system

Abstract

We provide the system. [Solution] An information processing device that inputs corporate goal setting information and generates an action plan, A user interface means for displaying the aforementioned action plan and requesting approval or modification, Based on the approved action plan, a control means for automatically collecting data, An analytical means for analyzing collected data and monitoring progress, A system that includes adjustment mechanisms to adapt action plans based on the latest regulatory information.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds 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 medium-sized manufacturing enterprises, in order to efficiently and effectively carry out environmental protection activities, an approach that takes into account a wide range of environmental goals and complex regulatory requirements is necessary. Under such circumstances, while aiming to build a sustainable business model, enterprises need to balance environmental load reduction and cost reduction. However, due to the lack of appropriate environmental management and data analysis resources, many enterprises are facing the problem that they cannot obtain sufficient effects.

Means for Solving the Problems

[0005] This invention provides an information processing means for generating customized action plans based on a company's environmental objectives. The generated plan can be approved or modified through a user interface. It also includes a control means for automatically collecting data and interacts with various devices within the company. By analyzing the collected data and using an analysis means to monitor progress, the system maintains an optimal strategy for reducing environmental impact. Furthermore, by including an adjustment means that allows for readjustment of the action plan based on the latest regulatory information, the effectiveness and efficiency of environmental protection activities can be improved.

[0006] "Corporate goal-setting information" refers to information about the specific environmental goals that a company wants to achieve and the regulatory requirements that it must comply with.

[0007] An "action plan" is a detailed plan that outlines the specific steps and activities necessary for a company to achieve its goals.

[0008] "Information processing means" refers to devices and systems, including software and hardware, used to create action plans based on input data.

[0009] A "user interface" is an interface that allows a user to interact with the system, verify and input information, and approve and modify plans.

[0010] "Control measures" refer to technologies that include systems for operating IoT devices within an enterprise and automating data collection based on approved action plans.

[0011] "Analysis means" refers to means that include technologies for analyzing collected data and for monitoring progress and evaluating the effectiveness of environmental measures.

[0012] "Adjustment mechanisms" refer to systems and processes for reflecting the latest regulatory information and re-evaluating and adjusting action plans as needed. [Brief explanation of the drawing]

[0013] [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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is a system for supporting the environmental protection activities of medium-sized manufacturing companies, and specifically provides a means for automatically generating and implementing action plans based on the company's environmental objectives.

[0035] The server receives environmental targets and regulatory requirements entered by corporate users and uses this data to generate customized action plans using information processing tools. Specifically, the generated action plans include the amount of carbon dioxide to be reduced, energy consumption, and waste management methods.

[0036] The generated action plan is displayed to the user on their device, and they can approve or modify it. The user can adjust the plan as needed and finally approve it. The approved plan is returned to the server and proceeds to the next stage.

[0037] The server controls the company's IoT devices via APIs and automates data collection in line with action plans. This includes equipment usage data and data collection from environmental sensors.

[0038] The collected data is analyzed on a server using analytical tools, and the progress of environmental protection activities is monitored. This allows companies to obtain specific information about their level of achievement and areas for improvement.

[0039] The latest environmental regulatory information and external data are regularly retrieved by the server, and the action plan is automatically adjusted as needed. For example, if emission standards are revised due to changes in legal regulations, the plan is flexibly re-evaluated at this stage.

[0040] By utilizing this system, companies can implement environmental protection activities quickly and effectively, and support the realization of sustainable business models.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users use a terminal to input the company's environmental goals and existing regulatory requirements. This includes specific reduction targets and detailed information about the regulations that must be complied with.

[0044] Step 2:

[0045] The server receives user input and uses a large-scale language model to generate an action plan tailored to the company. This plan includes specific action steps towards the set environmental objectives and is optimized for that purpose.

[0046] Step 3:

[0047] The device displays the generated action plan to the user. The user reviews the plan, enters any necessary revisions, and then confirms and approves it.

[0048] Step 4:

[0049] The server controls IoT devices within the enterprise via API according to an approved action plan and automatically begins collecting the necessary data. The data from the devices is reliably collected and sent to the server.

[0050] Step 5:

[0051] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step.

[0052] Step 6:

[0053] The server regularly retrieves information on the latest policy changes and new regulations, and adjusts the action plan based on this information. The results of the progress analysis are also taken into consideration in this reassessment.

[0054] Step 7:

[0055] Users receive alerts and reports from the server on their devices. This includes regular reports on plan-based activities and suggestions for improvement. Users utilize this information to review their next goals and strategies.

[0056] (Example 1)

[0057] 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."

[0058] For companies to effectively implement environmental protection activities and achieve sustainable operations, they need to develop concrete action plans based on environmental goals, automate data collection and analysis, and dynamically adjust plans. However, current methods have challenges such as being time-consuming and labor-intensive, lacking immediacy and flexibility, from goal setting to implementation and monitoring.

[0059] 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.

[0060] In this invention, the server includes information processing means for inputting target setting information and generating an action plan using a generation AI model; display means for displaying the action plan and requesting approval or modification; and control means for automatically collecting data in cooperation with target devices within the company based on the approved action plan. This enables companies to quickly formulate concrete and actionable action plans, automatically collect data, and monitor progress in real time. Furthermore, dynamic plan adjustments in response to changes in external data and regulations are realized, promoting the efficiency of environmental protection activities.

[0061] "Target setting information" refers to data that shows numerical or guideline objective values ​​related to the environment that a company aims to achieve.

[0062] A "generative AI model" is an artificial intelligence algorithm that automatically generates efficient action plans based on past data and best practices.

[0063] An "action plan" is a document that lists the specific steps and measures that should be implemented to achieve environmental goals.

[0064] "Information processing means" refers to a computer program or system for analyzing input data and generating a desired output.

[0065] "Display means" refers to screens or devices that users use to review and modify action plans.

[0066] "Control means" refers to a program or device for managing coordination with target devices within a company and for managing data collection.

[0067] "Target devices" refer to internal company hardware and devices related to the collection of environmental data and the implementation of action plans.

[0068] A "coordination mechanism" is a system or program that has the function of re-evaluating action plans based on external regulatory information and data, and making necessary changes.

[0069] This invention is a system designed to support companies' environmental protection activities. The server receives the company's goal setting information and uses a generating AI model to create an action plan aligned with the environmental goals. The server utilizes dedicated environmental management software as an information processing means to design an efficient plan based on the input data. For example, if a goal such as "reduce energy consumption by 15% annually" is set, the server will propose specific measures based on this goal.

[0070] The generated action plan is displayed on the user's device. The device provides a user interface, allowing the user to review the action plan and make modifications or approvals as needed. The user can make specific changes, such as "adjusting the operating time of a particular device."

[0071] Approved action plans are implemented by a control system in which the server interacts with target devices within the enterprise. The server uses APIs to operate the enterprise's IoT devices and automatically collect the necessary data, including equipment usage data and information from environmental sensors.

[0072] Once data collection is complete, the server analyzes the collected data using analytical tools and provides the user with a progress report. This allows the user to understand their progress toward achieving environmental goals and adjust measures as needed. For example, feedback such as "The monthly report shows that carbon dioxide emissions are exceeding the target value" is provided.

[0073] Furthermore, the server periodically acquires external regulatory information and market data, and automatically re-evaluates whether the action plan is relevant to the current situation. If there are changes, it can flexibly adjust the plan based on those changes and provide new instructions to the user. An example of a prompt message might be, "Use AI to generate a plan to improve the company's energy efficiency and monitor its progress."

[0074] This system enables companies to quickly and effectively promote environmental protection activities and realize sustainable business models.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] Users input their company's environmental goals and regulatory requirements using a terminal. This input includes specific numerical targets, such as "reduce annual carbon dioxide emissions by 20%." The terminal then transmits this information to a server, providing the foundational data for generating an action plan.

[0078] Step 2:

[0079] The server generates an action plan using an AI model based on the received goal-setting information. The server analyzes the input data using information processing tools, taking into account historical data and industry best practices to create the optimal action plan. The output is a plan containing specific measures.

[0080] Step 3:

[0081] On the terminal, the action plan generated from the server is displayed through the user interface. The user reviews this plan and checks if it matches the company's actual situation. If necessary, they make specific modifications, such as adjusting operating hours or changing target figures, and finally approve the plan.

[0082] Step 4:

[0083] The approved action plan is sent back to the server. The server uses control mechanisms that connect to target devices within the enterprise to initiate the execution of the approved plan. The server interacts with IoT devices via APIs to automatically collect facility operating status and environmental sensor data.

[0084] Step 5:

[0085] The server analyzes the collected data using analytical tools to understand the progress. Equipment usage data and environmental data are used as input for the analysis, and a detailed report on the current progress is generated as output. This report is sent to the user, notifying them of their progress towards goals and areas for improvement.

[0086] Step 6:

[0087] The server periodically retrieves external regulatory information and data. Using adjustment mechanisms, the server re-evaluates the action plan based on the latest information and automatically adjusts it as needed. For example, when emission standards change due to new regulations, the plan can be reviewed and new measures can be proposed.

[0088] (Application Example 1)

[0089] 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."

[0090] Currently, many organizations and individuals face challenges in setting efficient and effective goals and managing progress when engaging in environmental protection activities. In particular, it is difficult to comprehensively manage and effectively track progress across an entire city. This makes it difficult to accurately evaluate the contribution of organizations and individuals to environmental goals, resulting in a situation where sustainable activities are less likely to be encouraged.

[0091] 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.

[0092] In this invention, the server includes data processing means for inputting organizational goal setting data and generating individual action plans; user interface means for visualizing the action plans and prompting approval or modification; and management means for automatically collecting environmental data in accordance with the approved action plans. This makes it possible to centrally manage environmental protection activities across an organization or city and to clearly grasp the progress of individual activities.

[0093] "Organizational goal-setting data" refers to the specific numerical targets and policies related to environmental protection set by an organization, and is the information that forms the basis of an action plan.

[0094] An "individual action plan" is a specific action plan generated based on the environmental goals of a particular organization or individual, and includes actionable steps and methods for achieving those goals.

[0095] "Data processing means" refers to a device or program for processing input target setting data and generating an action plan based on that data.

[0096] "User interface means" refers to the means by which users can review, modify, and approve action plans, and consists of intuitively operable screens and devices.

[0097] "Management measures" refer to devices or systems for automatically collecting environmental data based on approved action plans.

[0098] "Cutting-edge regulatory information" refers to the latest information on laws and regulations, which serves as a basis for adjusting environmental goals and action plans.

[0099] An "integrated management system" is a mechanism for aggregating data on environmental protection activities of participants across the city and evaluating progress using unified standards.

[0100] This invention provides a dedicated system for organizations and cities to efficiently carry out environmental protection activities. The system consists of servers, terminals, and various types of devices, and each component works in cooperation with others.

[0101] The server receives organizational goal-setting data using cloud-based infrastructure (e.g., Google Cloud, AWS, Microsoft Azure). Based on this data, the server generates individual action plans using a generative AI model. These plans include specific means and steps necessary to achieve environmental goals.

[0102] The generated action plan is displayed in the user interface on the device the user is accessing. Through this interface, the user can review, modify, and approve the plan. The approved action plan is then sent back to the server.

[0103] The server automatically collects necessary environmental data from IoT devices and sensors inside and outside the organization through management mechanisms. This allows for real-time monitoring of the progress of environmental protection activities. The collected data is used to evaluate progress using analytical tools.

[0104] Furthermore, the server regularly acquires the latest regulatory information and dynamically adjusts action plans as needed. This allows for flexible responses to environmental changes and regulatory revisions. For example, if new emission standards are established, the corresponding actions can be quickly reflected in the plan.

[0105] As a concrete example, in a certain residential area, residents aim to effectively reduce carbon dioxide emissions, and this system is used to propose specific measures that each household should take. An example of a prompt would be, "Generate a feasible action plan to reduce my household's energy consumption by 10%."

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The server receives goal-setting data from the organization. This data includes reduction targets and regulatory requirements. Using a generative AI model, the server creates individual action plans based on this input data and stores them in a database.

[0109] Step 2:

[0110] Users access the server through their terminal and view the generated action plan through a user interface. Through this interface, users can modify and approve the plan. As a result of this operation, the modified action plan is sent to the server and updated to the latest state.

[0111] Step 3:

[0112] Based on the approved action plan, the server begins collecting environmental data from IoT devices and sensors. This includes receiving device status information and sending control commands to aggregate it in a central system for analysis.

