System

Abstract

A system is provided.SOLUTION: A terminal means for collecting vital data of a craftsman, a server means for receiving and storing the vital data transmitted from the terminal means, a generation AI algorithm means for analyzing a work time and a movement time of the craftsman by the server means and generating an optimum schedule, a notification means for transmitting the schedule generated by the server means to the terminal means, and an improvement means for transmitting performance data of the craftsman from the terminal means to the server means and performing re-analysis.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The problem this invention aims to solve is to improve the current situation in the construction industry, where labor shortages and long working hours are the norm due to an aging population and a declining workforce. In particular, there is a need to improve the working environment by streamlining work and travel time while monitoring the health status of craftsmen in real time and providing optimal schedules. It is also important to improve productivity throughout the construction industry by digitizing and automating these labor management processes. [Means for solving the problem]

[0005] The system of the present invention includes the following means.

[0006] The system includes a terminal means for collecting vital data of craftsmen, a server means for receiving and saving the vital data transmitted from the terminal means, a generation AI algorithm means for analyzing the work hours and travel times of the craftsmen in the server means and generating an optimal schedule, a notification means for transmitting the schedule generated by the server means to the terminal means, and an improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing it.

[0007] This makes it possible to optimize the work content of each day while understanding the health status of the workers in real time. Furthermore, by using generative AI, data-driven analysis is performed, leading to improved work efficiency. Furthermore, by generating and notifying improvement plans for the next day based on performance data, the working environment can be improved sustainably.

[0008] A "craftsman" is a worker who works in the construction industry and performs specific tasks and construction work.

[0009] "Vital data" refers to physiological data that indicates the health of the craftsman, such as heart rate, stress level, and sleep quality.

[0010] "Terminal means" refers to devices used to collect and transmit vital data on craftsmen, such as smartphones and wearable devices.

[0011] "Server Means" refers to a computer system that receives, stores, and analyzes data sent from Terminal Means.

[0012] The "generative AI algorithm means" refers to an artificial intelligence algorithm that runs on the server means and analyzes the work hours and travel times of craftsmen to generate an optimal schedule.

[0013] The "notification means" is a function for transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[0014] "Performance data" refers to data such as the status of work completion and the situation at the site that is entered by craftsmen after completing work.

[0015] "Improvement measures" refers to a function that analyzes actual data and generates and notifies the next day's schedule and improvement proposals. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention is a system for optimizing the working environment in the construction industry, and in particular, utilizes a generative AI algorithm to streamline work time and travel time while monitoring the health status of workers in real time. Specific embodiments of the present invention are described below.

[0038] System Overview

[0039] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, and an improvement means for reanalyzing.

[0040] Program processing overview

[0041] 1. Collecting and transmitting vital data

[0042] The terminal means collects vital data of the craftsman and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. The terminal means transmits this data to the server means via a dedicated application.

[0043] 2. Receipt and storage of data

[0044] The server receives the vital data transmitted from the terminal and stores it in a database. The server checks the integrity of the received data and filters out incomplete data and abnormal values.

[0045] 3. Schedule optimization

[0046] The server extracts the latest vital and work data from the database and uses a generating AI algorithm to calculate the optimal schedule, taking into account each worker's free time and travel time. The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition data.

[0047] 4. Schedule distribution and execution

[0048] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[0049] 5. Performance data collection and reanalysis

[0050] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[0051] Specific examples

[0052] Morning work

[0053] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0054] Daytime work

[0055] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[0056] Evening work

[0057] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0058] In this way, the system of the present invention aims to improve work efficiency while taking into account the health status of craftsmen, and achieves sustainable improvements in the working environment.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] In the morning, the user launches the smartphone app and connects it to the wearable device, which then measures vital data (heart rate, stress level, sleep quality) in real time.

[0062] Step 2:

[0063] The device sends the collected vital data in a specific format to the server, which receives the vital data and temporarily stores it in a database.

[0064] Step 3:

[0065] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[0066] Step 4:

[0067] The server extracts the latest vital and operational data from the database, constructs a dataset for analysis, and runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time.

[0068] Step 5:

[0069] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[0070] Step 6:

[0071] The user moves efficiently according to the displayed schedule and begins work. After completing work at each site, the device sends the current status and vital data to the server.

[0072] Step 7:

[0073] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server.

[0074] Step 8:

[0075] The server reanalyzes the performance data and additional vital data to generate the optimal schedule and improvement proposals for the next day. The improvement proposals are then sent to the user's device overnight so that they can be prepared for the next day.

[0076] Step 9:

[0077] The next morning, users receive a new schedule that reflects the proposed improvements and can work efficiently again, resulting in a sustainable improvement in the working environment.

[0078] Example 1

[0079] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0080] In the traditional construction industry, it was difficult to monitor the health of workers in real time, resulting in overwork and health problems. Furthermore, work hours and travel time were not optimized, resulting in a decrease in overall efficiency. Furthermore, there were also problems with incomplete data and outliers affecting the system.

[0081] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0082] In this invention, the server includes terminal means for collecting vital data of craftsmen, server means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the work hours and travel times of the craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing it, allocation means for allocating break times and work times taking into account the health status of the craftsmen based on the optimal schedule calculated by the generation AI algorithm means, and data consistency confirmation means for filtering out incomplete data and outliers. This makes it possible to provide an optimal work schedule while monitoring the health status of the craftsmen in real time, improving the working environment and increasing work efficiency.

[0083] "Terminal means" refers to devices that collect vital data of craftsmen and transmit it to the server. Specifically, this includes smartphones and wearable devices.

[0084] The term "server means" refers to a server system that receives and stores vital data transmitted from the terminal means and further analyzes the data.

[0085] "Generative AI Algorithm Means" refers to the algorithm used by the Server Means to analyze data and generate optimal schedules for each craftsman. The generative algorithm may include machine learning models and optimization techniques.

[0086] "Notification means" refers to a system for sending the generated schedule to the terminal means and notifying the craftsman. This includes push notification functions and messaging services.

[0087] "Improvement measures" refer to the means for reanalyzing the workforce's performance data and generating improvement plans for the next day, thereby continuously improving work efficiency and the health of the workforce.

[0088] The "data consistency checking means" refers to a means for checking the consistency of data received by the server means and filtering out incomplete data and abnormal values, thereby improving the reliability of the system.

[0089] The "allocation method" refers to the method for allocating break times and work hours of craftsmen based on the optimal schedule calculated by the generative AI algorithm. By taking into account the health status of craftsmen, we aim to improve the working environment.

[0090] "Vital data" refers to biometric data such as the worker's heart rate, stress level, and sleep quality, collected using wearable devices and other sensors.

[0091] "Display means" refers to a device for displaying the generated schedule, including the screen of a terminal means and a dedicated monitor.

[0092] The "user interface means" refers to an interface for transmitting performance data entered by a craftsman to the server means. Specifically, it includes a mobile application and a web interface.

[0093] The present invention relates to a system for optimizing the working environment in the construction industry. Specifically, the present invention provides a system that utilizes generative AI algorithms to monitor the health status of workers in real time and efficiently manage their work hours and travel time. Specific embodiments of the present invention are described below.

[0094] System Overview

[0095] The system consists of the following elements:

[0096] Terminal means for collecting vital data of craftsmen

[0097] Server means for receiving and storing vital data transmitted from the terminal means

[0098] A generative AI algorithm that analyzes the work hours and travel times of craftsmen and generates an optimal schedule

[0099] Notification means for transmitting the generated schedule to the terminal means

[0100] Improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it

[0101] Data integrity checks to filter incomplete data and outliers

[0102] A method of allocating break times and work hours that takes into account the health of workers

[0103] Hardware and software used

[0104] Terminal means:

[0105] Smartphone

[0106] Wearable devices (e.g., smartwatches)

[0107] Server means:

[0108] Database server (e.g. AWS RDS, Google Cloud SQL)

[0109] Data receiving server (e.g. Nginx, Apache)

[0110] Generative AI algorithm means:

[0111] Machine learning frameworks (e.g. TensorFlow, PyTorch)

[0112] Data analysis tools (e.g., Pandas, NumPy)

[0113] Means of notification:

[0114] Push notification service (e.g., Firebase Cloud Messaging)

[0115] Improvement measures:

[0116] Data reanalysis tools (e.g., Scikit-learn)

[0117] Data integrity verification methods:

[0118] Data cleaning tools (e.g., Python data manipulation libraries)

[0119] Placement means:

[0120] Scheduling algorithms (e.g., Google OR-Tools)

[0121] Example

[0122] Morning work

[0123] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0124] Daytime work

[0125] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[0126] Evening work

[0127] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0128] Example prompts for generative AI models

[0129] "Generate a schedule that optimally allocates break times and work times based on the worker's vital data and work data. The data includes: heart rate, stress level, sleep quality, and work performance data. Please propose the optimal schedule taking each data point into consideration."

[0130] By inputting this prompt into a generative AI model, the model can propose an efficient schedule. In this way, the system of the present invention aims to improve work efficiency while taking into account the health of the craftsmen, thereby achieving a sustainable improvement in the working environment.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1: Collect and transmit vital data

[0133] Specific behavior:

[0134] A user wakes up in the morning and turns on their smartphone and wearable device, which measures vital data such as heart rate, stress level, and sleep quality in real time.

[0135] input:

[0136] Heart rate, stress levels, and sleep quality data from wearable devices.

[0137] Data processing and calculation:

[0138] The device collects this vital data, formats it (e.g., in JSON format) through a dedicated application, and sends it to a server.

[0139] output:

[0140] A request to the server containing vital data.

[0141] Step 2: Receiving and storing data

[0142] Specific behavior:

[0143] The server receives vital data sent from the device as an HTTP request, checks the integrity of the received data, and filters out incomplete data and abnormal values.

[0144] input:

[0145] Vital data sent from the device (JSON format).

[0146] Data processing and calculation:

[0147] Run a script to check the integrity of the incoming data and filter out any outliers or incomplete data (e.g., if the heart rate shows an obviously abnormal value).

[0148] output:

[0149] Vital data whose integrity has been confirmed is stored in a database.

[0150] Step 3: Optimize your schedule

[0151] Specific behavior:

[0152] The server extracts the latest vital and operational data from the database, and uses a generative AI algorithm to calculate the optimal schedule for each worker.

[0153] input:

[0154] Latest vital and operational data from the database.

[0155] Data processing and calculation:

[0156] The extracted data is input into a generative AI algorithm, which then allocates appropriate break times and work hours based on the worker's physical condition data. Specifically, modeling is done using TensorFlow and PyTorch, and input is done using prompt statements. Rules such as "allocate longer breaks to workers with unstable heart rates" are applied.

[0157] output:

[0158] Optimized schedule.

[0159] Step 4: Schedule distribution and execution

[0160] Specific behavior:

[0161] The server sends the generated schedule to the terminal. The user checks the received schedule on the terminal and starts moving and working according to the instructions.

[0162] input:

[0163] Generated schedule.

[0164] Data processing and calculation:

[0165] The generated schedule is converted into an appropriate notification format and sent to the device using a push notification service such as Firebase Cloud Messaging.

[0166] output:

[0167] Schedule displayed in device notifications.

[0168] Step 5: Collect performance data and reanalyze

[0169] Specific behavior:

[0170] After completing a task, the user inputs performance data through a dedicated application, and the terminal sends this data to the server, which receives the performance data and stores it in a database.

[0171] input:

[0172] Work performance data entered by craftsmen.

[0173] Data processing and calculation:

[0174] The received performance data is analyzed and re-analyzed to generate schedule improvement proposals for the next day. Specifically, the data is re-analyzed using tools such as Scikit-learn to gain new insights.

[0175] output:

[0176] The schedule is updated based on the proposed improvements. Based on this data, the updated schedule is notified to the user the next morning.

[0177] (Application example 1)

[0178] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0179] By monitoring the health status of employees in real time and providing appropriate work instructions, it is necessary to improve work efficiency in factories and optimize employee health management and workload. With conventional systems, it was difficult to provide work instructions while adequately monitoring the health status of employees, resulting in health problems and reduced work efficiency.

[0180] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0181] In this invention, the server includes terminal means for collecting vital data, means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the vital data and working hours by the server means to generate an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means and notifying the same, robot means for providing appropriate work instructions based on the employee's vital data, notification means for the robot means to provide the employee with work instructions in real time, and improvement means for transmitting employee performance data from the terminal means to the server means, reanalyzing the data, and generating improvement proposals. This enables efficient work instructions and schedule management that takes employee health conditions into consideration.

[0182] "Terminal means" refers to a device or equipment that collects employee vital data and transmits it to a server.

[0183] "Server Means" refers to a server that receives and stores vital data transmitted from Terminal Means, and analyzes and processes the data based on the data.

[0184] The "generative AI algorithm means" is an artificial intelligence algorithm that analyzes vital data and working hours to generate an optimal schedule.

[0185] The "notification means" is a device or software that has the function of transmitting schedules and work instructions generated by the server means to the terminal means or robot means and notifying them.

[0186] "Robotic means" refers to an autonomous or remotely controlled robot that provides appropriate work instructions based on an employee's vital data.

[0187] The "improvement means" refers to a method or device for transmitting employee performance data from the terminal means to the server means, and for reanalyzing and generating improvement proposals based on that data.

[0188] "Vital data" refers to physiological data that indicates an employee's health status, such as heart rate, stress level, and body temperature.

[0189] A "generated schedule" is an optimal work plan for each employee created based on data analyzed by a generative AI algorithm.

[0190] "Performance data" refers to data that records the history and results of work performed by employees.

[0191] This invention is a system that monitors the health status of employees in a factory in real time and provides optimal work instructions. The system is composed of a terminal means for collecting vital data, a server means for receiving and storing the data, a generating AI algorithm means, a notification means, a robot means, and an improvement means. Specific embodiments are described below.

[0192] Hardware Configuration

[0193] 1. Use wearable devices (e.g., smart watches or smart bands) worn by employees as terminals. These wearable devices collect vital data such as heart rate, stress level, and body temperature and send it to a server.

[0194] 2. Prepare a high-performance server and use a database system (e.g., MySQL, PostgreSQL) to store the collected vital data. Install appropriate software (e.g., Python, TensorFlow) to analyze the data.

[0195] 3. As software for the generative AI algorithm, a generative AI model will be developed using Python and TensorFlow, which will analyze vital data and business data to generate an optimal schedule.

[0196] 4. As a notification means, the server has the function of sending the generated schedule and work instructions to the terminal means and robot means, using a communication protocol (e.g., HTTP, MQTT).

[0197] 5. Robotic means include autonomous or remotely controlled robots in factories that provide appropriate work instructions in real time based on employees' vital signs.

[0198] 6. As an improvement measure, the performance data recorded by the employee is sent from the terminal means to the server means, and the server analyzes the data again and generates an improvement plan for the next day.

[0199] Software Configuration

[0200] The server uses Python and TensorFlow to build a generative AI model and calculate a health score. As an example, we use the following prompt:

[0201] Prompt Sentence Examples

[0202] Employee Health:

[0203] Heart rate: 75 BPM

[0204] Stress level: 0.4

[0205] Body temperature: 36.7°C

[0206] Steps: 500

[0207] Use this data to assess your employees' current health scores and generate their next work orders.

[0208] The server analyzes the collected vital data in real time and evaluates the employee's health status. The generative AI model calculates a health score based on this data and generates an optimal work schedule. The generated schedule and work instructions are sent to the terminal means and robot means via notification means. In addition, performance data recorded by employees is sent to the server and used for reanalysis as a means of improvement.

[0209] In this way, the system of the present invention provides efficient work instructions while monitoring the health status of employees, thereby improving work efficiency within the factory and employee health management.

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] Collection of vital data

[0213] The wearable device, which serves as a terminal means, collects vital data such as the heart rate, stress level, and body temperature of the employee who is the user.

[0214] Input: Keiryochi's vital data (heart rate, stress level, body temperature)

[0215] Output: Collected vital data

[0216] Step 2:

[0217] Sending vital data

[0218] The terminal device sends the collected vital data to the server using HTTP or MQTT as the communication protocol.

[0219] Input: Collected vital data

[0220] Output: Vital data received on the server side

[0221] Step 3:

[0222] Receiving and storing vital data and business data

[0223] The server means receives the vital data sent from the terminal means and stores it in a database, such as MySQL or PostgreSQL, using SQL statements.

[0224] Input: Vital data received from the terminal means

[0225] Output: Vital data stored in a database

[0226] Step 4:

[0227] Data analysis and health score calculation

[0228] The server analyzes the vital data acquired by the AI ​​algorithm and calculates a health score for each employee. The AI ​​model uses TensorFlow and is processed using a Python script. The health score is expressed in a range from 0 to 1.

