the server's database.

[0701] Step 2:

[0702] The server analyzes the acquired environmental information using Python or TensorFlow. Here, it compares it with past data to determine if an anomaly exists. The input is the current environmental information, and the output is the anomaly detection result.

[0703] Step 3:

[0704] The server generates a work plan using an intelligent agent. Based on anomaly detection results and environmental information, it calculates the optimal work route and procedures, and generates work instructions. The output is a detailed work plan.

[0705] Step 4:

[0706] The server sends the generated work plan to the autonomous device. Using ROS (Robot Operating System), it runs the device's control script, and the device automatically starts the planned work. The input is the work plan, and the output is the execution of control commands.

[0707] Step 5:

[0708] The terminal monitors the progress of tasks received from the server in real time. Operators can check the status via the terminal and send additional instructions if an abnormal situation occurs. Input is task progress data, and output is corrective instructions as needed.

[0709] Step 6:

[0710] The server immediately switches autonomous equipment to safety mode if an anomaly or emergency is detected. This safely stops operations and collects data for subsequent investigation and recovery. Inputs are anomaly notifications, and outputs are safety control commands.

[0711] Step 7:

[0712] The user sends prompts to the generating AI model as needed and receives suggestions for a new work plan. An example prompt is: "Based on the current environmental data, an anomaly has been detected by the radiation sensor. Please suggest how to move the inspection robot to safely resume work. Please also consider real-time correction instructions." The input is the prompt, and the output is the new suggestion.

[0713] 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.

[0714] This invention is a system that efficiently manages work in a radiation environment while taking into account the user's emotional state, thereby achieving further improvements in safety and work efficiency. The autonomous machine incorporates an artificial intelligence agent and an emotion engine.

[0715] First, autonomous machinery uses advanced sensors to acquire environmental data such as radiation levels. This data is collected on a server and analyzed by AI algorithms. During this process, environmental safety is evaluated and reflected in the work plan.

[0716] Next, the emotion engine monitors the user's emotions in real time. This is done using multiple sensing technologies, such as the user's facial expressions, voice tone, and heart rate. This data is input to a server and analyzed by an emotion analysis algorithm.

[0717] The server integrates this emotional data into the AI-generated work plan. For example, if it determines that the user is experiencing extreme stress, the work plan is temporarily suspended, and alternative routes are searched for or tasks are prioritized. This ensures safety while reducing the user's psychological burden.

[0718] The terminal transmits the generated work plan to the autonomous machine and provides appropriate control instructions. It also monitors the progress of the work and responds immediately if any abnormalities or emergencies occur.

[0719] Users can view this information through the interface and fine-tune their work as needed. For example, they can issue new instructions to machinery to avoid specific high-radiation areas.

[0720] The combination of the emotion engine and AI in this invention enables efficient and flexible work management that takes both environmental and emotional data into consideration. This system is useful not only for providing a safe and secure work environment but also for maintaining the mental health of workers.

[0721] The following describes the processing flow.

[0722] Step 1:

[0723] The server collects data from environmental sensors in real time, monitoring radiation levels, temperature, and other parameters. This data is immediately analyzed and forms the basis for assessing environmental safety.

[0724] Step 2:

[0725] The emotion engine collects emotional data from the user's facial recognition device and voice recognition system. It detects the user's emotional state from changes in facial expressions, voice tone, heart rate, etc. This data is sent to a server.

[0726] Step 3:

[0727] The server integrates environmental and emotional data and generates a work plan based on this. An AI algorithm determines the optimal work steps and sequence, and adjusts the work procedure if an increase in stress or anxiety is detected.

[0728] Step 4:

[0729] The terminal transmits the work plan received from the server to the autonomous machine and sends specific control signals. During this process, the starting position of the work and the movement path of the machine are set.

[0730] Step 5:

[0731] Users can monitor the progress of their work in real time via a monitor. If any ambiguities or problems arise, users can request changes to the plan through their terminal.

[0732] Step 6:

[0733] As the autonomous machine completes its task, the terminal reports progress data to the server. In particular, if an anomaly or emergency is detected, it immediately notifies the server and triggers a response that allows the system to take appropriate action.

[0734] Step 7:

[0735] After all tasks are completed, the server comprehensively analyzes the collected data and generates feedback to improve efficiency in future tasks. This feedback is used to improve the accuracy of future plans.

[0736] (Example 2)

[0737] 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".

[0738] Modern work environments requiring both safety and efficiency are essential. However, the lack of accurate environmental information collection and flexible work management that includes workers' emotional states leads to problems such as inability to respond quickly to work interruptions or unforeseen circumstances, resulting in reduced work efficiency. Furthermore, existing systems lack sufficient processes to alleviate the mental burden on workers.