[0113] Step 4:

[0114] The server processes the collected data using analytical tools. The input data includes usage data and environmental parameters from each device, and analysis generates current status assessments and predictive data. These results are output as a progress report and notified to the administrator.

[0115] Step 5:

[0116] The server regularly retrieves the latest regulatory information and adjusts the action plan accordingly. This process involves querying regulatory information from external databases and analyzing its impact on the plan. If necessary, the server automatically updates the plan and notifies the user of the updates.

[0117] 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.

[0118] This invention aims to enable more effective implementation of action plans in a system that supports environmental protection activities in medium-sized manufacturing companies by incorporating an approach that takes user emotions into consideration. Specifically, it incorporates an emotion engine to recognize the user's emotional state and provide actions accordingly.

[0119] The server first receives goal-setting information provided by the company and uses information processing tools to generate an optimal action plan. This action plan includes environmental goals to be achieved and specific steps to achieve them.

[0120] The generated action plan is presented to the user via the device. The user's emotional state is analyzed by the emotion engine. For example, if the user is feeling stressed or anxious, the emotion engine restructures the action plan in a more understandable way and presents it to the user.

[0121] The server uses control mechanisms to operate IoT devices within the enterprise and collect data based on the action plan modified or approved by the user. Alerts are generated to provide feedback and support regarding project progress in response to changes in the user's emotions.

[0122] Furthermore, the server analyzes the data collected through the analysis tools and monitors the progress. Based on the analysis results, it ensures consistency with the latest regulatory information and makes necessary adjustments.

[0123] For example, if a user feels overwhelmed by the action plan, the emotion engine can detect this and have the server generate suggestions to alleviate the stress. This can improve the user's work experience and increase efficiency in achieving sustainable environmental protection activities.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] Users use a terminal to input the company's environmental goals and regulatory requirements. This includes specific reduction targets and specific regulatory conditions that must be complied with.

[0127] Step 2:

[0128] Based on the environmental goals and regulatory requirements received from the user, the server uses information processing tools to generate an action plan tailored to the company. This plan includes steps and necessary actions to achieve the goals.

[0129] Step 3:

[0130] The device displays the generated action plan to the user. During this process, the emotion engine recognizes the user's emotions and adjusts how the plan is presented accordingly. For example, if the user is feeling anxious, the server presents a more easily understandable and adjusted plan.

[0131] Step 4:

[0132] After receiving feedback from the emotion engine, users review the action plan, making revisions or approvals as needed. Once revisions are made, they are sent to the server and the plan is finalized.

[0133] Step 5:

[0134] Based on the approved action plan, the server uses control mechanisms to manage IoT devices within the enterprise and begins collecting the necessary data. This data collection proceeds in sync with the plan.

[0135] Step 6:

[0136] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step and used to adjust the plan.

[0137] Step 7:

[0138] The server continuously monitors the user's emotional state and generates alerts that provide appropriate support or improvement suggestions when stress or anxiety is detected. For example, it might suggest reducing the workload of an action plan.

[0139] Step 8:

[0140] Users receive reports and alerts from the server through their devices. Based on this information, they revise their strategies and plans for the future to facilitate the achievement of environmental goals.

[0141] (Example 2)

[0142] 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".

[0143] Traditional corporate environmental protection activities have faced problems such as excessive stress and inefficient plan execution because they fail to consider the emotional state of users when setting goals and implementing action plans. This has led to project delays and decreased motivation.

[0144] 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.

[0145] In this invention, the server includes information acquisition means for receiving corporate goal setting information, information processing means for generating an optimal action plan based on the goal setting information, and emotion recognition means for displaying the action plan to the user and recognizing and analyzing the user's emotional state. This enables flexible adjustment of the action plan based on the user's emotional state.

[0146] "Information acquisition means" refers to a means that has the function of receiving goal-setting information provided by a company.

[0147] "Information processing means" refers to means of processing data to generate an optimal action plan based on the received goal-setting information.

[0148] An "emotion recognition tool" is a tool equipped with the functionality to recognize and analyze a user's emotional state.

[0149] A "user interface means" is a means of presenting a provided action plan to the user and obtaining information through user interaction.

[0150] "Control means" refers to the means of operating equipment within a company and automatically collecting data based on an approved action plan.

[0151] "Analysis means" refers to methods for analyzing collected data and monitoring the progress of a project.

[0152] "Adjustment measures" refer to means for adjusting action plans based on the latest regulatory information.

[0153] Embodiments of this invention provide a system for medium-sized industrial organizations to effectively manage environmental protection activities. This system incorporates an approach that takes into account the emotional state of users in order to achieve the company's environmental goals.

[0154] The server first receives goal-setting information provided by the company using an information acquisition mechanism. This information is securely stored on the organization's server using a database management system (DBMS). Subsequently, an information processing mechanism generates an optimal action plan based on this information, utilizing a generated AI model. In this process, a specific AI algorithm is used to propose the optimal solution based on the input data.

[0155] The generated action plan is displayed to the user via their device. The user interface is intuitively designed, and the plan is presented visually through a web application or dedicated application. Users can easily grasp the tasks involved by viewing a detailed and easy-to-understand plan.

[0156] When a user interacts with a presented action plan, an emotion recognition system analyzes their emotional state. This emotion recognition is performed using natural language processing and emotion analysis algorithms, evaluating the emotional state in real time. If the user feels stressed or overwhelmed by the action plan, the server uses a generative AI model to readjust the plan and reconstruct it in a way that is easier for the user to understand.

[0157] Furthermore, based on the approved action plan, the server uses control mechanisms to send commands to various devices within the company and collect data. This enables real-time monitoring of environmental data and the operating status of devices within the company, utilizing IoT technology.

[0158] The server analyzes the collected data using analytical tools and monitors the progress. This data analysis uses big data analytics techniques to detect specific patterns and anomalies and provides feedback to administrators. Furthermore, based on the analysis results, the adjustment mechanism makes necessary updates to the action plan to ensure consistency with the latest regulatory information.

[0159] As a concrete example, this system can re-present actionable plans to users when they encounter new environmental regulations. By utilizing a generative AI model and inputting new prompts, it can be instructed, for example, "Propose specific steps to comply with the newly implemented regulations." In this way, it is possible to improve the user's work efficiency while promoting environmental protection efforts.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] The server receives goal-setting information provided by companies. The input consists of environmental targets based on the company's strategies and policies. The server stores this information in a database and analyzes the target content using data processing tools. The output is data in an easily processable format. This specific operation includes data format conversion and filtering.

[0163] Step 2:

[0164] The server utilizes an AI model generated using information processing tools to produce an optimal action plan based on the input data. The input here is processed target information. The server simulates multiple scenarios through the AI ​​model and obtains an optimized action plan as output. Specifically, this involves integrating past success data and repeatedly running simulations.

[0165] Step 3:

[0166] The terminal receives action plans sent from the server and displays them to the user through the user interface. The input is action plan data from the server. The terminal receives this data, outputs it in a visually understandable format, and presents it to the user. Specific operations include displaying the data in dashboard or list format.

[0167] Step 4:

[0168] The user reviews the action plan displayed on the device, and their emotional state is analyzed by emotion recognition tools. The input consists of data from the user's choices and actions. The server uses this information to perform emotion analysis and obtains the user's emotional state as output. Specific operations include natural language processing and emotion scoring.

[0169] Step 5:

[0170] The server adjusts the action plan based on the user's emotional state. The input here is the analyzed user's emotional data. The server then uses a regenerative AI model to restructure the plan to help the user understand it, and generates the adjusted action plan as output. Specific actions include simplifying the presented content and adding additional explanations.

[0171] Step 6:

[0172] The server operates devices within the enterprise and collects data using control mechanisms based on an approved action plan. The input is the final approved plan. The server uses this to control IoT devices and obtains real-time environmental data as output. Specific operations include issuing device operation commands and receiving data.

[0173] Step 7:

[0174] The server analyzes collected data using analytical tools and monitors project progress. The input is the collected raw data. The server performs data analysis and generates progress reports as output. Specific operations include data trend analysis and anomaly detection.

[0175] Step 8:

[0176] Based on the analysis results obtained, the server references the latest regulatory information and adjusts the action plan as needed. The inputs are the analysis results and regulatory information. The server outputs the adjusted plan and performs necessary optimizations. Specific operations include information matching and plan updates.

[0177] (Application Example 2)

[0178] 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".

[0179] For medium-sized manufacturing companies, the effectiveness of their environmental protection plans directly impacts their sustainability. However, traditional systems often fail to execute plans as intended, or users may experience stress or overburden due to the plans, making flexible adjustments difficult. Therefore, there is a need for a system that can dynamically adjust action plans while considering the emotional state of users.

[0180] 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.

[0181] In this invention, the server includes an information processing means for inputting corporate goal setting information and generating an action plan, an emotion engine for analyzing the user's emotional state, and a suggestion means for adjusting the action plan based on the analyzed emotional state. This enables flexible adjustment of the action plan in accordance with the user's emotions.

[0182] "Corporate goal-setting information" refers to information that describes the specific objectives and targets related to environmental protection and sustainability that a company aims to achieve.

[0183] An "action plan" is a plan that specifically outlines a series of activities and steps necessary to achieve a company's goals.

[0184] "Information processing means" refers to computer programs or systems used to analyze goal-setting information and generate optimal action plans.

[0185] "User interface means" refers to an interface that includes screens and input methods for users to review, approve, and modify action plans.

[0186] An "emotion engine" refers to an algorithm or system that analyzes and understands a user's emotional state based on their text and actions.

[0187] A "proposal tool" is a system for suggesting adjustments or modifications to the optimal action plan based on the analyzed emotional state.

[0188] "Control means" refers to a mechanism or system for automating data collection by operating various devices within a company based on an approved action plan.

[0189] "Analysis tools" refer to programs or systems used to analyze collected data and understand the progress being made.

[0190] "Adjustment measures" refer to systems that have the function of checking the latest regulatory information and adapting action plans accordingly.

[0191] The invention's implementation is described below. First, the server receives goal information set by the company and generates an optimal action plan using information processing means. This process utilizes the Python programming language, and a specific library (e.g., TextBlob) is used for sentiment analysis. The server sends the generated action plan to the terminal through a user interface means, prompting the user to approve or modify it.

[0192] The user reviews the action plan displayed on the device and inputs their emotional state. The emotion engine analyzes this input and generates an emotion score. Based on the results, the suggestion system adjusts the action plan as needed and presents it to the user. Furthermore, it is often implemented using web-related technologies such as JavaScript (registered trademark), and the emotion analysis and suggestions are performed in real time.

[0193] After the server has finished making emotion-based suggestions, it uses control mechanisms based on the approved plan and begins collecting data from various devices within the company. The data is then monitored for progress by analytical mechanisms. Furthermore, coordination mechanisms refer to the latest regulatory information to update the action plan as needed, providing support for sustainable environmental protection activities.

[0194] For example, if a factory manager is experiencing excessive stress due to newly set environmental targets, the emotion engine will detect this emotion and suggest adjustments to the work schedule or the allocation of additional resources through its suggestion system. This can reduce the workload.

[0195] Examples of prompt statements to input into a generative AI model include the following:

[0196] "The user's input text is as follows: Enter the user's text here. Analyze this sentiment and suggest appropriate action."

[0197] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0198] Step 1:

[0199] The server receives corporate goal setting information and generates an action plan using information processing tools. In this process, the server analyzes the input goal information, takes into account the company's resources and challenges, and calculates and outputs an actionable plan.

[0200] Step 2:

[0201] The generated action plan is sent from the server to the terminal and displayed to the user through a user interface. Here, the terminal provides a visually clear interface for displaying the action plan and gives the user the opportunity to approve or modify the plan.

[0202] Step 3:

[0203] The user inputs their emotional state into the device. This input information is sent from the device to the server and analyzed by an emotion engine. As a result, the server generates an emotion score, revealing the user's current psychological state.

[0204] Step 4:

[0205] The suggestion system uses the emotional score to adjust the action plan. The server evaluates the emotional score, modifies the plan's schedule and task priorities to reduce stress, and sends the adjusted plan to the terminal.

[0206] Step 5:

[0207] Once the user approves the adjusted action plan, the server uses control mechanisms to operate devices within the company and automatically begins data collection. At this time, smart sensors and IoT devices are activated and data is transferred based on the user's approval.

[0208] Step 6:

[0209] The collected data is processed by the server's analysis tools, and the project's progress is evaluated. The server aggregates the data and generates output that reports the goal achievement status to the user.