[0229] Input: Vital data stored in the database

[0230] Output: Calculated health score

[0231] Step 5:

[0232] Schedule optimization

[0233] The server generates an optimal schedule for each employee using the health score calculated by the generative AI algorithm, which is implemented in Python and adjusts work priorities and break times based on the employee's health status.

[0234] Input: Calculated Health Score

[0235] Output: The generated optimal schedule

[0236] Step 6:

[0237] Schedule and work order notifications

[0238] The server unit transmits the generated schedule and work instructions to the terminal unit and the robot unit, and notifies the employee of the schedule and work instructions. Notification methods include display on a wearable device and voice notification from the robot.

[0239] Input: Generated optimal schedule and work instructions

[0240] Output: Schedules and work instructions sent to terminal and robotic means

[0241] Step 7:

[0242] Collection of work performance data

[0243] After the user has completed the work, he or she inputs performance data through the terminal means, which includes the work content, completion time, and the like.

[0244] Input: Actual data after work is completed

[0245] Output: Actual data entered into the terminal means

[0246] Step 8:

[0247] Sending and storing performance data

[0248] The terminal means transmits the input work performance data to the server means, which then stores it in a database.

[0249] Input: Actual data sent from the terminal means

[0250] Output: Actual data stored in the database

[0251] Step 9:

[0252] Reanalysis and generation of improvement proposals

[0253] The server performs re-analysis based on the saved performance data and generates improvement proposals for the next day. The AI ​​model is used again for the re-analysis and generation of improvement proposals.

[0254] Input: Actual data stored in the database

[0255] Output: Generated improvement suggestions

[0256] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0257] The present invention is a system for optimizing the working environment in the construction industry, and utilizes a generative AI algorithm to improve the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[0258] System Overview

[0259] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, an improvement means, and an emotion engine for recognizing the user's emotions.

[0260] Program processing overview

[0261] 1. Collecting vital and emotional data

[0262] The terminal means collects the worker's vital data and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. In addition, the emotion engine analyzes the worker's facial expressions and tone of voice to collect emotional data. This data is transmitted from the terminal means to the server means.

[0263] 2. Receipt and storage of data

[0264] The server receives the vital data and emotion data sent from the terminal and stores the data in a database. The server checks the consistency of the received data and filters out incomplete data and abnormal values.

[0265] 3. Schedule optimization

[0266] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generating AI algorithm to calculate the optimal schedule that takes into account each worker's free time and travel time.The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition and emotional data.

[0267] 4. Schedule distribution and execution

[0268] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[0269] 5. Performance data collection and reanalysis

[0270] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[0271] Specific examples

[0272] Morning work

[0273] The user activates the smartphone and wearable device to collect vital data. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to collect emotional data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0274] Daytime work

[0275] The user starts work at each site, and the terminal device monitors the vital data and emotional data of the craftsman. The server device receives the data in real time and readjusts the schedule as necessary.

[0276] Evening work

[0277] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data and emotion data to propose improvements for the next day and notifies the user overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0278] Through this detailed program processing, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[0279] The processing flow will be explained below.

[0280] Step 1:

[0281] In the morning, the user launches the smartphone app and connects it to the wearable device. The smartphone then measures vital data (heart rate, stress level, sleep quality) in real time through the wearable device. The emotion engine also analyzes the user's facial expressions and tone of voice to collect emotional data.

[0282] Step 2:

[0283] The device sends the collected vital data and emotional data in a specific format to a server, which receives the vital data and emotional data sent from the device and temporarily stores them in a database.

[0284] Step 3:

[0285] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[0286] Step 4:

[0287] The server extracts the latest vital signs, emotional data, and work data from the database and builds a dataset for analysis. It then runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time. The generative AI also uses the workers' physical condition and emotional data to appropriately allocate break times and work hours.

[0288] Step 5:

[0289] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[0290] Step 6:

[0291] The user moves efficiently according to the displayed schedule and begins work. While working at each site, the device continues to monitor vital and emotional data and transmits this data to the server in real time.

[0292] Step 7:

[0293] The server receives real-time vital and emotional data and adjusts the schedule as needed. For example, if a worker is tired, the AI ​​will insert appropriate breaks.

[0294] Step 8:

[0295] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server. The emotion engine also detects the user's emotional state for that day and collects the data.

[0296] Step 9:

[0297] The server reanalyzes the performance data, vital data, and emotional data to generate an optimal schedule and improvement proposals for the next day. The improvement proposals include schedule adjustments that reduce psychological fatigue based on the user's emotional state.

[0298] Step 10:

[0299] The server notifies the user's device of the improvement proposals and schedules it generated overnight. The next morning, the user receives a new schedule that reflects the improvement proposals, allowing them to work efficiently again.

[0300] Through the detailed program processing described above, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[0301] Example 2

[0302] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0303] There is a need to improve the working environment by understanding the health and emotional state of workers in real time and optimizing work and travel time based on that information. However, previous systems did not optimize schedules by fully considering the health and emotional state of workers, making it difficult to carry out work efficiently.

[0304] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI model means for analyzing the vital data and emotional data of craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it. This makes it possible to optimize schedules based on the health and emotional states of craftsmen, thereby realizing continuous improvement of the working environment.

[0305] "Terminal means" refers to a device for collecting vital data and emotional data of craftsmen and transmitting them to a server.

[0306] "Server means" refers to a computer system for receiving, storing, and analyzing vital data and emotional data transmitted from terminal means.

[0307] "Generative AI model means" refers to an artificial intelligence algorithm for generating an optimal schedule for each craftsman based on data collected by the server means.

[0308] The "notification means" refers to a mechanism for transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[0309] "Improvement means" refers to a mechanism for transmitting the craftsman's performance data from the terminal means to the server means and for reanalysis.

[0310] "Vital data" refers to various indicators that show the health status of craftsmen, such as their heart rate, stress level, and sleep quality.

[0311] "Emotional data" refers to data that indicates the emotional state of the craftsman, such as facial expression analysis and tone of voice analysis data of the craftsman.

[0312] "Schedule" refers to a plan to optimize the work and travel time of craftsmen.

[0313] "Performance data" refers to data that records the actual work content and time performed by craftsmen.

[0314] The present invention is a system for improving the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[0315] System Overview

[0316] This system consists of a terminal means for collecting vital data and emotional data of craftsmen, a server means for receiving and storing vital data and emotional data, an algorithm means for calculating the optimal schedule using a generative AI model, a notification means, and an improvement means.

[0317] Hardware and software used

[0318] Hardware

[0319] Smartphones (e.g., general smartphone devices)

[0320] Wearable devices (e.g., common fitness trackers)

[0321] software

[0322] Vital data collection apps (e.g., health management applications)

[0323] Emotion engines (e.g., facial expression analysis software)

[0324] Databases (e.g., common relational database systems)

[0325] Program processing overview

[0326] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data. The collected data is sent from the terminal to the server. Data is collected with the prompt, "Please measure your heart rate."

[0327] The server receives and stores the vital data and emotion data sent from the device. After checking the integrity of the received data and filtering out incomplete data and outliers, the server stores the data in a database. The server executes data saving with the prompt "Please save the data."

[0328] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate an optimal schedule that takes into account each worker's free time and travel time. The generative AI model appropriately allocates break times and work hours based on the worker's physical condition and emotional data. Schedule generation begins with the prompt, "Please generate the optimal schedule."

[0329] The server sends the generated schedule to the terminal and notifies the user. The user checks the schedule for the day through the terminal and moves and works efficiently according to the instructions. The schedule is confirmed with the prompt "Please check today's schedule."

[0330] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotional data to propose improvements for the next day and notifies them overnight. Data input is performed with the prompt "Please enter performance data."

[0331] Through this detailed program processing, the system of the present invention can improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[0332] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0333] Step 1:

[0334] Collection of vital and emotional data

[0335] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data.

[0336] Input: Physical metrics (heart rate, stress level, sleep quality) and audio and facial expression data.

[0337] Output: The acquired vital and emotional data.

[0338] How it works: When a worker arrives at a job site, their heart rate and stress level are automatically measured using a smartphone and wearable device, while an emotion engine analyzes their voice and facial expressions in real time.

[0339] Step 2:

[0340] Receiving and storing data

[0341] The server receives the vital and emotional data sent from the device and stores them in a database. The server checks the integrity of the received data and filters out incomplete data and outliers.

[0342] Input: Vital and emotional data sent from the device.

[0343] Output: The filtered database entries.

[0344] Specific operation: The server receives data in real time, removes data that falls outside the range of abnormal values, and then stores the data in a database in a standard format.

[0345] Step 3:

[0346] Data analysis and schedule optimization

[0347] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate the optimal schedule that takes into account each worker's free time and travel time.

[0348] Input: Latest vital, emotional and operational data extracted from the database.

[0349] Output: The optimized schedule.

[0350] How it works: The server inputs data into the generative AI model, and the AI ​​algorithm analyzes each worker's physical condition and work data, resulting in the creation of an optimal work schedule.

[0351] Step 4:

[0352] Schedule distribution and execution

[0353] The server sends the generated schedule to the terminal and notifies the user. The user can check the schedule for the day through the terminal and move and work efficiently according to the instructions.

[0354] Input: The generated schedule.

[0355] Output: User notification and confirmed schedule.

[0356] Specific operation: The server sends the generated schedule to the terminal via WiFi, and a notification is displayed on the craftsman's smartphone. The craftsman checks the schedule on his smartphone and proceeds to the site.

[0357] Step 5:

[0358] Collection and reanalysis of performance data

[0359] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotion data to propose improvements for the next day and notifies the user overnight.

[0360] Input: Work performance data and additional vital and emotional data submitted by the user.

[0361] Output: Improvement proposals and new schedule for the next day.

[0362] How it works: When a worker finishes a task, he or she enters the results data into a smartphone app. The server receives and analyzes this data, generates a new schedule, and notifies the worker overnight.

[0363] This is the flow of the system's program processing, which allows for efficient and sustainable optimization of work schedules while taking into account the health and emotional state of the workers.

[0364] (Application example 2)

[0365] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0366] This invention is a system that efficiently manages work hours and travel time while monitoring the health and emotional state of craftsmen in real time in order to optimize the work environment of craftsmen. Conventional labor management systems are limited to collecting vital data and do not support schedule optimization that takes into account the emotional state of craftsmen. This makes it difficult to reduce stress and improve productivity for craftsmen.

[0367] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI algorithm means for generating an optimal schedule including the craftsmen's work hours and travel times in the server means, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for collecting craftsmen's performance data and transmitting it to the server means for reanalysis. This makes it possible to optimize the working environment taking into account the craftsmen's health and emotional state.

[0368] A "craftsman" is a skilled worker who performs work in a factory or on a construction site.

[0369] "Vital data" refers to data that indicates the physiological state of the craftsman, such as heart rate, stress level, and sleep quality.

[0370] "Emotional data" is data used to measure the emotional state of a craftsman, such as facial expressions and tone of voice.

[0371] "Terminal means" refers to equipment that collects vital data and emotional data and transmits them to a server, and includes smartphones and wearable devices.

[0372] The "server means" is a system that receives, stores, and analyzes data sent from the terminal means.

[0373] The "generative AI algorithm means" is an algorithm that generates an optimal schedule, including the work hours and travel times of craftsmen, based on the collected data.

[0374] The "notification means" is a system having a function of transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[0375] The "improvement means" is a method or device for transmitting the performance data entered by the craftsman to the server means and for reanalyzing the data.

[0376] The "display means" is a device for visually presenting the generated schedule to the craftsman, and includes a display or monitor.

[0377] The "user interface means" is an operation interface through which a craftsman inputs performance data and transmits it to the server means.

[0378] The present invention is a system for collecting vital data and emotional data of craftsmen and optimizing their work time and travel time. The system includes the following main components:

[0379] System configuration

[0380] 1. Terminal means

[0381] Smartphones and wearable devices are used to collect vital data such as heart rate, stress levels, and sleep quality.

[0382] Emotional data such as the craftsman's facial expressions and tone of voice is collected through cameras and microphones.

[0383] 2. Server Means

[0384] Store data in AWS DynamoDB (cloud database).

[0385] Receive and store vital data and emotional data for each craftsman.

[0386] 3. Generative AI Algorithm Means

[0387] Based on the collected data, a generative AI algorithm is run to generate a schedule that includes optimal working hours and travel times for each worker.

[0388] 4. Means of notification

[0389] The optimized schedule is transmitted to the terminal means and notified to the craftsman.

[0390] 5. Improvement measures

[0391] The performance data input by the craftsman is sent to the server means and reanalyzed.

[0392] Program processing

[0393] Hardware and Software

[0394] Hardware: Wearable devices (heart rate monitors, stress sensors), cameras, microphones, factory robots

[0395] Software: Python, AWS DynamoDB (database), Emotion Engine (virtual emotion engine), VitalDataCollector (virtual data collection module)

[0396] Data collection and transmission

[0397] The terminal means collects vital data using a wearable device and analyzes and collects emotional data using the Emotion Engine. This data is sent from the terminal means to AWS DynamoDB and stored.

[0398] Schedule optimization

[0399] The server uses a generative AI algorithm to generate an optimal work schedule for each worker based on the received vital and emotional data. For example, if a worker's stress level is high or their emotional state is unstable, it will adjust the schedule by increasing their break time.

[0400] Schedule execution and notifications

[0401] The generated schedule is sent to the craftsman through the notification means, and the craftsman uses the terminal means to proceed with the work according to the schedule.

[0402] Performance data collection and reanalysis

[0403] After completing the work, the craftsman inputs the performance data using the terminal means and transmits it to the server means, which then analyzes the collected data to optimize the next schedule.

[0404] Examples and prompts

[0405] In the morning, craftsmen turn on their smartphones and wearable devices to collect vital data such as heart rate and stress level. At the same time, cameras and microphones are used to analyze facial expressions and tone of voice, collecting emotional data. This data is sent to a cloud server, which generates an optimal schedule. For example, a craftsman with a high heart rate and high stress level could be assigned lighter work in the morning and scheduled for longer breaks in the afternoon.

[0406] Prompt Sentence Examples

[0407] An assistant system that optimizes robot activity and worker health in factories. It uses wearable devices and an emotion recognition engine to collect health and emotion data, which is then sent to a cloud server to provide optimal work schedules.

[0408] Key functions: health and emotional data collection, data transmission and storage, schedule optimization, schedule notification and execution.

[0409] The introduction of this system will enable the optimization of the working environment, taking into account the health and emotional state of the workers.

[0410] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0411] Step 1:

[0412] The terminal means collects vital data and emotional data of the craftsman. Heart rate, stress level, and sleep quality are obtained from the wearable device, and facial expressions and tone of voice are analyzed via a camera and microphone. Input data includes heart rate, stress level, sleep quality, facial expressions, and tone of voice. This data is temporarily stored in the internal memory of the terminal means.

[0413] Step 2:

[0414] The terminal means sends the collected data to the server means. The inputs include vital data and emotion data obtained from the wearable device and emotion engine. The server means receives this data and stores it in AWS DynamoDB. It checks the data for consistency and filters out incomplete data and outliers.

[0415] Step 3:

[0416] The server executes the generation AI algorithm and generates an optimal work schedule based on the stored vital data and emotional data. The received vital data and emotional data are input. The generation AI algorithm analyzes this data and calculates the optimal schedule for each worker. The generated work schedule is obtained as output.

[0417] Step 4:

[0418] The server means transmits the generated schedule to the terminal means. The generated work schedule is input. The schedule is notified to the worker using the notification means and displayed on the terminal means. The worker checks the notified schedule and proceeds with the work.

[0419] Step 5:

[0420] After the process is completed, the user inputs the performance data using the terminal means. The input includes performance data for each task (start and end times of the task, actual travel time, etc.). The terminal means transmits this data to the server means.

[0421] Step 6:

[0422] Based on the performance data received by the server means, an analysis is performed for the next schedule optimization. The performance data sent after the work is completed is used as input. This allows for new schedule optimization that takes into account the health and emotional state of the craftsmen. An updated schedule optimization proposal is obtained as output.

[0423] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0424] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0425] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0426] [Second embodiment]

[0427] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0428] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0429] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0430] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0431] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0432] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0433] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0434] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0435] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0436] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0437] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0438] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0439] The present invention is a system for optimizing the working environment in the construction industry, and in particular, utilizes a generative AI algorithm to streamline work time and travel time while monitoring the health status of workers in real time. Specific embodiments of the present invention are described below.

[0440] System Overview

[0441] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, and an improvement means for reanalyzing.

[0442] Program processing overview

[0443] 1. Collecting and transmitting vital data

[0444] The terminal means collects vital data of the craftsman and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. The terminal means transmits this data to the server means via a dedicated application.