[0739] 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.

[0740] In this invention, the server includes means for acquiring ambient environmental data, including radiation; means for generating a process plan; and means for evaluating the emotional state of on-site workers using an information analysis device and reflecting this in the work. This enables the generation and adjustment of plans that comprehensively consider environmental data and workers' emotional information, thereby improving safety, optimizing work efficiency, and reducing the psychological burden on workers.

[0741] "Autonomous mechanical devices" refer to robots and devices that perform tasks autonomously in a radiation environment, minimizing human intervention.

[0742] An "information processing device" refers to a computer system that collects and analyzes environmental data and worker sentiment data, and generates and adjusts process plans based on the results.

[0743] "Surrounding environment data" refers to data that provides detailed information about the work site, such as radiation levels, temperature and humidity, and air composition.

[0744] A "process plan" refers to a plan that outlines the procedures and routes for efficiently and safely carrying out a specific task.

[0745] An "information analysis device" refers to a device or system that analyzes data to extract useful information, enabling decision-making and adjustment of plans based on that information.

[0746] "Feedback" refers to the process of providing information about the next steps or areas for improvement based on data obtained after the completion of a task.

[0747] One embodiment of the present invention is a system for efficiently and safely performing work in a radiation environment. Specific embodiments thereof are described below.

[0748] First, the server collects ambient environmental data from autonomous mechanical devices. The hardware used includes devices equipped with high-performance sensors and communication modules. For software, libraries that execute AI algorithms such as TensorFlow and PyTorch are used for data analysis. This allows for the real-time acquisition of data such as radiation levels and temperature / humidity, enabling safety assessments.

[0749] Next, the information analysis device uses facial recognition and voice analysis technologies to evaluate the emotional state of workers. Data such as facial expressions, voice tone, and heart rate are processed using OpenCV and other emotion recognition software and reflected in the work plan. For example, if a worker is in a high-stress state, the work plan is dynamically adjusted and switched to a safety-first route. In this process, a generative AI model is used to automatically generate an efficient process plan.

[0750] The terminal transmits the work plan to the autonomous machine. The necessary hardware includes network-connected devices that use communication protocols to control the machine's operation. Furthermore, the terminal monitors the progress of the work and provides an interface for immediate response if any anomalies are detected.

[0751] Users verify the information obtained through this system via an interface. The interface is designed to provide the information necessary when the user performs manual operations. For example, it may be possible to issue new instructions to avoid high-radiation areas.

[0752] As a concrete example, consider the decontamination of a facility after a natural disaster. This system first monitors radiation levels and then provides the optimal work route based on the emotional state of the workers. An example of a prompt message would be, "Please tell me how to optimize the work while considering the user's emotional state."

[0753] Through the above process, a safe and efficient working environment is provided, and the psychological burden on workers is also reduced.

[0754] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0755] Step 1:

[0756] The server acquires ambient environmental data transmitted from autonomous machinery. This data includes radiation levels, temperature and humidity, and air composition. The acquired environmental data is input into an AI algorithm for data processing and analysis. Specifically, safety is evaluated using TensorFlow, the data is organized, and then output as basic information for process planning.

[0757] Step 2:

[0758] The server acquires emotional data from workers. This emotional data is collected based on facial expression data, voice tone, and heart rate entered by the user into a terminal. Face recognition is performed using image processing libraries such as OpenCV, and voice tone is analyzed using voice analysis software. The acquired emotional data is then analyzed, and stress levels and emotional states are quantified and output.

[0759] Step 3:

[0760] The server generates an optimal work plan using a generative AI model based on acquired environmental and emotional data. The generation process analyzes the input data and calculates steps that minimize radiation safety and worker psychological stress. The generated work plan is output in digital format and used as instructions for autonomous machinery.

[0761] Step 4:

[0762] The terminal transmits the work plan sent from the server to the autonomous machine. Using a communication protocol, it transmits the planned operation instructions to the machine. Upon receiving the instructions, the machine begins the specific actions based on the plan.

[0763] Step 5:

[0764] The terminal monitors the progress of the work in real time. It analyzes feedback from sensors and immediately notifies the server if any abnormalities or emergencies occur. This information is automatically recorded and used as data input for the next step.

[0765] Step 6:

[0766] Users can view work plans and progress information through the interface and add manual instructions as needed. Specifically, they can create new routes to avoid high-radiation areas. The results of this process are sent to the server and referenced within the system.

[0767] This series of processing steps enables work management that balances safety and efficiency.

[0768] (Application Example 2)

[0769] 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".