[0210] Step 7:

[0211] Finally, the adjustment mechanism compares the latest regulatory information with the plan and readjusts the action plan as necessary. If the server determines that the plan needs to be modified in accordance with laws and ethical standards, it will notify the user of the changes.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] 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.

[0218] 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).

[0219] 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.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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".

[0228] This invention is a system for supporting the environmental protection activities of medium-sized manufacturing companies, and specifically provides a means for automatically generating and implementing action plans based on the company's environmental objectives.

[0229] The server receives environmental targets and regulatory requirements entered by corporate users and uses this data to generate customized action plans using information processing tools. Specifically, the generated action plans include the amount of carbon dioxide to be reduced, energy consumption, and waste management methods.

[0230] The generated action plan is displayed to the user on their device, and they can approve or modify it. The user can adjust the plan as needed and finally approve it. The approved plan is returned to the server and proceeds to the next stage.

[0231] The server controls the company's IoT devices via APIs and automates data collection in line with action plans. This includes equipment usage data and data collection from environmental sensors.

[0232] The collected data is analyzed on a server using analytical tools, and the progress of environmental protection activities is monitored. This allows companies to obtain specific information about their level of achievement and areas for improvement.

[0233] The latest environmental regulatory information and external data are regularly retrieved by the server, and the action plan is automatically adjusted as needed. For example, if emission standards are revised due to changes in legal regulations, the plan is flexibly re-evaluated at this stage.

[0234] By utilizing this system, companies can implement environmental protection activities quickly and effectively, and support the realization of sustainable business models.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] Users use a terminal to input the company's environmental goals and existing regulatory requirements. This includes specific reduction targets and detailed information about the regulations that must be complied with.

[0238] Step 2:

[0239] The server receives user input and uses a large-scale language model to generate an action plan tailored to the company. This plan includes specific action steps towards the set environmental objectives and is optimized for that purpose.

[0240] Step 3:

[0241] The device displays the generated action plan to the user. The user reviews the plan, enters any necessary revisions, and then confirms and approves it.

[0242] Step 4:

[0243] The server controls IoT devices within the enterprise via API according to an approved action plan and automatically begins collecting the necessary data. The data from the devices is reliably collected and sent to the server.

[0244] Step 5:

[0245] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step.

[0246] Step 6:

[0247] The server regularly retrieves information on the latest policy changes and new regulations, and adjusts the action plan based on this information. The results of the progress analysis are also taken into consideration in this reassessment.

[0248] Step 7:

[0249] Users receive alerts and reports from the server on their devices. This includes regular reports on plan-based activities and suggestions for improvement. Users utilize this information to review their next goals and strategies.

[0250] (Example 1)

[0251] 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."

[0252] For companies to effectively implement environmental protection activities and achieve sustainable operations, they need to develop concrete action plans based on environmental goals, automate data collection and analysis, and dynamically adjust plans. However, current methods have challenges such as being time-consuming and labor-intensive, lacking immediacy and flexibility, from goal setting to implementation and monitoring.

[0253] 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.

[0254] In this invention, the server includes information processing means for inputting target setting information and generating an action plan using a generation AI model; display means for displaying the action plan and requesting approval or modification; and control means for automatically collecting data in cooperation with target devices within the company based on the approved action plan. This enables companies to quickly formulate concrete and actionable action plans, automatically collect data, and monitor progress in real time. Furthermore, dynamic plan adjustments in response to changes in external data and regulations are realized, promoting the efficiency of environmental protection activities.

[0255] "Target setting information" refers to data that shows numerical or guideline objective values ​​related to the environment that a company aims to achieve.

[0256] A "generative AI model" is an artificial intelligence algorithm that automatically generates efficient action plans based on past data and best practices.

[0257] An "action plan" is a document that lists the specific steps and measures that should be implemented to achieve environmental goals.

[0258] "Information processing means" refers to a computer program or system for analyzing input data and generating a desired output.

[0259] "Display means" refers to screens or devices that users use to review and modify action plans.

[0260] "Control means" refers to a program or device for managing coordination with target devices within a company and for managing data collection.

[0261] "Target devices" refer to internal company hardware and devices related to the collection of environmental data and the implementation of action plans.

[0262] A "coordination mechanism" is a system or program that has the function of re-evaluating action plans based on external regulatory information and data, and making necessary changes.

[0263] This invention is a system designed to support companies' environmental protection activities. The server receives the company's goal setting information and uses a generating AI model to create an action plan aligned with the environmental goals. The server utilizes dedicated environmental management software as an information processing means to design an efficient plan based on the input data. For example, if a goal such as "reduce energy consumption by 15% annually" is set, the server will propose specific measures based on this goal.

[0264] The generated action plan is displayed on the user's device. The device provides a user interface, allowing the user to review the action plan and make modifications or approvals as needed. The user can make specific changes, such as "adjusting the operating time of a particular device."

[0265] Approved action plans are implemented by a control system in which the server interacts with target devices within the enterprise. The server uses APIs to operate the enterprise's IoT devices and automatically collect the necessary data, including equipment usage data and information from environmental sensors.

[0266] Once data collection is complete, the server analyzes the collected data using analytical tools and provides the user with a progress report. This allows the user to understand their progress toward achieving environmental goals and adjust measures as needed. For example, feedback such as "The monthly report shows that carbon dioxide emissions are exceeding the target value" is provided.

[0267] Furthermore, the server periodically acquires external regulatory information and market data, and automatically re-evaluates whether the action plan is relevant to the current situation. If there are changes, it can flexibly adjust the plan based on those changes and provide new instructions to the user. An example of a prompt message might be, "Use AI to generate a plan to improve the company's energy efficiency and monitor its progress."

[0268] This system enables companies to quickly and effectively promote environmental protection activities and realize sustainable business models.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] Users input their company's environmental goals and regulatory requirements using a terminal. This input includes specific numerical targets, such as "reduce annual carbon dioxide emissions by 20%." The terminal then transmits this information to a server, providing the foundational data for generating an action plan.

[0272] Step 2:

[0273] The server generates an action plan using an AI model based on the received goal-setting information. The server analyzes the input data using information processing tools, taking into account historical data and industry best practices to create the optimal action plan. The output is a plan containing specific measures.

[0274] Step 3:

[0275] On the terminal, the action plan generated from the server is displayed through the user interface. The user reviews this plan and checks if it matches the company's actual situation. If necessary, they make specific modifications, such as adjusting operating hours or changing target figures, and finally approve the plan.

[0276] Step 4:

[0277] The approved action plan is sent back to the server. The server uses control mechanisms that connect to target devices within the enterprise to initiate the execution of the approved plan. The server interacts with IoT devices via APIs to automatically collect facility operating status and environmental sensor data.

[0278] Step 5:

[0279] The server analyzes the collected data using analytical tools to understand the progress. Equipment usage data and environmental data are used as input for the analysis, and a detailed report on the current progress is generated as output. This report is sent to the user, notifying them of their progress towards goals and areas for improvement.

[0280] Step 6:

[0281] The server periodically retrieves external regulatory information and data. Using adjustment mechanisms, the server re-evaluates the action plan based on the latest information and automatically adjusts it as needed. For example, when emission standards change due to new regulations, the plan can be reviewed and new measures can be proposed.

[0282] (Application Example 1)

[0283] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0284] Currently, when many organizations and individuals carry out environmental protection activities, there is a problem that it is difficult to set efficient and effective goals and manage progress. In particular, it is difficult to integrally manage the environmental protection activities of an entire city and effectively grasp the progress. As a result, it is impossible to accurately evaluate the contribution degree of an organization or an individual to environmental goals, and sustainable activities are not easily encouraged.

[0285] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means.

[0286] In this invention, the server includes data processing means for inputting the goal setting data of an organization and generating an individual action plan, user interface means for visualizing the action plan and prompting approval or modification, and management means for automatically collecting environmental data according to the approved action plan. Thereby, it becomes possible to integrally manage the environmental protection activities of an organization or an entire city and clearly grasp individual progress.

[0287] The "goal setting data of an organization" refers to specific goal numerical values and policies regarding environmental protection set by an organization, and is information that serves as the basis for an action plan.

[0288] The "individual action plan" is a specific activity plan generated based on the environmental goals of a specific organization or individual, and includes executable procedures and methods for achieving goals.

[0289] The "data processing means" is a device or program for processing the input goal setting data and generating an action plan based on it.

[0290] The "user interface means" is means for a user to confirm, modify, and approve an action plan, and is composed of a screen or a device that enables intuitive operations.

[0291] "Management measures" refer to devices or systems for automatically collecting environmental data based on approved action plans.

[0292] "Cutting-edge regulatory information" refers to the latest information on laws and regulations, which serves as a basis for adjusting environmental goals and action plans.

[0293] An "integrated management system" is a mechanism for aggregating data on environmental protection activities of participants across the city and evaluating progress using unified standards.

[0294] This invention provides a dedicated system for organizations and cities to efficiently carry out environmental protection activities. The system consists of servers, terminals, and various types of devices, and each component works in cooperation with others.

[0295] The server receives organizational goal-setting data using cloud-based infrastructure (e.g., Google Cloud, AWS, Microsoft Azure). Based on this data, the server generates individual action plans using generative AI models. These plans include specific means and steps necessary to achieve environmental goals.

[0296] The generated action plan is displayed in the user interface on the device the user is accessing. Through this interface, the user can review, modify, and approve the plan. The approved action plan is then sent back to the server.

[0297] The server automatically collects necessary environmental data from IoT devices and sensors inside and outside the organization through management mechanisms. This allows for real-time monitoring of the progress of environmental protection activities. The collected data is used to evaluate progress using analytical tools.

[0298] Furthermore, the server regularly acquires the latest regulatory information and dynamically adjusts action plans as needed. This allows for flexible responses to environmental changes and regulatory revisions. For example, if new emission standards are established, the corresponding actions can be quickly reflected in the plan.

[0299] As a concrete example, in a certain residential area, residents aim to effectively reduce carbon dioxide emissions, and this system is used to propose specific measures that each household should take. An example of a prompt would be, "Generate a feasible action plan to reduce my household's energy consumption by 10%."

[0300] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0301] Step 1:

[0302] The server receives goal-setting data from the organization. This data includes reduction targets and regulatory requirements. Using a generative AI model, the server creates individual action plans based on this input data and stores them in a database.

[0303] Step 2:

[0304] Users access the server through their terminal and view the generated action plan through a user interface. Through this interface, users can modify and approve the plan. As a result of this operation, the modified action plan is sent to the server and updated to the latest state.

[0305] Step 3:

[0306] Based on the approved action plan, the server begins collecting environmental data from IoT devices and sensors. This includes receiving device status information and sending control commands to aggregate it in a central system for analysis.

[0307] Step 4:

[0308] The server processes the collected data using analysis means. The input data includes usage data and environmental parameters from each device, and through analysis, current situation evaluations and prediction data are generated. This result is output as a progress report and notified to the administrator.

[0309] Step 5:

[0310] The server periodically obtains the latest regulatory information and adjusts the action plan. In this process, regulatory information is queried from an external database and the impact on the plan is analyzed. If necessary, the server automatically updates the plan and notifies the user of the update.

[0311] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0312] This invention is for a system that supports environmental protection activities in medium-sized manufacturing industries. By adopting an approach that takes into account the user's emotions, it is for more effectively implementing an action plan. Specifically, by incorporating an emotion engine, it recognizes the user's emotional state and provides actions accordingly.

[0313] The server first receives the target setting information provided by the enterprise and generates an optimal action plan using information processing means. This action plan describes the environmental goals to be achieved and the specific steps for that.

[0314] The generated action plan is presented to the user through the terminal. The user's emotional state is analyzed by the emotion engine. For example, when the user feels stress or anxiety, the emotion engine reorganizes the action plan into a more understandable form and presents it to the user.

[0315] The server uses control mechanisms to operate IoT devices within the enterprise and collect data based on the action plan modified or approved by the user. Alerts are generated to provide feedback and support regarding project progress in response to changes in the user's emotions.

[0316] Furthermore, the server analyzes the data collected through the analysis tools and monitors the progress. Based on the analysis results, it ensures consistency with the latest regulatory information and makes necessary adjustments.

[0317] For example, if a user feels overwhelmed by the action plan, the emotion engine can detect this and have the server generate suggestions to alleviate the stress. This can improve the user's work experience and increase efficiency in achieving sustainable environmental protection activities.

[0318] The following describes the processing flow.

[0319] Step 1:

[0320] Users use a terminal to input the company's environmental goals and regulatory requirements. This includes specific reduction targets and specific regulatory conditions that must be complied with.

