System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting specification data of a pole, a means for inputting specification data of an antenna, a means for transmitting the inputted data to a server, a means for collating an internal database based on the transmitted data and acquiring strength characteristics of the pole, a means for evaluating the possibility of mounting the antenna based on the acquired strength characteristics, a means for returning an evaluation result to a user terminal, and a means for displaying the evaluation result on the terminal.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] In recent years, advances in communications technology have led to an increasing number of antennas being mounted on concrete poles. However, if the weight of the antennas being mounted and the loads caused by wind pressure are not properly evaluated, there is a risk that the concrete poles will be insufficiently strong and will be compromised. This can reduce the stability of the entire system and pose a risk of the collapse of important communications infrastructure. Therefore, there is a need for a tool that can easily and quickly evaluate the strength of concrete poles and determine whether appropriate antenna mounting is possible. [Means for solving the problem]

[0005] The present invention is a system that includes a means for inputting concrete pole specification data and antenna specification data, a means for transmitting the input data to a server, a means for comparing the transmitted data with an internal database to acquire the strength characteristics of the concrete pole, a means for evaluating the feasibility of antenna installation based on the acquired strength characteristics, a means for returning the evaluation results to a user terminal, and a means for displaying the evaluation results on the terminal. This system allows users to quickly and accurately determine the safety of concrete poles, thereby enabling appropriate antenna installation. This improves the stability and safety of communication infrastructure.

[0006] "Concrete pole specification data" refers to information regarding the material, length, and diameter of the concrete pole.

[0007] "Antenna specification data" refers to information regarding the weight and wind pressure coefficient of the antenna.

[0008] "Input means" refers to an interface or device through which a user inputs data.

[0009] A "server" is a central computer that receives, processes, and transmits data.

[0010] An "internal database" is a database for storing various data stored within the server.

[0011] "Strength characteristics" refers to the physical load-bearing capacity and structural characteristics of concrete pillars.

[0012] "Means for assessing mountability" means an algorithm or process for calculating and determining whether an antenna can be properly attached to a concrete pole.

[0013] "Evaluation results" refers to the final conclusion or judgment based on the evaluation of feasibility.

[0014] "User terminal" refers to a device that allows a user to operate the system, input data, and check evaluation results.

[0015] The "display means" refers to a display or monitor for visually presenting the evaluation results to the user. [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] MODE FOR CARRYING OUT THE INVENTION

[0038] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of the system will be described in detail below.

[0039] System Configuration

[0040] The system mainly consists of the following components:

[0041] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[0042] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[0043] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[0044] Data Entry

[0045] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[0046] Data transmission

[0047] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[0048] Database collation

[0049] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[0050] strength calculation

[0051] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[0052] Returning results

[0053] The server returns the results of the strength calculation to the terminal, including an evaluation such as "Installable," "Reinforcement required," or "Cannot be installed."

[0054] Results display

[0055] The terminal then displays the received results to the user. The user interface visually displays the evaluation results and provides guidance on appropriate actions, such as whether the antenna can be installed, whether reinforcement is required, or whether installation is impossible.

[0056] Specific usage scenarios

[0057] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the specifications of the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to the server, which retrieves strength characteristic data from its internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can check this result on the terminal and proceed with the antenna installation work with peace of mind.

[0058] In this way, the system of the present invention can quickly and accurately examine the strength of concrete pillars, contributing to ensuring the safety and stability of communication infrastructure.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[0062] Step 2:

[0063] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[0064] json

[0065] {

[0066] "material": "iron",

[0067] "length": "10",

[0068] "diameter": "30",

[0069] "antenna_weight": "15",

[0070] "wind_coefficient": "1.2"

[0071] }

[0072] Step 3:

[0073] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for subsequent processing.

[0074] Step 4:

[0075] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[0076] sql

[0077] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[0078] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[0079] Step 5:

[0080] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding up the antenna's weight and wind pressure load. Specifically, the antenna's weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation yields the total load.

[0081] Step 6:

[0082] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[0083] Step 7:

[0084] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[0085] json

[0086] {

[0087] "result": "Installable"

[0088] }

[0089] Step 8:

[0090] The device analyzes the evaluation results received from the server and displays them on the user interface. The user can check the results on the device screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation work with peace of mind.

[0091] These steps allow the user to quickly and accurately assess the strength of the concrete pole and install the appropriate antenna.

[0092] Example 1

[0093] 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."

[0094] Previously, strength assessments for installing antennas on concrete poles were often done manually, which was time-consuming and involved the risk of calculation errors. Furthermore, there was a need for efficient processing of a variety of input data to quickly and accurately assess strength, but no system with these functions existed.

[0095] 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.

[0096] In this invention, the server includes means for receiving specification data for the concrete pole and the antenna input by the user, means for converting the input specification data into JSON or XML format, means for transmitting the converted data to the server, means for the server to compare the received data with an internal database and obtain strength characteristic data for the concrete pole, means for evaluating the feasibility of installing the antenna based on the obtained strength characteristic data, means for converting the evaluation results into JSON or XML format and returning them to the user terminal, and means for the user terminal to visually display the evaluation results and provide appropriate guidelines to the user. This enables complex and time-consuming strength evaluation work to be performed quickly and accurately, ensuring the safety and stability of the communication infrastructure.

[0097] A "user" is a person or organization that operates the system and inputs the required data.

[0098] A "terminal" is a device, such as a computer, smartphone, or tablet, that a user uses to enter data and view results.

[0099] A "server" is a central computer that receives data, checks it against an internal database, performs calculations, and returns the results.

[0100] "Specification data" refers to basic characteristic information about the concrete pole and antenna (material, length, diameter, weight, wind pressure coefficient, etc.).

[0101] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and is a concise, easy-to-read text format for structuring data.

[0102] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structuring and flexibly describing data.

[0103] The "internal database" is a database system for processing various data (such as strength characteristic data) stored in the server.

[0104] "Strength characteristic data" refers to data regarding the physical strength of a concrete pillar, calculated based on its material, length, diameter, etc.

[0105] "Attachability" is a criterion for assessing whether an antenna can be safely attached to a concrete pole.

[0106] A "user interface" is a screen display or input means that allows a user to input data and check the results.

[0107] An "HTTP request" is a request for data transmission made from a terminal to a server.

[0108] An "HTTP response" is a data response sent back from a server to a terminal.

[0109] "Visual display" means presenting data and evaluation results on the screen in a way that is intuitively easy for users to understand.

[0110] MODE FOR CARRYING OUT THE INVENTION

[0111] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of this system are described below.

[0112] System Configuration

[0113] The system mainly consists of the following components:

[0114] 1. User terminal: A device that allows users to input data and display results. This includes personal computers, smartphones, tablets, etc.

[0115] 2. Server: A device that performs central calculations, manages databases, and returns results. Often located in a data center.

[0116] 3. Internal database: A database system stored on a server that stores important information such as strength property data and the physical properties of materials. A general database management system (DBMS) is used.

[0117] Data Entry

[0118] The user uses the device's user interface (e.g., a web browser form) to enter the following specification data:

[0119] Concrete pillar material (e.g. iron)

[0120] Length of concrete pillar (e.g. 10 meters)

[0121] Diameter of the concrete pillar (e.g. 30 cm)

[0122] Antenna weight (e.g. 15 kg)

[0123] Antenna wind pressure coefficient (e.g. 1.2)

[0124] Data transmission

[0125] The terminal converts the specification data entered by the user into JSON or XML format and sends it to the server as an HTTP request. This conversion is important to maintain the reliability of the data.

[0126] Database collation

[0127] The server interprets the data it receives and checks it against its internal database. Specifically, the server performs a database query to obtain the following information:

[0128] Physical property data related to the material of concrete pillars

[0129] Strength data for concrete pillars according to length and diameter

[0130] strength calculation

[0131] The server performs a strength calculation based on the received data, which includes the following steps:

[0132] Calculate the total load by adding the weight of the antenna and the wind load.

[0133] Compare the maximum allowable load of the concrete pillar obtained from the database with the total load.

[0134] Evaluate the possibility of installing the antenna, taking into account safety factors.

[0135] Return and display of results

[0136] The server converts the calculation results into JSON or XML format and sends them back to the terminal as an HTTP response. The terminal visually displays the received results in a user interface. Specifically, the result is displayed as "Installation possible," "Reinforcement required," or "Installation not possible," and the appropriate course of action is provided.

[0137] Specific usage scenarios

[0138] Suppose a user needs to install a new antenna on a steel concrete pole for urban development. Using a terminal, the user inputs the specifications of the concrete pole (steel, 10 meters, 30 centimeters in diameter) and the specifications of the antenna (weight 15 kilograms, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from an internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can confirm this result and proceed with the antenna installation work with peace of mind.

[0139] Example prompts for generative AI models

[0140] "I would like to examine the strength of an antenna attached to a steel concrete pole for urban development. The specifications for the concrete pole are steel, 10 meters long, and 30 centimeters in diameter, and the antenna weighs 15 kilograms and has a wind pressure coefficient of 1.2. Please calculate the strength of the concrete pole based on this data and let me know the results."

[0141] In this way, the system of the present invention provides an effective means for quickly and accurately conducting strength studies on concrete columns, improving the safety and stability of communications infrastructure.

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] Program processing flow

[0144] Step 1: Data entry

[0145] The user uses the terminal's user interface to input the specifications of the concrete pole and antenna, such as the material, length, and diameter of the concrete pole, the weight of the antenna, and the wind pressure coefficient, into a form.

[0146] input:

[0147] Concrete pillar material (e.g. iron)

[0148] Length of concrete pillar (e.g. 10m)

[0149] Diameter of the concrete pillar (e.g. 30cm)

[0150] Antenna weight (e.g. 15kg)

[0151] Antenna wind pressure coefficient (e.g. 1.2)

[0152] output:

[0153] The data entered into the form is displayed on the device.

[0154] Step 2: Send data

[0155] The terminal converts the specification data entered by the user into JSON or XML format, ensuring the authenticity and integrity of the data, and then sends the converted data to the server as an HTTP request.

[0156] input:

[0157] Specification data entered into the form

[0158] Data processing:

[0159] Conversion to JSON or XML format

[0160] output:

[0161] HTTP request sent to the server

[0162] Step 3: Database Matching

[0163] The server interprets the received data and checks it against its internal database. The server performs a database query to retrieve physical property data and strength data related to the material, length, and diameter of the concrete pole.

[0164] input:

[0165] Specification data received

[0166] Data Calculation:

[0167] Executing a Database Query

[0168] output:

[0169] Obtained strength characteristic data

[0170] Step 4: Strength calculation

[0171] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load by adding the wind load to the weight of the antenna. Next, it compares this with the acquired maximum allowable load of the concrete pillar and applies a safety factor to make a final assessment.

[0172] input:

[0173] Obtained strength characteristic data

[0174] Specification data received

[0175] Data Calculation:

[0176] Calculating the total load

[0177] Comparison with maximum allowable load

[0178] Application and evaluation of safety factors

[0179] output:

[0180] Evaluation results for antenna installation feasibility

[0181] Step 5: Returning the results

[0182] The server converts the evaluation results into JSON or XML format and sends them back to the device as an HTTP response. This conversion ensures the reliability and integrity of the results.

[0183] input:

[0184] Evaluation results

[0185] Data processing:

[0186] Conversion to JSON or XML format

[0187] output:

[0188] Evaluation result as an HTTP response

[0189] Step 6: View the results

[0190] The terminal visually displays the received results on a user interface. Specifically, the evaluation results ("Installation Possible," "Reinforcement Required," "Installation Unavailable") are displayed on the screen, along with appropriate guidelines for action.

[0191] input:

[0192] Evaluation results sent from the server

[0193] output:

[0194] Displaying results on the user's device

[0195] Through this series of processes, users can quickly and accurately assess the strength of the concrete pillar, allowing them to proceed with antenna installation work with peace of mind.

[0196] (Application example 1)

[0197] 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."

[0198] When installing or renovating machinery in a factory environment, it is difficult to quickly and accurately perform strength analysis. Conventional methods require numerous manual calculations and checks before installation, which is time-consuming and labor-intensive, resulting in reduced productivity and safety risks due to incorrect installation.

[0199] 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.

[0200] In this invention, the server includes means for inputting specification data for the concrete pole, means for inputting specification data for the installation structure, means for transmitting the input data to the server, means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the structure, means for evaluating the feasibility of installing equipment based on the acquired strength characteristics, means for returning the evaluation results to a user terminal and an operation device, and means for displaying the evaluation results on the terminal and the operation device. This enables rapid and accurate strength assessment when installing or renovating machinery and equipment in a factory environment, thereby improving productivity and ensuring safety.

[0201] A "concrete pillar" is a columnar structure used for work and equipment installation.

[0202] "Installation structure" means the physical installation environment for mounting the equipment, including concrete columns and other supporting structures.

[0203] "Specification data" refers to data that includes specific numerical information regarding physical characteristics and design.

[0204] A "server" is a central computer that receives data, processes it, and returns the results.

[0205] The "internal database" is a system stored in the server that saves various strength data and characteristic data.

[0206] "Strength characteristics" are numerical data that indicate the characteristics of materials and structures, such as load-bearing capacity and wind resistance.

[0207] "Installability" is an index used to evaluate whether equipment can be installed safely and correctly under specific conditions.

[0208] A "user terminal" is a device that allows a user to input data and check the results.

[0209] The present invention is embodied as a system for quickly and accurately conducting strength studies when installing or modifying machinery in a factory environment. The system includes a user terminal, a server, an internal database, and an articulated robot arm.

[0210] Hardware and Software Configuration

[0211] Hardware: Multi-joint robot arm, user terminal (tablet PC), server (high-performance PC)

[0212] Software: Robot control software (ROS-based), data transmission and reception module (HTTP / REST API), internal database (PostgreSQL), strength calculation algorithm (Python script)

[0213] Processing Details

[0214] 1. User Interface:

[0215] The user uses a GUI form that runs on a tablet PC to input specification data for the equipment and installation structure, including data such as "material, length, dimensions," "weight, and pressure coefficient."

[0216] 2. Data transmission:

[0217] The user terminal converts the input specification data into JSON format and sends it to the server using an HTTP request.

[0218] 3. Server Processing:

[0219] The server receives the data using a Python script and compares it with a PostgreSQL database to obtain structural and material strength property data.

[0220] 4. Strength calculation:

[0221] The server uses the acquired characteristic data to perform the necessary strength calculations, including algorithms that evaluate safety and installability based on input data on the equipment and installation structure.

[0222] 5. Return of evaluation results:

[0223] The calculation results are sent back to the user device and robot in JSON format. The evaluation results include judgments such as "Installation possible," "Reinforcement required," and "Installation not possible."

[0224] 6. Results display and robot behavior:

[0225] The user terminal and robot decide the next action based on the evaluation results sent back. If an appropriate response is required, a warning or instruction is displayed.

[0226] Specific examples

[0227] When installing a new piece of machinery in a factory, the user inputs the material's specifications (steel, length: 2m, diameter: 10cm) and the equipment's weight (50kg, wind pressure coefficient: 1.5). This data is sent to the server, which compares it with its internal database and performs strength calculations. The result is a response that the equipment can be installed, allowing the user and robot to proceed with their work with peace of mind.

[0228] Example prompt for a generative AI model:

[0229] "Please assess the feasibility of mounting this equipment. The pole is made of steel, is 2m long, has a diameter of 10cm, weighs 50kg, and has a wind pressure coefficient of 1.5."

[0230] The system enables efficient and safe installation and modification of machinery in a factory environment.