[0445] 2. Receipt and storage of data

[0446] The server receives the vital data transmitted from the terminal and stores it in a database. The server checks the integrity of the received data and filters out incomplete data and abnormal values.

[0447] 3. Schedule optimization

[0448] The server extracts the latest vital and work data from the database and uses a generating AI algorithm to calculate the optimal schedule, taking into account each worker's free time and travel time. The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition data.

[0449] 4. Schedule distribution and execution

[0450] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[0451] 5. Performance data collection and reanalysis

[0452] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[0453] Specific examples

[0454] Morning work

[0455] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0456] Daytime work

[0457] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[0458] Evening work

[0459] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0460] In this way, the system of the present invention aims to improve work efficiency while taking into account the health status of craftsmen, and achieves sustainable improvements in the working environment.

[0461] The processing flow will be explained below.

[0462] Step 1:

[0463] In the morning, the user launches the smartphone app and connects it to the wearable device, which then measures vital data (heart rate, stress level, sleep quality) in real time.

[0464] Step 2:

[0465] The device sends the collected vital data in a specific format to the server, which receives the vital data and temporarily stores it in a database.

[0466] Step 3:

[0467] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[0468] Step 4:

[0469] The server extracts the latest vital and operational data from the database, constructs a dataset for analysis, and runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time.

[0470] Step 5:

[0471] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[0472] Step 6:

[0473] The user moves efficiently according to the displayed schedule and begins work. After completing work at each site, the device sends the current status and vital data to the server.

[0474] Step 7:

[0475] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server.

[0476] Step 8:

[0477] The server reanalyzes the performance data and additional vital data to generate the optimal schedule and improvement proposals for the next day. The improvement proposals are then sent to the user's device overnight so that they can be prepared for the next day.

[0478] Step 9:

[0479] The next morning, users receive a new schedule that reflects the proposed improvements and can work efficiently again, resulting in a sustainable improvement in the working environment.

[0480] Example 1

[0481] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0482] In the traditional construction industry, it was difficult to monitor the health of workers in real time, resulting in overwork and health problems. Furthermore, work hours and travel time were not optimized, resulting in a decrease in overall efficiency. Furthermore, there were also problems with incomplete data and outliers affecting the system.

[0483] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0484] In this invention, the server includes terminal means for collecting vital data of craftsmen, server means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the work hours and travel times of the craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing it, allocation means for allocating break times and work times taking into account the health status of the craftsmen based on the optimal schedule calculated by the generation AI algorithm means, and data consistency confirmation means for filtering out incomplete data and outliers. This makes it possible to provide an optimal work schedule while monitoring the health status of the craftsmen in real time, improving the working environment and increasing work efficiency.

[0485] "Terminal means" refers to devices that collect vital data of craftsmen and transmit it to the server. Specifically, this includes smartphones and wearable devices.

[0486] The term "server means" refers to a server system that receives and stores vital data transmitted from the terminal means and further analyzes the data.

[0487] "Generative AI Algorithm Means" refers to the algorithm used by the Server Means to analyze data and generate optimal schedules for each craftsman. The generative algorithm may include machine learning models and optimization techniques.

[0488] "Notification means" refers to a system for sending the generated schedule to the terminal means and notifying the craftsman. This includes push notification functions and messaging services.

[0489] "Improvement measures" refer to the means for reanalyzing the workforce's performance data and generating improvement plans for the next day, thereby continuously improving work efficiency and the health of the workforce.

[0490] The "data consistency checking means" refers to a means for checking the consistency of data received by the server means and filtering out incomplete data and abnormal values, thereby improving the reliability of the system.

[0491] The "allocation method" refers to the method for allocating break times and work hours of craftsmen based on the optimal schedule calculated by the generative AI algorithm. By taking into account the health status of craftsmen, we aim to improve the working environment.

[0492] "Vital data" refers to biometric data such as the worker's heart rate, stress level, and sleep quality, collected using wearable devices and other sensors.

[0493] "Display means" refers to a device for displaying the generated schedule, including the screen of a terminal means and a dedicated monitor.

[0494] The "user interface means" refers to an interface for transmitting performance data entered by a craftsman to the server means. Specifically, it includes a mobile application and a web interface.

[0495] The present invention relates to a system for optimizing the working environment in the construction industry. Specifically, the present invention provides a system that utilizes generative AI algorithms to monitor the health status of workers in real time and efficiently manage their work hours and travel time. Specific embodiments of the present invention are described below.

[0496] System Overview

[0497] The system consists of the following elements:

[0498] Terminal means for collecting vital data of craftsmen

[0499] Server means for receiving and storing vital data transmitted from the terminal means

[0500] A generative AI algorithm that analyzes the work hours and travel times of craftsmen and generates an optimal schedule

[0501] Notification means for transmitting the generated schedule to the terminal means

[0502] Improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it

[0503] Data integrity checks to filter incomplete data and outliers

[0504] A method of allocating break times and work hours that takes into account the health of workers

[0505] Hardware and software used

[0506] Terminal means:

[0507] Smartphone

[0508] Wearable devices (e.g., smartwatches)

[0509] Server means:

[0510] Database server (e.g. AWS RDS, Google Cloud SQL)

[0511] Data receiving server (e.g. Nginx, Apache)

[0512] Generative AI algorithm means:

[0513] Machine learning frameworks (e.g. TensorFlow, PyTorch)

[0514] Data analysis tools (e.g., Pandas, NumPy)

[0515] Means of notification:

[0516] Push notification service (e.g., Firebase Cloud Messaging)

[0517] Improvement measures:

[0518] Data reanalysis tools (e.g., Scikit-learn)

[0519] Data integrity verification methods:

[0520] Data cleaning tools (e.g., Python data manipulation libraries)

[0521] Placement means:

[0522] Scheduling algorithms (e.g., Google OR-Tools)

[0523] Example

[0524] Morning work

[0525] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0526] Daytime work

[0527] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[0528] Evening work

[0529] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0530] Example prompts for generative AI models

[0531] "Generate a schedule that optimally allocates break times and work times based on the worker's vital data and work data. The data includes: heart rate, stress level, sleep quality, and work performance data. Please propose the optimal schedule taking each data point into consideration."

[0532] By inputting this prompt into a generative AI model, the model can propose an efficient schedule. In this way, the system of the present invention aims to improve work efficiency while taking into account the health of the craftsmen, thereby achieving a sustainable improvement in the working environment.

[0533] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0534] Step 1: Collect and transmit vital data

[0535] Specific behavior:

[0536] A user wakes up in the morning and turns on their smartphone and wearable device, which measures vital data such as heart rate, stress level, and sleep quality in real time.

[0537] input:

[0538] Heart rate, stress levels, and sleep quality data from wearable devices.

[0539] Data processing and calculation:

[0540] The device collects this vital data, formats it (e.g., in JSON format) through a dedicated application, and sends it to a server.

[0541] output:

[0542] A request to the server containing vital data.

[0543] Step 2: Receiving and storing data

[0544] Specific behavior:

[0545] The server receives vital data sent from the device as an HTTP request, checks the integrity of the received data, and filters out incomplete data and abnormal values.

[0546] input:

[0547] Vital data sent from the device (JSON format).

[0548] Data processing and calculation:

[0549] Run a script to check the integrity of the incoming data and filter out any outliers or incomplete data (e.g., if the heart rate shows an obviously abnormal value).

[0550] output:

[0551] Vital data whose integrity has been confirmed is stored in a database.

[0552] Step 3: Optimize your schedule

[0553] Specific behavior:

[0554] The server extracts the latest vital and operational data from the database, and uses a generative AI algorithm to calculate the optimal schedule for each worker.

[0555] input:

[0556] Latest vital and operational data from the database.

[0557] Data processing and calculation:

[0558] The extracted data is input into a generative AI algorithm, which then allocates appropriate break times and work hours based on the worker's physical condition data. Specifically, modeling is done using TensorFlow and PyTorch, and input is done using prompt statements. Rules such as "allocate longer breaks to workers with unstable heart rates" are applied.

[0559] output:

[0560] Optimized schedule.

[0561] Step 4: Schedule distribution and execution

[0562] Specific behavior:

[0563] The server sends the generated schedule to the terminal. The user checks the received schedule on the terminal and starts moving and working according to the instructions.

[0564] input:

[0565] Generated schedule.

[0566] Data processing and calculation:

[0567] The generated schedule is converted into an appropriate notification format and sent to the device using a push notification service such as Firebase Cloud Messaging.

[0568] output:

[0569] Schedule displayed in device notifications.

[0570] Step 5: Collect performance data and reanalyze

[0571] Specific behavior:

[0572] After completing a task, the user inputs performance data through a dedicated application, and the terminal sends this data to the server, which receives the performance data and stores it in a database.

[0573] input:

[0574] Work performance data entered by craftsmen.

[0575] Data processing and calculation:

[0576] The received performance data is analyzed and re-analyzed to generate schedule improvement proposals for the next day. Specifically, the data is re-analyzed using tools such as Scikit-learn to gain new insights.

[0577] output:

[0578] The schedule is updated based on the proposed improvements. Based on this data, the updated schedule is notified to the user the next morning.

[0579] (Application example 1)

[0580] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0581] By monitoring the health status of employees in real time and providing appropriate work instructions, it is necessary to improve work efficiency in factories and optimize employee health management and workload. With conventional systems, it was difficult to provide work instructions while adequately monitoring the health status of employees, resulting in health problems and reduced work efficiency.

[0582] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0583] In this invention, the server includes terminal means for collecting vital data, means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the vital data and working hours by the server means to generate an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means and notifying the same, robot means for providing appropriate work instructions based on the employee's vital data, notification means for the robot means to provide the employee with work instructions in real time, and improvement means for transmitting employee performance data from the terminal means to the server means, reanalyzing the data, and generating improvement proposals. This enables efficient work instructions and schedule management that takes employee health conditions into consideration.

[0584] "Terminal means" refers to a device or equipment that collects employee vital data and transmits it to a server.

[0585] "Server Means" refers to a server that receives and stores vital data transmitted from Terminal Means, and analyzes and processes the data based on the data.

[0586] The "generative AI algorithm means" is an artificial intelligence algorithm that analyzes vital data and working hours to generate an optimal schedule.

[0587] The "notification means" is a device or software that has the function of transmitting schedules and work instructions generated by the server means to the terminal means or robot means and notifying them.

[0588] "Robotic means" refers to an autonomous or remotely controlled robot that provides appropriate work instructions based on an employee's vital data.

[0589] The "improvement means" refers to a method or device for transmitting employee performance data from the terminal means to the server means, and for reanalyzing and generating improvement proposals based on that data.

[0590] "Vital data" refers to physiological data that indicates an employee's health status, such as heart rate, stress level, and body temperature.

[0591] A "generated schedule" is an optimal work plan for each employee created based on data analyzed by a generative AI algorithm.

[0592] "Performance data" refers to data that records the history and results of work performed by employees.

[0593] This invention is a system that monitors the health status of employees in a factory in real time and provides optimal work instructions. The system is composed of a terminal means for collecting vital data, a server means for receiving and storing the data, a generating AI algorithm means, a notification means, a robot means, and an improvement means. Specific embodiments are described below.

[0594] Hardware Configuration

[0595] 1. Use wearable devices (e.g., smart watches or smart bands) worn by employees as terminals. These wearable devices collect vital data such as heart rate, stress level, and body temperature and send it to a server.

[0596] 2. Prepare a high-performance server and use a database system (e.g., MySQL, PostgreSQL) to store the collected vital data. Install appropriate software (e.g., Python, TensorFlow) to analyze the data.

[0597] 3. As software for the generative AI algorithm, a generative AI model will be developed using Python and TensorFlow, which will analyze vital data and business data to generate an optimal schedule.

[0598] 4. As a notification means, the server has the function of sending the generated schedule and work instructions to the terminal means and robot means, using a communication protocol (e.g., HTTP, MQTT).

[0599] 5. Robotic means include autonomous or remotely controlled robots in factories that provide appropriate work instructions in real time based on employees' vital signs.

[0600] 6. As an improvement measure, the performance data recorded by the employee is sent from the terminal means to the server means, and the server analyzes the data again and generates an improvement plan for the next day.

[0601] Software Configuration

[0602] The server uses Python and TensorFlow to build a generative AI model and calculate a health score. As an example, we use the following prompt:

[0603] Prompt Sentence Examples

[0604] Employee Health:

[0605] Heart rate: 75 BPM

[0606] Stress level: 0.4

[0607] Body temperature: 36.7°C

[0608] Steps: 500

[0609] Use this data to assess your employees' current health scores and generate their next work orders.

[0610] The server analyzes the collected vital data in real time and evaluates the employee's health status. The generative AI model calculates a health score based on this data and generates an optimal work schedule. The generated schedule and work instructions are sent to the terminal means and robot means via notification means. In addition, performance data recorded by employees is sent to the server and used for reanalysis as a means of improvement.

[0611] In this way, the system of the present invention provides efficient work instructions while monitoring the health status of employees, thereby improving work efficiency within the factory and employee health management.

[0612] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0613] Step 1:

[0614] Collection of vital data

[0615] The wearable device, which serves as a terminal means, collects vital data such as the heart rate, stress level, and body temperature of the employee who is the user.

[0616] Input: Keiryochi's vital data (heart rate, stress level, body temperature)

[0617] Output: Collected vital data

[0618] Step 2:

[0619] Sending vital data

[0620] The terminal device sends the collected vital data to the server using HTTP or MQTT as the communication protocol.

[0621] Input: Collected vital data

[0622] Output: Vital data received on the server side

[0623] Step 3:

[0624] Receiving and storing vital data and business data

[0625] The server means receives the vital data sent from the terminal means and stores it in a database, such as MySQL or PostgreSQL, using SQL statements.

[0626] Input: Vital data received from the terminal means

[0627] Output: Vital data stored in a database

[0628] Step 4:

[0629] Data analysis and health score calculation

[0630] The server analyzes the vital data acquired by the AI ​​algorithm and calculates a health score for each employee. The AI ​​model uses TensorFlow and is processed using a Python script. The health score is expressed in a range from 0 to 1.

[0631] Input: Vital data stored in the database

[0632] Output: Calculated health score

[0633] Step 5:

[0634] Schedule optimization

[0635] The server generates an optimal schedule for each employee using the health score calculated by the generative AI algorithm, which is implemented in Python and adjusts work priorities and break times based on the employee's health status.

[0636] Input: Calculated Health Score

[0637] Output: The generated optimal schedule

[0638] Step 6:

[0639] Schedule and work order notifications

[0640] The server unit transmits the generated schedule and work instructions to the terminal unit and the robot unit, and notifies the employee of the schedule and work instructions. Notification methods include display on a wearable device and voice notification from the robot.

[0641] Input: Generated optimal schedule and work instructions

[0642] Output: Schedules and work instructions sent to terminal and robotic means

[0643] Step 7:

[0644] Collection of work performance data

[0645] After the user has completed the work, he or she inputs performance data through the terminal means, which includes the work content, completion time, and the like.

[0646] Input: Actual data after work is completed

[0647] Output: Actual data entered into the terminal means

[0648] Step 8:

[0649] Sending and storing performance data

[0650] The terminal means transmits the input work performance data to the server means, which then stores it in a database.

[0651] Input: Actual data sent from the terminal means

[0652] Output: Actual data stored in the database

[0653] Step 9:

[0654] Reanalysis and generation of improvement proposals

[0655] The server performs re-analysis based on the saved performance data and generates improvement proposals for the next day. The AI ​​model is used again for the re-analysis and generation of improvement proposals.

[0656] Input: Actual data stored in the database

[0657] Output: Generated improvement suggestions

[0658] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0659] The present invention is a system for optimizing the working environment in the construction industry, and utilizes a generative AI algorithm to improve the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[0660] System Overview

[0661] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, an improvement means, and an emotion engine for recognizing the user's emotions.

[0662] Program processing overview

[0663] 1. Collecting vital and emotional data

[0664] The terminal means collects the worker's vital data and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. In addition, the emotion engine analyzes the worker's facial expressions and tone of voice to collect emotional data. This data is transmitted from the terminal means to the server means.

[0665] 2. Receipt and storage of data

[0666] The server receives the vital data and emotion data sent from the terminal and stores the data in a database. The server checks the consistency of the received data and filters out incomplete data and abnormal values.

[0667] 3. Schedule optimization

[0668] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generating AI algorithm to calculate the optimal schedule that takes into account each worker's free time and travel time.The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition and emotional data.