[0321] Step 2:

[0322] Based on the environmental goals and regulatory requirements received from the user, the server uses information processing tools to generate an action plan tailored to the company. This plan includes steps and necessary actions to achieve the goals.

[0323] Step 3:

[0324] The device displays the generated action plan to the user. During this process, the emotion engine recognizes the user's emotions and adjusts how the plan is presented accordingly. For example, if the user is feeling anxious, the server presents a more easily understandable and adjusted plan.

[0325] Step 4:

[0326] After receiving feedback from the emotion engine, users review the action plan, making revisions or approvals as needed. Once revisions are made, they are sent to the server and the plan is finalized.

[0327] Step 5:

[0328] Based on the approved action plan, the server uses control mechanisms to manage IoT devices within the enterprise and begins collecting the necessary data. This data collection proceeds in sync with the plan.

[0329] Step 6:

[0330] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step and used to adjust the plan.

[0331] Step 7:

[0332] The server continuously monitors the user's emotional state and generates alerts that provide appropriate support or improvement suggestions when stress or anxiety is detected. For example, it might suggest reducing the workload of an action plan.

[0333] Step 8:

[0334] Users receive reports and alerts from the server through their devices. Based on this information, they revise their strategies and plans for the future to facilitate the achievement of environmental goals.

[0335] (Example 2)

[0336] 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".

[0337] Traditional corporate environmental protection activities have faced problems such as excessive stress and inefficient plan execution because they fail to consider the emotional state of users when setting goals and implementing action plans. This has led to project delays and decreased motivation.

[0338] 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.

[0339] In this invention, the server includes information acquisition means for receiving corporate goal setting information, information processing means for generating an optimal action plan based on the goal setting information, and emotion recognition means for displaying the action plan to the user and recognizing and analyzing the user's emotional state. This enables flexible adjustment of the action plan based on the user's emotional state.

[0340] "Information acquisition means" refers to a means that has the function of receiving goal-setting information provided by a company.

[0341] "Information processing means" refers to means of processing data to generate an optimal action plan based on the received goal-setting information.

[0342] An "emotion recognition tool" is a tool equipped with the functionality to recognize and analyze a user's emotional state.

[0343] A "user interface means" is a means of presenting a provided action plan to the user and obtaining information through user interaction.

[0344] "Control means" refers to the means of operating equipment within a company and automatically collecting data based on an approved action plan.

[0345] "Analysis means" refers to methods for analyzing collected data and monitoring the progress of a project.

[0346] "Adjustment measures" refer to means for adjusting action plans based on the latest regulatory information.

[0347] Embodiments of this invention provide a system for medium-sized industrial organizations to effectively manage environmental protection activities. This system incorporates an approach that takes into account the emotional state of users in order to achieve the company's environmental goals.

[0348] The server first receives goal-setting information provided by the company using an information acquisition mechanism. This information is securely stored on the organization's server using a database management system (DBMS). Subsequently, an information processing mechanism generates an optimal action plan based on this information, utilizing a generated AI model. In this process, a specific AI algorithm is used to propose the optimal solution based on the input data.

[0349] The generated action plan is displayed to the user via their device. The user interface is intuitively designed, and the plan is presented visually through a web application or dedicated application. Users can easily grasp the tasks involved by viewing a detailed and easy-to-understand plan.

[0350] When a user interacts with a presented action plan, an emotion recognition system analyzes their emotional state. This emotion recognition is performed using natural language processing and emotion analysis algorithms, evaluating the emotional state in real time. If the user feels stressed or overwhelmed by the action plan, the server uses a generative AI model to readjust the plan and reconstruct it in a way that is easier for the user to understand.

[0351] Furthermore, based on the approved action plan, the server uses control mechanisms to send commands to various devices within the company and collect data. This enables real-time monitoring of environmental data and the operating status of devices within the company, utilizing IoT technology.

[0352] The server analyzes the collected data using analytical tools and monitors the progress. This data analysis uses big data analytics techniques to detect specific patterns and anomalies and provides feedback to administrators. Furthermore, based on the analysis results, the adjustment mechanism makes necessary updates to the action plan to ensure consistency with the latest regulatory information.

[0353] As a concrete example, this system can re-present actionable plans to users when they encounter new environmental regulations. By utilizing a generative AI model and inputting new prompts, it can be instructed, for example, "Propose specific steps to comply with the newly implemented regulations." In this way, it is possible to improve the user's work efficiency while promoting environmental protection efforts.

[0354] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0355] Step 1:

[0356] The server receives goal-setting information provided by companies. The input consists of environmental targets based on the company's strategies and policies. The server stores this information in a database and analyzes the target content using data processing tools. The output is data in an easily processable format. This specific operation includes data format conversion and filtering.

[0357] Step 2:

[0358] The server utilizes an AI model generated using information processing tools to produce an optimal action plan based on the input data. The input here is processed target information. The server simulates multiple scenarios through the AI ​​model and obtains an optimized action plan as output. Specifically, this involves integrating past success data and repeatedly running simulations.

[0359] Step 3:

[0360] The terminal receives action plans sent from the server and displays them to the user through the user interface. The input is action plan data from the server. The terminal receives this data, outputs it in a visually understandable format, and presents it to the user. Specific operations include displaying the data in dashboard or list format.

[0361] Step 4:

[0362] The user reviews the action plan displayed on the device, and their emotional state is analyzed by emotion recognition tools. The input consists of data from the user's choices and actions. The server uses this information to perform emotion analysis and obtains the user's emotional state as output. Specific operations include natural language processing and emotion scoring.

[0363] Step 5:

[0364] The server adjusts the action plan based on the user's emotional state. The input here is the analyzed user's emotional data. The server then uses a regenerative AI model to restructure the plan to help the user understand it, and generates the adjusted action plan as output. Specific actions include simplifying the presented content and adding additional explanations.

[0365] Step 6:

[0366] The server operates devices within the enterprise and collects data using control mechanisms based on an approved action plan. The input is the final approved plan. The server uses this to control IoT devices and obtains real-time environmental data as output. Specific operations include issuing device operation commands and receiving data.

[0367] Step 7:

[0368] The server analyzes collected data using analytical tools and monitors project progress. The input is the collected raw data. The server performs data analysis and generates progress reports as output. Specific operations include data trend analysis and anomaly detection.

[0369] Step 8:

[0370] Based on the analysis results obtained, the server references the latest regulatory information and adjusts the action plan as needed. The inputs are the analysis results and regulatory information. The server outputs the adjusted plan and performs necessary optimizations. Specific operations include information matching and plan updates.

[0371] (Application Example 2)

[0372] 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."

[0373] For medium-sized manufacturing companies, the effectiveness of their environmental protection plans directly impacts their sustainability. However, traditional systems often fail to execute plans as intended, or users may experience stress or overburden due to the plans, making flexible adjustments difficult. Therefore, there is a need for a system that can dynamically adjust action plans while considering the emotional state of users.

[0374] 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.

[0375] In this invention, the server includes an information processing means for inputting corporate goal setting information and generating an action plan, an emotion engine for analyzing the user's emotional state, and a suggestion means for adjusting the action plan based on the analyzed emotional state. This enables flexible adjustment of the action plan in accordance with the user's emotions.

[0376] "Corporate goal-setting information" refers to information that describes the specific objectives and targets related to environmental protection and sustainability that a company aims to achieve.

[0377] An "action plan" is a plan that specifically outlines a series of activities and steps necessary to achieve a company's goals.

[0378] "Information processing means" refers to computer programs or systems used to analyze goal-setting information and generate optimal action plans.

[0379] "User interface means" refers to an interface that includes screens and input methods for users to review, approve, and modify action plans.

[0380] An "emotion engine" refers to an algorithm or system that analyzes and understands a user's emotional state based on their text and actions.

[0381] A "proposal tool" is a system for suggesting adjustments or modifications to the optimal action plan based on the analyzed emotional state.

[0382] "Control means" refers to a mechanism or system for automating data collection by operating various devices within a company based on an approved action plan.

[0383] "Analysis tools" refer to programs or systems used to analyze collected data and understand the progress being made.

[0384] "Adjustment measures" refer to systems that have the function of checking the latest regulatory information and adapting action plans accordingly.

[0385] The invention's implementation is described below. First, the server receives goal information set by the company and generates an optimal action plan using information processing means. This process utilizes the Python programming language, and a specific library (e.g., TextBlob) is used for sentiment analysis. The server sends the generated action plan to the terminal through a user interface means, prompting the user to approve or modify it.

[0386] The user reviews the action plan displayed on the device and inputs their emotional state. The emotion engine analyzes this input and generates an emotion score. Based on the results, the suggestion system adjusts the action plan as needed and presents it to the user. Furthermore, it is often implemented using web-related technologies such as JavaScript, and the emotion analysis and suggestions are performed in real time.

[0387] After the server has finished making emotion-based suggestions, it uses control mechanisms based on the approved plan and begins collecting data from various devices within the company. The data is then monitored for progress by analytical mechanisms. Furthermore, coordination mechanisms refer to the latest regulatory information to update the action plan as needed, providing support for sustainable environmental protection activities.

[0388] For example, if a factory manager is experiencing excessive stress due to newly set environmental targets, the emotion engine will detect this emotion and suggest adjustments to the work schedule or the allocation of additional resources through its suggestion system. This can reduce the workload.

[0389] Examples of prompt statements to input into a generative AI model include the following:

[0390] "The user's input text is as follows: Enter the user's text here. Analyze this sentiment and suggest appropriate action."

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The server receives corporate goal setting information and generates an action plan using information processing tools. In this process, the server analyzes the input goal information, takes into account the company's resources and challenges, and calculates and outputs an actionable plan.

[0394] Step 2:

[0395] The generated action plan is sent from the server to the terminal and displayed to the user through a user interface. Here, the terminal provides a visually clear interface for displaying the action plan and gives the user the opportunity to approve or modify the plan.

[0396] Step 3:

[0397] The user inputs their emotional state into the device. This input information is sent from the device to the server and analyzed by an emotion engine. As a result, the server generates an emotion score, revealing the user's current psychological state.

[0398] Step 4:

[0399] The suggestion system uses the emotional score to adjust the action plan. The server evaluates the emotional score, modifies the plan's schedule and task priorities to reduce stress, and sends the adjusted plan to the terminal.

[0400] Step 5:

[0401] Once the user approves the adjusted action plan, the server uses control mechanisms to operate devices within the company and automatically begins data collection. At this time, smart sensors and IoT devices are activated and data is transferred based on the user's approval.

[0402] Step 6:

[0403] The collected data is processed by the server's analysis tools, and the project's progress is evaluated. The server aggregates the data and generates output that reports the goal achievement status to the user.

[0404] Step 7:

[0405] Finally, the adjustment mechanism compares the latest regulatory information with the plan and readjusts the action plan as necessary. If the server determines that the plan needs to be modified in accordance with laws and ethical standards, it will notify the user of the changes.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] [Third Embodiment]

[0410] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0411] 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.

[0412] 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).

[0413] 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.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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".

[0422] This invention is a system for supporting the environmental protection activities of medium-sized manufacturing companies, and specifically provides a means for automatically generating and implementing action plans based on the company's environmental objectives.

[0423] The server receives environmental targets and regulatory requirements entered by corporate users and uses this data to generate customized action plans using information processing tools. Specifically, the generated action plans include the amount of carbon dioxide to be reduced, energy consumption, and waste management methods.

[0424] The generated action plan is displayed to the user on their device, and they can approve or modify it. The user can adjust the plan as needed and finally approve it. The approved plan is returned to the server and proceeds to the next stage.

[0425] The server controls the company's IoT devices via APIs and automates data collection in line with action plans. This includes equipment usage data and data collection from environmental sensors.

[0426] The collected data is analyzed on a server using analytical tools, and the progress of environmental protection activities is monitored. This allows companies to obtain specific information about their level of achievement and areas for improvement.

[0427] The latest environmental regulatory information and external data are regularly retrieved by the server, and the action plan is automatically adjusted as needed. For example, if emission standards are revised due to changes in legal regulations, the plan is flexibly re-evaluated at this stage.

[0428] By utilizing this system, companies can implement environmental protection activities quickly and effectively, and support the realization of sustainable business models.

[0429] The following describes the processing flow.

[0430] Step 1:

[0431] Users use a terminal to input the company's environmental goals and existing regulatory requirements. This includes specific reduction targets and detailed information about the regulations that must be complied with.