[0231] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0232] Step 1:

[0233] Data entry in the user interface

[0234] Users use a GUI form on a tablet PC to input specification data for the equipment and installation structure, such as the material, length, and dimensions of the columns and the weight and wind pressure coefficient of the equipment. This data is then digitally imported into the system.

[0235] (Input:) Specifications of the equipment and installation structure entered by the user (e.g., material: steel, length: 2 m, diameter: 10 cm, weight: 50 kg, wind pressure coefficient: 1.5)

[0236] (Output:) Digital representation of input data

[0237] Step 2:

[0238] Data Conversion and Transmission

[0239] The terminal converts the input specification data into JSON format, which is then sent to the server as an HTTP request.

[0240] (Input:) Digital specification data

[0241] (Output:) JSON formatted data and HTTP request

[0242] Step 3:

[0243] Receiving data on the server

[0244] The server receives the HTTP request and parses the JSON data, which is then ready to be checked against an internal database.

[0245] (Input:) JSON data sent as an HTTP request

[0246] (Output:) Parsed data

[0247] Step 4:

[0248] Database collation

[0249] Based on the analyzed data, the server checks the PostgreSQL database to obtain strength property data of the installation structure and materials, which are used for strength calculations.

[0250] (Input:) Parsed specification data

[0251] (Output:) Strength property data retrieved from the database

[0252] Step 5:

[0253] strength calculation

[0254] The server performs the necessary strength calculations using the acquired strength characteristic data. First, it calculates the pressure and load based on the input amount and characteristic data, and then calculates the safety factor and other factors based on that.

[0255] (Input:) Obtained strength characteristic data and specification data from the user

[0256] (Output:) Strength calculation results (assessment of installation feasibility: installable, reinforcement required, not installable)

[0257] Step 6:

[0258] Return of evaluation results

[0259] The server converts the calculation results into JSON format and sends them back to the user's device and the robot, thereby transmitting the evaluation results to the device and the robot.

[0260] (Input:) Strength calculation result

[0261] (Output:) Evaluation result data in JSON format

[0262] Step 7:

[0263] Result display and robot operation

[0264] The user terminal and robot receive the returned evaluation results and display the results in the GUI or control interface. For example, if the result is "Installation possible," the robot will begin the installation work. If the evaluation result is anything other than that, the robot will display a warning and stop the work.

[0265] (Input:) Evaluation result data in JSON format

[0266] (Output:) Display of evaluation results and robot control actions

[0267] 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.

[0268] MODE FOR CARRYING OUT THE INVENTION

[0269] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the way the evaluation results are displayed and improve the user experience. Specific embodiments of this system are described in detail below.

[0270] System Configuration

[0271] The system mainly consists of the following components:

[0272] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[0273] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[0274] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[0275] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[0276] Data Entry

[0277] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[0278] Data transmission

[0279] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[0280] Database collation

[0281] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[0282] strength calculation

[0283] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[0284] Returning results

[0285] The server converts the strength calculation results into JSON or XML format and sends them back to the terminal. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[0286] Displaying results and using the emotion engine

[0287] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[0288] For example, if a user is anxious or suspicious about the assessment results, the emotion engine will provide detailed explanations and support options for the "reinforcement needed" result, whereas if the user is relaxed, only the basic result will be displayed.

[0289] Logging the user's emotional state

[0290] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[0291] Specific usage scenarios

[0292] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from its internal database. The server then performs strength calculations and returns the result "Installation possible" to the terminal.

[0293] If the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is feeling anxious, it will not only tell the user that installation is possible, but also provide technical background information and safety guarantees, allowing the user to proceed with the antenna installation with peace of mind.

[0294] In this way, the system of the present invention can quickly and accurately assess the strength of concrete pillars, and by providing appropriate information in response to the user's emotions, ensure the safety and stability of the communications infrastructure.

[0295] The processing flow will be explained below.

[0296] Step 1:

[0297] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[0298] Step 2:

[0299] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[0300] json

[0301] {

[0302] "material": "iron",

[0303] "length": "10",

[0304] "diameter": "30",

[0305] "antenna_weight": "15",

[0306] "wind_coefficient": "1.2"

[0307] }

[0308] Step 3:

[0309] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for further processing.

[0310] Step 4:

[0311] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[0312] sql

[0313] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[0314] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[0315] Step 5:

[0316] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding the antenna weight and wind pressure load. Specifically, the antenna weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation derives the total load.

[0317] Step 6:

[0318] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[0319] Step 7:

[0320] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[0321] json

[0322] {

[0323] "result": "Installable"

[0324] }

[0325] Step 8:

[0326] The device analyzes the evaluation results received from the server, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions.

[0327] Step 9:

[0328] The emotion engine recognizes the user's emotions and adjusts the display accordingly. For example, if the user is anxious or uncertain, the system will provide a detailed explanation and support options for the "reinforcement needed" result. On the other hand, if the user is relaxed, the system will only display the basic result.

[0329] Step 10:

[0330] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[0331] Step 11:

[0332] The terminal displays the final evaluation result on the user interface. The user can check the result on the screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation with peace of mind.

[0333] Example 2

[0334] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0335] Conventional strength assessment systems for installing antennas on concrete poles require time-consuming calculation and evaluation processes, and the display method is not adjusted to reflect user needs. This results in a poor user experience and can make it difficult to understand the strength assessment results. Furthermore, some users feel uneasy or have doubts, leading to problems with not being able to trust the assessment results.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0337] In this invention, the server includes means for inputting concrete pole specification data, means for inputting antenna specification data, means for transmitting the input data to a central computing device, means for comparing the transmitted data with an internal database to obtain the strength characteristics of the concrete pole, means for evaluating the feasibility of antenna installation based on the obtained strength characteristics, means for returning the evaluation results to a user terminal, means for displaying the evaluation results on the terminal, and an emotion engine for recognizing the user's emotions and adjusting the display method of the evaluation results. This enables the strength consideration process to be carried out quickly and accurately, and also makes it possible to provide appropriate information according to the user's emotional state, thereby improving the user experience and facilitating understanding of the evaluation results.

[0338] "Specification data for concrete poles" refers to data that represents the physical and material characteristics of concrete poles, such as the material, length, and diameter of the concrete poles.

[0339] "Antenna specification data" refers to data that describes the physical and usage conditions of an antenna, such as the antenna's weight and wind pressure coefficient.

[0340] A "central computing device" is a server that receives input data, processes it, and returns the results.

[0341] The "internal database" is a data storage device stored within the server that stores various data, such as strength characteristic data for concrete columns.

[0342] The "emotion engine" is a system that recognizes the user's emotional state and adjusts the way evaluation results are displayed based on that information.

[0343] The "evaluation results" are the results of a strength evaluation when attaching an antenna to a concrete pole, and are data that includes information such as "installable," "reinforcement required," and "uninstallable."

[0344] A "user terminal" is a device that refers to a computer or smart device that provides an interface for users to input data and display evaluation results.

[0345] "Strength characteristics" refers to physical property data relating to the strength of the concrete pillar based on its material and shape, and is standard data for making the evaluations required for antenna installation.

[0346] "Specification Data" means data that defines the physical and functional characteristics of a particular pole or antenna.

[0347] MODE FOR CARRYING OUT THE INVENTION

[0348] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it adjusts the way the evaluation results are displayed, improving the user experience. Specific embodiments of this system are described in detail below.

[0349] System Configuration

[0350] The system consists of the following components:

[0351] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[0352] 2. Server: A central computing device that is responsible for receiving data, processing it, and returning the results.

[0353] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[0354] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[0355] How to use the system

[0356] 1. Data Entry

[0357] The user uses the user terminal to input specification data for the concrete pole and the antenna. For example, the material, length, and diameter are input as specifications for the concrete pole, and the weight and wind pressure coefficient are input as specifications for the antenna.

[0358] 2. Data Transmission

[0359] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[0360] 3. Database Verification

[0361] The server compares the received data with its internal database to obtain strength characteristic data corresponding to the material, length, and diameter of the concrete pole, enabling it to evaluate the strength required for antenna installation.

[0362] 4. Strength calculation

[0363] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Next, it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[0364] 5. Return of results

[0365] The server converts the strength calculation results into JSON or XML format and sends them back to the user's device. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[0366] 6. Displaying results and using the emotion engine

[0367] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[0368] For example, if a user wants to install a new antenna on a steel concrete pole for urban development, the user uses the terminal to enter the following specification data:

[0369] Concrete pillar specifications: iron, 10m, diameter 30cm

[0370] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[0371] This data is sent to a server, which retrieves strength characteristic data from an internal database, performs strength calculations, and returns a result of "Installation Possible" to the user's device. At this time, the emotion engine analyzes the user's facial expression and tone of voice, and if it recognizes that the user is feeling anxious, it displays the "Installation Possible" result along with detailed technical explanations and information about safety guarantees. In this way, the user's anxiety is alleviated, allowing them to proceed with the antenna installation work with peace of mind.

[0372] Example usage scenarios

[0373] For example, you can use the system with the following prompt:

[0374] "Please quickly and accurately evaluate the strength of attaching an antenna to a steel concrete pole, and adjust the way the results are displayed depending on the user's emotional state. Please perform strength calculations based on the following specifications and return the results."

[0375] Concrete pillar specifications: iron, 10m, diameter 30cm

[0376] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[0377] This system not only enables rapid and accurate strength assessment of concrete pillars, but also provides information according to the user's emotions, ensuring the safety of the communications infrastructure.

[0378] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0379] Step 1: Data entry

[0380] The user accesses the system using a user terminal. They enter the specifications of the concrete pole and antenna into the specified form. Specifically, they enter the specifications of the concrete pole (material, length, diameter) and the antenna (weight, wind pressure coefficient). For example, the material of the concrete pole is entered as "iron," the length as "10m," and the diameter as "30cm," and the weight of the antenna as "15kg" and the wind pressure coefficient as "1.2." The user checks the information entered and clicks the send button.

[0381] Input: User input of specification data (material, length, diameter, weight, wind pressure coefficient)

[0382] Output: Formatted specification data

[0383] Step 2: Send data

[0384] The terminal takes the specification data entered by the user and converts it into JSON or XML format. The converted data is sent to the server. For example, the converted data looks like this:

[0385] json

[0386] {

[0387] "Con Pillar": {

[0388] "Material": "Iron",

[0389] "Length": "10m",

[0390] "Diameter": "30cm"

[0391] },

[0392] "antenna": {

[0393] "Weight": "15kg",

[0394] "Wind Pressure Coefficient": "1.2"

[0395] }

[0396] }

[0397] Input: Formatted specification data

[0398] Output: Data sent to the server

[0399] Step 3: Database Matching

[0400] The server receives and analyzes the data sent from the terminal. Specifically, it checks the internal database based on the material, length, and diameter of the concrete pole to obtain strength characteristic data. For example, it obtains corresponding strength characteristic data from existing data for steel concrete poles.

[0401] Input: Data sent to the server (material, length, diameter, weight, wind pressure coefficient)

[0402] Output: Strength characteristic data

[0403] Step 4: Strength calculation

[0404] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind pressure load to the weight of the antenna to calculate the total load. Next, it compares the calculated total load with the maximum allowable load of the concrete pillar acquired from the database, and then applies a safety factor to make a final evaluation. Specifically, for example, it calculates total load = 15 kg (weight) + (1.2 x wind pressure rate) and compares it with the maximum allowable load.

[0405] Input: Strength characteristics data and input specification data

[0406] Output: Strength evaluation result (Installable, Reinforcement required, Uninstallable)

[0407] Step 5: Returning the results

[0408] The server converts the results of the strength calculation into JSON or XML format and sends it back to the user device. For example, the result data looks like this:

[0409] json

[0410] {

[0411] "Evaluation result": "Installable"

[0412] }

[0413] Input: Strength evaluation results

[0414] Output: Evaluation results sent to the user's device

[0415] Step 6: Displaying the results and using the emotion engine

[0416] The device receives the result data returned from the server and activates the emotion engine before analyzing it. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state. Based on the results, the display of the evaluation results can be adjusted. For example, if the user is feeling anxious, the device will display the "Installable" result along with technical details and safety guarantees. On the other hand, if the user is relaxed, only the basic results will be displayed.

[0417] Input: Evaluation results and user's emotional state

[0418] Output: Evaluation results in a tailored display format

[0419] Step 7: Logging the user's emotional state

[0420] The emotion engine records the user's emotional state as log data and feeds it back into future evaluations and display adjustments. This allows the system to learn the user's usage patterns and emotional responses, enabling more accurate emotion recognition and display results in the future.

[0421] Input: User's emotional state

[0422] Output: Log data and feedback information

[0423] (Application example 2)

[0424] 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."

[0425] In the past, logistics center workers lacked a system for obtaining information on how to handle packages and taking appropriate measures immediately. Furthermore, there was a lack of information provided based on the strength assessment of package handling and the emotional state of the workers, resulting in issues with safety and efficiency. The present invention aims to solve these issues and improve the safety and efficiency of workers at logistics centers.

[0426] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0427] In this invention, the server includes: means for inputting specification data of the concrete pole; means for inputting specification data of the communication device; means for transmitting the input data to a central computer; means for comparing the transmitted data with an internal database to obtain strength characteristics of the concrete pole; means for evaluating the feasibility of attaching the communication device based on the obtained strength characteristics; means for returning the evaluation results to a user terminal; means for displaying the evaluation results on the terminal; means for recognizing the emotional state of the user and adjusting the display method of the evaluation results; and means for enabling a user at a logistics center to use smart glasses to check how to handle packages and providing help information and warnings according to the user's emotional state. This allows workers at the logistics center to instantly check how to handle packages and improves safety and efficiency.

[0428] A "concrete pole" is a column-shaped structural member used to install and secure communication devices and other equipment.

[0429] A "communication device" is a device for sending and receiving data, and refers to a wide range of equipment including antennas and sensors.

[0430] "Specification data" refers to information that indicates the characteristics of concrete pillars and communication devices, such as their materials, dimensions, weight, and wind pressure coefficients.

[0431] A "central computer" is a computer system that centralizes data processing and typically functions as a server.

[0432] "Internal Database" means a data storage device that can store, search, and use required characteristic data.

[0433] "Strength properties" are physical characteristics that indicate how much load or pressure a material or structure can withstand.

[0434] "Attachability" is an index that evaluates whether a communication device can be attached safely and effectively to a concrete pole.

[0435] "User terminal" refers to a device used by a user to receive and display evaluation results, and includes smartphones, tablets, etc.

[0436] "Emotional state" indicates the user's current psychological and emotional state and is identified through facial expressions, tone of voice, etc.

[0437] "Smart glasses" are eyeglass-type devices that have the function of displaying information and are based on augmented reality (AR) technology.

[0438] "Help information" refers to support information that can be referred to when a worker performs a required operation.

[0439] "Caution" refers to information that provides warnings or advice to workers about specific actions or situations.

[0440] A "logistics center" is a facility that centralizes operations such as storing, sorting, and shipping goods.

[0441] The system for carrying out the present invention aims to improve the efficiency and safety of work in a logistics center. The system configuration is as follows.

[0442] System Configuration

[0443] 1. User device (smart glasses):

[0444] This is a device that allows users to input data and check the displayed results. Workers wear smart glasses and check how to handle packages and important points to note.

[0445] 2. Central computer (server):

[0446] This is the central computer that receives data, processes it, and returns the results. It evaluates the strength of the package and displays the results.

[0447] 3. Internal database:

[0448] This is a database that stores various strength data and characteristic data stored in the server.

[0449] 4. Emotion Engine:

[0450] This system recognizes the user's emotions and adjusts the way evaluation results are displayed based on that information.

[0451] Data Entry

[0452] The user uses the smart glasses to input package specifications, such as package type, weight, and dimensions, using voice commands or touch operations. A form is used as the input interface.