[0669] 4. Schedule distribution and execution

[0670] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[0671] 5. Performance data collection and reanalysis

[0672] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[0673] Specific examples

[0674] Morning work

[0675] The user activates the smartphone and wearable device to collect vital data. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to collect emotional data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0676] Daytime work

[0677] The user starts work at each site, and the terminal device monitors the vital data and emotional data of the craftsman. The server device receives the data in real time and readjusts the schedule as necessary.

[0678] Evening work

[0679] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data and emotion data to propose improvements for the next day and notifies the user overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0680] Through this detailed program processing, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[0681] The processing flow will be explained below.

[0682] Step 1:

[0683] In the morning, the user launches the smartphone app and connects it to the wearable device. The smartphone then measures vital data (heart rate, stress level, sleep quality) in real time through the wearable device. The emotion engine also analyzes the user's facial expressions and tone of voice to collect emotional data.

[0684] Step 2:

[0685] The device sends the collected vital data and emotional data in a specific format to a server, which receives the vital data and emotional data sent from the device and temporarily stores them in a database.

[0686] Step 3:

[0687] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[0688] Step 4:

[0689] The server extracts the latest vital signs, emotional data, and work data from the database and builds a dataset for analysis. It then runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time. The generative AI also uses the workers' physical condition and emotional data to appropriately allocate break times and work hours.

[0690] Step 5:

[0691] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[0692] Step 6:

[0693] The user moves efficiently according to the displayed schedule and begins work. While working at each site, the device continues to monitor vital and emotional data and transmits this data to the server in real time.

[0694] Step 7:

[0695] The server receives real-time vital and emotional data and adjusts the schedule as needed. For example, if a worker is tired, the AI ​​will insert appropriate breaks.

[0696] Step 8:

[0697] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server. The emotion engine also detects the user's emotional state for that day and collects the data.

[0698] Step 9:

[0699] The server reanalyzes the performance data, vital data, and emotional data to generate an optimal schedule and improvement proposals for the next day. The improvement proposals include schedule adjustments that reduce psychological fatigue based on the user's emotional state.

[0700] Step 10:

[0701] The server notifies the user's device of the improvement proposals and schedules it generated overnight. The next morning, the user receives a new schedule that reflects the improvement proposals, allowing them to work efficiently again.

[0702] Through the detailed program processing described above, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[0703] Example 2

[0704] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0705] There is a need to improve the working environment by understanding the health and emotional state of workers in real time and optimizing work and travel time based on that information. However, previous systems did not optimize schedules by fully considering the health and emotional state of workers, making it difficult to carry out work efficiently.

[0706] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI model means for analyzing the vital data and emotional data of craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it. This makes it possible to optimize schedules based on the health and emotional states of craftsmen, thereby realizing continuous improvement of the working environment.

[0707] "Terminal means" refers to a device for collecting vital data and emotional data of craftsmen and transmitting them to a server.

[0708] "Server means" refers to a computer system for receiving, storing, and analyzing vital data and emotional data transmitted from terminal means.

[0709] "Generative AI model means" refers to an artificial intelligence algorithm for generating an optimal schedule for each craftsman based on data collected by the server means.

[0710] The "notification means" refers to a mechanism for transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[0711] "Improvement means" refers to a mechanism for transmitting the craftsman's performance data from the terminal means to the server means and for reanalysis.

[0712] "Vital data" refers to various indicators that show the health status of craftsmen, such as their heart rate, stress level, and sleep quality.

[0713] "Emotional data" refers to data that indicates the emotional state of the craftsman, such as facial expression analysis and tone of voice analysis data of the craftsman.

[0714] "Schedule" refers to a plan to optimize the work and travel time of craftsmen.

[0715] "Performance data" refers to data that records the actual work content and time performed by craftsmen.

[0716] The present invention is a system for improving the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[0717] System Overview

[0718] This system consists of a terminal means for collecting vital data and emotional data of craftsmen, a server means for receiving and storing vital data and emotional data, an algorithm means for calculating the optimal schedule using a generative AI model, a notification means, and an improvement means.

[0719] Hardware and software used

[0720] Hardware

[0721] Smartphones (e.g., general smartphone devices)

[0722] Wearable devices (e.g., common fitness trackers)

[0723] software

[0724] Vital data collection apps (e.g., health management applications)

[0725] Emotion engines (e.g., facial expression analysis software)

[0726] Databases (e.g., common relational database systems)

[0727] Program processing overview

[0728] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data. The collected data is sent from the terminal to the server. Data is collected with the prompt, "Please measure your heart rate."

[0729] The server receives and stores the vital data and emotion data sent from the device. After checking the integrity of the received data and filtering out incomplete data and outliers, the server stores the data in a database. The server executes data saving with the prompt "Please save the data."

[0730] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate an optimal schedule that takes into account each worker's free time and travel time. The generative AI model appropriately allocates break times and work hours based on the worker's physical condition and emotional data. Schedule generation begins with the prompt, "Please generate the optimal schedule."

[0731] The server sends the generated schedule to the terminal and notifies the user. The user checks the schedule for the day through the terminal and moves and works efficiently according to the instructions. The schedule is confirmed with the prompt "Please check today's schedule."

[0732] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotional data to propose improvements for the next day and notifies them overnight. Data input is performed with the prompt "Please enter performance data."

[0733] Through this detailed program processing, the system of the present invention can improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[0734] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0735] Step 1:

[0736] Collection of vital and emotional data

[0737] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data.

[0738] Input: Physical metrics (heart rate, stress level, sleep quality) and audio and facial expression data.

[0739] Output: The acquired vital and emotional data.

[0740] How it works: When a worker arrives at a job site, their heart rate and stress level are automatically measured using a smartphone and wearable device, while an emotion engine analyzes their voice and facial expressions in real time.

[0741] Step 2:

[0742] Receiving and storing data

[0743] The server receives the vital and emotional data sent from the device and stores them in a database. The server checks the integrity of the received data and filters out incomplete data and outliers.

[0744] Input: Vital and emotional data sent from the device.

[0745] Output: The filtered database entries.

[0746] Specific operation: The server receives data in real time, removes data that falls outside the range of abnormal values, and then stores the data in a database in a standard format.

[0747] Step 3:

[0748] Data analysis and schedule optimization

[0749] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate the optimal schedule that takes into account each worker's free time and travel time.

[0750] Input: Latest vital, emotional and operational data extracted from the database.

[0751] Output: The optimized schedule.

[0752] How it works: The server inputs data into the generative AI model, and the AI ​​algorithm analyzes each worker's physical condition and work data, resulting in the creation of an optimal work schedule.

[0753] Step 4:

[0754] Schedule distribution and execution

[0755] The server sends the generated schedule to the terminal and notifies the user. The user can check the schedule for the day through the terminal and move and work efficiently according to the instructions.

[0756] Input: The generated schedule.

[0757] Output: User notification and confirmed schedule.

[0758] Specific operation: The server sends the generated schedule to the terminal via WiFi, and a notification is displayed on the craftsman's smartphone. The craftsman checks the schedule on his smartphone and proceeds to the site.

[0759] Step 5:

[0760] Collection and reanalysis of performance data

[0761] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotion data to propose improvements for the next day and notifies the user overnight.

[0762] Input: Work performance data and additional vital and emotional data submitted by the user.

[0763] Output: Improvement proposals and new schedule for the next day.

[0764] How it works: When a worker finishes a task, he or she enters the results data into a smartphone app. The server receives and analyzes this data, generates a new schedule, and notifies the worker overnight.

[0765] This is the flow of the system's program processing, which allows for efficient and sustainable optimization of work schedules while taking into account the health and emotional state of the workers.

[0766] (Application example 2)

[0767] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0768] This invention is a system that efficiently manages work hours and travel time while monitoring the health and emotional state of craftsmen in real time in order to optimize the work environment of craftsmen. Conventional labor management systems are limited to collecting vital data and do not support schedule optimization that takes into account the emotional state of craftsmen. This makes it difficult to reduce stress and improve productivity for craftsmen.

[0769] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI algorithm means for generating an optimal schedule including the craftsmen's work hours and travel times in the server means, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for collecting craftsmen's performance data and transmitting it to the server means for reanalysis. This makes it possible to optimize the working environment taking into account the craftsmen's health and emotional state.

[0770] A "craftsman" is a skilled worker who performs work in a factory or on a construction site.

[0771] "Vital data" refers to data that indicates the physiological state of the craftsman, such as heart rate, stress level, and sleep quality.

[0772] "Emotional data" is data used to measure the emotional state of a craftsman, such as facial expressions and tone of voice.

[0773] "Terminal means" refers to equipment that collects vital data and emotional data and transmits them to a server, and includes smartphones and wearable devices.

[0774] The "server means" is a system that receives, stores, and analyzes data sent from the terminal means.

[0775] The "generative AI algorithm means" is an algorithm that generates an optimal schedule, including the work hours and travel times of craftsmen, based on the collected data.

[0776] The "notification means" is a system having a function of transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[0777] The "improvement means" is a method or device for transmitting the performance data entered by the craftsman to the server means and for reanalyzing the data.

[0778] The "display means" is a device for visually presenting the generated schedule to the craftsman, and includes a display or monitor.

[0779] The "user interface means" is an operation interface through which a craftsman inputs performance data and transmits it to the server means.

[0780] The present invention is a system for collecting vital data and emotional data of craftsmen and optimizing their work time and travel time. The system includes the following main components:

[0781] System configuration

[0782] 1. Terminal means

[0783] Smartphones and wearable devices are used to collect vital data such as heart rate, stress levels, and sleep quality.

[0784] Emotional data such as the craftsman's facial expressions and tone of voice is collected through cameras and microphones.

[0785] 2. Server Means

[0786] Store data in AWS DynamoDB (cloud database).

[0787] Receive and store vital data and emotional data for each craftsman.

[0788] 3. Generative AI Algorithm Means

[0789] Based on the collected data, a generative AI algorithm is run to generate a schedule that includes optimal working hours and travel times for each worker.

[0790] 4. Means of notification

[0791] The optimized schedule is transmitted to the terminal means and notified to the craftsman.

[0792] 5. Improvement measures

[0793] The performance data input by the craftsman is sent to the server means and reanalyzed.

[0794] Program processing

[0795] Hardware and Software

[0796] Hardware: Wearable devices (heart rate monitors, stress sensors), cameras, microphones, factory robots

[0797] Software: Python, AWS DynamoDB (database), Emotion Engine (virtual emotion engine), VitalDataCollector (virtual data collection module)

[0798] Data collection and transmission

[0799] The terminal means collects vital data using a wearable device and analyzes and collects emotional data using the Emotion Engine. This data is sent from the terminal means to AWS DynamoDB and stored.

[0800] Schedule optimization

[0801] The server uses a generative AI algorithm to generate an optimal work schedule for each worker based on the received vital and emotional data. For example, if a worker's stress level is high or their emotional state is unstable, it will adjust the schedule by increasing their break time.

[0802] Schedule execution and notifications

[0803] The generated schedule is sent to the craftsman through the notification means, and the craftsman uses the terminal means to proceed with the work according to the schedule.

[0804] Performance data collection and reanalysis

[0805] After completing the work, the craftsman inputs the performance data using the terminal means and transmits it to the server means, which then analyzes the collected data to optimize the next schedule.

[0806] Examples and prompts

[0807] In the morning, craftsmen turn on their smartphones and wearable devices to collect vital data such as heart rate and stress level. At the same time, cameras and microphones are used to analyze facial expressions and tone of voice, collecting emotional data. This data is sent to a cloud server, which generates an optimal schedule. For example, a craftsman with a high heart rate and high stress level could be assigned lighter work in the morning and scheduled for longer breaks in the afternoon.

[0808] Prompt Sentence Examples

[0809] An assistant system that optimizes robot activity and worker health in factories. It uses wearable devices and an emotion recognition engine to collect health and emotion data, which is then sent to a cloud server to provide optimal work schedules.

[0810] Key functions: health and emotional data collection, data transmission and storage, schedule optimization, schedule notification and execution.

[0811] The introduction of this system will enable the optimization of the working environment, taking into account the health and emotional state of the workers.

[0812] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0813] Step 1:

[0814] The terminal means collects vital data and emotional data of the craftsman. Heart rate, stress level, and sleep quality are obtained from the wearable device, and facial expressions and tone of voice are analyzed via a camera and microphone. Input data includes heart rate, stress level, sleep quality, facial expressions, and tone of voice. This data is temporarily stored in the internal memory of the terminal means.

[0815] Step 2:

[0816] The terminal means sends the collected data to the server means. The inputs include vital data and emotion data obtained from the wearable device and emotion engine. The server means receives this data and stores it in AWS DynamoDB. It checks the data for consistency and filters out incomplete data and outliers.

[0817] Step 3:

[0818] The server executes the generation AI algorithm and generates an optimal work schedule based on the stored vital data and emotional data. The received vital data and emotional data are input. The generation AI algorithm analyzes this data and calculates the optimal schedule for each worker. The generated work schedule is obtained as output.

[0819] Step 4:

[0820] The server means transmits the generated schedule to the terminal means. The generated work schedule is input. The schedule is notified to the worker using the notification means and displayed on the terminal means. The worker checks the notified schedule and proceeds with the work.

[0821] Step 5:

[0822] After the process is completed, the user inputs the performance data using the terminal means. The input includes performance data for each task (start and end times of the task, actual travel time, etc.). The terminal means transmits this data to the server means.

[0823] Step 6:

[0824] Based on the performance data received by the server means, an analysis is performed for the next schedule optimization. The performance data sent after the work is completed is used as input. This allows for new schedule optimization that takes into account the health and emotional state of the craftsmen. An updated schedule optimization proposal is obtained as output.

[0825] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0826] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0827] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0828] [Third embodiment]

[0829] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0830] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0831] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0832] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0833] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0834] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0835] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0836] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0837] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0838] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0839] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0840] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0841] The present invention is a system for optimizing the working environment in the construction industry, and in particular, utilizes a generative AI algorithm to streamline work time and travel time while monitoring the health status of workers in real time. Specific embodiments of the present invention are described below.

[0842] System Overview

[0843] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, and an improvement means for reanalyzing.

[0844] Program processing overview

[0845] 1. Collecting and transmitting vital data

[0846] The terminal means collects vital data of the craftsman and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. The terminal means transmits this data to the server means via a dedicated application.

[0847] 2. Receipt and storage of data

[0848] The server receives the vital data transmitted from the terminal and stores it in a database. The server checks the integrity of the received data and filters out incomplete data and abnormal values.

[0849] 3. Schedule optimization

[0850] The server extracts the latest vital and work data from the database and uses a generating AI algorithm to calculate the optimal schedule, taking into account each worker's free time and travel time. The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition data.

[0851] 4. Schedule distribution and execution

[0852] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[0853] 5. Performance data collection and reanalysis

[0854] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[0855] Specific examples

[0856] Morning work

[0857] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0858] Daytime work

[0859] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[0860] Evening work

[0861] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0862] In this way, the system of the present invention aims to improve work efficiency while taking into account the health status of craftsmen, and achieves sustainable improvements in the working environment.

[0863] The processing flow will be explained below.

[0864] Step 1:

[0865] In the morning, the user launches the smartphone app and connects it to the wearable device, which then measures vital data (heart rate, stress level, sleep quality) in real time.

[0866] Step 2:

[0867] The device sends the collected vital data in a specific format to the server, which receives the vital data and temporarily stores it in a database.

[0868] Step 3:

[0869] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[0870] Step 4:

[0871] The server extracts the latest vital and operational data from the database, constructs a dataset for analysis, and runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time.

[0872] Step 5:

[0873] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[0874] Step 6:

[0875] The user moves efficiently according to the displayed schedule and begins work. After completing work at each site, the device sends the current status and vital data to the server.

[0876] Step 7:

[0877] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server.

[0878] Step 8:

[0879] The server reanalyzes the performance data and additional vital data to generate the optimal schedule and improvement proposals for the next day. The improvement proposals are then sent to the user's device overnight so that they can be prepared for the next day.

[0880] Step 9:

[0881] The next morning, users receive a new schedule that reflects the proposed improvements and can work efficiently again, resulting in a sustainable improvement in the working environment.

[0882] Example 1

[0883] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0884] In the traditional construction industry, it was difficult to monitor the health of workers in real time, resulting in overwork and health problems. Furthermore, work hours and travel time were not optimized, resulting in a decrease in overall efficiency. Furthermore, there were also problems with incomplete data and outliers affecting the system.

[0885] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0886] In this invention, the server includes terminal means for collecting vital data of craftsmen, server means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the work hours and travel times of the craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing it, allocation means for allocating break times and work times taking into account the health status of the craftsmen based on the optimal schedule calculated by the generation AI algorithm means, and data consistency confirmation means for filtering out incomplete data and outliers. This makes it possible to provide an optimal work schedule while monitoring the health status of the craftsmen in real time, improving the working environment and increasing work efficiency.