[0432] Step 2:

[0433] The server receives user input and uses a large-scale language model to generate an action plan tailored to the company. This plan includes specific action steps towards the set environmental objectives and is optimized for that purpose.

[0434] Step 3:

[0435] The device displays the generated action plan to the user. The user reviews the plan, enters any necessary revisions, and then confirms and approves it.

[0436] Step 4:

[0437] The server controls IoT devices within the enterprise via API according to an approved action plan and automatically begins collecting the necessary data. The data from the devices is reliably collected and sent to the server.

[0438] Step 5:

[0439] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step.

[0440] Step 6:

[0441] The server regularly retrieves information on the latest policy changes and new regulations, and adjusts the action plan based on this information. The results of the progress analysis are also taken into consideration in this reassessment.

[0442] Step 7:

[0443] Users receive alerts and reports from the server on their devices. This includes regular reports on plan-based activities and suggestions for improvement. Users utilize this information to review their next goals and strategies.

[0444] (Example 1)

[0445] 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."

[0446] For companies to effectively implement environmental protection activities and achieve sustainable operations, they need to develop concrete action plans based on environmental goals, automate data collection and analysis, and dynamically adjust plans. However, current methods have challenges such as being time-consuming and labor-intensive, lacking immediacy and flexibility, from goal setting to implementation and monitoring.

[0447] 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.

[0448] In this invention, the server includes information processing means for inputting target setting information and generating an action plan using a generation AI model; display means for displaying the action plan and requesting approval or modification; and control means for automatically collecting data in cooperation with target devices within the company based on the approved action plan. This enables companies to quickly formulate concrete and actionable action plans, automatically collect data, and monitor progress in real time. Furthermore, dynamic plan adjustments in response to changes in external data and regulations are realized, promoting the efficiency of environmental protection activities.

[0449] "Target setting information" refers to data that shows numerical or guideline objective values ​​related to the environment that a company aims to achieve.

[0450] A "generative AI model" is an artificial intelligence algorithm that automatically generates efficient action plans based on past data and best practices.

[0451] An "action plan" is a document that lists the specific steps and measures that should be implemented to achieve environmental goals.

[0452] "Information processing means" refers to a computer program or system for analyzing input data and generating a desired output.

[0453] "Display means" refers to screens or devices that users use to review and modify action plans.

[0454] "Control means" refers to a program or device for managing coordination with target devices within a company and for managing data collection.

[0455] "Target devices" refer to internal company hardware and devices related to the collection of environmental data and the implementation of action plans.

[0456] A "coordination mechanism" is a system or program that has the function of re-evaluating action plans based on external regulatory information and data, and making necessary changes.

[0457] This invention is a system designed to support companies' environmental protection activities. The server receives the company's goal setting information and uses a generating AI model to create an action plan aligned with the environmental goals. The server utilizes dedicated environmental management software as an information processing means to design an efficient plan based on the input data. For example, if a goal such as "reduce energy consumption by 15% annually" is set, the server will propose specific measures based on this goal.

[0458] The generated action plan is displayed on the user's device. The device provides a user interface, allowing the user to review the action plan and make modifications or approvals as needed. The user can make specific changes, such as "adjusting the operating time of a particular device."

[0459] Approved action plans are implemented by a control system in which the server interacts with target devices within the enterprise. The server uses APIs to operate the enterprise's IoT devices and automatically collect the necessary data, including equipment usage data and information from environmental sensors.

[0460] Once data collection is complete, the server analyzes the collected data using analytical tools and provides the user with a progress report. This allows the user to understand their progress toward achieving environmental goals and adjust measures as needed. For example, feedback such as "The monthly report shows that carbon dioxide emissions are exceeding the target value" is provided.

[0461] Furthermore, the server periodically acquires external regulatory information and market data, and automatically re-evaluates whether the action plan is relevant to the current situation. If there are changes, it can flexibly adjust the plan based on those changes and provide new instructions to the user. An example of a prompt message might be, "Use AI to generate a plan to improve the company's energy efficiency and monitor its progress."

[0462] This system enables companies to quickly and effectively promote environmental protection activities and realize sustainable business models.

[0463] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0464] Step 1:

[0465] Users input their company's environmental goals and regulatory requirements using a terminal. This input includes specific numerical targets, such as "reduce annual carbon dioxide emissions by 20%." The terminal then transmits this information to a server, providing the foundational data for generating an action plan.

[0466] Step 2:

[0467] The server generates an action plan using an AI model based on the received goal-setting information. The server analyzes the input data using information processing tools, taking into account historical data and industry best practices to create the optimal action plan. The output is a plan containing specific measures.

[0468] Step 3:

[0469] On the terminal, the action plan generated from the server is displayed through the user interface. The user reviews this plan and checks if it matches the company's actual situation. If necessary, they make specific modifications, such as adjusting operating hours or changing target figures, and finally approve the plan.

[0470] Step 4:

[0471] The approved action plan is sent back to the server. The server uses control mechanisms that connect to target devices within the enterprise to initiate the execution of the approved plan. The server interacts with IoT devices via APIs to automatically collect facility operating status and environmental sensor data.

[0472] Step 5:

[0473] The server analyzes the collected data using analytical tools to understand the progress. Equipment usage data and environmental data are used as input for the analysis, and a detailed report on the current progress is generated as output. This report is sent to the user, notifying them of their progress towards goals and areas for improvement.

[0474] Step 6:

[0475] The server periodically retrieves external regulatory information and data. Using adjustment mechanisms, the server re-evaluates the action plan based on the latest information and automatically adjusts it as needed. For example, when emission standards change due to new regulations, the plan can be reviewed and new measures can be proposed.

[0476] (Application Example 1)

[0477] 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."

[0478] Currently, many organizations and individuals face challenges in setting efficient and effective goals and managing progress when engaging in environmental protection activities. In particular, it is difficult to comprehensively manage and effectively track progress across an entire city. This makes it difficult to accurately evaluate the contribution of organizations and individuals to environmental goals, resulting in a situation where sustainable activities are less likely to be encouraged.

[0479] 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.

[0480] In this invention, the server includes data processing means for inputting organizational goal setting data and generating individual action plans; user interface means for visualizing the action plans and prompting approval or modification; and management means for automatically collecting environmental data in accordance with the approved action plans. This makes it possible to centrally manage environmental protection activities across an organization or city and to clearly grasp the progress of individual activities.

[0481] "Organizational goal-setting data" refers to the specific numerical targets and policies related to environmental protection set by an organization, and is the information that forms the basis of an action plan.

[0482] An "individual action plan" is a specific action plan generated based on the environmental goals of a particular organization or individual, and includes actionable steps and methods for achieving those goals.

[0483] "Data processing means" refers to a device or program for processing input target setting data and generating an action plan based on that data.

[0484] "User interface means" refers to the means by which users can review, modify, and approve action plans, and consists of intuitively operable screens and devices.

[0485] "Management measures" refer to devices or systems for automatically collecting environmental data based on approved action plans.

[0486] "Cutting-edge regulatory information" refers to the latest information on laws and regulations, which serves as a basis for adjusting environmental goals and action plans.

[0487] An "integrated management system" is a mechanism for aggregating data on environmental protection activities of participants across the city and evaluating progress using unified standards.

[0488] This invention provides a dedicated system for organizations and cities to efficiently carry out environmental protection activities. The system consists of servers, terminals, and various types of devices, and each component works in cooperation with others.

[0489] The server receives organizational goal-setting data using cloud-based infrastructure (e.g., Google Cloud, AWS, Microsoft Azure). Based on this data, the server generates individual action plans using generative AI models. These plans include specific means and steps necessary to achieve environmental goals.

[0490] The generated action plan is displayed in the user interface on the device the user is accessing. Through this interface, the user can review, modify, and approve the plan. The approved action plan is then sent back to the server.

[0491] The server automatically collects necessary environmental data from IoT devices and sensors inside and outside the organization through management mechanisms. This allows for real-time monitoring of the progress of environmental protection activities. The collected data is used to evaluate progress using analytical tools.

[0492] Furthermore, the server regularly acquires the latest regulatory information and dynamically adjusts action plans as needed. This allows for flexible responses to environmental changes and regulatory revisions. For example, if new emission standards are established, the corresponding actions can be quickly reflected in the plan.

[0493] As a concrete example, in a certain residential area, residents aim to effectively reduce carbon dioxide emissions, and this system is used to propose specific measures that each household should take. An example of a prompt would be, "Generate a feasible action plan to reduce my household's energy consumption by 10%."

[0494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0495] Step 1:

[0496] The server receives goal-setting data from the organization. This data includes reduction targets and regulatory requirements. Using a generative AI model, the server creates individual action plans based on this input data and stores them in a database.

[0497] Step 2:

[0498] Users access the server through their terminal and view the generated action plan through a user interface. Through this interface, users can modify and approve the plan. As a result of this operation, the modified action plan is sent to the server and updated to the latest state.

[0499] Step 3:

[0500] Based on the approved action plan, the server begins collecting environmental data from IoT devices and sensors. This includes receiving device status information and sending control commands to aggregate it in a central system for analysis.

[0501] Step 4:

[0502] The server processes the collected data using analytical tools. The input data includes usage data and environmental parameters from each device, and analysis generates current status assessments and predictive data. These results are output as a progress report and notified to the administrator.

[0503] Step 5:

[0504] The server regularly retrieves the latest regulatory information and adjusts the action plan accordingly. This process involves querying regulatory information from external databases and analyzing its impact on the plan. If necessary, the server automatically updates the plan and notifies the user of the updates.

[0505] 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.

[0506] This invention aims to enable more effective implementation of action plans in a system that supports environmental protection activities in medium-sized manufacturing companies by incorporating an approach that takes user emotions into consideration. Specifically, it incorporates an emotion engine to recognize the user's emotional state and provide actions accordingly.

[0507] The server first receives goal-setting information provided by the company and uses information processing tools to generate an optimal action plan. This action plan includes environmental goals to be achieved and specific steps to achieve them.

[0508] The generated action plan is presented to the user via the device. The user's emotional state is analyzed by the emotion engine. For example, if the user is feeling stressed or anxious, the emotion engine restructures the action plan in a more understandable way and presents it to the user.

[0509] The server uses control mechanisms to operate IoT devices within the enterprise and collect data based on the action plan modified or approved by the user. Alerts are generated to provide feedback and support regarding project progress in response to changes in the user's emotions.

[0510] Furthermore, the server analyzes the data collected through the analysis tools and monitors the progress. Based on the analysis results, it ensures consistency with the latest regulatory information and makes necessary adjustments.

[0511] For example, if a user feels overwhelmed by the action plan, the emotion engine can detect this and have the server generate suggestions to alleviate the stress. This can improve the user's work experience and increase efficiency in achieving sustainable environmental protection activities.

[0512] The following describes the processing flow.

[0513] Step 1:

[0514] Users use a terminal to input the company's environmental goals and regulatory requirements. This includes specific reduction targets and specific regulatory conditions that must be complied with.

[0515] Step 2:

[0516] Based on the environmental goals and regulatory requirements received from the user, the server uses information processing tools to generate an action plan tailored to the company. This plan includes steps and necessary actions to achieve the goals.

[0517] Step 3:

[0518] The device displays the generated action plan to the user. During this process, the emotion engine recognizes the user's emotions and adjusts how the plan is presented accordingly. For example, if the user is feeling anxious, the server presents a more easily understandable and adjusted plan.

[0519] Step 4:

[0520] After receiving feedback from the emotion engine, users review the action plan, making revisions or approvals as needed. Once revisions are made, they are sent to the server and the plan is finalized.

[0521] Step 5:

[0522] Based on the approved action plan, the server uses control mechanisms to manage IoT devices within the enterprise and begins collecting the necessary data. This data collection proceeds in sync with the plan.

[0523] Step 6:

[0524] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step and used to adjust the plan.

[0525] Step 7:

[0526] The server continuously monitors the user's emotional state and generates alerts that provide appropriate support or improvement suggestions when stress or anxiety is detected. For example, it might suggest reducing the workload of an action plan.

[0527] Step 8:

[0528] Users receive reports and alerts from the server through their devices. Based on this information, they revise their strategies and plans for the future to facilitate the achievement of environmental goals.

[0529] (Example 2)

[0530] 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."

[0531] Traditional corporate environmental protection activities have faced problems such as excessive stress and inefficient plan execution because they fail to consider the emotional state of users when setting goals and implementing action plans. This has led to project delays and decreased motivation.

[0532] 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.