[0453] Data transmission

[0454] The device converts the input specification data into JSON or XML format and sends it to the server, where the smart glasses send the data to the server via Wi-Fi or Bluetooth.

[0455] Database collation

[0456] The server compares the received data with an internal database to obtain the strength characteristics data of the package, which contains the package's material, dimensions, and strength characteristics.

[0457] strength calculation

[0458] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load based on the weight of the package, then compares it with the maximum allowable load of the package acquired from the database, and applies a safety factor to make a final assessment and determine whether the package can be handled.

[0459] Results display

[0460] The server converts the strength calculation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Can be handled," "Caution required," and "Cannot be handled."

[0461] Use of emotion engine

[0462] The device analyzes the received results, and an emotion engine recognizes the user's emotional state before displaying them. It uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotions. It adjusts the display method based on the results. For example, if the user has concerns or questions about the assessment results, it provides a detailed explanation and support options for the "Caution Required" result.

[0463] Logging the user's emotional state

[0464] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[0465] Specific examples

[0466] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[0467] Prompt Sentence Examples

[0468] "What is the maximum weight allowable for this luggage?"

[0469] "Please tell me the steps to safely transport this package."

[0470] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0471] Step 1:

[0472] The user uses the smart glasses to input package specifications (package type, weight, dimensions) using voice commands or touch operations. The input data is acquired by a voice recognition system or touch sensor and converted into JSON or XML format within the device.

[0473] Input: Package type, weight, dimensions

[0474] Output: Package specification data in JSON or XML format

[0475] Step 2:

[0476] The terminal sends the converted specification data to the server via Wi-Fi or Bluetooth, using the communication module of the smart glasses.

[0477] Input: Package specification data in JSON or XML format

[0478] Output: Send data to the server

[0479] Step 3:

[0480] The server analyzes the received data and retrieves the strength characteristics data of the package by checking the data against its internal database. A database query module in the server is used.

[0481] Input: Package specification data sent by the user

[0482] Output: Strength characteristics data of the luggage

[0483] Step 4:

[0484] The server performs strength calculations based on the acquired strength characteristic data. The calculation module uses data such as weight, dimensions, and wind pressure coefficients to calculate the total load, compare it with the maximum allowable load, and apply a safety factor.

[0485] Input: Package strength characteristics data

[0486] Output: Evaluation result of the cargo handling feasibility

[0487] Step 5:

[0488] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation module is responsible for converting the results.

[0489] Input: Evaluation result of the cargo's feasibility

[0490] Output: Evaluation results in JSON or XML format

[0491] Step 6:

[0492] The terminal receives the evaluation results and parses the data. An analysis module interprets the data format and prepares it for display.

[0493] Input: Evaluation result returned from the server

[0494] Output: Analyzed evaluation result data

[0495] Step 7:

[0496] The device's emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state, and emotion recognition algorithms are used to generate the user's emotion data.

[0497] Input: User's facial expression, tone of voice

[0498] Output: User emotion data

[0499] Step 8:

[0500] The emotion engine adjusts the way the rating results are displayed based on the user's emotional state. For example, if the user is feeling anxious, it might display additional detailed explanations or support options. The display module is used.

[0501] Input: Analyzed evaluation result data, user emotion data

[0502] Output: Adjusted evaluation results

[0503] Step 9:

[0504] The terminal then displays the adjusted evaluation results on the smart glasses' display, allowing the worker to check how to handle the package and proceed with the work safely and efficiently.

[0505] Input: Adjusted evaluation results display

[0506] Output: Evaluation results displayed on the smart glasses display

[0507] Examples:

[0508] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[0509] Example prompt sentence:

[0510] "What is the maximum weight allowable for this luggage?"

[0511] "Please tell me the steps to safely transport this package."

[0512] 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.

[0513] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0514] 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.

[0515] [Second embodiment]

[0516] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0517] 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.

[0518] 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).

[0519] 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.

[0520] 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.

[0521] 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).

[0522] 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. 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.

[0523] 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.

[0524] 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.

[0525] 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.

[0526] In the smart glasses 214, 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.

[0527] 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."

[0528] MODE FOR CARRYING OUT THE INVENTION

[0529] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of the system will be described in detail below.

[0530] System Configuration

[0531] The system mainly consists of the following components:

[0532] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[0533] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[0534] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[0535] Data Entry

[0536] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[0537] Data transmission

[0538] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[0539] Database collation

[0540] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[0541] strength calculation

[0542] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[0543] Returning results

[0544] The server returns the results of the strength calculation to the terminal, including an evaluation such as "Installable," "Reinforcement required," or "Cannot be installed."

[0545] Results display

[0546] The terminal then displays the received results to the user. The user interface visually displays the evaluation results and provides guidance on appropriate actions, such as whether the antenna can be installed, whether reinforcement is required, or whether installation is impossible.

[0547] Specific usage scenarios

[0548] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the specifications of the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to the server, which retrieves strength characteristic data from its internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can check this result on the terminal and proceed with the antenna installation work with peace of mind.

[0549] In this way, the system of the present invention can quickly and accurately examine the strength of concrete pillars, contributing to ensuring the safety and stability of communication infrastructure.

[0550] The processing flow will be explained below.

[0551] Step 1:

[0552] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[0553] Step 2:

[0554] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[0555] json

[0556] {

[0557] "material": "iron",

[0558] "length": "10",

[0559] "diameter": "30",

[0560] "antenna_weight": "15",

[0561] "wind_coefficient": "1.2"

[0562] }

[0563] Step 3:

[0564] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for subsequent processing.

[0565] Step 4:

[0566] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[0567] sql

[0568] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[0569] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[0570] Step 5:

[0571] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding up the antenna's weight and wind pressure load. Specifically, the antenna's weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation yields the total load.

[0572] Step 6:

[0573] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[0574] Step 7:

[0575] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[0576] json

[0577] {

[0578] "result": "Installable"

[0579] }

[0580] Step 8:

[0581] The device analyzes the evaluation results received from the server and displays them on the user interface. The user can check the results on the device screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation work with peace of mind.

[0582] These steps allow the user to quickly and accurately assess the strength of the concrete pole and install the appropriate antenna.

[0583] Example 1

[0584] 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."

[0585] Previously, strength assessments for installing antennas on concrete poles were often done manually, which was time-consuming and involved the risk of calculation errors. Furthermore, there was a need for efficient processing of a variety of input data to quickly and accurately assess strength, but no system with these functions existed.

[0586] 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.

[0587] In this invention, the server includes means for receiving specification data for the concrete pole and the antenna input by the user, means for converting the input specification data into JSON or XML format, means for transmitting the converted data to the server, means for the server to compare the received data with an internal database and obtain strength characteristic data for the concrete pole, means for evaluating the feasibility of installing the antenna based on the obtained strength characteristic data, means for converting the evaluation results into JSON or XML format and returning them to the user terminal, and means for the user terminal to visually display the evaluation results and provide appropriate guidelines to the user. This enables complex and time-consuming strength evaluation work to be performed quickly and accurately, ensuring the safety and stability of the communication infrastructure.

[0588] A "user" is a person or organization that operates the system and inputs the required data.

[0589] A "terminal" is a device, such as a computer, smartphone, or tablet, that a user uses to enter data and view results.

[0590] A "server" is a central computer that receives data, checks it against an internal database, performs calculations, and returns the results.

[0591] "Specification data" refers to basic characteristic information about the concrete pole and antenna (material, length, diameter, weight, wind pressure coefficient, etc.).

[0592] "JSON format" stands for JavaScript Object Notation, a concise, easy-to-read text format for structuring data.

[0593] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structuring and flexibly describing data.

[0594] The "internal database" is a database system for processing various data (such as strength characteristic data) stored in the server.

[0595] "Strength characteristic data" refers to data regarding the physical strength of a concrete pillar, calculated based on its material, length, diameter, etc.

[0596] "Attachability" is a criterion for assessing whether an antenna can be safely attached to a concrete pole.

[0597] A "user interface" is a screen display or input means that allows a user to input data and check the results.

[0598] An "HTTP request" is a request for data transmission made from a terminal to a server.

[0599] An "HTTP response" is a data response sent back from a server to a terminal.

[0600] "Visual display" means presenting data and evaluation results on the screen in a way that is intuitively easy for users to understand.

[0601] MODE FOR CARRYING OUT THE INVENTION

[0602] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of this system are described below.

[0603] System Configuration

[0604] The system mainly consists of the following components:

[0605] 1. User terminal: A device that allows users to input data and display results. This includes personal computers, smartphones, tablets, etc.

[0606] 2. Server: A device that performs central calculations, manages databases, and returns results. Often located in a data center.

[0607] 3. Internal database: A database system stored on a server that stores important information such as strength property data and the physical properties of materials. A general database management system (DBMS) is used.

[0608] Data Entry

[0609] The user uses the device's user interface (e.g., a web browser form) to enter the following specification data:

[0610] Concrete pillar material (e.g. iron)

[0611] Length of concrete pillar (e.g. 10 meters)

[0612] Diameter of the concrete pillar (e.g. 30 cm)

[0613] Antenna weight (e.g. 15 kg)

[0614] Antenna wind pressure coefficient (e.g. 1.2)

[0615] Data transmission

[0616] The terminal converts the specification data entered by the user into JSON or XML format and sends it to the server as an HTTP request. This conversion is important to maintain the reliability of the data.

[0617] Database collation

[0618] The server interprets the data it receives and checks it against its internal database. Specifically, the server performs a database query to obtain the following information:

[0619] Physical property data related to the material of concrete pillars

[0620] Strength data for concrete pillars according to length and diameter

[0621] strength calculation

[0622] The server performs a strength calculation based on the received data, which includes the following steps:

[0623] Calculate the total load by adding the weight of the antenna and the wind load.

[0624] Compare the maximum allowable load of the concrete pillar obtained from the database with the total load.

[0625] Evaluate the possibility of installing the antenna, taking into account safety factors.

[0626] Return and display of results

[0627] The server converts the calculation results into JSON or XML format and sends them back to the terminal as an HTTP response. The terminal visually displays the received results in a user interface. Specifically, the result is displayed as "Installation possible," "Reinforcement required," or "Installation not possible," and the appropriate course of action is provided.

[0628] Specific usage scenarios

[0629] Suppose a user needs to install a new antenna on a steel concrete pole for urban development. Using a terminal, the user inputs the specifications of the concrete pole (steel, 10 meters, 30 centimeters in diameter) and the specifications of the antenna (weight 15 kilograms, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from an internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can confirm this result and proceed with the antenna installation work with peace of mind.

[0630] Example prompts for generative AI models

[0631] "I would like to examine the strength of an antenna attached to a steel concrete pole for urban development. The specifications for the concrete pole are steel, 10 meters long, and 30 centimeters in diameter, and the antenna weighs 15 kilograms and has a wind pressure coefficient of 1.2. Please calculate the strength of the concrete pole based on this data and let me know the results."

[0632] In this way, the system of the present invention provides an effective means for quickly and accurately conducting strength studies on concrete columns, improving the safety and stability of communications infrastructure.

[0633] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0634] Program processing flow

[0635] Step 1: Data entry

[0636] The user uses the terminal's user interface to input the specifications of the concrete pole and antenna, such as the material, length, and diameter of the concrete pole, the weight of the antenna, and the wind pressure coefficient, into a form.

[0637] input:

[0638] Concrete pillar material (e.g. iron)

[0639] Length of concrete pillar (e.g. 10m)

[0640] Diameter of the concrete pillar (e.g. 30cm)

[0641] Antenna weight (e.g. 15kg)

[0642] Antenna wind pressure coefficient (e.g. 1.2)

[0643] output:

[0644] The data entered into the form is displayed on the device.

[0645] Step 2: Send data

[0646] The terminal converts the specification data entered by the user into JSON or XML format, ensuring the authenticity and integrity of the data, and then sends the converted data to the server as an HTTP request.

[0647] input:

[0648] Specification data entered into the form

[0649] Data processing:

[0650] Conversion to JSON or XML format

[0651] output:

[0652] HTTP request sent to the server

[0653] Step 3: Database Matching

[0654] The server interprets the received data and checks it against its internal database. The server performs a database query to retrieve physical property data and strength data related to the material, length, and diameter of the concrete pole.

[0655] input:

[0656] Specification data received

[0657] Data Calculation:

[0658] Executing a Database Query

[0659] output:

[0660] Obtained strength characteristic data

[0661] Step 4: Strength calculation

[0662] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load by adding the wind load to the weight of the antenna. Next, it compares this with the acquired maximum allowable load of the concrete pillar and applies a safety factor to make a final assessment.

[0663] input:

[0664] Obtained strength characteristic data

[0665] Specification data received

[0666] Data Calculation:

[0667] Calculating the total load

[0668] Comparison with maximum allowable load

[0669] Application and evaluation of safety factors

[0670] output:

[0671] Evaluation results for antenna installation feasibility

[0672] Step 5: Returning the results

[0673] The server converts the evaluation results into JSON or XML format and sends them back to the device as an HTTP response. This conversion ensures the reliability and integrity of the results.

[0674] input:

[0675] Evaluation results

[0676] Data processing:

[0677] Conversion to JSON or XML format

[0678] output:

[0679] Evaluation result as an HTTP response

[0680] Step 6: View the results

[0681] The terminal visually displays the received results on a user interface. Specifically, the evaluation results ("Installation Possible," "Reinforcement Required," "Installation Unavailable") are displayed on the screen, along with appropriate guidelines for action.

[0682] input:

[0683] Evaluation results sent from the server

[0684] output:

[0685] Displaying results on the user's device

[0686] Through this series of processes, users can quickly and accurately assess the strength of the concrete pillar, allowing them to proceed with antenna installation work with peace of mind.

[0687] (Application example 1)

[0688] 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."

[0689] When installing or renovating machinery in a factory environment, it is difficult to quickly and accurately perform strength analysis. Conventional methods require numerous manual calculations and checks before installation, which is time-consuming and labor-intensive, resulting in reduced productivity and safety risks due to incorrect installation.

[0690] 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.

[0691] In this invention, the server includes means for inputting specification data for the concrete pole, means for inputting specification data for the installation structure, means for transmitting the input data to the server, means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the structure, means for evaluating the feasibility of installing equipment based on the acquired strength characteristics, means for returning the evaluation results to a user terminal and an operation device, and means for displaying the evaluation results on the terminal and the operation device. This enables rapid and accurate strength assessment when installing or renovating machinery and equipment in a factory environment, thereby improving productivity and ensuring safety.

[0692] A "concrete pillar" is a columnar structure used for work and equipment installation.

[0693] "Installation structure" means the physical installation environment for mounting the equipment, including concrete columns and other supporting structures.

[0694] "Specification data" refers to data that includes specific numerical information regarding physical characteristics and design.

[0695] A "server" is a central computer that receives data, processes it, and returns the results.

[0696] The "internal database" is a system stored in the server that saves various strength data and characteristic data.

[0697] "Strength characteristics" are numerical data that indicate the characteristics of materials and structures, such as load-bearing capacity and wind resistance.

[0698] "Installability" is an index used to evaluate whether equipment can be installed safely and correctly under specific conditions.

[0699] A "user terminal" is a device that allows a user to input data and check the results.

[0700] The present invention is embodied as a system for quickly and accurately conducting strength studies when installing or modifying machinery in a factory environment. The system includes a user terminal, a server, an internal database, and an articulated robot arm.