[0770] Working in a radiation-affected environment is highly stressful for workers, and this psychological burden can negatively impact work efficiency and safety. Furthermore, existing systems only provide work plans based on environmental data, failing to implement flexible and safe work management that considers the emotional state of workers. Against this backdrop, there is a need for a new system that simultaneously ensures the safety of the work environment and the mental well-being of workers.

[0771] 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.

[0772] In this invention, the server includes means for collecting and analyzing environmental data, means for collecting and analyzing worker emotional data using an emotional analysis function, and means for flexibly adjusting and generating work plans based on the emotional state of the workers. This makes it possible to reduce the psychological burden on workers even in a radiation environment and to manage work in a way that combines safety and efficiency.

[0773] An "autonomous machine" is a machine equipped with artificial intelligence that automatically performs tasks according to set environmental conditions.

[0774] An "artificial intelligence agent" is a program that analyzes environmental data and emotional data to generate work plans and optimize work efficiency.

[0775] "Environmental data" refers to information about the work environment, such as radiation levels, temperature, and humidity.

[0776] "Emotion analysis function" is a technology that uses the worker's facial expressions, tone of voice, heart rate, etc., to determine their emotional state in real time.

[0777] A "work plan" refers to a specific process and procedure generated based on environmental and emotional data to ensure that work is carried out efficiently and safely.

[0778] "Emotional data" refers to information that reflects the emotional state of a worker, and includes heart rate, facial expressions, and vocal characteristics.

[0779] An "abnormal or emergency situation" refers to a situation or event that makes it difficult to continue normal operations and requires a swift response.

[0780] "Feedback" is a procedure for analyzing data and results obtained after a task is completed and using that information to inform future work plans.

[0781] To implement this invention, a system is required in which a server, terminal, and user work together.

[0782] The server first collects environmental data such as radiation levels, temperature, and humidity from environmental sensors and stores it in a database. Based on this data, an artificial intelligence agent performs analysis and generates a safe work plan. The server also processes emotional data obtained from workers using emotion analysis capabilities. For example, it monitors the emotional state of workers in real time using cameras and heart rate monitors, and analyzes this data to understand their emotional state.

[0783] The terminal issues control instructions to autonomous machine devices based on work plans and sentiment analysis results sent from the server. These instructions control the devices to select the optimal route and perform tasks safely and efficiently. In the event of an anomaly or emergency, an alarm is immediately issued from the server, enabling a rapid response.

[0784] Users can monitor their work progress and emotional state in real time through the terminal interface. They can fine-tune their work as needed, further improving safety and efficiency. Specifically, the system can issue new instructions to help users avoid high-radiation areas. Utilizing a generative AI model, an example of a prompt might be: "Analyze the user's emotions while working in this environment and restructure the work plan. If the user is experiencing significant stress, suggest a new work route and provide an optimal work environment."

[0785] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0786] Step 1:

[0787] The server receives data from environmental sensors, including environmental data such as radiation levels, temperature, and humidity. This data is then stored and managed in a database. An AI algorithm is used to analyze this environmental data and extract the fundamental values ​​and conditions necessary to generate safe work plans.

[0788] Step 2:

[0789] The server performs sentiment analysis using data obtained from cameras and heart rate monitors as input. This includes the worker's facial expressions, voice tone, and heart rate. Using sentiment analysis algorithms, the server quantifies the worker's stress and emotional state, monitoring it in real time. This result is fed back to the server and expressed as metrics indicating the emotional state.

[0790] Step 3:

[0791] The server integrates the results of environmental data analysis and emotional data analysis, and uses a generative AI model to create a flexible work plan. If the user's emotional state is determined to be excessively stressed, it generates a prompt message and suggests temporarily changing the work plan. For example, it might introduce a specific prompt message such as, "If the user is feeling very stressed, suggest a new work route and provide an optimal work environment."

[0792] Step 4:

[0793] The terminal controls the autonomous machinery based on the work plan and control instructions sent from the server. Specifically, it selects the optimal work path and performs the work using automatic control functions. Furthermore, the terminal monitors the operation of the machinery and sends a warning to the server if an abnormal situation occurs, enabling a rapid response.

[0794] Step 5:

[0795] Users can use the interface provided by the terminal to check the progress of their work and the results of sentiment analysis. Based on this, they can fine-tune work instructions and change the control settings of machinery and equipment as needed. For example, a user might instruct a new route to avoid high-radiation areas.

[0796] 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.

[0797] 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.

[0798] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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."

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] The following is further disclosed regarding the embodiments described above.