[0533] In this invention, the server includes information acquisition means for receiving corporate goal setting information, information processing means for generating an optimal action plan based on the goal setting information, and emotion recognition means for displaying the action plan to the user and recognizing and analyzing the user's emotional state. This enables flexible adjustment of the action plan based on the user's emotional state.

[0534] "Information acquisition means" refers to a means that has the function of receiving goal-setting information provided by a company.

[0535] "Information processing means" refers to means of processing data to generate an optimal action plan based on the received goal-setting information.

[0536] An "emotion recognition tool" is a tool equipped with the functionality to recognize and analyze a user's emotional state.

[0537] A "user interface means" is a means of presenting a provided action plan to the user and obtaining information through user interaction.

[0538] "Control means" refers to the means of operating equipment within a company and automatically collecting data based on an approved action plan.

[0539] "Analysis means" refers to methods for analyzing collected data and monitoring the progress of a project.

[0540] "Adjustment measures" refer to means for adjusting action plans based on the latest regulatory information.

[0541] Embodiments of this invention provide a system for medium-sized industrial organizations to effectively manage environmental protection activities. This system incorporates an approach that takes into account the emotional state of users in order to achieve the company's environmental goals.

[0542] The server first receives goal-setting information provided by the company using an information acquisition mechanism. This information is securely stored on the organization's server using a database management system (DBMS). Subsequently, an information processing mechanism generates an optimal action plan based on this information, utilizing a generated AI model. In this process, a specific AI algorithm is used to propose the optimal solution based on the input data.

[0543] The generated action plan is displayed to the user via their device. The user interface is intuitively designed, and the plan is presented visually through a web application or dedicated application. Users can easily grasp the tasks involved by viewing a detailed and easy-to-understand plan.

[0544] When a user interacts with a presented action plan, an emotion recognition system analyzes their emotional state. This emotion recognition is performed using natural language processing and emotion analysis algorithms, evaluating the emotional state in real time. If the user feels stressed or overwhelmed by the action plan, the server uses a generative AI model to readjust the plan and reconstruct it in a way that is easier for the user to understand.

[0545] Furthermore, based on the approved action plan, the server uses control mechanisms to send commands to various devices within the company and collect data. This enables real-time monitoring of environmental data and the operating status of devices within the company, utilizing IoT technology.

[0546] The server analyzes the collected data using analytical tools and monitors the progress. This data analysis uses big data analytics techniques to detect specific patterns and anomalies and provides feedback to administrators. Furthermore, based on the analysis results, the adjustment mechanism makes necessary updates to the action plan to ensure consistency with the latest regulatory information.

[0547] As a concrete example, this system can re-present actionable plans to users when they encounter new environmental regulations. By utilizing a generative AI model and inputting new prompts, it can be instructed, for example, "Propose specific steps to comply with the newly implemented regulations." In this way, it is possible to improve the user's work efficiency while promoting environmental protection efforts.

[0548] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0549] Step 1:

[0550] The server receives goal-setting information provided by companies. The input consists of environmental targets based on the company's strategies and policies. The server stores this information in a database and analyzes the target content using data processing tools. The output is data in an easily processable format. This specific operation includes data format conversion and filtering.

[0551] Step 2:

[0552] The server utilizes an AI model generated using information processing tools to produce an optimal action plan based on the input data. The input here is processed target information. The server simulates multiple scenarios through the AI ​​model and obtains an optimized action plan as output. Specifically, this involves integrating past success data and repeatedly running simulations.

[0553] Step 3:

[0554] The terminal receives action plans sent from the server and displays them to the user through the user interface. The input is action plan data from the server. The terminal receives this data, outputs it in a visually understandable format, and presents it to the user. Specific operations include displaying the data in dashboard or list format.

[0555] Step 4:

[0556] The user reviews the action plan displayed on the device, and their emotional state is analyzed by emotion recognition tools. The input consists of data from the user's choices and actions. The server uses this information to perform emotion analysis and obtains the user's emotional state as output. Specific operations include natural language processing and emotion scoring.

[0557] Step 5:

[0558] The server adjusts the action plan based on the user's emotional state. The input here is the analyzed user's emotional data. The server then uses a regenerative AI model to restructure the plan to help the user understand it, and generates the adjusted action plan as output. Specific actions include simplifying the presented content and adding additional explanations.

[0559] Step 6:

[0560] The server operates devices within the enterprise and collects data using control mechanisms based on an approved action plan. The input is the final approved plan. The server uses this to control IoT devices and obtains real-time environmental data as output. Specific operations include issuing device operation commands and receiving data.

[0561] Step 7:

[0562] The server analyzes collected data using analytical tools and monitors project progress. The input is the collected raw data. The server performs data analysis and generates progress reports as output. Specific operations include data trend analysis and anomaly detection.

[0563] Step 8:

[0564] Based on the analysis results obtained, the server references the latest regulatory information and adjusts the action plan as needed. The inputs are the analysis results and regulatory information. The server outputs the adjusted plan and performs necessary optimizations. Specific operations include information matching and plan updates.

[0565] (Application Example 2)

[0566] 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."

[0567] For medium-sized manufacturing companies, the effectiveness of their environmental protection plans directly impacts their sustainability. However, traditional systems often fail to execute plans as intended, or users may experience stress or overburden due to the plans, making flexible adjustments difficult. Therefore, there is a need for a system that can dynamically adjust action plans while considering the emotional state of users.

[0568] 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.

[0569] In this invention, the server includes an information processing means for inputting corporate goal setting information and generating an action plan, an emotion engine for analyzing the user's emotional state, and a suggestion means for adjusting the action plan based on the analyzed emotional state. This enables flexible adjustment of the action plan in accordance with the user's emotions.

[0570] "Corporate goal-setting information" refers to information that describes the specific objectives and targets related to environmental protection and sustainability that a company aims to achieve.

[0571] An "action plan" is a plan that specifically outlines a series of activities and steps necessary to achieve a company's goals.

[0572] "Information processing means" refers to computer programs or systems used to analyze goal-setting information and generate optimal action plans.

[0573] "User interface means" refers to an interface that includes screens and input methods for users to review, approve, and modify action plans.

[0574] An "emotion engine" refers to an algorithm or system that analyzes and understands a user's emotional state based on their text and actions.

[0575] A "proposal tool" is a system for suggesting adjustments or modifications to the optimal action plan based on the analyzed emotional state.

[0576] "Control means" refers to a mechanism or system for automating data collection by operating various devices within a company based on an approved action plan.

[0577] "Analysis tools" refer to programs or systems used to analyze collected data and understand the progress being made.

[0578] "Adjustment measures" refer to systems that have the function of checking the latest regulatory information and adapting action plans accordingly.

[0579] The invention's implementation is described below. First, the server receives goal information set by the company and generates an optimal action plan using information processing means. This process utilizes the Python programming language, and a specific library (e.g., TextBlob) is used for sentiment analysis. The server sends the generated action plan to the terminal through a user interface means, prompting the user to approve or modify it.

[0580] The user reviews the action plan displayed on the device and inputs their emotional state. The emotion engine analyzes this input and generates an emotion score. Based on the results, the suggestion system adjusts the action plan as needed and presents it to the user. Furthermore, it is often implemented using web-related technologies such as JavaScript, and the emotion analysis and suggestions are performed in real time.

[0581] After the server has finished making emotion-based suggestions, it uses control mechanisms based on the approved plan and begins collecting data from various devices within the company. The data is then monitored for progress by analytical mechanisms. Furthermore, coordination mechanisms refer to the latest regulatory information to update the action plan as needed, providing support for sustainable environmental protection activities.

[0582] For example, if a factory manager is experiencing excessive stress due to newly set environmental targets, the emotion engine will detect this emotion and suggest adjustments to the work schedule or the allocation of additional resources through its suggestion system. This can reduce the workload.

[0583] Examples of prompt statements to input into a generative AI model include the following:

[0584] "The user's input text is as follows: Enter the user's text here. Analyze this sentiment and suggest appropriate action."

[0585] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0586] Step 1:

[0587] The server receives corporate goal setting information and generates an action plan using information processing tools. In this process, the server analyzes the input goal information, takes into account the company's resources and challenges, and calculates and outputs an actionable plan.

[0588] Step 2:

[0589] The generated action plan is sent from the server to the terminal and displayed to the user through a user interface. Here, the terminal provides a visually clear interface for displaying the action plan and gives the user the opportunity to approve or modify the plan.

[0590] Step 3:

[0591] The user inputs their emotional state into the device. This input information is sent from the device to the server and analyzed by an emotion engine. As a result, the server generates an emotion score, revealing the user's current psychological state.

[0592] Step 4:

[0593] The suggestion system uses the emotional score to adjust the action plan. The server evaluates the emotional score, modifies the plan's schedule and task priorities to reduce stress, and sends the adjusted plan to the terminal.

[0594] Step 5:

[0595] Once the user approves the adjusted action plan, the server uses control mechanisms to operate devices within the company and automatically begins data collection. At this time, smart sensors and IoT devices are activated and data is transferred based on the user's approval.

[0596] Step 6:

[0597] The collected data is processed by the server's analysis tools, and the project's progress is evaluated. The server aggregates the data and generates output that reports the goal achievement status to the user.

[0598] Step 7:

[0599] Finally, the adjustment mechanism compares the latest regulatory information with the plan and readjusts the action plan as necessary. If the server determines that the plan needs to be modified in accordance with laws and ethical standards, it will notify the user of the changes.

[0600] 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.

[0601] 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.

[0602] 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.

[0603] [Fourth Embodiment]

[0604] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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).

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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".

[0617] This invention is a system for supporting the environmental protection activities of medium-sized manufacturing companies, and specifically provides a means for automatically generating and implementing action plans based on the company's environmental objectives.

[0618] The server receives environmental targets and regulatory requirements entered by corporate users and uses this data to generate customized action plans using information processing tools. Specifically, the generated action plans include the amount of carbon dioxide to be reduced, energy consumption, and waste management methods.

[0619] The generated action plan is displayed to the user on their device, and they can approve or modify it. The user can adjust the plan as needed and finally approve it. The approved plan is returned to the server and proceeds to the next stage.

[0620] The server controls the company's IoT devices via APIs and automates data collection in line with action plans. This includes equipment usage data and data collection from environmental sensors.

[0621] The collected data is analyzed on a server using analytical tools, and the progress of environmental protection activities is monitored. This allows companies to obtain specific information about their level of achievement and areas for improvement.

[0622] The latest environmental regulatory information and external data are regularly retrieved by the server, and the action plan is automatically adjusted as needed. For example, if emission standards are revised due to changes in legal regulations, the plan is flexibly re-evaluated at this stage.

[0623] By utilizing this system, companies can implement environmental protection activities quickly and effectively, and support the realization of sustainable business models.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] Users use a terminal to input the company's environmental goals and existing regulatory requirements. This includes specific reduction targets and detailed information about the regulations that must be complied with.

[0627] Step 2:

[0628] The server receives user input and uses a large-scale language model to generate an action plan tailored to the company. This plan includes specific action steps towards the set environmental objectives and is optimized for that purpose.

[0629] Step 3:

[0630] The device displays the generated action plan to the user. The user reviews the plan, enters any necessary revisions, and then confirms and approves it.

[0631] Step 4:

[0632] The server controls IoT devices within the enterprise via API according to an approved action plan and automatically begins collecting the necessary data. The data from the devices is reliably collected and sent to the server.

[0633] Step 5:

[0634] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step.

[0635] Step 6:

[0636] The server regularly retrieves information on the latest policy changes and new regulations, and adjusts the action plan based on this information. The results of the progress analysis are also taken into consideration in this reassessment.

[0637] Step 7:

[0638] Users receive alerts and reports from the server on their devices. This includes regular reports on plan-based activities and suggestions for improvement. Users utilize this information to review their next goals and strategies.

[0639] (Example 1)

[0640] 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".

[0641] For companies to effectively implement environmental protection activities and achieve sustainable operations, they need to develop concrete action plans based on environmental goals, automate data collection and analysis, and dynamically adjust plans. However, current methods have challenges such as being time-consuming and labor-intensive, lacking immediacy and flexibility, from goal setting to implementation and monitoring.

[0642] 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.

[0643] In this invention, the server includes information processing means for inputting target setting information and generating an action plan using a generation AI model; display means for displaying the action plan and requesting approval or modification; and control means for automatically collecting data in cooperation with target devices within the company based on the approved action plan. This enables companies to quickly formulate concrete and actionable action plans, automatically collect data, and monitor progress in real time. Furthermore, dynamic plan adjustments in response to changes in external data and regulations are realized, promoting the efficiency of environmental protection activities.