[0701] Hardware and Software Configuration

[0702] Hardware: Multi-joint robot arm, user terminal (tablet PC), server (high-performance PC)

[0703] Software: Robot control software (ROS-based), data transmission and reception module (HTTP / REST API), internal database (PostgreSQL), strength calculation algorithm (Python script)

[0704] Processing Details

[0705] 1. User Interface:

[0706] The user uses a GUI form that runs on a tablet PC to input specification data for the equipment and installation structure, including data such as "material, length, dimensions," "weight, and pressure coefficient."

[0707] 2. Data transmission:

[0708] The user terminal converts the input specification data into JSON format and sends it to the server using an HTTP request.

[0709] 3. Server Processing:

[0710] The server receives the data using a Python script and compares it with a PostgreSQL database to obtain structural and material strength property data.

[0711] 4. Strength calculation:

[0712] The server uses the acquired characteristic data to perform the necessary strength calculations, including algorithms that evaluate safety and installability based on input data on the equipment and installation structure.

[0713] 5. Return of evaluation results:

[0714] The calculation results are sent back to the user device and robot in JSON format. The evaluation results include judgments such as "Installation possible," "Reinforcement required," and "Installation not possible."

[0715] 6. Results display and robot behavior:

[0716] The user terminal and robot decide the next action based on the evaluation results sent back. If an appropriate response is required, a warning or instruction is displayed.

[0717] Specific examples

[0718] When installing a new piece of machinery in a factory, the user inputs the material's specifications (steel, length: 2m, diameter: 10cm) and the equipment's weight (50kg, wind pressure coefficient: 1.5). This data is sent to the server, which compares it with its internal database and performs strength calculations. The result is a response that the equipment can be installed, allowing the user and robot to proceed with their work with peace of mind.

[0719] Example prompt for a generative AI model:

[0720] "Please assess the feasibility of mounting this equipment. The pole is made of steel, is 2m long, has a diameter of 10cm, weighs 50kg, and has a wind pressure coefficient of 1.5."

[0721] The system enables efficient and safe installation and modification of machinery in a factory environment.

[0722] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0723] Step 1:

[0724] Data entry in the user interface

[0725] Users use a GUI form on a tablet PC to input specification data for the equipment and installation structure, such as the material, length, and dimensions of the columns and the weight and wind pressure coefficient of the equipment. This data is then digitally imported into the system.

[0726] (Input:) Specifications of the equipment and installation structure entered by the user (e.g., material: steel, length: 2 m, diameter: 10 cm, weight: 50 kg, wind pressure coefficient: 1.5)

[0727] (Output:) Digital representation of input data

[0728] Step 2:

[0729] Data Conversion and Transmission

[0730] The terminal converts the input specification data into JSON format, which is then sent to the server as an HTTP request.

[0731] (Input:) Digital specification data

[0732] (Output:) JSON formatted data and HTTP request

[0733] Step 3:

[0734] Receiving data on the server

[0735] The server receives the HTTP request and parses the JSON data, which is then ready to be checked against an internal database.

[0736] (Input:) JSON data sent as an HTTP request

[0737] (Output:) Parsed data

[0738] Step 4:

[0739] Database collation

[0740] Based on the analyzed data, the server checks the PostgreSQL database to obtain strength property data of the installation structure and materials, which are used for strength calculations.

[0741] (Input:) Parsed specification data

[0742] (Output:) Strength property data retrieved from the database

[0743] Step 5:

[0744] strength calculation

[0745] The server performs the necessary strength calculations using the acquired strength characteristic data. First, it calculates the pressure and load based on the input amount and characteristic data, and then calculates the safety factor and other factors based on that.

[0746] (Input:) Obtained strength characteristic data and specification data from the user

[0747] (Output:) Strength calculation results (assessment of installation feasibility: installable, reinforcement required, not installable)

[0748] Step 6:

[0749] Return of evaluation results

[0750] The server converts the calculation results into JSON format and sends them back to the user's device and the robot, thereby transmitting the evaluation results to the device and the robot.

[0751] (Input:) Strength calculation result

[0752] (Output:) Evaluation result data in JSON format

[0753] Step 7:

[0754] Result display and robot operation

[0755] The user terminal and robot receive the returned evaluation results and display the results in the GUI or control interface. For example, if the result is "Installation possible," the robot will begin the installation work. If the evaluation result is anything other than that, the robot will display a warning and stop the work.

[0756] (Input:) Evaluation result data in JSON format

[0757] (Output:) Display of evaluation results and robot control actions

[0758] 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.

[0759] MODE FOR CARRYING OUT THE INVENTION

[0760] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the way the evaluation results are displayed and improve the user experience. Specific embodiments of this system are described in detail below.

[0761] System Configuration

[0762] The system mainly consists of the following components:

[0763] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[0764] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[0765] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[0766] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[0767] Data Entry

[0768] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[0769] Data transmission

[0770] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[0771] Database collation

[0772] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[0773] strength calculation

[0774] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[0775] Returning results

[0776] The server converts the strength calculation results into JSON or XML format and sends them back to the terminal. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[0777] Displaying results and using the emotion engine

[0778] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[0779] For example, if a user is anxious or suspicious about the assessment results, the emotion engine will provide detailed explanations and support options for the "reinforcement needed" result, whereas if the user is relaxed, only the basic result will be displayed.

[0780] Logging the user's emotional state

[0781] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[0782] Specific usage scenarios

[0783] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from its internal database. The server then performs strength calculations and returns the result "Installation possible" to the terminal.

[0784] If the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is feeling anxious, it will not only tell the user that installation is possible, but also provide technical background information and safety guarantees, allowing the user to proceed with the antenna installation with peace of mind.

[0785] In this way, the system of the present invention can quickly and accurately assess the strength of concrete pillars, and by providing appropriate information in response to the user's emotions, ensure the safety and stability of the communications infrastructure.

[0786] The processing flow will be explained below.

[0787] Step 1:

[0788] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[0789] Step 2:

[0790] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[0791] json

[0792] {

[0793] "material": "iron",

[0794] "length": "10",

[0795] "diameter": "30",

[0796] "antenna_weight": "15",

[0797] "wind_coefficient": "1.2"

[0798] }

[0799] Step 3:

[0800] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for further processing.

[0801] Step 4:

[0802] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[0803] sql

[0804] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[0805] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[0806] Step 5:

[0807] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding the antenna weight and wind pressure load. Specifically, the antenna weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation derives the total load.

[0808] Step 6:

[0809] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[0810] Step 7:

[0811] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[0812] json

[0813] {

[0814] "result": "Installable"

[0815] }

[0816] Step 8:

[0817] The device analyzes the evaluation results received from the server, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions.

[0818] Step 9:

[0819] The emotion engine recognizes the user's emotions and adjusts the display accordingly. For example, if the user is anxious or uncertain, the system will provide a detailed explanation and support options for the "reinforcement needed" result. On the other hand, if the user is relaxed, the system will only display the basic result.

[0820] Step 10:

[0821] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[0822] Step 11:

[0823] The terminal displays the final evaluation result on the user interface. The user can check the result on the screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation with peace of mind.

[0824] Example 2

[0825] 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."

[0826] Conventional strength assessment systems for installing antennas on concrete poles require time-consuming calculation and evaluation processes, and the display method is not adjusted to reflect user needs. This results in a poor user experience and can make it difficult to understand the strength assessment results. Furthermore, some users feel uneasy or have doubts, leading to problems with not being able to trust the assessment results.

[0827] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0828] In this invention, the server includes means for inputting concrete pole specification data, means for inputting antenna specification data, means for transmitting the input data to a central computing device, means for comparing the transmitted data with an internal database to obtain the strength characteristics of the concrete pole, means for evaluating the feasibility of antenna installation based on the obtained strength characteristics, means for returning the evaluation results to a user terminal, means for displaying the evaluation results on the terminal, and an emotion engine for recognizing the user's emotions and adjusting the display method of the evaluation results. This enables the strength consideration process to be carried out quickly and accurately, and also makes it possible to provide appropriate information according to the user's emotional state, thereby improving the user experience and facilitating understanding of the evaluation results.

[0829] "Specification data for concrete poles" refers to data that represents the physical and material characteristics of concrete poles, such as the material, length, and diameter of the concrete poles.

[0830] "Antenna specification data" refers to data that describes the physical and usage conditions of an antenna, such as the antenna's weight and wind pressure coefficient.

[0831] A "central computing device" is a server that receives input data, processes it, and returns the results.

[0832] The "internal database" is a data storage device stored within the server that stores various data, such as strength characteristic data for concrete columns.

[0833] The "emotion engine" is a system that recognizes the user's emotional state and adjusts the way evaluation results are displayed based on that information.

[0834] The "evaluation results" are the results of a strength evaluation when attaching an antenna to a concrete pole, and are data that includes information such as "installable," "reinforcement required," and "uninstallable."

[0835] A "user terminal" is a device that refers to a computer or smart device that provides an interface for users to input data and display evaluation results.

[0836] "Strength characteristics" refers to physical property data relating to the strength of the concrete pillar based on its material and shape, and is standard data for making the evaluations required for antenna installation.

[0837] "Specification Data" means data that defines the physical and functional characteristics of a particular pole or antenna.

[0838] MODE FOR CARRYING OUT THE INVENTION

[0839] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it adjusts the way the evaluation results are displayed, improving the user experience. Specific embodiments of this system are described in detail below.

[0840] System Configuration

[0841] The system consists of the following components:

[0842] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[0843] 2. Server: A central computing device that is responsible for receiving data, processing it, and returning the results.

[0844] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[0845] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[0846] How to use the system

[0847] 1. Data Entry

[0848] The user uses the user terminal to input specification data for the concrete pole and the antenna. For example, the material, length, and diameter are input as specifications for the concrete pole, and the weight and wind pressure coefficient are input as specifications for the antenna.

[0849] 2. Data Transmission

[0850] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[0851] 3. Database Verification

[0852] The server compares the received data with its internal database to obtain strength characteristic data corresponding to the material, length, and diameter of the concrete pole, enabling it to evaluate the strength required for antenna installation.

[0853] 4. Strength calculation

[0854] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Next, it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[0855] 5. Return of results

[0856] The server converts the strength calculation results into JSON or XML format and sends them back to the user's device. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[0857] 6. Displaying results and using the emotion engine

[0858] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[0859] For example, if a user wants to install a new antenna on a steel concrete pole for urban development, the user uses the terminal to enter the following specification data:

[0860] Concrete pillar specifications: iron, 10m, diameter 30cm

[0861] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[0862] This data is sent to a server, which retrieves strength characteristic data from an internal database, performs strength calculations, and returns a result of "Installation Possible" to the user's device. At this time, the emotion engine analyzes the user's facial expression and tone of voice, and if it recognizes that the user is feeling anxious, it displays the "Installation Possible" result along with detailed technical explanations and information about safety guarantees. In this way, the user's anxiety is alleviated, allowing them to proceed with the antenna installation work with peace of mind.

[0863] Example usage scenarios

[0864] For example, you can use the system with the following prompt:

[0865] "Please quickly and accurately evaluate the strength of attaching an antenna to a steel concrete pole, and adjust the way the results are displayed depending on the user's emotional state. Please perform strength calculations based on the following specifications and return the results."

[0866] Concrete pillar specifications: iron, 10m, diameter 30cm

[0867] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[0868] This system not only enables rapid and accurate strength assessment of concrete pillars, but also provides information according to the user's emotions, ensuring the safety of the communications infrastructure.

[0869] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0870] Step 1: Data entry

[0871] The user accesses the system using a user terminal. They enter the specifications of the concrete pole and antenna into the specified form. Specifically, they enter the specifications of the concrete pole (material, length, diameter) and the antenna (weight, wind pressure coefficient). For example, the material of the concrete pole is entered as "iron," the length as "10m," and the diameter as "30cm," and the weight of the antenna as "15kg" and the wind pressure coefficient as "1.2." The user checks the information entered and clicks the send button.

[0872] Input: User input of specification data (material, length, diameter, weight, wind pressure coefficient)

[0873] Output: Formatted specification data

[0874] Step 2: Send data

[0875] The terminal takes the specification data entered by the user and converts it into JSON or XML format. The converted data is sent to the server. For example, the converted data looks like this:

[0876] json

[0877] {

[0878] "Con Pillar": {

[0879] "Material": "Iron",

[0880] "Length": "10m",

[0881] "Diameter": "30cm"

[0882] },

[0883] "antenna": {

[0884] "Weight": "15kg",

[0885] "Wind Pressure Coefficient": "1.2"

[0886] }

[0887] }

[0888] Input: Formatted specification data

[0889] Output: Data sent to the server

[0890] Step 3: Database Matching

[0891] The server receives and analyzes the data sent from the terminal. Specifically, it checks the internal database based on the material, length, and diameter of the concrete pole to obtain strength characteristic data. For example, it obtains corresponding strength characteristic data from existing data for steel concrete poles.

[0892] Input: Data sent to the server (material, length, diameter, weight, wind pressure coefficient)

[0893] Output: Strength characteristic data

[0894] Step 4: Strength calculation

[0895] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind pressure load to the weight of the antenna to calculate the total load. Next, it compares the calculated total load with the maximum allowable load of the concrete pillar acquired from the database, and then applies a safety factor to make a final evaluation. Specifically, for example, it calculates total load = 15 kg (weight) + (1.2 x wind pressure rate) and compares it with the maximum allowable load.

[0896] Input: Strength characteristics data and input specification data

[0897] Output: Strength evaluation result (Installable, Reinforcement required, Uninstallable)

[0898] Step 5: Returning the results

[0899] The server converts the results of the strength calculation into JSON or XML format and sends it back to the user device. For example, the result data looks like this:

[0900] json

[0901] {

[0902] "Evaluation result": "Installable"

[0903] }

[0904] Input: Strength evaluation results

[0905] Output: Evaluation results sent to the user's device

[0906] Step 6: Displaying the results and using the emotion engine

[0907] The device receives the result data returned from the server and activates the emotion engine before analyzing it. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state. Based on the results, the display of the evaluation results can be adjusted. For example, if the user is feeling anxious, the device will display the "Installable" result along with technical details and safety guarantees. On the other hand, if the user is relaxed, only the basic results will be displayed.

[0908] Input: Evaluation results and user's emotional state

[0909] Output: Evaluation results in a tailored display format

[0910] Step 7: Logging the user's emotional state

[0911] The emotion engine records the user's emotional state as log data and feeds it back into future evaluations and display adjustments. This allows the system to learn the user's usage patterns and emotional responses, enabling more accurate emotion recognition and display results in the future.

[0912] Input: User's emotional state

[0913] Output: Log data and feedback information

[0914] (Application example 2)

[0915] 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."

[0916] In the past, logistics center workers lacked a system for obtaining information on how to handle packages and taking appropriate measures immediately. Furthermore, there was a lack of information provided based on the strength assessment of package handling and the emotional state of the workers, resulting in issues with safety and efficiency. The present invention aims to solve these issues and improve the safety and efficiency of workers at logistics centers.

[0917] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0918] In this invention, the server includes: means for inputting specification data of the concrete pole; means for inputting specification data of the communication device; means for transmitting the input data to a central computer; means for comparing the transmitted data with an internal database to obtain strength characteristics of the concrete pole; means for evaluating the feasibility of attaching the communication device based on the obtained strength characteristics; means for returning the evaluation results to a user terminal; means for displaying the evaluation results on the terminal; means for recognizing the emotional state of the user and adjusting the display method of the evaluation results; and means for enabling a user at a logistics center to use smart glasses to check how to handle packages and providing help information and warnings according to the user's emotional state. This allows workers at the logistics center to instantly check how to handle packages and improves safety and efficiency.

[0919] A "concrete pole" is a column-shaped structural member used to install and secure communication devices and other equipment.

[0920] A "communication device" is a device for sending and receiving data, and refers to a wide range of equipment including antennas and sensors.