[0887] "Terminal means" refers to devices that collect vital data of craftsmen and transmit it to the server. Specifically, this includes smartphones and wearable devices.

[0888] The term "server means" refers to a server system that receives and stores vital data transmitted from the terminal means and further analyzes the data.

[0889] "Generative AI Algorithm Means" refers to the algorithm used by the Server Means to analyze data and generate optimal schedules for each craftsman. The generative algorithm may include machine learning models and optimization techniques.

[0890] "Notification means" refers to a system for sending the generated schedule to the terminal means and notifying the craftsman. This includes push notification functions and messaging services.

[0891] "Improvement measures" refer to the means for reanalyzing the workforce's performance data and generating improvement plans for the next day, thereby continuously improving work efficiency and the health of the workforce.

[0892] The "data consistency checking means" refers to a means for checking the consistency of data received by the server means and filtering out incomplete data and abnormal values, thereby improving the reliability of the system.

[0893] The "allocation method" refers to the method for allocating break times and work hours of craftsmen based on the optimal schedule calculated by the generative AI algorithm. By taking into account the health status of craftsmen, we aim to improve the working environment.

[0894] "Vital data" refers to biometric data such as the worker's heart rate, stress level, and sleep quality, collected using wearable devices and other sensors.

[0895] "Display means" refers to a device for displaying the generated schedule, including the screen of a terminal means and a dedicated monitor.

[0896] The "user interface means" refers to an interface for transmitting performance data entered by a craftsman to the server means. Specifically, it includes a mobile application and a web interface.

[0897] The present invention relates to a system for optimizing the working environment in the construction industry. Specifically, the present invention provides a system that utilizes generative AI algorithms to monitor the health status of workers in real time and efficiently manage their work hours and travel time. Specific embodiments of the present invention are described below.

[0898] System Overview

[0899] The system consists of the following elements:

[0900] Terminal means for collecting vital data of craftsmen

[0901] Server means for receiving and storing vital data transmitted from the terminal means

[0902] A generative AI algorithm that analyzes the work hours and travel times of craftsmen and generates an optimal schedule

[0903] Notification means for transmitting the generated schedule to the terminal means

[0904] Improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it

[0905] Data integrity checks to filter incomplete data and outliers

[0906] A method of allocating break times and work hours that takes into account the health of workers

[0907] Hardware and software used

[0908] Terminal means:

[0909] Smartphone

[0910] Wearable devices (e.g., smartwatches)

[0911] Server means:

[0912] Database server (e.g. AWS RDS, Google Cloud SQL)

[0913] Data receiving server (e.g. Nginx, Apache)

[0914] Generative AI algorithm means:

[0915] Machine learning frameworks (e.g. TensorFlow, PyTorch)

[0916] Data analysis tools (e.g., Pandas, NumPy)

[0917] Means of notification:

[0918] Push notification service (e.g., Firebase Cloud Messaging)

[0919] Improvement measures:

[0920] Data reanalysis tools (e.g., Scikit-learn)

[0921] Data integrity verification methods:

[0922] Data cleaning tools (e.g., Python data manipulation libraries)

[0923] Placement means:

[0924] Scheduling algorithms (e.g., Google OR-Tools)

[0925] Example

[0926] Morning work

[0927] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[0928] Daytime work

[0929] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[0930] Evening work

[0931] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[0932] Example prompts for generative AI models

[0933] "Generate a schedule that optimally allocates break times and work times based on the worker's vital data and work data. The data includes: heart rate, stress level, sleep quality, and work performance data. Please propose the optimal schedule taking each data point into consideration."

[0934] By inputting this prompt into a generative AI model, the model can propose an efficient schedule. In this way, the system of the present invention aims to improve work efficiency while taking into account the health of the craftsmen, thereby achieving a sustainable improvement in the working environment.

[0935] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0936] Step 1: Collect and transmit vital data

[0937] Specific behavior:

[0938] A user wakes up in the morning and turns on their smartphone and wearable device, which measures vital data such as heart rate, stress level, and sleep quality in real time.

[0939] input:

[0940] Heart rate, stress levels, and sleep quality data from wearable devices.

[0941] Data processing and calculation:

[0942] The device collects this vital data, formats it (e.g., in JSON format) through a dedicated application, and sends it to a server.

[0943] output:

[0944] A request to the server containing vital data.

[0945] Step 2: Receiving and storing data

[0946] Specific behavior:

[0947] The server receives vital data sent from the device as an HTTP request, checks the integrity of the received data, and filters out incomplete data and abnormal values.

[0948] input:

[0949] Vital data sent from the device (JSON format).

[0950] Data processing and calculation:

[0951] Run a script to check the integrity of the incoming data and filter out any outliers or incomplete data (e.g., if the heart rate shows an obviously abnormal value).

[0952] output:

[0953] Vital data whose integrity has been confirmed is stored in a database.

[0954] Step 3: Optimize your schedule

[0955] Specific behavior:

[0956] The server extracts the latest vital and operational data from the database, and uses a generative AI algorithm to calculate the optimal schedule for each worker.

[0957] input:

[0958] Latest vital and operational data from the database.

[0959] Data processing and calculation:

[0960] The extracted data is input into a generative AI algorithm, which then allocates appropriate break times and work hours based on the worker's physical condition data. Specifically, modeling is done using TensorFlow and PyTorch, and input is done using prompt statements. Rules such as "allocate longer breaks to workers with unstable heart rates" are applied.

[0961] output:

[0962] Optimized schedule.

[0963] Step 4: Schedule distribution and execution

[0964] Specific behavior:

[0965] The server sends the generated schedule to the terminal. The user checks the received schedule on the terminal and starts moving and working according to the instructions.

[0966] input:

[0967] Generated schedule.

[0968] Data processing and calculation:

[0969] The generated schedule is converted into an appropriate notification format and sent to the device using a push notification service such as Firebase Cloud Messaging.

[0970] output:

[0971] Schedule displayed in device notifications.

[0972] Step 5: Collect performance data and reanalyze

[0973] Specific behavior:

[0974] After completing a task, the user inputs performance data through a dedicated application, and the terminal sends this data to the server, which receives the performance data and stores it in a database.

[0975] input:

[0976] Work performance data entered by craftsmen.

[0977] Data processing and calculation:

[0978] The received performance data is analyzed and re-analyzed to generate schedule improvement proposals for the next day. Specifically, the data is re-analyzed using tools such as Scikit-learn to gain new insights.

[0979] output:

[0980] The schedule is updated based on the proposed improvements. Based on this data, the updated schedule is notified to the user the next morning.

[0981] (Application example 1)

[0982] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0983] By monitoring the health status of employees in real time and providing appropriate work instructions, it is necessary to improve work efficiency in factories and optimize employee health management and workload. With conventional systems, it was difficult to provide work instructions while adequately monitoring the health status of employees, resulting in health problems and reduced work efficiency.

[0984] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0985] In this invention, the server includes terminal means for collecting vital data, means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the vital data and working hours by the server means to generate an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means and notifying the same, robot means for providing appropriate work instructions based on the employee's vital data, notification means for the robot means to provide the employee with work instructions in real time, and improvement means for transmitting employee performance data from the terminal means to the server means, reanalyzing the data, and generating improvement proposals. This enables efficient work instructions and schedule management that takes employee health conditions into consideration.

[0986] "Terminal means" refers to a device or equipment that collects employee vital data and transmits it to a server.

[0987] "Server Means" refers to a server that receives and stores vital data transmitted from Terminal Means, and analyzes and processes the data based on the data.

[0988] The "generative AI algorithm means" is an artificial intelligence algorithm that analyzes vital data and working hours to generate an optimal schedule.

[0989] The "notification means" is a device or software that has the function of transmitting schedules and work instructions generated by the server means to the terminal means or robot means and notifying them.

[0990] "Robotic means" refers to an autonomous or remotely controlled robot that provides appropriate work instructions based on an employee's vital data.

[0991] The "improvement means" refers to a method or device for transmitting employee performance data from the terminal means to the server means, and for reanalyzing and generating improvement proposals based on that data.

[0992] "Vital data" refers to physiological data that indicates an employee's health status, such as heart rate, stress level, and body temperature.

[0993] A "generated schedule" is an optimal work plan for each employee created based on data analyzed by a generative AI algorithm.

[0994] "Performance data" refers to data that records the history and results of work performed by employees.

[0995] This invention is a system that monitors the health status of employees in a factory in real time and provides optimal work instructions. The system is composed of a terminal means for collecting vital data, a server means for receiving and storing the data, a generating AI algorithm means, a notification means, a robot means, and an improvement means. Specific embodiments are described below.

[0996] Hardware Configuration

[0997] 1. Use wearable devices (e.g., smart watches or smart bands) worn by employees as terminals. These wearable devices collect vital data such as heart rate, stress level, and body temperature and send it to a server.

[0998] 2. Prepare a high-performance server and use a database system (e.g., MySQL, PostgreSQL) to store the collected vital data. Install appropriate software (e.g., Python, TensorFlow) to analyze the data.

[0999] 3. As software for the generative AI algorithm, a generative AI model will be developed using Python and TensorFlow, which will analyze vital data and business data to generate an optimal schedule.

[1000] 4. As a notification means, the server has the function of sending the generated schedule and work instructions to the terminal means and robot means, using a communication protocol (e.g., HTTP, MQTT).

[1001] 5. Robotic means include autonomous or remotely controlled robots in factories that provide appropriate work instructions in real time based on employees' vital signs.

[1002] 6. As an improvement measure, the performance data recorded by the employee is sent from the terminal means to the server means, and the server analyzes the data again and generates an improvement plan for the next day.

[1003] Software Configuration

[1004] The server uses Python and TensorFlow to build a generative AI model and calculate a health score. As an example, we use the following prompt:

[1005] Prompt Sentence Examples

[1006] Employee Health:

[1007] Heart rate: 75 BPM

[1008] Stress level: 0.4

[1009] Body temperature: 36.7°C

[1010] Steps: 500

[1011] Use this data to assess your employees' current health scores and generate their next work orders.

[1012] The server analyzes the collected vital data in real time and evaluates the employee's health status. The generative AI model calculates a health score based on this data and generates an optimal work schedule. The generated schedule and work instructions are sent to the terminal means and robot means via notification means. In addition, performance data recorded by employees is sent to the server and used for reanalysis as a means of improvement.

[1013] In this way, the system of the present invention provides efficient work instructions while monitoring the health status of employees, thereby improving work efficiency within the factory and employee health management.

[1014] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1015] Step 1:

[1016] Collection of vital data

[1017] The wearable device, which serves as a terminal means, collects vital data such as the heart rate, stress level, and body temperature of the employee who is the user.

[1018] Input: Keiryochi's vital data (heart rate, stress level, body temperature)

[1019] Output: Collected vital data

[1020] Step 2:

[1021] Sending vital data

[1022] The terminal device sends the collected vital data to the server using HTTP or MQTT as the communication protocol.

[1023] Input: Collected vital data

[1024] Output: Vital data received on the server side

[1025] Step 3:

[1026] Receiving and storing vital data and business data

[1027] The server means receives the vital data sent from the terminal means and stores it in a database, such as MySQL or PostgreSQL, using SQL statements.

[1028] Input: Vital data received from the terminal means

[1029] Output: Vital data stored in a database

[1030] Step 4:

[1031] Data analysis and health score calculation

[1032] The server analyzes the vital data acquired by the AI ​​algorithm and calculates a health score for each employee. The AI ​​model uses TensorFlow and is processed using a Python script. The health score is expressed in a range from 0 to 1.

[1033] Input: Vital data stored in the database

[1034] Output: Calculated health score

[1035] Step 5:

[1036] Schedule optimization

[1037] The server generates an optimal schedule for each employee using the health score calculated by the generative AI algorithm, which is implemented in Python and adjusts work priorities and break times based on the employee's health status.

[1038] Input: Calculated Health Score

[1039] Output: The generated optimal schedule

[1040] Step 6:

[1041] Schedule and work order notifications

[1042] The server unit transmits the generated schedule and work instructions to the terminal unit and the robot unit, and notifies the employee of the schedule and work instructions. Notification methods include display on a wearable device and voice notification from the robot.

[1043] Input: Generated optimal schedule and work instructions

[1044] Output: Schedules and work instructions sent to terminal and robotic means

[1045] Step 7:

[1046] Collection of work performance data

[1047] After the user has completed the work, he or she inputs performance data through the terminal means, which includes the work content, completion time, and the like.

[1048] Input: Actual data after work is completed

[1049] Output: Actual data entered into the terminal means

[1050] Step 8:

[1051] Sending and storing performance data

[1052] The terminal means transmits the input work performance data to the server means, which then stores it in a database.

[1053] Input: Actual data sent from the terminal means

[1054] Output: Actual data stored in the database

[1055] Step 9:

[1056] Reanalysis and generation of improvement proposals

[1057] The server performs re-analysis based on the saved performance data and generates improvement proposals for the next day. The AI ​​model is used again for the re-analysis and generation of improvement proposals.

[1058] Input: Actual data stored in the database

[1059] Output: Generated improvement suggestions

[1060] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1061] The present invention is a system for optimizing the working environment in the construction industry, and utilizes a generative AI algorithm to improve the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[1062] System Overview

[1063] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, an improvement means, and an emotion engine for recognizing the user's emotions.

[1064] Program processing overview

[1065] 1. Collecting vital and emotional data

[1066] The terminal means collects the worker's vital data and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. In addition, the emotion engine analyzes the worker's facial expressions and tone of voice to collect emotional data. This data is transmitted from the terminal means to the server means.

[1067] 2. Receipt and storage of data

[1068] The server receives the vital data and emotion data sent from the terminal and stores the data in a database. The server checks the consistency of the received data and filters out incomplete data and abnormal values.

[1069] 3. Schedule optimization

[1070] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generating AI algorithm to calculate the optimal schedule that takes into account each worker's free time and travel time.The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition and emotional data.

[1071] 4. Schedule distribution and execution

[1072] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[1073] 5. Performance data collection and reanalysis

[1074] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[1075] Specific examples

[1076] Morning work

[1077] The user activates the smartphone and wearable device to collect vital data. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to collect emotional data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[1078] Daytime work

[1079] The user starts work at each site, and the terminal device monitors the vital data and emotional data of the craftsman. The server device receives the data in real time and readjusts the schedule as necessary.

[1080] Evening work

[1081] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data and emotion data to propose improvements for the next day and notifies the user overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[1082] Through this detailed program processing, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[1083] The processing flow will be explained below.

[1084] Step 1:

[1085] In the morning, the user launches the smartphone app and connects it to the wearable device. The smartphone then measures vital data (heart rate, stress level, sleep quality) in real time through the wearable device. The emotion engine also analyzes the user's facial expressions and tone of voice to collect emotional data.

[1086] Step 2:

[1087] The device sends the collected vital data and emotional data in a specific format to a server, which receives the vital data and emotional data sent from the device and temporarily stores them in a database.

[1088] Step 3:

[1089] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[1090] Step 4:

[1091] The server extracts the latest vital signs, emotional data, and work data from the database and builds a dataset for analysis. It then runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time. The generative AI also uses the workers' physical condition and emotional data to appropriately allocate break times and work hours.

[1092] Step 5:

[1093] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[1094] Step 6:

[1095] The user moves efficiently according to the displayed schedule and begins work. While working at each site, the device continues to monitor vital and emotional data and transmits this data to the server in real time.

[1096] Step 7:

[1097] The server receives real-time vital and emotional data and adjusts the schedule as needed. For example, if a worker is tired, the AI ​​will insert appropriate breaks.

[1098] Step 8:

[1099] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server. The emotion engine also detects the user's emotional state for that day and collects the data.

[1100] Step 9:

[1101] The server reanalyzes the performance data, vital data, and emotional data to generate an optimal schedule and improvement proposals for the next day. The improvement proposals include schedule adjustments that reduce psychological fatigue based on the user's emotional state.

[1102] Step 10:

[1103] The server notifies the user's device of the improvement proposals and schedules it generated overnight. The next morning, the user receives a new schedule that reflects the improvement proposals, allowing them to work efficiently again.

[1104] Through the detailed program processing described above, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[1105] Example 2

[1106] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1107] There is a need to improve the working environment by understanding the health and emotional state of workers in real time and optimizing work and travel time based on that information. However, previous systems did not optimize schedules by fully considering the health and emotional state of workers, making it difficult to carry out work efficiently.

[1108] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI model means for analyzing the vital data and emotional data of craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it. This makes it possible to optimize schedules based on the health and emotional states of craftsmen, thereby realizing continuous improvement of the working environment.