[0644] "Target setting information" refers to data that shows numerical or guideline objective values ​​related to the environment that a company aims to achieve.

[0645] A "generative AI model" is an artificial intelligence algorithm that automatically generates efficient action plans based on past data and best practices.

[0646] An "action plan" is a document that lists the specific steps and measures that should be implemented to achieve environmental goals.

[0647] "Information processing means" refers to a computer program or system for analyzing input data and generating a desired output.

[0648] "Display means" refers to screens or devices that users use to review and modify action plans.

[0649] "Control means" refers to a program or device for managing coordination with target devices within a company and for managing data collection.

[0650] "Target devices" refer to internal company hardware and devices related to the collection of environmental data and the implementation of action plans.

[0651] A "coordination mechanism" is a system or program that has the function of re-evaluating action plans based on external regulatory information and data, and making necessary changes.

[0652] This invention is a system designed to support companies' environmental protection activities. The server receives the company's goal setting information and uses a generating AI model to create an action plan aligned with the environmental goals. The server utilizes dedicated environmental management software as an information processing means to design an efficient plan based on the input data. For example, if a goal such as "reduce energy consumption by 15% annually" is set, the server will propose specific measures based on this goal.

[0653] The generated action plan is displayed on the user's device. The device provides a user interface, allowing the user to review the action plan and make modifications or approvals as needed. The user can make specific changes, such as "adjusting the operating time of a particular device."

[0654] Approved action plans are implemented by a control system in which the server interacts with target devices within the enterprise. The server uses APIs to operate the enterprise's IoT devices and automatically collect the necessary data, including equipment usage data and information from environmental sensors.

[0655] Once data collection is complete, the server analyzes the collected data using analytical tools and provides the user with a progress report. This allows the user to understand their progress toward achieving environmental goals and adjust measures as needed. For example, feedback such as "The monthly report shows that carbon dioxide emissions are exceeding the target value" is provided.

[0656] Furthermore, the server periodically acquires external regulatory information and market data, and automatically re-evaluates whether the action plan is relevant to the current situation. If there are changes, it can flexibly adjust the plan based on those changes and provide new instructions to the user. An example of a prompt message might be, "Use AI to generate a plan to improve the company's energy efficiency and monitor its progress."

[0657] This system enables companies to quickly and effectively promote environmental protection activities and realize sustainable business models.

[0658] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0659] Step 1:

[0660] Users input their company's environmental goals and regulatory requirements using a terminal. This input includes specific numerical targets, such as "reduce annual carbon dioxide emissions by 20%." The terminal then transmits this information to a server, providing the foundational data for generating an action plan.

[0661] Step 2:

[0662] The server generates an action plan using an AI model based on the received goal-setting information. The server analyzes the input data using information processing tools, taking into account historical data and industry best practices to create the optimal action plan. The output is a plan containing specific measures.

[0663] Step 3:

[0664] On the terminal, the action plan generated from the server is displayed through the user interface. The user reviews this plan and checks if it matches the company's actual situation. If necessary, they make specific modifications, such as adjusting operating hours or changing target figures, and finally approve the plan.

[0665] Step 4:

[0666] The approved action plan is sent back to the server. The server uses control mechanisms that connect to target devices within the enterprise to initiate the execution of the approved plan. The server interacts with IoT devices via APIs to automatically collect facility operating status and environmental sensor data.

[0667] Step 5:

[0668] The server analyzes the collected data using analytical tools to understand the progress. Equipment usage data and environmental data are used as input for the analysis, and a detailed report on the current progress is generated as output. This report is sent to the user, notifying them of their progress towards goals and areas for improvement.

[0669] Step 6:

[0670] The server periodically retrieves external regulatory information and data. Using adjustment mechanisms, the server re-evaluates the action plan based on the latest information and automatically adjusts it as needed. For example, when emission standards change due to new regulations, the plan can be reviewed and new measures can be proposed.

[0671] (Application Example 1)

[0672] 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".

[0673] Currently, many organizations and individuals face challenges in setting efficient and effective goals and managing progress when engaging in environmental protection activities. In particular, it is difficult to comprehensively manage and effectively track progress across an entire city. This makes it difficult to accurately evaluate the contribution of organizations and individuals to environmental goals, resulting in a situation where sustainable activities are less likely to be encouraged.

[0674] 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.

[0675] In this invention, the server includes data processing means for inputting organizational goal setting data and generating individual action plans; user interface means for visualizing the action plans and prompting approval or modification; and management means for automatically collecting environmental data in accordance with the approved action plans. This makes it possible to centrally manage environmental protection activities across an organization or city and to clearly grasp the progress of individual activities.

[0676] "Organizational goal-setting data" refers to the specific numerical targets and policies related to environmental protection set by an organization, and is the information that forms the basis of an action plan.

[0677] An "individual action plan" is a specific action plan generated based on the environmental goals of a particular organization or individual, and includes actionable steps and methods for achieving those goals.

[0678] "Data processing means" refers to a device or program for processing input target setting data and generating an action plan based on that data.

[0679] "User interface means" refers to the means by which users can review, modify, and approve action plans, and consists of intuitively operable screens and devices.

[0680] "Management measures" refer to devices or systems for automatically collecting environmental data based on approved action plans.

[0681] "Cutting-edge regulatory information" refers to the latest information on laws and regulations, which serves as a basis for adjusting environmental goals and action plans.

[0682] An "integrated management system" is a mechanism for aggregating data on environmental protection activities of participants across the city and evaluating progress using unified standards.

[0683] This invention provides a dedicated system for organizations and cities to efficiently carry out environmental protection activities. The system consists of servers, terminals, and various types of devices, and each component works in cooperation with others.

[0684] The server receives organizational goal-setting data using cloud-based infrastructure (e.g., Google Cloud, AWS, Microsoft Azure). Based on this data, the server generates individual action plans using generative AI models. These plans include specific means and steps necessary to achieve environmental goals.

[0685] The generated action plan is displayed in the user interface on the device the user is accessing. Through this interface, the user can review, modify, and approve the plan. The approved action plan is then sent back to the server.

[0686] The server automatically collects necessary environmental data from IoT devices and sensors inside and outside the organization through management mechanisms. This allows for real-time monitoring of the progress of environmental protection activities. The collected data is used to evaluate progress using analytical tools.

[0687] Furthermore, the server regularly acquires the latest regulatory information and dynamically adjusts action plans as needed. This allows for flexible responses to environmental changes and regulatory revisions. For example, if new emission standards are established, the corresponding actions can be quickly reflected in the plan.

[0688] As a concrete example, in a certain residential area, residents aim to effectively reduce carbon dioxide emissions, and this system is used to propose specific measures that each household should take. An example of a prompt would be, "Generate a feasible action plan to reduce my household's energy consumption by 10%."

[0689] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0690] Step 1:

[0691] The server receives goal-setting data from the organization. This data includes reduction targets and regulatory requirements. Using a generative AI model, the server creates individual action plans based on this input data and stores them in a database.

[0692] Step 2:

[0693] Users access the server through their terminal and view the generated action plan through a user interface. Through this interface, users can modify and approve the plan. As a result of this operation, the modified action plan is sent to the server and updated to the latest state.

[0694] Step 3:

[0695] Based on the approved action plan, the server begins collecting environmental data from IoT devices and sensors. This includes receiving device status information and sending control commands to aggregate it in a central system for analysis.

[0696] Step 4:

[0697] The server processes the collected data using analytical tools. The input data includes usage data and environmental parameters from each device, and analysis generates current status assessments and predictive data. These results are output as a progress report and notified to the administrator.

[0698] Step 5:

[0699] The server regularly retrieves the latest regulatory information and adjusts the action plan accordingly. This process involves querying regulatory information from external databases and analyzing its impact on the plan. If necessary, the server automatically updates the plan and notifies the user of the updates.

[0700] 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.

[0701] This invention aims to enable more effective implementation of action plans in a system that supports environmental protection activities in medium-sized manufacturing companies by incorporating an approach that takes user emotions into consideration. Specifically, it incorporates an emotion engine to recognize the user's emotional state and provide actions accordingly.

[0702] The server first receives goal-setting information provided by the company and uses information processing tools to generate an optimal action plan. This action plan includes environmental goals to be achieved and specific steps to achieve them.

[0703] The generated action plan is presented to the user via the device. The user's emotional state is analyzed by the emotion engine. For example, if the user is feeling stressed or anxious, the emotion engine restructures the action plan in a more understandable way and presents it to the user.

[0704] The server uses control mechanisms to operate IoT devices within the enterprise and collect data based on the action plan modified or approved by the user. Alerts are generated to provide feedback and support regarding project progress in response to changes in the user's emotions.

[0705] Furthermore, the server analyzes the data collected through the analysis tools and monitors the progress. Based on the analysis results, it ensures consistency with the latest regulatory information and makes necessary adjustments.

[0706] For example, if a user feels overwhelmed by the action plan, the emotion engine can detect this and have the server generate suggestions to alleviate the stress. This can improve the user's work experience and increase efficiency in achieving sustainable environmental protection activities.

[0707] The following describes the processing flow.

[0708] Step 1:

[0709] Users use a terminal to input the company's environmental goals and regulatory requirements. This includes specific reduction targets and specific regulatory conditions that must be complied with.

[0710] Step 2:

[0711] Based on the environmental goals and regulatory requirements received from the user, the server uses information processing tools to generate an action plan tailored to the company. This plan includes steps and necessary actions to achieve the goals.

[0712] Step 3:

[0713] The device displays the generated action plan to the user. During this process, the emotion engine recognizes the user's emotions and adjusts how the plan is presented accordingly. For example, if the user is feeling anxious, the server presents a more easily understandable and adjusted plan.

[0714] Step 4:

[0715] After receiving feedback from the emotion engine, users review the action plan, making revisions or approvals as needed. Once revisions are made, they are sent to the server and the plan is finalized.

[0716] Step 5:

[0717] Based on the approved action plan, the server uses control mechanisms to manage IoT devices within the enterprise and begins collecting the necessary data. This data collection proceeds in sync with the plan.

[0718] Step 6:

[0719] The server analyzes the collected data using analytical tools and monitors the progress in real time. The analysis results are fed back into the next step and used to adjust the plan.

[0720] Step 7:

[0721] The server continuously monitors the user's emotional state and generates alerts that provide appropriate support or improvement suggestions when stress or anxiety is detected. For example, it might suggest reducing the workload of an action plan.

[0722] Step 8:

[0723] Users receive reports and alerts from the server through their devices. Based on this information, they revise their strategies and plans for the future to facilitate the achievement of environmental goals.

[0724] (Example 2)

[0725] 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".

[0726] Traditional corporate environmental protection activities have faced problems such as excessive stress and inefficient plan execution because they fail to consider the emotional state of users when setting goals and implementing action plans. This has led to project delays and decreased motivation.

[0727] 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.

[0728] In this invention, the server includes information acquisition means for receiving corporate goal setting information, information processing means for generating an optimal action plan based on the goal setting information, and emotion recognition means for displaying the action plan to the user and recognizing and analyzing the user's emotional state. This enables flexible adjustment of the action plan based on the user's emotional state.

[0729] "Information acquisition means" refers to a means that has the function of receiving goal-setting information provided by a company.

[0730] "Information processing means" refers to means of processing data to generate an optimal action plan based on the received goal-setting information.

[0731] An "emotion recognition tool" is a tool equipped with the functionality to recognize and analyze a user's emotional state.

[0732] A "user interface means" is a means of presenting a provided action plan to the user and obtaining information through user interaction.

[0733] "Control means" refers to the means of operating equipment within a company and automatically collecting data based on an approved action plan.

[0734] "Analysis means" refers to methods for analyzing collected data and monitoring the progress of a project.

[0735] "Adjustment measures" refer to means for adjusting action plans based on the latest regulatory information.

[0736] Embodiments of this invention provide a system for medium-sized industrial organizations to effectively manage environmental protection activities. This system incorporates an approach that takes into account the emotional state of users in order to achieve the company's environmental goals.

[0737] The server first receives goal-setting information provided by the company using an information acquisition mechanism. This information is securely stored on the organization's server using a database management system (DBMS). Subsequently, an information processing mechanism generates an optimal action plan based on this information, utilizing a generated AI model. In this process, a specific AI algorithm is used to propose the optimal solution based on the input data.

[0738] The generated action plan is displayed to the user via their device. The user interface is intuitively designed, and the plan is presented visually through a web application or dedicated application. Users can easily grasp the tasks involved by viewing a detailed and easy-to-understand plan.