[0921] "Specification data" refers to information that indicates the characteristics of concrete pillars and communication devices, such as their materials, dimensions, weight, and wind pressure coefficients.

[0922] A "central computer" is a computer system that centralizes data processing and typically functions as a server.

[0923] "Internal Database" means a data storage device that can store, search, and use required characteristic data.

[0924] "Strength properties" are physical characteristics that indicate how much load or pressure a material or structure can withstand.

[0925] "Attachability" is an index that evaluates whether a communication device can be attached safely and effectively to a concrete pole.

[0926] "User terminal" refers to a device used by a user to receive and display evaluation results, and includes smartphones, tablets, etc.

[0927] "Emotional state" indicates the user's current psychological and emotional state and is identified through facial expressions, tone of voice, etc.

[0928] "Smart glasses" are eyeglass-type devices that have the function of displaying information and are based on augmented reality (AR) technology.

[0929] "Help information" refers to support information that can be referred to when a worker performs a required operation.

[0930] "Caution" refers to information that provides warnings or advice to workers about specific actions or situations.

[0931] A "logistics center" is a facility that centralizes operations such as storing, sorting, and shipping goods.

[0932] The system for carrying out the present invention aims to improve the efficiency and safety of work in a logistics center. The system configuration is as follows.

[0933] System Configuration

[0934] 1. User device (smart glasses):

[0935] This is a device that allows users to input data and check the displayed results. Workers wear smart glasses and check how to handle packages and important points to note.

[0936] 2. Central computer (server):

[0937] This is the central computer that receives data, processes it, and returns the results. It evaluates the strength of the package and displays the results.

[0938] 3. Internal database:

[0939] This is a database that stores various strength data and characteristic data stored in the server.

[0940] 4. Emotion Engine:

[0941] This system recognizes the user's emotions and adjusts the way evaluation results are displayed based on that information.

[0942] Data Entry

[0943] The user uses the smart glasses to input package specifications, such as package type, weight, and dimensions, using voice commands or touch operations. A form is used as the input interface.

[0944] Data transmission

[0945] The device converts the input specification data into JSON or XML format and sends it to the server, where the smart glasses send the data to the server via Wi-Fi or Bluetooth.

[0946] Database collation

[0947] The server compares the received data with an internal database to obtain the strength characteristics data of the package, which contains the package's material, dimensions, and strength characteristics.

[0948] strength calculation

[0949] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load based on the weight of the package, then compares it with the maximum allowable load of the package acquired from the database, and applies a safety factor to make a final assessment and determine whether the package can be handled.

[0950] Results display

[0951] The server converts the strength calculation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Can be handled," "Caution required," and "Cannot be handled."

[0952] Use of emotion engine

[0953] The device analyzes the received results, and an emotion engine recognizes the user's emotional state before displaying them. It uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotions. It adjusts the display method based on the results. For example, if the user has concerns or questions about the assessment results, it provides a detailed explanation and support options for the "Caution Required" result.

[0954] Logging the user's emotional state

[0955] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[0956] Specific examples

[0957] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[0958] Prompt Sentence Examples

[0959] "What is the maximum weight allowable for this luggage?"

[0960] "Please tell me the steps to safely transport this package."

[0961] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0962] Step 1:

[0963] The user uses the smart glasses to input package specifications (package type, weight, dimensions) using voice commands or touch operations. The input data is acquired by a voice recognition system or touch sensor and converted into JSON or XML format within the device.

[0964] Input: Package type, weight, dimensions

[0965] Output: Package specification data in JSON or XML format

[0966] Step 2:

[0967] The terminal sends the converted specification data to the server via Wi-Fi or Bluetooth, using the communication module of the smart glasses.

[0968] Input: Package specification data in JSON or XML format

[0969] Output: Send data to the server

[0970] Step 3:

[0971] The server analyzes the received data and retrieves the strength characteristics data of the package by checking the data against its internal database. A database query module in the server is used.

[0972] Input: Package specification data sent by the user

[0973] Output: Strength characteristics data of the luggage

[0974] Step 4:

[0975] The server performs strength calculations based on the acquired strength characteristic data. The calculation module uses data such as weight, dimensions, and wind pressure coefficients to calculate the total load, compare it with the maximum allowable load, and apply a safety factor.

[0976] Input: Package strength characteristics data

[0977] Output: Evaluation result of the cargo handling feasibility

[0978] Step 5:

[0979] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation module is responsible for converting the results.

[0980] Input: Evaluation result of the cargo's feasibility

[0981] Output: Evaluation results in JSON or XML format

[0982] Step 6:

[0983] The terminal receives the evaluation results and parses the data. An analysis module interprets the data format and prepares it for display.

[0984] Input: Evaluation result returned from the server

[0985] Output: Analyzed evaluation result data

[0986] Step 7:

[0987] The device's emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state, and emotion recognition algorithms are used to generate the user's emotion data.

[0988] Input: User's facial expression, tone of voice

[0989] Output: User emotion data

[0990] Step 8:

[0991] The emotion engine adjusts the way the rating results are displayed based on the user's emotional state. For example, if the user is feeling anxious, it might display additional detailed explanations or support options. The display module is used.

[0992] Input: Analyzed evaluation result data, user emotion data

[0993] Output: Adjusted evaluation results

[0994] Step 9:

[0995] The terminal then displays the adjusted evaluation results on the smart glasses' display, allowing the worker to check how to handle the package and proceed with the work safely and efficiently.

[0996] Input: Adjusted evaluation results display

[0997] Output: Evaluation results displayed on the smart glasses display

[0998] Examples:

[0999] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[1000] Example prompt sentence:

[1001] "What is the maximum weight allowable for this luggage?"

[1002] "Please tell me the steps to safely transport this package."

[1003] 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.

[1004] 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.

[1005] 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.

[1006] [Third embodiment]

[1007] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1008] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1009] 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).

[1010] 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.

[1011] 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.

[1012] 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).

[1013] 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. 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.

[1014] 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.

[1015] 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.

[1016] 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.

[1017] 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.

[1018] 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."

[1019] MODE FOR CARRYING OUT THE INVENTION

[1020] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of the system will be described in detail below.

[1021] System Configuration

[1022] The system mainly consists of the following components:

[1023] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[1024] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[1025] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[1026] Data Entry

[1027] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[1028] Data transmission

[1029] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[1030] Database collation

[1031] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[1032] strength calculation

[1033] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[1034] Returning results

[1035] The server returns the results of the strength calculation to the terminal, including an evaluation such as "Installable," "Reinforcement required," or "Cannot be installed."

[1036] Results display

[1037] The terminal then displays the received results to the user. The user interface visually displays the evaluation results and provides guidance on appropriate actions, such as whether the antenna can be installed, whether reinforcement is required, or whether installation is impossible.

[1038] Specific usage scenarios

[1039] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the specifications of the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to the server, which retrieves strength characteristic data from its internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can check this result on the terminal and proceed with the antenna installation work with peace of mind.

[1040] In this way, the system of the present invention can quickly and accurately examine the strength of concrete pillars, contributing to ensuring the safety and stability of communication infrastructure.

[1041] The processing flow will be explained below.

[1042] Step 1:

[1043] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[1044] Step 2:

[1045] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[1046] json

[1047] {

[1048] "material": "iron",

[1049] "length": "10",

[1050] "diameter": "30",

[1051] "antenna_weight": "15",

[1052] "wind_coefficient": "1.2"

[1053] }

[1054] Step 3:

[1055] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for subsequent processing.

[1056] Step 4:

[1057] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[1058] sql

[1059] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[1060] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[1061] Step 5:

[1062] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding up the antenna's weight and wind pressure load. Specifically, the antenna's weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation yields the total load.

[1063] Step 6:

[1064] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[1065] Step 7:

[1066] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[1067] json

[1068] {

[1069] "result": "Installable"

[1070] }

[1071] Step 8:

[1072] The device analyzes the evaluation results received from the server and displays them on the user interface. The user can check the results on the device screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation work with peace of mind.

[1073] These steps allow the user to quickly and accurately assess the strength of the concrete pole and install the appropriate antenna.

[1074] Example 1

[1075] 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."

[1076] Previously, strength assessments for installing antennas on concrete poles were often done manually, which was time-consuming and involved the risk of calculation errors. Furthermore, there was a need for efficient processing of a variety of input data to quickly and accurately assess strength, but no system with these functions existed.

[1077] 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.

[1078] In this invention, the server includes means for receiving specification data for the concrete pole and the antenna input by the user, means for converting the input specification data into JSON or XML format, means for transmitting the converted data to the server, means for the server to compare the received data with an internal database and obtain strength characteristic data for the concrete pole, means for evaluating the feasibility of installing the antenna based on the obtained strength characteristic data, means for converting the evaluation results into JSON or XML format and returning them to the user terminal, and means for the user terminal to visually display the evaluation results and provide appropriate guidelines to the user. This enables complex and time-consuming strength evaluation work to be performed quickly and accurately, ensuring the safety and stability of the communication infrastructure.

[1079] A "user" is a person or organization that operates the system and inputs the required data.

[1080] A "terminal" is a device, such as a computer, smartphone, or tablet, that a user uses to enter data and view results.

[1081] A "server" is a central computer that receives data, checks it against an internal database, performs calculations, and returns the results.

[1082] "Specification data" refers to basic characteristic information about the concrete pole and antenna (material, length, diameter, weight, wind pressure coefficient, etc.).

[1083] "JSON format" stands for JavaScript Object Notation, a concise, easy-to-read text format for structuring data.

[1084] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structuring and flexibly describing data.

[1085] The "internal database" is a database system for processing various data (such as strength characteristic data) stored in the server.

[1086] "Strength characteristic data" refers to data regarding the physical strength of a concrete pillar, calculated based on its material, length, diameter, etc.

[1087] "Attachability" is a criterion for assessing whether an antenna can be safely attached to a concrete pole.

[1088] A "user interface" is a screen display or input means that allows a user to input data and check the results.

[1089] An "HTTP request" is a request for data transmission made from a terminal to a server.

[1090] An "HTTP response" is a data response sent back from a server to a terminal.

[1091] "Visual display" means presenting data and evaluation results on the screen in a way that is intuitively easy for users to understand.

[1092] MODE FOR CARRYING OUT THE INVENTION

[1093] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of this system are described below.

[1094] System Configuration

[1095] The system mainly consists of the following components:

[1096] 1. User terminal: A device that allows users to input data and display results. This includes personal computers, smartphones, tablets, etc.

[1097] 2. Server: A device that performs central calculations, manages databases, and returns results. Often located in a data center.

[1098] 3. Internal database: A database system stored on a server that stores important information such as strength property data and the physical properties of materials. A general database management system (DBMS) is used.

[1099] Data Entry

[1100] The user uses the device's user interface (e.g., a web browser form) to enter the following specification data:

[1101] Concrete pillar material (e.g. iron)

[1102] Length of concrete pillar (e.g. 10 meters)

[1103] Diameter of the concrete pillar (e.g. 30 cm)

[1104] Antenna weight (e.g. 15 kg)

[1105] Antenna wind pressure coefficient (e.g. 1.2)

[1106] Data transmission

[1107] The terminal converts the specification data entered by the user into JSON or XML format and sends it to the server as an HTTP request. This conversion is important to maintain the reliability of the data.

[1108] Database collation

[1109] The server interprets the data it receives and checks it against its internal database. Specifically, the server performs a database query to obtain the following information:

[1110] Physical property data related to the material of concrete pillars

[1111] Strength data for concrete pillars according to length and diameter

[1112] strength calculation

[1113] The server performs a strength calculation based on the received data, which includes the following steps:

[1114] Calculate the total load by adding the weight of the antenna and the wind load.

[1115] Compare the maximum allowable load of the concrete pillar obtained from the database with the total load.

[1116] Evaluate the possibility of installing the antenna, taking into account safety factors.

[1117] Return and display of results

[1118] The server converts the calculation results into JSON or XML format and sends them back to the terminal as an HTTP response. The terminal visually displays the received results in a user interface. Specifically, the result is displayed as "Installation possible," "Reinforcement required," or "Installation not possible," and the appropriate course of action is provided.

[1119] Specific usage scenarios

[1120] Suppose a user needs to install a new antenna on a steel concrete pole for urban development. Using a terminal, the user inputs the specifications of the concrete pole (steel, 10 meters, 30 centimeters in diameter) and the specifications of the antenna (weight 15 kilograms, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from an internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can confirm this result and proceed with the antenna installation work with peace of mind.

[1121] Example prompts for generative AI models

[1122] "I would like to examine the strength of an antenna attached to a steel concrete pole for urban development. The specifications for the concrete pole are steel, 10 meters long, and 30 centimeters in diameter, and the antenna weighs 15 kilograms and has a wind pressure coefficient of 1.2. Please calculate the strength of the concrete pole based on this data and let me know the results."

[1123] In this way, the system of the present invention provides an effective means for quickly and accurately conducting strength studies on concrete columns, improving the safety and stability of communications infrastructure.

[1124] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1125] Program processing flow

[1126] Step 1: Data entry

[1127] The user uses the terminal's user interface to input the specifications of the concrete pole and antenna, such as the material, length, and diameter of the concrete pole, the weight of the antenna, and the wind pressure coefficient, into a form.

[1128] input:

[1129] Concrete pillar material (e.g. iron)

[1130] Length of concrete pillar (e.g. 10m)

[1131] Diameter of the concrete pillar (e.g. 30cm)

[1132] Antenna weight (e.g. 15kg)

[1133] Antenna wind pressure coefficient (e.g. 1.2)

[1134] output:

[1135] The data entered into the form is displayed on the device.

[1136] Step 2: Send data

[1137] The terminal converts the specification data entered by the user into JSON or XML format, ensuring the authenticity and integrity of the data, and then sends the converted data to the server as an HTTP request.

[1138] input:

[1139] Specification data entered into the form

[1140] Data processing:

[1141] Conversion to JSON or XML format

[1142] output:

[1143] HTTP request sent to the server

[1144] Step 3: Database Matching

[1145] The server interprets the received data and checks it against its internal database. The server performs a database query to retrieve physical property data and strength data related to the material, length, and diameter of the concrete pole.

[1146] input:

[1147] Specification data received

[1148] Data Calculation:

[1149] Executing a Database Query

[1150] output:

[1151] Obtained strength characteristic data

[1152] Step 4: Strength calculation

[1153] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load by adding the wind load to the weight of the antenna. Next, it compares this with the acquired maximum allowable load of the concrete pillar and applies a safety factor to make a final assessment.

[1154] input:

[1155] Obtained strength characteristic data

[1156] Specification data received

[1157] Data Calculation:

[1158] Calculating the total load

[1159] Comparison with maximum allowable load

[1160] Application and evaluation of safety factors

[1161] output:

[1162] Evaluation results for antenna installation feasibility

[1163] Step 5: Returning the results

[1164] The server converts the evaluation results into JSON or XML format and sends them back to the device as an HTTP response. This conversion ensures the reliability and integrity of the results.

[1165] input:

[1166] Evaluation results

[1167] Data processing:

[1168] Conversion to JSON or XML format

[1169] output:

[1170] Evaluation result as an HTTP response

[1171] Step 6: View the results

[1172] The terminal visually displays the received results on a user interface. Specifically, the evaluation results ("Installation Possible," "Reinforcement Required," "Installation Unavailable") are displayed on the screen, along with appropriate guidelines for action.

[1173] input:

[1174] Evaluation results sent from the server

[1175] output:

[1176] Displaying results on the user's device

[1177] Through this series of processes, users can quickly and accurately assess the strength of the concrete pillar, allowing them to proceed with antenna installation work with peace of mind.

[1178] (Application example 1)

[1179] 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."