[1109] "Terminal means" refers to a device for collecting vital data and emotional data of craftsmen and transmitting them to a server.

[1110] "Server means" refers to a computer system for receiving, storing, and analyzing vital data and emotional data transmitted from terminal means.

[1111] "Generative AI model means" refers to an artificial intelligence algorithm for generating an optimal schedule for each craftsman based on data collected by the server means.

[1112] The "notification means" refers to a mechanism for transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[1113] "Improvement means" refers to a mechanism for transmitting the craftsman's performance data from the terminal means to the server means and for reanalysis.

[1114] "Vital data" refers to various indicators that show the health status of craftsmen, such as their heart rate, stress level, and sleep quality.

[1115] "Emotional data" refers to data that indicates the emotional state of the craftsman, such as facial expression analysis and tone of voice analysis data of the craftsman.

[1116] "Schedule" refers to a plan to optimize the work and travel time of craftsmen.

[1117] "Performance data" refers to data that records the actual work content and time performed by craftsmen.

[1118] The present invention is a system for improving the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[1119] System Overview

[1120] This system consists of a terminal means for collecting vital data and emotional data of craftsmen, a server means for receiving and storing vital data and emotional data, an algorithm means for calculating the optimal schedule using a generative AI model, a notification means, and an improvement means.

[1121] Hardware and software used

[1122] Hardware

[1123] Smartphones (e.g., general smartphone devices)

[1124] Wearable devices (e.g., common fitness trackers)

[1125] software

[1126] Vital data collection apps (e.g., health management applications)

[1127] Emotion engines (e.g., facial expression analysis software)

[1128] Databases (e.g., common relational database systems)

[1129] Program processing overview

[1130] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data. The collected data is sent from the terminal to the server. Data is collected with the prompt, "Please measure your heart rate."

[1131] The server receives and stores the vital data and emotion data sent from the device. After checking the integrity of the received data and filtering out incomplete data and outliers, the server stores the data in a database. The server executes data saving with the prompt "Please save the data."

[1132] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate an optimal schedule that takes into account each worker's free time and travel time. The generative AI model appropriately allocates break times and work hours based on the worker's physical condition and emotional data. Schedule generation begins with the prompt, "Please generate the optimal schedule."

[1133] The server sends the generated schedule to the terminal and notifies the user. The user checks the schedule for the day through the terminal and moves and works efficiently according to the instructions. The schedule is confirmed with the prompt "Please check today's schedule."

[1134] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotional data to propose improvements for the next day and notifies them overnight. Data input is performed with the prompt "Please enter performance data."

[1135] Through this detailed program processing, the system of the present invention can improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[1136] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1137] Step 1:

[1138] Collection of vital and emotional data

[1139] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data.

[1140] Input: Physical metrics (heart rate, stress level, sleep quality) and audio and facial expression data.

[1141] Output: The acquired vital and emotional data.

[1142] How it works: When a worker arrives at a job site, their heart rate and stress level are automatically measured using a smartphone and wearable device, while an emotion engine analyzes their voice and facial expressions in real time.

[1143] Step 2:

[1144] Receiving and storing data

[1145] The server receives the vital and emotional data sent from the device and stores them in a database. The server checks the integrity of the received data and filters out incomplete data and outliers.

[1146] Input: Vital and emotional data sent from the device.

[1147] Output: The filtered database entries.

[1148] Specific operation: The server receives data in real time, removes data that falls outside the range of abnormal values, and then stores the data in a database in a standard format.

[1149] Step 3:

[1150] Data analysis and schedule optimization

[1151] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate the optimal schedule that takes into account each worker's free time and travel time.

[1152] Input: Latest vital, emotional and operational data extracted from the database.

[1153] Output: The optimized schedule.

[1154] How it works: The server inputs data into the generative AI model, and the AI ​​algorithm analyzes each worker's physical condition and work data, resulting in the creation of an optimal work schedule.

[1155] Step 4:

[1156] Schedule distribution and execution

[1157] The server sends the generated schedule to the terminal and notifies the user. The user can check the schedule for the day through the terminal and move and work efficiently according to the instructions.

[1158] Input: The generated schedule.

[1159] Output: User notification and confirmed schedule.

[1160] Specific operation: The server sends the generated schedule to the terminal via WiFi, and a notification is displayed on the craftsman's smartphone. The craftsman checks the schedule on his smartphone and proceeds to the site.

[1161] Step 5:

[1162] Collection and reanalysis of performance data

[1163] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotion data to propose improvements for the next day and notifies the user overnight.

[1164] Input: Work performance data and additional vital and emotional data submitted by the user.

[1165] Output: Improvement proposals and new schedule for the next day.

[1166] How it works: When a worker finishes a task, he or she enters the results data into a smartphone app. The server receives and analyzes this data, generates a new schedule, and notifies the worker overnight.

[1167] This is the flow of the system's program processing, which allows for efficient and sustainable optimization of work schedules while taking into account the health and emotional state of the workers.

[1168] (Application example 2)

[1169] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1170] This invention is a system that efficiently manages work hours and travel time while monitoring the health and emotional state of craftsmen in real time in order to optimize the work environment of craftsmen. Conventional labor management systems are limited to collecting vital data and do not support schedule optimization that takes into account the emotional state of craftsmen. This makes it difficult to reduce stress and improve productivity for craftsmen.

[1171] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI algorithm means for generating an optimal schedule including the craftsmen's work hours and travel times in the server means, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for collecting craftsmen's performance data and transmitting it to the server means for reanalysis. This makes it possible to optimize the working environment taking into account the craftsmen's health and emotional state.

[1172] A "craftsman" is a skilled worker who performs work in a factory or on a construction site.

[1173] "Vital data" refers to data that indicates the physiological state of the craftsman, such as heart rate, stress level, and sleep quality.

[1174] "Emotional data" is data used to measure the emotional state of a craftsman, such as facial expressions and tone of voice.

[1175] "Terminal means" refers to equipment that collects vital data and emotional data and transmits them to a server, and includes smartphones and wearable devices.

[1176] The "server means" is a system that receives, stores, and analyzes data sent from the terminal means.

[1177] The "generative AI algorithm means" is an algorithm that generates an optimal schedule, including the work hours and travel times of craftsmen, based on the collected data.

[1178] The "notification means" is a system having a function of transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[1179] The "improvement means" is a method or device for transmitting the performance data entered by the craftsman to the server means and for reanalyzing the data.

[1180] The "display means" is a device for visually presenting the generated schedule to the craftsman, and includes a display or monitor.

[1181] The "user interface means" is an operation interface through which a craftsman inputs performance data and transmits it to the server means.

[1182] The present invention is a system for collecting vital data and emotional data of craftsmen and optimizing their work time and travel time. The system includes the following main components:

[1183] System configuration

[1184] 1. Terminal means

[1185] Smartphones and wearable devices are used to collect vital data such as heart rate, stress levels, and sleep quality.

[1186] Emotional data such as the craftsman's facial expressions and tone of voice is collected through cameras and microphones.

[1187] 2. Server Means

[1188] Store data in AWS DynamoDB (cloud database).

[1189] Receive and store vital data and emotional data for each craftsman.

[1190] 3. Generative AI Algorithm Means

[1191] Based on the collected data, a generative AI algorithm is run to generate a schedule that includes optimal working hours and travel times for each worker.

[1192] 4. Means of notification

[1193] The optimized schedule is transmitted to the terminal means and notified to the craftsman.

[1194] 5. Improvement measures

[1195] The performance data input by the craftsman is sent to the server means and reanalyzed.

[1196] Program processing

[1197] Hardware and Software

[1198] Hardware: Wearable devices (heart rate monitors, stress sensors), cameras, microphones, factory robots

[1199] Software: Python, AWS DynamoDB (database), Emotion Engine (virtual emotion engine), VitalDataCollector (virtual data collection module)

[1200] Data collection and transmission

[1201] The terminal means collects vital data using a wearable device and analyzes and collects emotional data using the Emotion Engine. This data is sent from the terminal means to AWS DynamoDB and stored.

[1202] Schedule optimization

[1203] The server uses a generative AI algorithm to generate an optimal work schedule for each worker based on the received vital and emotional data. For example, if a worker's stress level is high or their emotional state is unstable, it will adjust the schedule by increasing their break time.

[1204] Schedule execution and notifications

[1205] The generated schedule is sent to the craftsman through the notification means, and the craftsman uses the terminal means to proceed with the work according to the schedule.

[1206] Performance data collection and reanalysis

[1207] After completing the work, the craftsman inputs the performance data using the terminal means and transmits it to the server means, which then analyzes the collected data to optimize the next schedule.

[1208] Examples and prompts

[1209] In the morning, craftsmen turn on their smartphones and wearable devices to collect vital data such as heart rate and stress level. At the same time, cameras and microphones are used to analyze facial expressions and tone of voice, collecting emotional data. This data is sent to a cloud server, which generates an optimal schedule. For example, a craftsman with a high heart rate and high stress level could be assigned lighter work in the morning and scheduled for longer breaks in the afternoon.

[1210] Prompt Sentence Examples

[1211] An assistant system that optimizes robot activity and worker health in factories. It uses wearable devices and an emotion recognition engine to collect health and emotion data, which is then sent to a cloud server to provide optimal work schedules.

[1212] Key functions: health and emotional data collection, data transmission and storage, schedule optimization, schedule notification and execution.

[1213] The introduction of this system will enable the optimization of the working environment, taking into account the health and emotional state of the workers.

[1214] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1215] Step 1:

[1216] The terminal means collects vital data and emotional data of the craftsman. Heart rate, stress level, and sleep quality are obtained from the wearable device, and facial expressions and tone of voice are analyzed via a camera and microphone. Input data includes heart rate, stress level, sleep quality, facial expressions, and tone of voice. This data is temporarily stored in the internal memory of the terminal means.

[1217] Step 2:

[1218] The terminal means sends the collected data to the server means. The inputs include vital data and emotion data obtained from the wearable device and emotion engine. The server means receives this data and stores it in AWS DynamoDB. It checks the data for consistency and filters out incomplete data and outliers.

[1219] Step 3:

[1220] The server executes the generation AI algorithm and generates an optimal work schedule based on the stored vital data and emotional data. The received vital data and emotional data are input. The generation AI algorithm analyzes this data and calculates the optimal schedule for each worker. The generated work schedule is obtained as output.

[1221] Step 4:

[1222] The server means transmits the generated schedule to the terminal means. The generated work schedule is input. The schedule is notified to the worker using the notification means and displayed on the terminal means. The worker checks the notified schedule and proceeds with the work.

[1223] Step 5:

[1224] After the process is completed, the user inputs the performance data using the terminal means. The input includes performance data for each task (start and end times of the task, actual travel time, etc.). The terminal means transmits this data to the server means.

[1225] Step 6:

[1226] Based on the performance data received by the server means, an analysis is performed for the next schedule optimization. The performance data sent after the work is completed is used as input. This allows for new schedule optimization that takes into account the health and emotional state of the craftsmen. An updated schedule optimization proposal is obtained as output.

[1227] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1228] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1229] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1230] [Fourth embodiment]

[1231] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1232] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1233] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1234] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1235] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1236] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1237] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1238] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1239] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1240] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1241] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1242] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1243] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1244] The present invention is a system for optimizing the working environment in the construction industry, and in particular, utilizes a generative AI algorithm to streamline work time and travel time while monitoring the health status of workers in real time. Specific embodiments of the present invention are described below.

[1245] System Overview

[1246] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, and an improvement means for reanalyzing.

[1247] Program processing overview

[1248] 1. Collecting and transmitting vital data

[1249] The terminal means collects vital data of the craftsman and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. The terminal means transmits this data to the server means via a dedicated application.

[1250] 2. Receipt and storage of data

[1251] The server receives the vital data transmitted from the terminal and stores it in a database. The server checks the integrity of the received data and filters out incomplete data and abnormal values.

[1252] 3. Schedule optimization

[1253] The server extracts the latest vital and work data from the database and uses a generating AI algorithm to calculate the optimal schedule, taking into account each worker's free time and travel time. The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition data.

[1254] 4. Schedule distribution and execution

[1255] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[1256] 5. Performance data collection and reanalysis

[1257] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[1258] Specific examples

[1259] Morning work

[1260] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[1261] Daytime work

[1262] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[1263] Evening work

[1264] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[1265] In this way, the system of the present invention aims to improve work efficiency while taking into account the health status of craftsmen, and achieves sustainable improvements in the working environment.

[1266] The processing flow will be explained below.

[1267] Step 1:

[1268] In the morning, the user launches the smartphone app and connects it to the wearable device, which then measures vital data (heart rate, stress level, sleep quality) in real time.

[1269] Step 2:

[1270] The device sends the collected vital data in a specific format to the server, which receives the vital data and temporarily stores it in a database.

[1271] Step 3:

[1272] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[1273] Step 4:

[1274] The server extracts the latest vital and operational data from the database, constructs a dataset for analysis, and runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time.

[1275] Step 5:

[1276] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[1277] Step 6:

[1278] The user moves efficiently according to the displayed schedule and begins work. After completing work at each site, the device sends the current status and vital data to the server.

[1279] Step 7:

[1280] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server.

[1281] Step 8:

[1282] The server reanalyzes the performance data and additional vital data to generate the optimal schedule and improvement proposals for the next day. The improvement proposals are then sent to the user's device overnight so that they can be prepared for the next day.

[1283] Step 9:

[1284] The next morning, users receive a new schedule that reflects the proposed improvements and can work efficiently again, resulting in a sustainable improvement in the working environment.

[1285] Example 1

[1286] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1287] In the traditional construction industry, it was difficult to monitor the health of workers in real time, resulting in overwork and health problems. Furthermore, work hours and travel time were not optimized, resulting in a decrease in overall efficiency. Furthermore, there were also problems with incomplete data and outliers affecting the system.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1289] In this invention, the server includes terminal means for collecting vital data of craftsmen, server means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the work hours and travel times of the craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing it, allocation means for allocating break times and work times taking into account the health status of the craftsmen based on the optimal schedule calculated by the generation AI algorithm means, and data consistency confirmation means for filtering out incomplete data and outliers. This makes it possible to provide an optimal work schedule while monitoring the health status of the craftsmen in real time, improving the working environment and increasing work efficiency.

[1290] "Terminal means" refers to devices that collect vital data of craftsmen and transmit it to the server. Specifically, this includes smartphones and wearable devices.

[1291] The term "server means" refers to a server system that receives and stores vital data transmitted from the terminal means and further analyzes the data.

[1292] "Generative AI Algorithm Means" refers to the algorithm used by the Server Means to analyze data and generate optimal schedules for each craftsman. The generative algorithm may include machine learning models and optimization techniques.

[1293] "Notification means" refers to a system for sending the generated schedule to the terminal means and notifying the craftsman. This includes push notification functions and messaging services.

[1294] "Improvement measures" refer to the means for reanalyzing the workforce's performance data and generating improvement plans for the next day, thereby continuously improving work efficiency and the health of the workforce.

[1295] The "data consistency checking means" refers to a means for checking the consistency of data received by the server means and filtering out incomplete data and abnormal values, thereby improving the reliability of the system.

[1296] The "allocation method" refers to the method for allocating break times and work hours of craftsmen based on the optimal schedule calculated by the generative AI algorithm. By taking into account the health status of craftsmen, we aim to improve the working environment.

[1297] "Vital data" refers to biometric data such as the worker's heart rate, stress level, and sleep quality, collected using wearable devices and other sensors.

[1298] "Display means" refers to a device for displaying the generated schedule, including the screen of a terminal means and a dedicated monitor.

[1299] The "user interface means" refers to an interface for transmitting performance data entered by a craftsman to the server means. Specifically, it includes a mobile application and a web interface.

[1300] The present invention relates to a system for optimizing the working environment in the construction industry. Specifically, the present invention provides a system that utilizes generative AI algorithms to monitor the health status of workers in real time and efficiently manage their work hours and travel time. Specific embodiments of the present invention are described below.