[0739] When a user interacts with a presented action plan, an emotion recognition system analyzes their emotional state. This emotion recognition is performed using natural language processing and emotion analysis algorithms, evaluating the emotional state in real time. If the user feels stressed or overwhelmed by the action plan, the server uses a generative AI model to readjust the plan and reconstruct it in a way that is easier for the user to understand.

[0740] Furthermore, based on the approved action plan, the server uses control mechanisms to send commands to various devices within the company and collect data. This enables real-time monitoring of environmental data and the operating status of devices within the company, utilizing IoT technology.

[0741] The server analyzes the collected data using analytical tools and monitors the progress. This data analysis uses big data analytics techniques to detect specific patterns and anomalies and provides feedback to administrators. Furthermore, based on the analysis results, the adjustment mechanism makes necessary updates to the action plan to ensure consistency with the latest regulatory information.

[0742] As a concrete example, this system can re-present actionable plans to users when they encounter new environmental regulations. By utilizing a generative AI model and inputting new prompts, it can be instructed, for example, "Propose specific steps to comply with the newly implemented regulations." In this way, it is possible to improve the user's work efficiency while promoting environmental protection efforts.

[0743] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0744] Step 1:

[0745] The server receives goal-setting information provided by companies. The input consists of environmental targets based on the company's strategies and policies. The server stores this information in a database and analyzes the target content using data processing tools. The output is data in an easily processable format. This specific operation includes data format conversion and filtering.

[0746] Step 2:

[0747] The server utilizes an AI model generated using information processing tools to produce an optimal action plan based on the input data. The input here is processed target information. The server simulates multiple scenarios through the AI ​​model and obtains an optimized action plan as output. Specifically, this involves integrating past success data and repeatedly running simulations.

[0748] Step 3:

[0749] The terminal receives action plans sent from the server and displays them to the user through the user interface. The input is action plan data from the server. The terminal receives this data, outputs it in a visually understandable format, and presents it to the user. Specific operations include displaying the data in dashboard or list format.

[0750] Step 4:

[0751] The user reviews the action plan displayed on the device, and their emotional state is analyzed by emotion recognition tools. The input consists of data from the user's choices and actions. The server uses this information to perform emotion analysis and obtains the user's emotional state as output. Specific operations include natural language processing and emotion scoring.

[0752] Step 5:

[0753] The server adjusts the action plan based on the user's emotional state. The input here is the analyzed user's emotional data. The server then uses a regenerative AI model to restructure the plan to help the user understand it, and generates the adjusted action plan as output. Specific actions include simplifying the presented content and adding additional explanations.

[0754] Step 6:

[0755] The server operates devices within the enterprise and collects data using control mechanisms based on an approved action plan. The input is the final approved plan. The server uses this to control IoT devices and obtains real-time environmental data as output. Specific operations include issuing device operation commands and receiving data.

[0756] Step 7:

[0757] The server analyzes collected data using analytical tools and monitors project progress. The input is the collected raw data. The server performs data analysis and generates progress reports as output. Specific operations include data trend analysis and anomaly detection.

[0758] Step 8:

[0759] Based on the analysis results obtained, the server references the latest regulatory information and adjusts the action plan as needed. The inputs are the analysis results and regulatory information. The server outputs the adjusted plan and performs necessary optimizations. Specific operations include information matching and plan updates.

[0760] (Application Example 2)

[0761] 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".

[0762] For medium-sized manufacturing companies, the effectiveness of their environmental protection plans directly impacts their sustainability. However, traditional systems often fail to execute plans as intended, or users may experience stress or overburden due to the plans, making flexible adjustments difficult. Therefore, there is a need for a system that can dynamically adjust action plans while considering the emotional state of users.

[0763] 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.

[0764] In this invention, the server includes an information processing means for inputting corporate goal setting information and generating an action plan, an emotion engine for analyzing the user's emotional state, and a suggestion means for adjusting the action plan based on the analyzed emotional state. This enables flexible adjustment of the action plan in accordance with the user's emotions.

[0765] "Corporate goal-setting information" refers to information that describes the specific objectives and targets related to environmental protection and sustainability that a company aims to achieve.

[0766] An "action plan" is a plan that specifically outlines a series of activities and steps necessary to achieve a company's goals.

[0767] "Information processing means" refers to computer programs or systems used to analyze goal-setting information and generate optimal action plans.

[0768] "User interface means" refers to an interface that includes screens and input methods for users to review, approve, and modify action plans.

[0769] An "emotion engine" refers to an algorithm or system that analyzes and understands a user's emotional state based on their text and actions.

[0770] A "proposal tool" is a system for suggesting adjustments or modifications to the optimal action plan based on the analyzed emotional state.

[0771] "Control means" refers to a mechanism or system for automating data collection by operating various devices within a company based on an approved action plan.

[0772] "Analysis tools" refer to programs or systems used to analyze collected data and understand the progress being made.

[0773] "Adjustment measures" refer to systems that have the function of checking the latest regulatory information and adapting action plans accordingly.

[0774] The invention's implementation is described below. First, the server receives goal information set by the company and generates an optimal action plan using information processing means. This process utilizes the Python programming language, and a specific library (e.g., TextBlob) is used for sentiment analysis. The server sends the generated action plan to the terminal through a user interface means, prompting the user to approve or modify it.

[0775] The user reviews the action plan displayed on the device and inputs their emotional state. The emotion engine analyzes this input and generates an emotion score. Based on the results, the suggestion system adjusts the action plan as needed and presents it to the user. Furthermore, it is often implemented using web-related technologies such as JavaScript, and the emotion analysis and suggestions are performed in real time.

[0776] After the server has finished making emotion-based suggestions, it uses control mechanisms based on the approved plan and begins collecting data from various devices within the company. The data is then monitored for progress by analytical mechanisms. Furthermore, coordination mechanisms refer to the latest regulatory information to update the action plan as needed, providing support for sustainable environmental protection activities.

[0777] For example, if a factory manager is experiencing excessive stress due to newly set environmental targets, the emotion engine will detect this emotion and suggest adjustments to the work schedule or the allocation of additional resources through its suggestion system. This can reduce the workload.

[0778] Examples of prompt statements to input into a generative AI model include the following:

[0779] "The user's input text is as follows: Enter the user's text here. Analyze this sentiment and suggest appropriate action."

[0780] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0781] Step 1:

[0782] The server receives corporate goal setting information and generates an action plan using information processing tools. In this process, the server analyzes the input goal information, takes into account the company's resources and challenges, and calculates and outputs an actionable plan.

[0783] Step 2:

[0784] The generated action plan is sent from the server to the terminal and displayed to the user through a user interface. Here, the terminal provides a visually clear interface for displaying the action plan and gives the user the opportunity to approve or modify the plan.

[0785] Step 3:

[0786] The user inputs their emotional state into the device. This input information is sent from the device to the server and analyzed by an emotion engine. As a result, the server generates an emotion score, revealing the user's current psychological state.

[0787] Step 4:

[0788] The suggestion system uses the emotional score to adjust the action plan. The server evaluates the emotional score, modifies the plan's schedule and task priorities to reduce stress, and sends the adjusted plan to the terminal.

[0789] Step 5:

[0790] Once the user approves the adjusted action plan, the server uses control mechanisms to operate devices within the company and automatically begins data collection. At this time, smart sensors and IoT devices are activated and data is transferred based on the user's approval.

[0791] Step 6:

[0792] The collected data is processed by the server's analysis tools, and the project's progress is evaluated. The server aggregates the data and generates output that reports the goal achievement status to the user.

[0793] Step 7:

[0794] Finally, the adjustment mechanism compares the latest regulatory information with the plan and readjusts the action plan as necessary. If the server determines that the plan needs to be modified in accordance with laws and ethical standards, it will notify the user of the changes.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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."

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] The following is further disclosed regarding the embodiments described above.

[0817] (Claim 1)

[0818] An information processing device that inputs corporate goal setting information and generates an action plan,

[0819] A user interface means for displaying the aforementioned action plan and requesting approval or modification,

[0820] Based on the approved action plan, a control means for automatically collecting data,

[0821] An analytical means for analyzing collected data and monitoring progress,

[0822] A system that includes adjustment mechanisms to adapt action plans based on the latest regulatory information.

[0823] (Claim 2)

[0824] The system according to claim 1, wherein the user interface means has a function to resend the modified action plan to the server and reapprove it.

[0825] (Claim 3)

[0826] The system according to claim 1, wherein the control means includes a function to start and stop data collection in cooperation with various devices within the company.

[0827] "Example 1"

[0828] (Claim 1)

[0829] An information processing means that takes goal setting information as input and generates an action plan using a generated AI model,

[0830] A display means for displaying the aforementioned action plan and requesting approval or modification,

[0831] Based on the aforementioned approved action plan, a control means is provided to automatically collect data in cooperation with target devices within the company,

[0832] An analytical tool for analyzing collected data and monitoring progress,

[0833] A system that includes adjustment mechanisms for re-evaluating and adjusting action plans based on the latest regulatory information and external data.

[0834] (Claim 2)

[0835] The system according to claim 1, wherein the display means has a function to resend and approve the revised action plan.

[0836] (Claim 3)

[0837] The system according to claim 1, wherein the control means includes a function to start and stop monitoring the use of a target device and collecting data from environmental sensors.

[0838] "Application Example 1"

[0839] (Claim 1)

[0840] A data processing means that inputs organizational goal setting data and generates individual action plans,

[0841] A user interface means for visualizing the aforementioned action plan and prompting approval or modification,

[0842] A management system for automatically collecting environmental data in accordance with the approved action plan,

[0843] An analytical means for interpreting collected data and evaluating the progress of activities,

[0844] A means of coordinating action plans based on the latest regulatory information,

[0845] A system that includes an integrated management mechanism for centrally managing and reporting on the progress of activity data from participants across the entire city.

[0846] (Claim 2)

[0847] The system according to claim 1, wherein the user interface means has a function to send the modified action plan back to the data server and perform re-approval.

[0848] (Claim 3)

[0849] The system according to claim 1, wherein the management means includes a function to start and stop data collection in cooperation with various devices inside and outside the organization.

[0850] "Example 2 of combining an emotion engine"

[0851] (Claim 1)

[0852] Information acquisition methods for receiving corporate goal setting information,

[0853] Information processing means for generating an optimal action plan based on the aforementioned goal setting information,

[0854] The aforementioned action plan is displayed to the user, and an emotion recognition means recognizes and analyzes the emotional state,

[0855] A user interface means for adjusting and re-presenting an action plan based on the aforementioned analysis,

[0856] A control means that automatically collects data based on an approved action plan,

[0857] An analytical means for analyzing collected data and monitoring progress,

[0858] A system that includes adjustment mechanisms to adapt action plans based on the latest regulatory information.

[0859] (Claim 2)

[0860] The system according to claim 1, wherein the user interface means has a function to receive the revised action plan again and re-approve it through reconstruction based on emotion recognition.

[0861] (Claim 3)

[0862] The system according to claim 1, wherein the control means includes a function to start and stop data collection in cooperation with various devices within the organization.

[0863] "Application example 2 when combining with an emotional engine"

[0864] (Claim 1)

[0865] An information processing device that inputs corporate goal setting information and generates an action plan,

[0866] A user interface means for displaying the aforementioned action plan and requesting approval or modification,

[0867] An emotion engine that analyzes the user's emotional state,

[0868] A means for suggesting adjustments to the action plan based on the analyzed emotional state,

[0869] Based on the approved action plan, a control means for automatically collecting data,

[0870] An analytical means for analyzing collected data and monitoring progress,

[0871] A system that includes adjustment mechanisms to adapt action plans based on the latest regulatory information.

[0872] (Claim 2)

[0873] The system according to claim 1, wherein the user interface means has a function to resend the modified action plan to the server and reapprove it.

[0874] (Claim 3)

[0875] The system according to claim 1, wherein the control means includes a function to start and stop data collection in cooperation with various devices within the company. [Explanation of symbols]

[0876] 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. An information processing device that inputs corporate goal setting information and generates an action plan, A user interface means for displaying the aforementioned action plan and requesting approval or modification, Based on the approved action plan, a control means for automatically collecting data, An analytical means for analyzing collected data and monitoring progress, A system that includes adjustment mechanisms to adapt action plans based on the latest regulatory information.

2. The system according to claim 1, wherein the user interface means has a function to resend the modified action plan to the server and re-approve it.

3. The system according to claim 1, wherein the control means includes a function to start and stop data collection in cooperation with various devices within the company.

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