[1180] When installing or renovating machinery in a factory environment, it is difficult to quickly and accurately perform strength analysis. Conventional methods require numerous manual calculations and checks before installation, which is time-consuming and labor-intensive, resulting in reduced productivity and safety risks due to incorrect installation.

[1181] 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.

[1182] In this invention, the server includes means for inputting specification data for the concrete pole, means for inputting specification data for the installation structure, means for transmitting the input data to the server, means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the structure, means for evaluating the feasibility of installing equipment based on the acquired strength characteristics, means for returning the evaluation results to a user terminal and an operation device, and means for displaying the evaluation results on the terminal and the operation device. This enables rapid and accurate strength assessment when installing or renovating machinery and equipment in a factory environment, thereby improving productivity and ensuring safety.

[1183] A "concrete pillar" is a columnar structure used for work and equipment installation.

[1184] "Installation structure" means the physical installation environment for mounting the equipment, including concrete columns and other supporting structures.

[1185] "Specification data" refers to data that includes specific numerical information regarding physical characteristics and design.

[1186] A "server" is a central computer that receives data, processes it, and returns the results.

[1187] The "internal database" is a system stored in the server that saves various strength data and characteristic data.

[1188] "Strength characteristics" are numerical data that indicate the characteristics of materials and structures, such as load-bearing capacity and wind resistance.

[1189] "Installability" is an index used to evaluate whether equipment can be installed safely and correctly under specific conditions.

[1190] A "user terminal" is a device that allows a user to input data and check the results.

[1191] The present invention is embodied as a system for quickly and accurately conducting strength studies when installing or modifying machinery in a factory environment. The system includes a user terminal, a server, an internal database, and an articulated robot arm.

[1192] Hardware and Software Configuration

[1193] Hardware: Multi-joint robot arm, user terminal (tablet PC), server (high-performance PC)

[1194] Software: Robot control software (ROS-based), data transmission and reception module (HTTP / REST API), internal database (PostgreSQL), strength calculation algorithm (Python script)

[1195] Processing Details

[1196] 1. User Interface:

[1197] The user uses a GUI form that runs on a tablet PC to input specification data for the equipment and installation structure, including data such as "material, length, dimensions," "weight, and pressure coefficient."

[1198] 2. Data transmission:

[1199] The user terminal converts the input specification data into JSON format and sends it to the server using an HTTP request.

[1200] 3. Server Processing:

[1201] The server receives the data using a Python script and compares it with a PostgreSQL database to obtain structural and material strength property data.

[1202] 4. Strength calculation:

[1203] The server uses the acquired characteristic data to perform the necessary strength calculations, including algorithms that evaluate safety and installability based on input data on the equipment and installation structure.

[1204] 5. Return of evaluation results:

[1205] The calculation results are sent back to the user device and robot in JSON format. The evaluation results include judgments such as "Installation possible," "Reinforcement required," and "Installation not possible."

[1206] 6. Results display and robot behavior:

[1207] The user terminal and robot decide the next action based on the evaluation results sent back. If an appropriate response is required, a warning or instruction is displayed.

[1208] Specific examples

[1209] When installing a new piece of machinery in a factory, the user inputs the material's specifications (steel, length: 2m, diameter: 10cm) and the equipment's weight (50kg, wind pressure coefficient: 1.5). This data is sent to the server, which compares it with its internal database and performs strength calculations. The result is a response that the equipment can be installed, allowing the user and robot to proceed with their work with peace of mind.

[1210] Example prompt for a generative AI model:

[1211] "Please assess the feasibility of mounting this equipment. The pole is made of steel, is 2m long, has a diameter of 10cm, weighs 50kg, and has a wind pressure coefficient of 1.5."

[1212] The system enables efficient and safe installation and modification of machinery in a factory environment.

[1213] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1214] Step 1:

[1215] Data entry in the user interface

[1216] Users use a GUI form on a tablet PC to input specification data for the equipment and installation structure, such as the material, length, and dimensions of the columns and the weight and wind pressure coefficient of the equipment. This data is then digitally imported into the system.

[1217] (Input:) Specifications of the equipment and installation structure entered by the user (e.g., material: steel, length: 2 m, diameter: 10 cm, weight: 50 kg, wind pressure coefficient: 1.5)

[1218] (Output:) Digital representation of input data

[1219] Step 2:

[1220] Data Conversion and Transmission

[1221] The terminal converts the input specification data into JSON format, which is then sent to the server as an HTTP request.

[1222] (Input:) Digital specification data

[1223] (Output:) JSON formatted data and HTTP request

[1224] Step 3:

[1225] Receiving data on the server

[1226] The server receives the HTTP request and parses the JSON data, which is then ready to be checked against an internal database.

[1227] (Input:) JSON data sent as an HTTP request

[1228] (Output:) Parsed data

[1229] Step 4:

[1230] Database collation

[1231] Based on the analyzed data, the server checks the PostgreSQL database to obtain strength property data of the installation structure and materials, which are used for strength calculations.

[1232] (Input:) Parsed specification data

[1233] (Output:) Strength property data retrieved from the database

[1234] Step 5:

[1235] strength calculation

[1236] The server performs the necessary strength calculations using the acquired strength characteristic data. First, it calculates the pressure and load based on the input amount and characteristic data, and then calculates the safety factor and other factors based on that.

[1237] (Input:) Obtained strength characteristic data and specification data from the user

[1238] (Output:) Strength calculation results (assessment of installation feasibility: installable, reinforcement required, not installable)

[1239] Step 6:

[1240] Return of evaluation results

[1241] The server converts the calculation results into JSON format and sends them back to the user's device and the robot, thereby transmitting the evaluation results to the device and the robot.

[1242] (Input:) Strength calculation result

[1243] (Output:) Evaluation result data in JSON format

[1244] Step 7:

[1245] Result display and robot operation

[1246] The user terminal and robot receive the returned evaluation results and display the results in the GUI or control interface. For example, if the result is "Installation possible," the robot will begin the installation work. If the evaluation result is anything other than that, the robot will display a warning and stop the work.

[1247] (Input:) Evaluation result data in JSON format

[1248] (Output:) Display of evaluation results and robot control actions

[1249] 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.

[1250] MODE FOR CARRYING OUT THE INVENTION

[1251] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the way the evaluation results are displayed and improve the user experience. Specific embodiments of this system are described in detail below.

[1252] System Configuration

[1253] The system mainly consists of the following components:

[1254] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[1255] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[1256] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[1257] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[1258] Data Entry

[1259] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[1260] Data transmission

[1261] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[1262] Database collation

[1263] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[1264] strength calculation

[1265] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[1266] Returning results

[1267] The server converts the strength calculation results into JSON or XML format and sends them back to the terminal. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[1268] Displaying results and using the emotion engine

[1269] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[1270] For example, if a user is anxious or suspicious about the assessment results, the emotion engine will provide detailed explanations and support options for the "reinforcement needed" result, whereas if the user is relaxed, only the basic result will be displayed.

[1271] Logging the user's emotional state

[1272] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[1273] Specific usage scenarios

[1274] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from its internal database. The server then performs strength calculations and returns the result "Installation possible" to the terminal.

[1275] If the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is feeling anxious, it will not only tell the user that installation is possible, but also provide technical background information and safety guarantees, allowing the user to proceed with the antenna installation with peace of mind.

[1276] In this way, the system of the present invention can quickly and accurately assess the strength of concrete pillars, and by providing appropriate information in response to the user's emotions, ensure the safety and stability of the communications infrastructure.

[1277] The processing flow will be explained below.

[1278] Step 1:

[1279] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[1280] Step 2:

[1281] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[1282] json

[1283] {

[1284] "material": "iron",

[1285] "length": "10",

[1286] "diameter": "30",

[1287] "antenna_weight": "15",

[1288] "wind_coefficient": "1.2"

[1289] }

[1290] Step 3:

[1291] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for further processing.

[1292] Step 4:

[1293] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[1294] sql

[1295] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[1296] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[1297] Step 5:

[1298] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding the antenna weight and wind pressure load. Specifically, the antenna weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation derives the total load.

[1299] Step 6:

[1300] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[1301] Step 7:

[1302] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[1303] json

[1304] {

[1305] "result": "Installable"

[1306] }

[1307] Step 8:

[1308] The device analyzes the evaluation results received from the server, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions.

[1309] Step 9:

[1310] The emotion engine recognizes the user's emotions and adjusts the display accordingly. For example, if the user is anxious or uncertain, the system will provide a detailed explanation and support options for the "reinforcement needed" result. On the other hand, if the user is relaxed, the system will only display the basic result.

[1311] Step 10:

[1312] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[1313] Step 11:

[1314] The terminal displays the final evaluation result on the user interface. The user can check the result on the screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation with peace of mind.

[1315] Example 2

[1316] 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."

[1317] Conventional strength assessment systems for installing antennas on concrete poles require time-consuming calculation and evaluation processes, and the display method is not adjusted to reflect user needs. This results in a poor user experience and can make it difficult to understand the strength assessment results. Furthermore, some users feel uneasy or have doubts, leading to problems with not being able to trust the assessment results.

[1318] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1319] In this invention, the server includes means for inputting concrete pole specification data, means for inputting antenna specification data, means for transmitting the input data to a central computing device, means for comparing the transmitted data with an internal database to obtain the strength characteristics of the concrete pole, means for evaluating the feasibility of antenna installation based on the obtained strength characteristics, means for returning the evaluation results to a user terminal, means for displaying the evaluation results on the terminal, and an emotion engine for recognizing the user's emotions and adjusting the display method of the evaluation results. This enables the strength consideration process to be carried out quickly and accurately, and also makes it possible to provide appropriate information according to the user's emotional state, thereby improving the user experience and facilitating understanding of the evaluation results.

[1320] "Specification data for concrete poles" refers to data that represents the physical and material characteristics of concrete poles, such as the material, length, and diameter of the concrete poles.

[1321] "Antenna specification data" refers to data that describes the physical and usage conditions of an antenna, such as the antenna's weight and wind pressure coefficient.

[1322] A "central computing device" is a server that receives input data, processes it, and returns the results.

[1323] The "internal database" is a data storage device stored within the server that stores various data, such as strength characteristic data for concrete columns.

[1324] The "emotion engine" is a system that recognizes the user's emotional state and adjusts the way evaluation results are displayed based on that information.

[1325] The "evaluation results" are the results of a strength evaluation when attaching an antenna to a concrete pole, and are data that includes information such as "installable," "reinforcement required," and "uninstallable."

[1326] A "user terminal" is a device that refers to a computer or smart device that provides an interface for users to input data and display evaluation results.

[1327] "Strength characteristics" refers to physical property data relating to the strength of the concrete pillar based on its material and shape, and is standard data for making the evaluations required for antenna installation.

[1328] "Specification Data" means data that defines the physical and functional characteristics of a particular pole or antenna.

[1329] MODE FOR CARRYING OUT THE INVENTION

[1330] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it adjusts the way the evaluation results are displayed, improving the user experience. Specific embodiments of this system are described in detail below.

[1331] System Configuration

[1332] The system consists of the following components:

[1333] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[1334] 2. Server: A central computing device that is responsible for receiving data, processing it, and returning the results.

[1335] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[1336] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[1337] How to use the system

[1338] 1. Data Entry

[1339] The user uses the user terminal to input specification data for the concrete pole and the antenna. For example, the material, length, and diameter are input as specifications for the concrete pole, and the weight and wind pressure coefficient are input as specifications for the antenna.

[1340] 2. Data Transmission

[1341] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[1342] 3. Database Verification

[1343] The server compares the received data with its internal database to obtain strength characteristic data corresponding to the material, length, and diameter of the concrete pole, enabling it to evaluate the strength required for antenna installation.

[1344] 4. Strength calculation

[1345] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Next, it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[1346] 5. Return of results

[1347] The server converts the strength calculation results into JSON or XML format and sends them back to the user's device. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[1348] 6. Displaying results and using the emotion engine

[1349] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[1350] For example, if a user wants to install a new antenna on a steel concrete pole for urban development, the user uses the terminal to enter the following specification data:

[1351] Concrete pillar specifications: iron, 10m, diameter 30cm

[1352] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[1353] This data is sent to a server, which retrieves strength characteristic data from an internal database, performs strength calculations, and returns a result of "Installation Possible" to the user's device. At this time, the emotion engine analyzes the user's facial expression and tone of voice, and if it recognizes that the user is feeling anxious, it displays the "Installation Possible" result along with detailed technical explanations and information about safety guarantees. In this way, the user's anxiety is alleviated, allowing them to proceed with the antenna installation work with peace of mind.

[1354] Example usage scenarios

[1355] For example, you can use the system with the following prompt:

[1356] "Please quickly and accurately evaluate the strength of attaching an antenna to a steel concrete pole, and adjust the way the results are displayed depending on the user's emotional state. Please perform strength calculations based on the following specifications and return the results."

[1357] Concrete pillar specifications: iron, 10m, diameter 30cm

[1358] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[1359] This system not only enables rapid and accurate strength assessment of concrete pillars, but also provides information according to the user's emotions, ensuring the safety of the communications infrastructure.

[1360] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1361] Step 1: Data entry

[1362] The user accesses the system using a user terminal. They enter the specifications of the concrete pole and antenna into the specified form. Specifically, they enter the specifications of the concrete pole (material, length, diameter) and the antenna (weight, wind pressure coefficient). For example, the material of the concrete pole is entered as "iron," the length as "10m," and the diameter as "30cm," and the weight of the antenna as "15kg" and the wind pressure coefficient as "1.2." The user checks the information entered and clicks the send button.

[1363] Input: User input of specification data (material, length, diameter, weight, wind pressure coefficient)

[1364] Output: Formatted specification data

[1365] Step 2: Send data

[1366] The terminal takes the specification data entered by the user and converts it into JSON or XML format. The converted data is sent to the server. For example, the converted data looks like this:

[1367] json

[1368] {

[1369] "Con Pillar": {

[1370] "Material": "Iron",

[1371] "Length": "10m",

[1372] "Diameter": "30cm"

[1373] },

[1374] "antenna": {

[1375] "Weight": "15kg",

[1376] "Wind Pressure Coefficient": "1.2"

[1377] }

[1378] }

[1379] Input: Formatted specification data

[1380] Output: Data sent to the server

[1381] Step 3: Database Matching

[1382] The server receives and analyzes the data sent from the terminal. Specifically, it checks the internal database based on the material, length, and diameter of the concrete pole to obtain strength characteristic data. For example, it obtains corresponding strength characteristic data from existing data for steel concrete poles.

[1383] Input: Data sent to the server (material, length, diameter, weight, wind pressure coefficient)

[1384] Output: Strength characteristic data

[1385] Step 4: Strength calculation

[1386] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind pressure load to the weight of the antenna to calculate the total load. Next, it compares the calculated total load with the maximum allowable load of the concrete pillar acquired from the database, and then applies a safety factor to make a final evaluation. Specifically, for example, it calculates total load = 15 kg (weight) + (1.2 x wind pressure rate) and compares it with the maximum allowable load.

[1387] Input: Strength characteristics data and input specification data

[1388] Output: Strength evaluation result (Installable, Reinforcement required, Uninstallable)

[1389] Step 5: Returning the results

[1390] The server converts the results of the strength calculation into JSON or XML format and sends it back to the user device. For example, the result data looks like this:

[1391] json

[1392] {

[1393] "Evaluation result": "Installable"

[1394] }

[1395] Input: Strength evaluation results

[1396] Output: Evaluation results sent to the user's device

[1397] Step 6: Displaying the results and using the emotion engine

[1398] The device receives the result data returned from the server and activates the emotion engine before analyzing it. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state. Based on the results, the display of the evaluation results can be adjusted. For example, if the user is feeling anxious, the device will display the "Installable" result along with technical details and safety guarantees. On the other hand, if the user is relaxed, only the basic results will be displayed.