[1301] System Overview

[1302] The system consists of the following elements:

[1303] Terminal means for collecting vital data of craftsmen

[1304] Server means for receiving and storing vital data transmitted from the terminal means

[1305] A generative AI algorithm that analyzes the work hours and travel times of craftsmen and generates an optimal schedule

[1306] Notification means for transmitting the generated schedule to the terminal means

[1307] Improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it

[1308] Data integrity checks to filter incomplete data and outliers

[1309] A method of allocating break times and work hours that takes into account the health of workers

[1310] Hardware and software used

[1311] Terminal means:

[1312] Smartphone

[1313] Wearable devices (e.g., smartwatches)

[1314] Server means:

[1315] Database server (e.g. AWS RDS, Google Cloud SQL)

[1316] Data receiving server (e.g. Nginx, Apache)

[1317] Generative AI algorithm means:

[1318] Machine learning frameworks (e.g. TensorFlow, PyTorch)

[1319] Data analysis tools (e.g., Pandas, NumPy)

[1320] Means of notification:

[1321] Push notification service (e.g., Firebase Cloud Messaging)

[1322] Improvement measures:

[1323] Data reanalysis tools (e.g., Scikit-learn)

[1324] Data integrity verification methods:

[1325] Data cleaning tools (e.g., Python data manipulation libraries)

[1326] Placement means:

[1327] Scheduling algorithms (e.g., Google OR-Tools)

[1328] Example

[1329] Morning work

[1330] The user activates the smartphone and wearable device to collect vital data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[1331] Daytime work

[1332] The user starts work at each site, and the terminal device monitors the vital data of the craftsmen. The server device receives the data in real time and readjusts the schedule as necessary.

[1333] Evening work

[1334] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data to propose improvements for the next day and notifies them overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[1335] Example prompts for generative AI models

[1336] "Generate a schedule that optimally allocates break times and work times based on the worker's vital data and work data. The data includes: heart rate, stress level, sleep quality, and work performance data. Please propose the optimal schedule taking each data point into consideration."

[1337] By inputting this prompt into a generative AI model, the model can propose an efficient schedule. In this way, the system of the present invention aims to improve work efficiency while taking into account the health of the craftsmen, thereby achieving a sustainable improvement in the working environment.

[1338] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1339] Step 1: Collect and transmit vital data

[1340] Specific behavior:

[1341] A user wakes up in the morning and turns on their smartphone and wearable device, which measures vital data such as heart rate, stress level, and sleep quality in real time.

[1342] input:

[1343] Heart rate, stress levels, and sleep quality data from wearable devices.

[1344] Data processing and calculation:

[1345] The device collects this vital data, formats it (e.g., in JSON format) through a dedicated application, and sends it to a server.

[1346] output:

[1347] A request to the server containing vital data.

[1348] Step 2: Receiving and storing data

[1349] Specific behavior:

[1350] The server receives vital data sent from the device as an HTTP request, checks the integrity of the received data, and filters out incomplete data and abnormal values.

[1351] input:

[1352] Vital data sent from the device (JSON format).

[1353] Data processing and calculation:

[1354] Run a script to check the integrity of the incoming data and filter out any outliers or incomplete data (e.g., if the heart rate shows an obviously abnormal value).

[1355] output:

[1356] Vital data whose integrity has been confirmed is stored in a database.

[1357] Step 3: Optimize your schedule

[1358] Specific behavior:

[1359] The server extracts the latest vital and operational data from the database, and uses a generative AI algorithm to calculate the optimal schedule for each worker.

[1360] input:

[1361] Latest vital and operational data from the database.

[1362] Data processing and calculation:

[1363] The extracted data is input into a generative AI algorithm, which then allocates appropriate break times and work hours based on the worker's physical condition data. Specifically, modeling is done using TensorFlow and PyTorch, and input is done using prompt statements. Rules such as "allocate longer breaks to workers with unstable heart rates" are applied.

[1364] output:

[1365] Optimized schedule.

[1366] Step 4: Schedule distribution and execution

[1367] Specific behavior:

[1368] The server sends the generated schedule to the terminal. The user checks the received schedule on the terminal and starts moving and working according to the instructions.

[1369] input:

[1370] Generated schedule.

[1371] Data processing and calculation:

[1372] The generated schedule is converted into an appropriate notification format and sent to the device using a push notification service such as Firebase Cloud Messaging.

[1373] output:

[1374] Schedule displayed in device notifications.

[1375] Step 5: Collect performance data and reanalyze

[1376] Specific behavior:

[1377] After completing a task, the user inputs performance data through a dedicated application, and the terminal sends this data to the server, which receives the performance data and stores it in a database.

[1378] input:

[1379] Work performance data entered by craftsmen.

[1380] Data processing and calculation:

[1381] The received performance data is analyzed and re-analyzed to generate schedule improvement proposals for the next day. Specifically, the data is re-analyzed using tools such as Scikit-learn to gain new insights.

[1382] output:

[1383] The schedule is updated based on the proposed improvements. Based on this data, the updated schedule is notified to the user the next morning.

[1384] (Application example 1)

[1385] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1386] By monitoring the health status of employees in real time and providing appropriate work instructions, it is necessary to improve work efficiency in factories and optimize employee health management and workload. With conventional systems, it was difficult to provide work instructions while adequately monitoring the health status of employees, resulting in health problems and reduced work efficiency.

[1387] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1388] In this invention, the server includes terminal means for collecting vital data, means for receiving and storing the vital data transmitted from the terminal means, generation AI algorithm means for analyzing the vital data and working hours by the server means to generate an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means and notifying the same, robot means for providing appropriate work instructions based on the employee's vital data, notification means for the robot means to provide the employee with work instructions in real time, and improvement means for transmitting employee performance data from the terminal means to the server means, reanalyzing the data, and generating improvement proposals. This enables efficient work instructions and schedule management that takes employee health conditions into consideration.

[1389] "Terminal means" refers to a device or equipment that collects employee vital data and transmits it to a server.

[1390] "Server Means" refers to a server that receives and stores vital data transmitted from Terminal Means, and analyzes and processes the data based on the data.

[1391] The "generative AI algorithm means" is an artificial intelligence algorithm that analyzes vital data and working hours to generate an optimal schedule.

[1392] The "notification means" is a device or software that has the function of transmitting schedules and work instructions generated by the server means to the terminal means or robot means and notifying them.

[1393] "Robotic means" refers to an autonomous or remotely controlled robot that provides appropriate work instructions based on an employee's vital data.

[1394] The "improvement means" refers to a method or device for transmitting employee performance data from the terminal means to the server means, and for reanalyzing and generating improvement proposals based on that data.

[1395] "Vital data" refers to physiological data that indicates an employee's health status, such as heart rate, stress level, and body temperature.

[1396] A "generated schedule" is an optimal work plan for each employee created based on data analyzed by a generative AI algorithm.

[1397] "Performance data" refers to data that records the history and results of work performed by employees.

[1398] This invention is a system that monitors the health status of employees in a factory in real time and provides optimal work instructions. The system is composed of a terminal means for collecting vital data, a server means for receiving and storing the data, a generating AI algorithm means, a notification means, a robot means, and an improvement means. Specific embodiments are described below.

[1399] Hardware Configuration

[1400] 1. Use wearable devices (e.g., smart watches or smart bands) worn by employees as terminals. These wearable devices collect vital data such as heart rate, stress level, and body temperature and send it to a server.

[1401] 2. Prepare a high-performance server and use a database system (e.g., MySQL, PostgreSQL) to store the collected vital data. Install appropriate software (e.g., Python, TensorFlow) to analyze the data.

[1402] 3. As software for the generative AI algorithm, a generative AI model will be developed using Python and TensorFlow, which will analyze vital data and business data to generate an optimal schedule.

[1403] 4. As a notification means, the server has the function of sending the generated schedule and work instructions to the terminal means and robot means, using a communication protocol (e.g., HTTP, MQTT).

[1404] 5. Robotic means include autonomous or remotely controlled robots in factories that provide appropriate work instructions in real time based on employees' vital signs.

[1405] 6. As an improvement measure, the performance data recorded by the employee is sent from the terminal means to the server means, and the server analyzes the data again and generates an improvement plan for the next day.

[1406] Software Configuration

[1407] The server uses Python and TensorFlow to build a generative AI model and calculate a health score. As an example, we use the following prompt:

[1408] Prompt Sentence Examples

[1409] Employee Health:

[1410] Heart rate: 75 BPM

[1411] Stress level: 0.4

[1412] Body temperature: 36.7°C

[1413] Steps: 500

[1414] Use this data to assess your employees' current health scores and generate their next work orders.

[1415] The server analyzes the collected vital data in real time and evaluates the employee's health status. The generative AI model calculates a health score based on this data and generates an optimal work schedule. The generated schedule and work instructions are sent to the terminal means and robot means via notification means. In addition, performance data recorded by employees is sent to the server and used for reanalysis as a means of improvement.

[1416] In this way, the system of the present invention provides efficient work instructions while monitoring the health status of employees, thereby improving work efficiency within the factory and employee health management.

[1417] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1418] Step 1:

[1419] Collection of vital data

[1420] The wearable device, which serves as a terminal means, collects vital data such as the heart rate, stress level, and body temperature of the employee who is the user.

[1421] Input: Keiryochi's vital data (heart rate, stress level, body temperature)

[1422] Output: Collected vital data

[1423] Step 2:

[1424] Sending vital data

[1425] The terminal device sends the collected vital data to the server using HTTP or MQTT as the communication protocol.

[1426] Input: Collected vital data

[1427] Output: Vital data received on the server side

[1428] Step 3:

[1429] Receiving and storing vital data and business data

[1430] The server means receives the vital data sent from the terminal means and stores it in a database, such as MySQL or PostgreSQL, using SQL statements.

[1431] Input: Vital data received from the terminal means

[1432] Output: Vital data stored in a database

[1433] Step 4:

[1434] Data analysis and health score calculation

[1435] The server analyzes the vital data acquired by the AI ​​algorithm and calculates a health score for each employee. The AI ​​model uses TensorFlow and is processed using a Python script. The health score is expressed in a range from 0 to 1.

[1436] Input: Vital data stored in the database

[1437] Output: Calculated health score

[1438] Step 5:

[1439] Schedule optimization

[1440] The server generates an optimal schedule for each employee using the health score calculated by the generative AI algorithm, which is implemented in Python and adjusts work priorities and break times based on the employee's health status.

[1441] Input: Calculated Health Score

[1442] Output: The generated optimal schedule

[1443] Step 6:

[1444] Schedule and work order notifications

[1445] The server unit transmits the generated schedule and work instructions to the terminal unit and the robot unit, and notifies the employee of the schedule and work instructions. Notification methods include display on a wearable device and voice notification from the robot.

[1446] Input: Generated optimal schedule and work instructions

[1447] Output: Schedules and work instructions sent to terminal and robotic means

[1448] Step 7:

[1449] Collection of work performance data

[1450] After the user has completed the work, he or she inputs performance data through the terminal means, which includes the work content, completion time, and the like.

[1451] Input: Actual data after work is completed

[1452] Output: Actual data entered into the terminal means

[1453] Step 8:

[1454] Sending and storing performance data

[1455] The terminal means transmits the input work performance data to the server means, which then stores it in a database.

[1456] Input: Actual data sent from the terminal means

[1457] Output: Actual data stored in the database

[1458] Step 9:

[1459] Reanalysis and generation of improvement proposals

[1460] The server performs re-analysis based on the saved performance data and generates improvement proposals for the next day. The AI ​​model is used again for the re-analysis and generation of improvement proposals.

[1461] Input: Actual data stored in the database

[1462] Output: Generated improvement suggestions

[1463] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1464] The present invention is a system for optimizing the working environment in the construction industry, and utilizes a generative AI algorithm to improve the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[1465] System Overview

[1466] This system consists of a terminal means for collecting vital data of craftsmen, a server means for receiving and storing vital data and work performance data, an algorithm means for calculating the optimal schedule using a generative AI algorithm, a notification means, an improvement means, and an emotion engine for recognizing the user's emotions.

[1467] Program processing overview

[1468] 1. Collecting vital and emotional data

[1469] The terminal means collects the worker's vital data and transmits it to the server means. Specifically, data such as heart rate, stress level, and sleep quality are measured in real time using a smartphone or wearable device. In addition, the emotion engine analyzes the worker's facial expressions and tone of voice to collect emotional data. This data is transmitted from the terminal means to the server means.

[1470] 2. Receipt and storage of data

[1471] The server receives the vital data and emotion data sent from the terminal and stores the data in a database. The server checks the consistency of the received data and filters out incomplete data and abnormal values.

[1472] 3. Schedule optimization

[1473] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generating AI algorithm to calculate the optimal schedule that takes into account each worker's free time and travel time.The generating AI algorithm then appropriately allocates break times and work hours based on the worker's physical condition and emotional data.

[1474] 4. Schedule distribution and execution

[1475] The server means transmits the generated schedule to the terminal means and notifies the craftsmen. The craftsmen check the schedule for the day through the terminal means and move and work efficiently according to the instructions.

[1476] 5. Performance data collection and reanalysis

[1477] After the work is completed, the craftsman inputs the performance data using the terminal means and transmits it to the server means. The server means generates an improvement plan for the next day based on the performance data and notifies the worker at night.

[1478] Specific examples

[1479] Morning work

[1480] The user activates the smartphone and wearable device to collect vital data. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to collect emotional data. The terminal means transmits this data to the server means. The server means analyzes the received data, generates an optimal schedule for that day, and transmits it to the terminal means. The user then travels to the site according to the displayed schedule.

[1481] Daytime work

[1482] The user starts work at each site, and the terminal device monitors the vital data and emotional data of the craftsman. The server device receives the data in real time and readjusts the schedule as necessary.

[1483] Evening work

[1484] After completing a task, the user uses the terminal means to input the work results and send them to the server means. The server means analyzes the results data and additional vital data and emotion data to propose improvements for the next day and notifies the user overnight. The next morning, the user receives a new schedule that reflects the improvements, allowing them to work efficiently again.

[1485] Through this detailed program processing, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[1486] The processing flow will be explained below.

[1487] Step 1:

[1488] In the morning, the user launches the smartphone app and connects it to the wearable device. The smartphone then measures vital data (heart rate, stress level, sleep quality) in real time through the wearable device. The emotion engine also analyzes the user's facial expressions and tone of voice to collect emotional data.

[1489] Step 2:

[1490] The device sends the collected vital data and emotional data in a specific format to a server, which receives the vital data and emotional data sent from the device and temporarily stores them in a database.

[1491] Step 3:

[1492] The server checks the data received for consistency and completeness, identifies incomplete data and outliers, and stores the validated data in a database, ready for analysis.

[1493] Step 4:

[1494] The server extracts the latest vital signs, emotional data, and work data from the database and builds a dataset for analysis. It then runs a generative AI algorithm to generate an optimal schedule for each worker, taking into account their free time and travel time. The generative AI also uses the workers' physical condition and emotional data to appropriately allocate break times and work hours.

[1495] Step 5:

[1496] The server sends the generated schedule to the user's terminal, which notifies the user of the new schedule and displays detailed task information.

[1497] Step 6:

[1498] The user moves efficiently according to the displayed schedule and begins work. While working at each site, the device continues to monitor vital and emotional data and transmits this data to the server in real time.

[1499] Step 7:

[1500] The server receives real-time vital and emotional data and adjusts the schedule as needed. For example, if a worker is tired, the AI ​​will insert appropriate breaks.

[1501] Step 8:

[1502] After the user completes the work, they input the work performance data (work completion status, on-site situation) from the terminal and send it to the server. The emotion engine also detects the user's emotional state for that day and collects the data.

[1503] Step 9:

[1504] The server reanalyzes the performance data, vital data, and emotional data to generate an optimal schedule and improvement proposals for the next day. The improvement proposals include schedule adjustments that reduce psychological fatigue based on the user's emotional state.

[1505] Step 10:

[1506] The server notifies the user's device of the improvement proposals and schedules it generated overnight. The next morning, the user receives a new schedule that reflects the improvement proposals, allowing them to work efficiently again.

[1507] Through the detailed program processing described above, the system of the present invention aims to improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[1508] Example 2

[1509] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1510] There is a need to improve the working environment by understanding the health and emotional state of workers in real time and optimizing work and travel time based on that information. However, previous systems did not optimize schedules by fully considering the health and emotional state of workers, making it difficult to carry out work efficiently.

[1511] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI model means for analyzing the vital data and emotional data of craftsmen by the server means and generating an optimal schedule, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for transmitting the performance data of craftsmen from the terminal means to the server means and reanalyzing it. This makes it possible to optimize schedules based on the health and emotional states of craftsmen, thereby realizing continuous improvement of the working environment.

[1512] "Terminal means" refers to a device for collecting vital data and emotional data of craftsmen and transmitting them to a server.

[1513] "Server means" refers to a computer system for receiving, storing, and analyzing vital data and emotional data transmitted from terminal means.

[1514] "Generative AI model means" refers to an artificial intelligence algorithm for generating an optimal schedule for each craftsman based on data collected by the server means.

[1515] The "notification means" refers to a mechanism for transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[1516] "Improvement means" refers to a mechanism for transmitting the craftsman's performance data from the terminal means to the server means and for reanalysis.