[0818] (Claim 1)

[0819] A means of collecting environmental data using an artificial intelligence agent installed in an autonomous machine designed to work in a radiation environment,

[0820] A means for generating a work plan using the aforementioned artificial intelligence agent,

[0821] Based on the aforementioned work plan, means for remotely operating or automatically controlling the autonomous machine device,

[0822] Means for immediate response in the event of an anomaly or emergency,

[0823] A means for providing feedback on work completion data obtained from the autonomous machine,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, wherein the autonomous mechanical device is for performing equipment inspection or decontamination work.

[0827] (Claim 3)

[0828] The system according to claim 1, wherein the artificial intelligence agent has means for calculating a path to optimize work efficiency.

[0829] "Example 1"

[0830] (Claim 1)

[0831] A means of aggregating environmental information and analyzing it by comparing it with past information,

[0832] A means for generating a work plan using artificial intelligence and instructing a machine to implement that plan,

[0833] Based on the plan, means for controlling an autonomous mechanical device using a remote control terminal,

[0834] A means to immediately switch to safety mode when an emergency situation occurs,

[0835] A means to monitor work progress and revise plans in real time,

[0836] A means of storing completed work in a database and providing feedback,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, wherein the autonomous mechanical device is for performing maintenance or cleaning of a facility.

[0840] (Claim 3)

[0841] The system according to claim 1, comprising means for calculating an efficient work path using artificial intelligence.

[0842] "Application Example 1"

[0843] (Claim 1)

[0844] A means of collecting environmental information by an intelligent agent installed in an autonomous device for working in a radiation environment,

[0845] A means for creating a work plan using the aforementioned intelligent agent,

[0846] Based on the aforementioned work plan, means for remotely operating or automatically controlling the autonomous device,

[0847] Means for immediate response when an abnormal or emergency situation is detected,

[0848] A means for providing feedback on work completion information obtained from the autonomous device,

[0849] A means of providing automated inspection or maintenance work based on information processing in a hazardous environment including radiation,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1, wherein the autonomous device is for inspecting or decontaminating equipment, and the system also enables monitoring of the situation using a remote information display device.

[0853] (Claim 3)

[0854] The system according to claim 1, wherein the intelligent agent has means for calculating a path to optimize work efficiency and has a facilitating function for correcting its actions based on real-time information updates.

[0855] "Example 2 of combining an emotion engine"

[0856] (Claim 1)

[0857] A means of acquiring surrounding environmental data by an information processing device mounted on an autonomous machine designed to work in a radiation environment,

[0858] The means for generating a process plan using the aforementioned information processing device,

[0859] Based on the aforementioned process plan, means for remotely operating or automatically controlling the autonomous machine,

[0860] The information analysis device provides a means to evaluate the emotional state of on-site workers and reflect it in their work.

[0861] Means for immediate response in the event of an anomaly or emergency,

[0862] A means for providing feedback on work completion data obtained from the autonomous machine,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1, wherein the autonomous mechanical device is for performing inspection or cleaning work on a facility.

[0866] (Claim 3)

[0867] The system according to claim 1, wherein the information processing device has means for calculating a path to optimize work efficiency, and further has means for performing adaptive process adjustments based on worker emotional information.

[0868] "Application example 2 when combining with an emotional engine"

[0869] (Claim 1)

[0870] A means of collecting environmental data using an artificial intelligence agent installed in an autonomous machine designed to work in a radiation environment,

[0871] A means for collecting and analyzing worker emotional data using the aforementioned artificial intelligence agent and emotion analysis function, and generating a work plan,

[0872] Based on the aforementioned work plan, means for remotely operating or automatically controlling the autonomous machine device,

[0873] Means for immediate response in the event of an anomaly or emergency,

[0874] A means for feeding back work completion data obtained from the autonomous machine and adjusting the work environment according to the worker's mental state,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, wherein the autonomous mechanical device is for performing equipment inspection or decontamination work and environmental adjustments based on the worker's condition.

[0878] (Claim 3)

[0879] The system according to claim 1, wherein the artificial intelligence agent has means for calculating a path to optimize work efficiency and further proposing a flexible work plan that takes into account the emotional state of the worker. [Explanation of symbols]

[0880] 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. A means of collecting environmental data using an artificial intelligence agent installed in an autonomous machine designed to work in a radiation environment, A means for generating a work plan using the aforementioned artificial intelligence agent, Based on the aforementioned work plan, means for remotely operating or automatically controlling the autonomous machine device, Means for immediate response in the event of an anomaly or emergency, A means for providing feedback on work completion data obtained from the autonomous machine, A system that includes this.

2. The system according to claim 1, wherein the autonomous mechanical device is for performing equipment inspection or decontamination work.

3. The system according to claim 1, wherein the artificial intelligence agent has means for calculating a path to optimize work efficiency.

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