[1399] Input: Evaluation results and user's emotional state

[1400] Output: Evaluation results in a tailored display format

[1401] Step 7: Logging the user's emotional state

[1402] The emotion engine records the user's emotional state as log data and feeds it back into future evaluations and display adjustments. This allows the system to learn the user's usage patterns and emotional responses, enabling more accurate emotion recognition and display results in the future.

[1403] Input: User's emotional state

[1404] Output: Log data and feedback information

[1405] (Application example 2)

[1406] 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."

[1407] In the past, logistics center workers lacked a system for obtaining information on how to handle packages and taking appropriate measures immediately. Furthermore, there was a lack of information provided based on the strength assessment of package handling and the emotional state of the workers, resulting in issues with safety and efficiency. The present invention aims to solve these issues and improve the safety and efficiency of workers at logistics centers.

[1408] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1409] In this invention, the server includes: means for inputting specification data of the concrete pole; means for inputting specification data of the communication device; means for transmitting the input data to a central computer; means for comparing the transmitted data with an internal database to obtain strength characteristics of the concrete pole; means for evaluating the feasibility of attaching the communication device based on the obtained strength characteristics; means for returning the evaluation results to a user terminal; means for displaying the evaluation results on the terminal; means for recognizing the emotional state of the user and adjusting the display method of the evaluation results; and means for enabling a user at a logistics center to use smart glasses to check how to handle packages and providing help information and warnings according to the user's emotional state. This allows workers at the logistics center to instantly check how to handle packages and improves safety and efficiency.

[1410] A "concrete pole" is a column-shaped structural member used to install and secure communication devices and other equipment.

[1411] A "communication device" is a device for sending and receiving data, and refers to a wide range of equipment including antennas and sensors.

[1412] "Specification data" refers to information that indicates the characteristics of concrete pillars and communication devices, such as their materials, dimensions, weight, and wind pressure coefficients.

[1413] A "central computer" is a computer system that centralizes data processing and typically functions as a server.

[1414] "Internal Database" means a data storage device that can store, search, and use required characteristic data.

[1415] "Strength properties" are physical characteristics that indicate how much load or pressure a material or structure can withstand.

[1416] "Attachability" is an index that evaluates whether a communication device can be attached safely and effectively to a concrete pole.

[1417] "User terminal" refers to a device used by a user to receive and display evaluation results, and includes smartphones, tablets, etc.

[1418] "Emotional state" indicates the user's current psychological and emotional state and is identified through facial expressions, tone of voice, etc.

[1419] "Smart glasses" are eyeglass-type devices that have the function of displaying information and are based on augmented reality (AR) technology.

[1420] "Help information" refers to support information that can be referred to when a worker performs a required operation.

[1421] "Caution" refers to information that provides warnings or advice to workers about specific actions or situations.

[1422] A "logistics center" is a facility that centralizes operations such as storing, sorting, and shipping goods.

[1423] The system for carrying out the present invention aims to improve the efficiency and safety of work in a logistics center. The system configuration is as follows.

[1424] System Configuration

[1425] 1. User device (smart glasses):

[1426] This is a device that allows users to input data and check the displayed results. Workers wear smart glasses and check how to handle packages and important points to note.

[1427] 2. Central computer (server):

[1428] This is the central computer that receives data, processes it, and returns the results. It evaluates the strength of the package and displays the results.

[1429] 3. Internal database:

[1430] This is a database that stores various strength data and characteristic data stored in the server.

[1431] 4. Emotion Engine:

[1432] This system recognizes the user's emotions and adjusts the way evaluation results are displayed based on that information.

[1433] Data Entry

[1434] The user uses the smart glasses to input package specifications, such as package type, weight, and dimensions, using voice commands or touch operations. A form is used as the input interface.

[1435] Data transmission

[1436] The device converts the input specification data into JSON or XML format and sends it to the server, where the smart glasses send the data to the server via Wi-Fi or Bluetooth.

[1437] Database collation

[1438] The server compares the received data with an internal database to obtain the strength characteristics data of the package, which contains the package's material, dimensions, and strength characteristics.

[1439] strength calculation

[1440] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load based on the weight of the package, then compares it with the maximum allowable load of the package acquired from the database, and applies a safety factor to make a final assessment and determine whether the package can be handled.

[1441] Results display

[1442] The server converts the strength calculation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Can be handled," "Caution required," and "Cannot be handled."

[1443] Use of emotion engine

[1444] The device analyzes the received results, and an emotion engine recognizes the user's emotional state before displaying them. It uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotions. It adjusts the display method based on the results. For example, if the user has concerns or questions about the assessment results, it provides a detailed explanation and support options for the "Caution Required" result.

[1445] Logging the user's emotional state

[1446] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[1447] Specific examples

[1448] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[1449] Prompt Sentence Examples

[1450] "What is the maximum weight allowable for this luggage?"

[1451] "Please tell me the steps to safely transport this package."

[1452] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1453] Step 1:

[1454] The user uses the smart glasses to input package specifications (package type, weight, dimensions) using voice commands or touch operations. The input data is acquired by a voice recognition system or touch sensor and converted into JSON or XML format within the device.

[1455] Input: Package type, weight, dimensions

[1456] Output: Package specification data in JSON or XML format

[1457] Step 2:

[1458] The terminal sends the converted specification data to the server via Wi-Fi or Bluetooth, using the communication module of the smart glasses.

[1459] Input: Package specification data in JSON or XML format

[1460] Output: Send data to the server

[1461] Step 3:

[1462] The server analyzes the received data and retrieves the strength characteristics data of the package by checking the data against its internal database. A database query module in the server is used.

[1463] Input: Package specification data sent by the user

[1464] Output: Strength characteristics data of the luggage

[1465] Step 4:

[1466] The server performs strength calculations based on the acquired strength characteristic data. The calculation module uses data such as weight, dimensions, and wind pressure coefficients to calculate the total load, compare it with the maximum allowable load, and apply a safety factor.

[1467] Input: Package strength characteristics data

[1468] Output: Evaluation result of the cargo handling feasibility

[1469] Step 5:

[1470] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation module is responsible for converting the results.

[1471] Input: Evaluation result of the cargo's feasibility

[1472] Output: Evaluation results in JSON or XML format

[1473] Step 6:

[1474] The terminal receives the evaluation results and parses the data. An analysis module interprets the data format and prepares it for display.

[1475] Input: Evaluation result returned from the server

[1476] Output: Analyzed evaluation result data

[1477] Step 7:

[1478] The device's emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state, and emotion recognition algorithms are used to generate the user's emotion data.

[1479] Input: User's facial expression, tone of voice

[1480] Output: User emotion data

[1481] Step 8:

[1482] The emotion engine adjusts the way the rating results are displayed based on the user's emotional state. For example, if the user is feeling anxious, it might display additional detailed explanations or support options. The display module is used.

[1483] Input: Analyzed evaluation result data, user emotion data

[1484] Output: Adjusted evaluation results

[1485] Step 9:

[1486] The terminal then displays the adjusted evaluation results on the smart glasses' display, allowing the worker to check how to handle the package and proceed with the work safely and efficiently.

[1487] Input: Adjusted evaluation results display

[1488] Output: Evaluation results displayed on the smart glasses display

[1489] Examples:

[1490] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[1491] Example prompt sentence:

[1492] "What is the maximum weight allowable for this luggage?"

[1493] "Please tell me the steps to safely transport this package."

[1494] 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.

[1495] 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.

[1496] 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.

[1497] [Fourth embodiment]

[1498] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1499] 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.

[1500] 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).

[1501] 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.

[1502] 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.

[1503] 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).

[1504] 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. 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.

[1505] 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.

[1506] 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.

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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."

[1511] MODE FOR CARRYING OUT THE INVENTION

[1512] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of the system will be described in detail below.

[1513] System Configuration

[1514] The system mainly consists of the following components:

[1515] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[1516] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[1517] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[1518] Data Entry

[1519] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[1520] Data transmission

[1521] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[1522] Database collation

[1523] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[1524] strength calculation

[1525] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[1526] Returning results

[1527] The server returns the results of the strength calculation to the terminal, including an evaluation such as "Installable," "Reinforcement required," or "Cannot be installed."

[1528] Results display

[1529] The terminal then displays the received results to the user. The user interface visually displays the evaluation results and provides guidance on appropriate actions, such as whether the antenna can be installed, whether reinforcement is required, or whether installation is impossible.

[1530] Specific usage scenarios

[1531] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the specifications of the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to the server, which retrieves strength characteristic data from its internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can check this result on the terminal and proceed with the antenna installation work with peace of mind.

[1532] In this way, the system of the present invention can quickly and accurately examine the strength of concrete pillars, contributing to ensuring the safety and stability of communication infrastructure.

[1533] The processing flow will be explained below.

[1534] Step 1:

[1535] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[1536] Step 2:

[1537] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[1538] json

[1539] {

[1540] "material": "iron",

[1541] "length": "10",

[1542] "diameter": "30",

[1543] "antenna_weight": "15",

[1544] "wind_coefficient": "1.2"

[1545] }

[1546] Step 3:

[1547] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for subsequent processing.

[1548] Step 4:

[1549] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[1550] sql

[1551] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[1552] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[1553] Step 5:

[1554] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding up the antenna's weight and wind pressure load. Specifically, the antenna's weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation yields the total load.

[1555] Step 6:

[1556] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[1557] Step 7:

[1558] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[1559] json

[1560] {

[1561] "result": "Installable"

[1562] }

[1563] Step 8:

[1564] The device analyzes the evaluation results received from the server and displays them on the user interface. The user can check the results on the device screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation work with peace of mind.

[1565] These steps allow the user to quickly and accurately assess the strength of the concrete pole and install the appropriate antenna.

[1566] Example 1

[1567] 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."

[1568] Previously, strength assessments for installing antennas on concrete poles were often done manually, which was time-consuming and involved the risk of calculation errors. Furthermore, there was a need for efficient processing of a variety of input data to quickly and accurately assess strength, but no system with these functions existed.

[1569] 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.

[1570] In this invention, the server includes means for receiving specification data for the concrete pole and the antenna input by the user, means for converting the input specification data into JSON or XML format, means for transmitting the converted data to the server, means for the server to compare the received data with an internal database and obtain strength characteristic data for the concrete pole, means for evaluating the feasibility of installing the antenna based on the obtained strength characteristic data, means for converting the evaluation results into JSON or XML format and returning them to the user terminal, and means for the user terminal to visually display the evaluation results and provide appropriate guidelines to the user. This enables complex and time-consuming strength evaluation work to be performed quickly and accurately, ensuring the safety and stability of the communication infrastructure.

[1571] A "user" is a person or organization that operates the system and inputs the required data.

[1572] A "terminal" is a device, such as a computer, smartphone, or tablet, that a user uses to enter data and view results.

[1573] A "server" is a central computer that receives data, checks it against an internal database, performs calculations, and returns the results.

[1574] "Specification data" refers to basic characteristic information about the concrete pole and antenna (material, length, diameter, weight, wind pressure coefficient, etc.).

[1575] "JSON format" stands for JavaScript Object Notation, a concise, easy-to-read text format for structuring data.

[1576] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structuring and flexibly describing data.

[1577] The "internal database" is a database system for processing various data (such as strength characteristic data) stored in the server.

[1578] "Strength characteristic data" refers to data regarding the physical strength of a concrete pillar, calculated based on its material, length, diameter, etc.

[1579] "Attachability" is a criterion for assessing whether an antenna can be safely attached to a concrete pole.

[1580] A "user interface" is a screen display or input means that allows a user to input data and check the results.

[1581] An "HTTP request" is a request for data transmission made from a terminal to a server.

[1582] An "HTTP response" is a data response sent back from a server to a terminal.

[1583] "Visual display" means presenting data and evaluation results on the screen in a way that is intuitively easy for users to understand.

[1584] MODE FOR CARRYING OUT THE INVENTION

[1585] This invention provides a system for quickly and accurately examining the strength of an antenna when attaching it to a concrete pole. Specific embodiments of this system are described below.

[1586] System Configuration

[1587] The system mainly consists of the following components:

[1588] 1. User terminal: A device that allows users to input data and display results. This includes personal computers, smartphones, tablets, etc.

[1589] 2. Server: A device that performs central calculations, manages databases, and returns results. Often located in a data center.

[1590] 3. Internal database: A database system stored on a server that stores important information such as strength property data and the physical properties of materials. A general database management system (DBMS) is used.

[1591] Data Entry

[1592] The user uses the device's user interface (e.g., a web browser form) to enter the following specification data:

[1593] Concrete pillar material (e.g. iron)

[1594] Length of concrete pillar (e.g. 10 meters)

[1595] Diameter of the concrete pillar (e.g. 30 cm)

[1596] Antenna weight (e.g. 15 kg)

[1597] Antenna wind pressure coefficient (e.g. 1.2)

[1598] Data transmission

[1599] The terminal converts the specification data entered by the user into JSON or XML format and sends it to the server as an HTTP request. This conversion is important to maintain the reliability of the data.

[1600] Database collation

[1601] The server interprets the data it receives and checks it against its internal database. Specifically, the server performs a database query to obtain the following information:

[1602] Physical property data related to the material of concrete pillars

[1603] Strength data for concrete pillars according to length and diameter

[1604] strength calculation

[1605] The server performs a strength calculation based on the received data, which includes the following steps:

[1606] Calculate the total load by adding the weight of the antenna and the wind load.

[1607] Compare the maximum allowable load of the concrete pillar obtained from the database with the total load.

[1608] Evaluate the possibility of installing the antenna, taking into account safety factors.

[1609] Return and display of results

[1610] The server converts the calculation results into JSON or XML format and sends them back to the terminal as an HTTP response. The terminal visually displays the received results in a user interface. Specifically, the result is displayed as "Installation possible," "Reinforcement required," or "Installation not possible," and the appropriate course of action is provided.

[1611] Specific usage scenarios

[1612] Suppose a user needs to install a new antenna on a steel concrete pole for urban development. Using a terminal, the user inputs the specifications of the concrete pole (steel, 10 meters, 30 centimeters in diameter) and the specifications of the antenna (weight 15 kilograms, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from an internal database. The server then performs a strength calculation and returns the result "Installation possible" to the terminal. The user can confirm this result and proceed with the antenna installation work with peace of mind.

[1613] Example prompts for generative AI models

[1614] "I would like to examine the strength of an antenna attached to a steel concrete pole for urban development. The specifications for the concrete pole are steel, 10 meters long, and 30 centimeters in diameter, and the antenna weighs 15 kilograms and has a wind pressure coefficient of 1.2. Please calculate the strength of the concrete pole based on this data and let me know the results."

[1615] In this way, the system of the present invention provides an effective means for quickly and accurately conducting strength studies on concrete columns, improving the safety and stability of communications infrastructure.

[1616] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1617] Program processing flow

[1618] Step 1: Data entry

[1619] The user uses the terminal's user interface to input the specifications of the concrete pole and antenna, such as the material, length, and diameter of the concrete pole, the weight of the antenna, and the wind pressure coefficient, into a form.

[1620] input:

[1621] Concrete pillar material (e.g. iron)

[1622] Length of concrete pillar (e.g. 10m)

[1623] Diameter of the concrete pillar (e.g. 30cm)

[1624] Antenna weight (e.g. 15kg)

[1625] Antenna wind pressure coefficient (e.g. 1.2)

[1626] output:

[1627] The data entered into the form is displayed on the device.