[1517] "Vital data" refers to various indicators that show the health status of craftsmen, such as their heart rate, stress level, and sleep quality.

[1518] "Emotional data" refers to data that indicates the emotional state of the craftsman, such as facial expression analysis and tone of voice analysis data of the craftsman.

[1519] "Schedule" refers to a plan to optimize the work and travel time of craftsmen.

[1520] "Performance data" refers to data that records the actual work content and time performed by craftsmen.

[1521] The present invention is a system for improving the efficiency of work time and travel time while monitoring the health and emotional state of workers in real time. Specific embodiments of the present invention are described below.

[1522] System Overview

[1523] This system consists of a terminal means for collecting vital data and emotional data of craftsmen, a server means for receiving and storing vital data and emotional data, an algorithm means for calculating the optimal schedule using a generative AI model, a notification means, and an improvement means.

[1524] Hardware and software used

[1525] Hardware

[1526] Smartphones (e.g., general smartphone devices)

[1527] Wearable devices (e.g., common fitness trackers)

[1528] software

[1529] Vital data collection apps (e.g., health management applications)

[1530] Emotion engines (e.g., facial expression analysis software)

[1531] Databases (e.g., common relational database systems)

[1532] Program processing overview

[1533] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data. The collected data is sent from the terminal to the server. Data is collected with the prompt, "Please measure your heart rate."

[1534] The server receives and stores the vital data and emotion data sent from the device. After checking the integrity of the received data and filtering out incomplete data and outliers, the server stores the data in a database. The server executes data saving with the prompt "Please save the data."

[1535] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate an optimal schedule that takes into account each worker's free time and travel time. The generative AI model appropriately allocates break times and work hours based on the worker's physical condition and emotional data. Schedule generation begins with the prompt, "Please generate the optimal schedule."

[1536] The server sends the generated schedule to the terminal and notifies the user. The user checks the schedule for the day through the terminal and moves and works efficiently according to the instructions. The schedule is confirmed with the prompt "Please check today's schedule."

[1537] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotional data to propose improvements for the next day and notifies them overnight. Data input is performed with the prompt "Please enter performance data."

[1538] Through this detailed program processing, the system of the present invention can improve work efficiency while taking into account the health and emotional state of the craftsman, thereby achieving a sustainable improvement in the working environment.

[1539] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1540] Step 1:

[1541] Collection of vital and emotional data

[1542] The terminal collects the worker's vital and emotional data. Specifically, the worker wears a smartphone and a wearable device to measure vital data such as heart rate, stress level, and sleep quality in real time. At the same time, the emotion engine analyzes the worker's facial expressions and tone of voice to obtain emotional data.

[1543] Input: Physical metrics (heart rate, stress level, sleep quality) and audio and facial expression data.

[1544] Output: The acquired vital and emotional data.

[1545] How it works: When a worker arrives at a job site, their heart rate and stress level are automatically measured using a smartphone and wearable device, while an emotion engine analyzes their voice and facial expressions in real time.

[1546] Step 2:

[1547] Receiving and storing data

[1548] The server receives the vital and emotional data sent from the device and stores them in a database. The server checks the integrity of the received data and filters out incomplete data and outliers.

[1549] Input: Vital and emotional data sent from the device.

[1550] Output: The filtered database entries.

[1551] Specific operation: The server receives data in real time, removes data that falls outside the range of abnormal values, and then stores the data in a database in a standard format.

[1552] Step 3:

[1553] Data analysis and schedule optimization

[1554] The server extracts the latest vital data, emotional data, and work data from the database, and uses a generative AI model to calculate the optimal schedule that takes into account each worker's free time and travel time.

[1555] Input: Latest vital, emotional and operational data extracted from the database.

[1556] Output: The optimized schedule.

[1557] How it works: The server inputs data into the generative AI model, and the AI ​​algorithm analyzes each worker's physical condition and work data, resulting in the creation of an optimal work schedule.

[1558] Step 4:

[1559] Schedule distribution and execution

[1560] The server sends the generated schedule to the terminal and notifies the user. The user can check the schedule for the day through the terminal and move and work efficiently according to the instructions.

[1561] Input: The generated schedule.

[1562] Output: User notification and confirmed schedule.

[1563] Specific operation: The server sends the generated schedule to the terminal via WiFi, and a notification is displayed on the craftsman's smartphone. The craftsman checks the schedule on his smartphone and proceeds to the site.

[1564] Step 5:

[1565] Collection and reanalysis of performance data

[1566] After completing a task, the user inputs the work performance data using a terminal and sends it to the server. The server analyzes the performance data, additional vital data, and emotion data to propose improvements for the next day and notifies the user overnight.

[1567] Input: Work performance data and additional vital and emotional data submitted by the user.

[1568] Output: Improvement proposals and new schedule for the next day.

[1569] How it works: When a worker finishes a task, he or she enters the results data into a smartphone app. The server receives and analyzes this data, generates a new schedule, and notifies the worker overnight.

[1570] This is the flow of the system's program processing, which allows for efficient and sustainable optimization of work schedules while taking into account the health and emotional state of the workers.

[1571] (Application example 2)

[1572] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1573] This invention is a system that efficiently manages work hours and travel time while monitoring the health and emotional state of craftsmen in real time in order to optimize the work environment of craftsmen. Conventional labor management systems are limited to collecting vital data and do not support schedule optimization that takes into account the emotional state of craftsmen. This makes it difficult to reduce stress and improve productivity for craftsmen.

[1574] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes terminal means for collecting vital data and emotional data of craftsmen, server means for receiving and storing the vital data and emotional data transmitted from the terminal means, generation AI algorithm means for generating an optimal schedule including the craftsmen's work hours and travel times in the server means, notification means for transmitting the schedule generated by the server means to the terminal means, and improvement means for collecting craftsmen's performance data and transmitting it to the server means for reanalysis. This makes it possible to optimize the working environment taking into account the craftsmen's health and emotional state.

[1575] A "craftsman" is a skilled worker who performs work in a factory or on a construction site.

[1576] "Vital data" refers to data that indicates the physiological state of the craftsman, such as heart rate, stress level, and sleep quality.

[1577] "Emotional data" is data used to measure the emotional state of a craftsman, such as facial expressions and tone of voice.

[1578] "Terminal means" refers to equipment that collects vital data and emotional data and transmits them to a server, and includes smartphones and wearable devices.

[1579] The "server means" is a system that receives, stores, and analyzes data sent from the terminal means.

[1580] The "generative AI algorithm means" is an algorithm that generates an optimal schedule, including the work hours and travel times of craftsmen, based on the collected data.

[1581] The "notification means" is a system having a function of transmitting the schedule generated by the server means to the terminal means and notifying the craftsmen.

[1582] The "improvement means" is a method or device for transmitting the performance data entered by the craftsman to the server means and for reanalyzing the data.

[1583] The "display means" is a device for visually presenting the generated schedule to the craftsman, and includes a display or monitor.

[1584] The "user interface means" is an operation interface through which a craftsman inputs performance data and transmits it to the server means.

[1585] The present invention is a system for collecting vital data and emotional data of craftsmen and optimizing their work time and travel time. The system includes the following main components:

[1586] System configuration

[1587] 1. Terminal means

[1588] Smartphones and wearable devices are used to collect vital data such as heart rate, stress levels, and sleep quality.

[1589] Emotional data such as the craftsman's facial expressions and tone of voice is collected through cameras and microphones.

[1590] 2. Server Means

[1591] Store data in AWS DynamoDB (cloud database).

[1592] Receive and store vital data and emotional data for each craftsman.

[1593] 3. Generative AI Algorithm Means

[1594] Based on the collected data, a generative AI algorithm is run to generate a schedule that includes optimal working hours and travel times for each worker.

[1595] 4. Means of notification

[1596] The optimized schedule is transmitted to the terminal means and notified to the craftsman.

[1597] 5. Improvement measures

[1598] The performance data input by the craftsman is sent to the server means and reanalyzed.

[1599] Program processing

[1600] Hardware and Software

[1601] Hardware: Wearable devices (heart rate monitors, stress sensors), cameras, microphones, factory robots

[1602] Software: Python, AWS DynamoDB (database), Emotion Engine (virtual emotion engine), VitalDataCollector (virtual data collection module)

[1603] Data collection and transmission

[1604] The terminal means collects vital data using a wearable device and analyzes and collects emotional data using the Emotion Engine. This data is sent from the terminal means to AWS DynamoDB and stored.

[1605] Schedule optimization

[1606] The server uses a generative AI algorithm to generate an optimal work schedule for each worker based on the received vital and emotional data. For example, if a worker's stress level is high or their emotional state is unstable, it will adjust the schedule by increasing their break time.

[1607] Schedule execution and notifications

[1608] The generated schedule is sent to the craftsman through the notification means, and the craftsman uses the terminal means to proceed with the work according to the schedule.

[1609] Performance data collection and reanalysis

[1610] After completing the work, the craftsman inputs the performance data using the terminal means and transmits it to the server means, which then analyzes the collected data to optimize the next schedule.

[1611] Examples and prompts

[1612] In the morning, craftsmen turn on their smartphones and wearable devices to collect vital data such as heart rate and stress level. At the same time, cameras and microphones are used to analyze facial expressions and tone of voice, collecting emotional data. This data is sent to a cloud server, which generates an optimal schedule. For example, a craftsman with a high heart rate and high stress level could be assigned lighter work in the morning and scheduled for longer breaks in the afternoon.

[1613] Prompt Sentence Examples

[1614] An assistant system that optimizes robot activity and worker health in factories. It uses wearable devices and an emotion recognition engine to collect health and emotion data, which is then sent to a cloud server to provide optimal work schedules.

[1615] Key functions: health and emotional data collection, data transmission and storage, schedule optimization, schedule notification and execution.

[1616] The introduction of this system will enable the optimization of the working environment, taking into account the health and emotional state of the workers.

[1617] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1618] Step 1:

[1619] The terminal means collects vital data and emotional data of the craftsman. Heart rate, stress level, and sleep quality are obtained from the wearable device, and facial expressions and tone of voice are analyzed via a camera and microphone. Input data includes heart rate, stress level, sleep quality, facial expressions, and tone of voice. This data is temporarily stored in the internal memory of the terminal means.

[1620] Step 2:

[1621] The terminal means sends the collected data to the server means. The inputs include vital data and emotion data obtained from the wearable device and emotion engine. The server means receives this data and stores it in AWS DynamoDB. It checks the data for consistency and filters out incomplete data and outliers.

[1622] Step 3:

[1623] The server executes the generation AI algorithm and generates an optimal work schedule based on the stored vital data and emotional data. The received vital data and emotional data are input. The generation AI algorithm analyzes this data and calculates the optimal schedule for each worker. The generated work schedule is obtained as output.

[1624] Step 4:

[1625] The server means transmits the generated schedule to the terminal means. The generated work schedule is input. The schedule is notified to the worker using the notification means and displayed on the terminal means. The worker checks the notified schedule and proceeds with the work.

[1626] Step 5:

[1627] After the process is completed, the user inputs the performance data using the terminal means. The input includes performance data for each task (start and end times of the task, actual travel time, etc.). The terminal means transmits this data to the server means.

[1628] Step 6:

[1629] Based on the performance data received by the server means, an analysis is performed for the next schedule optimization. The performance data sent after the work is completed is used as input. This allows for new schedule optimization that takes into account the health and emotional state of the craftsmen. An updated schedule optimization proposal is obtained as output.

[1630] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1631] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1632] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1633] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1634] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1635] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1636] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1637] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1638] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1639] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1640] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1641] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1642] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1643] 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.

[1644] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1645] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1646] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1647] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1648] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1649] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1650] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1651] The following is further disclosed regarding the above embodiment.

[1652] (Claim 1)

[1653] A terminal means for collecting vital data of craftsmen;

[1654] a server means for receiving and storing the vital data transmitted from the terminal means;

[1655] a generating AI algorithm means for analyzing the work hours and travel times of craftsmen in the server means and generating an optimal schedule;

[1656] notification means for transmitting the schedule generated by the server means to the terminal means;

[1657] an improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing the data;

[1658] A system including:

[1659] (Claim 2)

[1660] 10. The system of claim 1, wherein the vital data includes heart rate, stress level, and sleep quality.

[1661] (Claim 3)

[1662] 2. The system according to claim 1, further comprising a display means for displaying the generated schedule, and a user interface means for transmitting performance data input by a craftsman to the server means.

[1663] "Example 1"

[1664] (Claim 1)

[1665] A terminal means for collecting vital data of craftsmen;

[1666] a server means for receiving and storing the vital data transmitted from the terminal means;

[1667] a generating AI algorithm means for analyzing the work hours and travel times of craftsmen in the server means and generating an optimal schedule;

[1668] notification means for transmitting the schedule generated by the server means to the terminal means;

[1669] an improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing the data;

[1670] an allocation means for allocating break times and work times based on the optimal schedule calculated by the generating AI algorithm means, taking into consideration the health status of the workers;

[1671] a data integrity checker that filters out incomplete data and outliers;

[1672] A system including:

[1673] (Claim 2)

[1674] 10. The system of claim 1, wherein the vital data includes heart rate, stress level, and sleep quality.

[1675] (Claim 3)

[1676] 2. The system according to claim 1, further comprising a display means for displaying the generated schedule, and a user interface means for transmitting performance data input by a craftsman to the server means.

[1677] "Application Example 1"

[1678] (Claim 1)

[1679] A terminal means for collecting vital data;

[1680] a server means for receiving and storing the vital data transmitted from the terminal means;

[1681] a generating AI algorithm means for analyzing vital data and working hours in the server means and generating an optimal schedule;

[1682] means for transmitting and notifying the schedule generated by said server means to said terminal means;

[1683] A robotic means for providing appropriate work instructions based on the vital data of employees;

[1684] notification means for the robot means to provide real-time work instructions to the employee;

[1685] an improvement means for transmitting the employee performance data from the terminal means to the server means, and for reanalyzing and generating improvement proposals;

[1686] A system including:

[1687] (Claim 2)

[1688] 2. The system of claim 1, wherein the vital data includes heart rate, stress level, and body temperature.

[1689] (Claim 3)

[1690] 2. The system according to claim 1, further comprising a display means for displaying the generated schedule and work instructions, and a user interface means for transmitting performance data input by an employee to the server means.

[1691] "Example 2: Combining Emotion Engines"

[1692] (Claim 1)

[1693] a terminal means for collecting vital data and emotional data of the craftsman;

[1694] a server means for receiving and storing the vital data and emotion data transmitted from the terminal means;

[1695] a generating AI model means for analyzing vital data and emotional data of craftsmen in the server means and generating an optimal schedule;

[1696] notification means for transmitting the schedule generated by the server means to the terminal means;

[1697] an improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing the data;

[1698] A system including:

[1699] (Claim 2)

[1700] 2. The system of claim 1, wherein the vital data includes heart rate, stress level, and sleep quality, and the emotional data includes facial expression analysis and tone of voice analysis data.

[1701] (Claim 3)

[1702] 2. The system according to claim 1, further comprising a display means for displaying the generated schedule, and a user interface means for transmitting performance data input by a craftsman to the server means.

[1703] "Application example 2 when combining emotion engines"

[1704] (Claim 1)

[1705] a terminal means for collecting vital data and emotional data of the craftsman;

[1706] a server means for receiving and storing the vital data and emotion data transmitted from the terminal means;

[1707] a generating AI algorithm means for generating an optimal schedule including work hours and travel times of craftsmen in the server means;

[1708] notification means for transmitting the schedule generated by the server means to the terminal means;

[1709] an improvement means for collecting craftsman performance data and transmitting it to a server means for reanalysis;

[1710] A system including:

[1711] (Claim 2)

[1712] Vital data includes heart rate, stress level and sleep quality.

[1713] 10. The system of claim 1, wherein the emotional data includes facial expressions and tone of voice.

[1714] (Claim 3)

[1715] 2. The system according to claim 1, further comprising a display means for displaying the generated schedule, and a user interface means for transmitting performance data input by the craftsman to the server means. [Explanation of symbols]

[1716] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal means for collecting vital data of craftsmen; a server means for receiving and storing the vital data transmitted from the terminal means; a generating AI algorithm means for analyzing the work hours and travel times of craftsmen in the server means and generating an optimal schedule; notification means for transmitting the schedule generated by the server means to the terminal means; an improvement means for transmitting the performance data of the craftsmen from the terminal means to the server means and reanalyzing the data; A system including:

2. The system of claim 1 , wherein the vital data includes heart rate, stress level, and sleep quality.

3. 2. The system according to claim 1, further comprising a display means for displaying the generated schedule, and a user interface means for transmitting performance data input by the craftsman to the server means.

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