[1628] Step 2: Send data

[1629] The terminal converts the specification data entered by the user into JSON or XML format, ensuring the authenticity and integrity of the data, and then sends the converted data to the server as an HTTP request.

[1630] input:

[1631] Specification data entered into the form

[1632] Data processing:

[1633] Conversion to JSON or XML format

[1634] output:

[1635] HTTP request sent to the server

[1636] Step 3: Database Matching

[1637] The server interprets the received data and checks it against its internal database. The server performs a database query to retrieve physical property data and strength data related to the material, length, and diameter of the concrete pole.

[1638] input:

[1639] Specification data received

[1640] Data Calculation:

[1641] Executing a Database Query

[1642] output:

[1643] Obtained strength characteristic data

[1644] Step 4: Strength calculation

[1645] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load by adding the wind load to the weight of the antenna. Next, it compares this with the acquired maximum allowable load of the concrete pillar and applies a safety factor to make a final assessment.

[1646] input:

[1647] Obtained strength characteristic data

[1648] Specification data received

[1649] Data Calculation:

[1650] Calculating the total load

[1651] Comparison with maximum allowable load

[1652] Application and evaluation of safety factors

[1653] output:

[1654] Evaluation results for antenna installation feasibility

[1655] Step 5: Returning the results

[1656] The server converts the evaluation results into JSON or XML format and sends them back to the device as an HTTP response. This conversion ensures the reliability and integrity of the results.

[1657] input:

[1658] Evaluation results

[1659] Data processing:

[1660] Conversion to JSON or XML format

[1661] output:

[1662] Evaluation result as an HTTP response

[1663] Step 6: View the results

[1664] The terminal visually displays the received results on a user interface. Specifically, the evaluation results ("Installation Possible," "Reinforcement Required," "Installation Unavailable") are displayed on the screen, along with appropriate guidelines for action.

[1665] input:

[1666] Evaluation results sent from the server

[1667] output:

[1668] Displaying results on the user's device

[1669] Through this series of processes, users can quickly and accurately assess the strength of the concrete pillar, allowing them to proceed with antenna installation work with peace of mind.

[1670] (Application example 1)

[1671] 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."

[1672] When installing or renovating machinery in a factory environment, it is difficult to quickly and accurately perform strength analysis. Conventional methods require numerous manual calculations and checks before installation, which is time-consuming and labor-intensive, resulting in reduced productivity and safety risks due to incorrect installation.

[1673] 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.

[1674] In this invention, the server includes means for inputting specification data for the concrete pole, means for inputting specification data for the installation structure, means for transmitting the input data to the server, means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the structure, means for evaluating the feasibility of installing equipment based on the acquired strength characteristics, means for returning the evaluation results to a user terminal and an operation device, and means for displaying the evaluation results on the terminal and the operation device. This enables rapid and accurate strength assessment when installing or renovating machinery and equipment in a factory environment, thereby improving productivity and ensuring safety.

[1675] A "concrete pillar" is a columnar structure used for work and equipment installation.

[1676] "Installation structure" means the physical installation environment for mounting the equipment, including concrete columns and other supporting structures.

[1677] "Specification data" refers to data that includes specific numerical information regarding physical characteristics and design.

[1678] A "server" is a central computer that receives data, processes it, and returns the results.

[1679] The "internal database" is a system stored in the server that saves various strength data and characteristic data.

[1680] "Strength characteristics" are numerical data that indicate the characteristics of materials and structures, such as load-bearing capacity and wind resistance.

[1681] "Installability" is an index used to evaluate whether equipment can be installed safely and correctly under specific conditions.

[1682] A "user terminal" is a device that allows a user to input data and check the results.

[1683] The present invention is embodied as a system for quickly and accurately conducting strength studies when installing or modifying machinery in a factory environment. The system includes a user terminal, a server, an internal database, and an articulated robot arm.

[1684] Hardware and Software Configuration

[1685] Hardware: Multi-joint robot arm, user terminal (tablet PC), server (high-performance PC)

[1686] Software: Robot control software (ROS-based), data transmission and reception module (HTTP / REST API), internal database (PostgreSQL), strength calculation algorithm (Python script)

[1687] Processing Details

[1688] 1. User Interface:

[1689] The user uses a GUI form that runs on a tablet PC to input specification data for the equipment and installation structure, including data such as "material, length, dimensions," "weight, and pressure coefficient."

[1690] 2. Data transmission:

[1691] The user terminal converts the input specification data into JSON format and sends it to the server using an HTTP request.

[1692] 3. Server Processing:

[1693] The server receives the data using a Python script and compares it with a PostgreSQL database to obtain structural and material strength property data.

[1694] 4. Strength calculation:

[1695] The server uses the acquired characteristic data to perform the necessary strength calculations, including algorithms that evaluate safety and installability based on input data on the equipment and installation structure.

[1696] 5. Return of evaluation results:

[1697] The calculation results are sent back to the user device and robot in JSON format. The evaluation results include judgments such as "Installation possible," "Reinforcement required," and "Installation not possible."

[1698] 6. Results display and robot behavior:

[1699] The user terminal and robot decide the next action based on the evaluation results sent back. If an appropriate response is required, a warning or instruction is displayed.

[1700] Specific examples

[1701] When installing a new piece of machinery in a factory, the user inputs the material's specifications (steel, length: 2m, diameter: 10cm) and the equipment's weight (50kg, wind pressure coefficient: 1.5). This data is sent to the server, which compares it with its internal database and performs strength calculations. The result is a response that the equipment can be installed, allowing the user and robot to proceed with their work with peace of mind.

[1702] Example prompt for a generative AI model:

[1703] "Please assess the feasibility of mounting this equipment. The pole is made of steel, is 2m long, has a diameter of 10cm, weighs 50kg, and has a wind pressure coefficient of 1.5."

[1704] The system enables efficient and safe installation and modification of machinery in a factory environment.

[1705] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1706] Step 1:

[1707] Data entry in the user interface

[1708] Users use a GUI form on a tablet PC to input specification data for the equipment and installation structure, such as the material, length, and dimensions of the columns and the weight and wind pressure coefficient of the equipment. This data is then digitally imported into the system.

[1709] (Input:) Specifications of the equipment and installation structure entered by the user (e.g., material: steel, length: 2 m, diameter: 10 cm, weight: 50 kg, wind pressure coefficient: 1.5)

[1710] (Output:) Digital representation of input data

[1711] Step 2:

[1712] Data Conversion and Transmission

[1713] The terminal converts the input specification data into JSON format, which is then sent to the server as an HTTP request.

[1714] (Input:) Digital specification data

[1715] (Output:) JSON formatted data and HTTP request

[1716] Step 3:

[1717] Receiving data on the server

[1718] The server receives the HTTP request and parses the JSON data, which is then ready to be checked against an internal database.

[1719] (Input:) JSON data sent as an HTTP request

[1720] (Output:) Parsed data

[1721] Step 4:

[1722] Database collation

[1723] Based on the analyzed data, the server checks the PostgreSQL database to obtain strength property data of the installation structure and materials, which are used for strength calculations.

[1724] (Input:) Parsed specification data

[1725] (Output:) Strength property data retrieved from the database

[1726] Step 5:

[1727] strength calculation

[1728] The server performs the necessary strength calculations using the acquired strength characteristic data. First, it calculates the pressure and load based on the input amount and characteristic data, and then calculates the safety factor and other factors based on that.

[1729] (Input:) Obtained strength characteristic data and specification data from the user

[1730] (Output:) Strength calculation results (assessment of installation feasibility: installable, reinforcement required, not installable)

[1731] Step 6:

[1732] Return of evaluation results

[1733] The server converts the calculation results into JSON format and sends them back to the user's device and the robot, thereby transmitting the evaluation results to the device and the robot.

[1734] (Input:) Strength calculation result

[1735] (Output:) Evaluation result data in JSON format

[1736] Step 7:

[1737] Result display and robot operation

[1738] The user terminal and robot receive the returned evaluation results and display the results in the GUI or control interface. For example, if the result is "Installation possible," the robot will begin the installation work. If the evaluation result is anything other than that, the robot will display a warning and stop the work.

[1739] (Input:) Evaluation result data in JSON format

[1740] (Output:) Display of evaluation results and robot control actions

[1741] 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.

[1742] MODE FOR CARRYING OUT THE INVENTION

[1743] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the way the evaluation results are displayed and improve the user experience. Specific embodiments of this system are described in detail below.

[1744] System Configuration

[1745] The system mainly consists of the following components:

[1746] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[1747] 2. Server: A central computer that is responsible for receiving data, processing it, and returning the results.

[1748] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[1749] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[1750] Data Entry

[1751] The user uses a terminal to input the specification data of the concrete pole and the antenna. The specification data of the concrete pole includes the material, length, and diameter, and the specification data of the antenna includes the weight and wind pressure coefficient. This input is done via a user interface (e.g., a form).

[1752] Data transmission

[1753] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[1754] Database collation

[1755] The server compares the received data with its internal database, obtaining strength characteristic data corresponding to the material, length, and diameter of the concrete pole from the database, which allows it to evaluate the strength required for antenna installation.

[1756] strength calculation

[1757] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Then it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[1758] Returning results

[1759] The server converts the strength calculation results into JSON or XML format and sends them back to the terminal. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[1760] Displaying results and using the emotion engine

[1761] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[1762] For example, if a user is anxious or suspicious about the assessment results, the emotion engine will provide detailed explanations and support options for the "reinforcement needed" result, whereas if the user is relaxed, only the basic result will be displayed.

[1763] Logging the user's emotional state

[1764] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[1765] Specific usage scenarios

[1766] Suppose a user needs to install a new antenna on a steel concrete pole due to urban development. The user uses a terminal to input the specifications of the concrete pole (steel, 10m, diameter 30cm) and the antenna (weight 15kg, wind pressure coefficient 1.2). This data is sent to a server, which retrieves strength characteristic data from its internal database. The server then performs strength calculations and returns the result "Installation possible" to the terminal.

[1767] If the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is feeling anxious, it will not only tell the user that installation is possible, but also provide technical background information and safety guarantees, allowing the user to proceed with the antenna installation with peace of mind.

[1768] In this way, the system of the present invention can quickly and accurately assess the strength of concrete pillars, and by providing appropriate information in response to the user's emotions, ensure the safety and stability of the communications infrastructure.

[1769] The processing flow will be explained below.

[1770] Step 1:

[1771] The user uses the terminal to input the specification data of the concrete pole (material, length, diameter) and the specification data of the antenna (weight, wind pressure coefficient). This operation is performed via the terminal's user interface. The user enters information in each field and presses the "Submit" button.

[1772] Step 2:

[1773] The terminal converts the data entered by the user into JSON or XML format and sends it to the server. For example, the following JSON data is generated:

[1774] json

[1775] {

[1776] "material": "iron",

[1777] "length": "10",

[1778] "diameter": "30",

[1779] "antenna_weight": "15",

[1780] "wind_coefficient": "1.2"

[1781] }

[1782] Step 3:

[1783] The server analyzes the data received from the terminal and extracts the necessary information. This analysis confirms the contents of each data item and prepares it for further processing.

[1784] Step 4:

[1785] The server checks its internal database to obtain the strength characteristics corresponding to the concrete column specification data. This involves issuing an SQL query. For example, the following SQL query is executed:

[1786] sql

[1787] SELECT FROM strength_data WHERE material = "iron" AND length = 10 AND diameter = 30;

[1788] The data obtained from the query includes information such as the maximum allowable load of a concrete pole.

[1789] Step 5:

[1790] The feasibility of installing an antenna is evaluated based on the strength characteristic data acquired by the server. First, the total load is calculated by adding the antenna weight and wind pressure load. Specifically, the antenna weight (15 kg) is added to the wind pressure load (1.2 times the load at a height of 10 m). This calculation derives the total load.

[1791] Step 6:

[1792] The server compares the total load obtained with the maximum allowable load obtained from the database. It then evaluates whether it falls within the actual allowable load range, taking into account the safety factor. For example, if the maximum allowable load is 100 kg and the safety factor is 1.5, the actual allowable load is 100 kg / 1.5 = 66.67 kg. If the total load is less than this, it is determined to be "installable."

[1793] Step 7:

[1794] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Installable," "Reinforcement required," and "Not installable." For example, the following JSON data is returned:

[1795] json

[1796] {

[1797] "result": "Installable"

[1798] }

[1799] Step 8:

[1800] The device analyzes the evaluation results received from the server, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions.

[1801] Step 9:

[1802] The emotion engine recognizes the user's emotions and adjusts the display accordingly. For example, if the user is anxious or uncertain, the system will provide a detailed explanation and support options for the "reinforcement needed" result. On the other hand, if the user is relaxed, the system will only display the basic result.

[1803] Step 10:

[1804] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[1805] Step 11:

[1806] The terminal displays the final evaluation result on the user interface. The user can check the result on the screen and take appropriate action. For example, if the result shows "Installation possible," the user can proceed with the antenna installation with peace of mind.

[1807] Example 2

[1808] 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."

[1809] Conventional strength assessment systems for installing antennas on concrete poles require time-consuming calculation and evaluation processes, and the display method is not adjusted to reflect user needs. This results in a poor user experience and can make it difficult to understand the strength assessment results. Furthermore, some users feel uneasy or have doubts, leading to problems with not being able to trust the assessment results.

[1810] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1811] In this invention, the server includes means for inputting concrete pole specification data, means for inputting antenna specification data, means for transmitting the input data to a central computing device, means for comparing the transmitted data with an internal database to obtain the strength characteristics of the concrete pole, means for evaluating the feasibility of antenna installation based on the obtained strength characteristics, means for returning the evaluation results to a user terminal, means for displaying the evaluation results on the terminal, and an emotion engine for recognizing the user's emotions and adjusting the display method of the evaluation results. This enables the strength consideration process to be carried out quickly and accurately, and also makes it possible to provide appropriate information according to the user's emotional state, thereby improving the user experience and facilitating understanding of the evaluation results.

[1812] "Specification data for concrete poles" refers to data that represents the physical and material characteristics of concrete poles, such as the material, length, and diameter of the concrete poles.

[1813] "Antenna specification data" refers to data that describes the physical and usage conditions of an antenna, such as the antenna's weight and wind pressure coefficient.

[1814] A "central computing device" is a server that receives input data, processes it, and returns the results.

[1815] The "internal database" is a data storage device stored within the server that stores various data, such as strength characteristic data for concrete columns.

[1816] The "emotion engine" is a system that recognizes the user's emotional state and adjusts the way evaluation results are displayed based on that information.

[1817] The "evaluation results" are the results of a strength evaluation when attaching an antenna to a concrete pole, and are data that includes information such as "installable," "reinforcement required," and "uninstallable."

[1818] A "user terminal" is a device that refers to a computer or smart device that provides an interface for users to input data and display evaluation results.

[1819] "Strength characteristics" refers to physical property data relating to the strength of the concrete pillar based on its material and shape, and is standard data for making the evaluations required for antenna installation.

[1820] "Specification Data" means data that defines the physical and functional characteristics of a particular pole or antenna.

[1821] MODE FOR CARRYING OUT THE INVENTION

[1822] This invention is a system for quickly and accurately assessing the strength of an antenna when attaching it to a concrete pole, and by combining it with an emotion engine that recognizes the user's emotions, it adjusts the way the evaluation results are displayed, improving the user experience. Specific embodiments of this system are described in detail below.

[1823] System Configuration

[1824] The system consists of the following components:

[1825] 1. User terminal: A device for inputting data and displaying results. This includes computers, smartphones, etc.

[1826] 2. Server: A central computing device that is responsible for receiving data, processing it, and returning the results.

[1827] 3. Internal database: A database that stores various strength data and characteristic data stored within the server.

[1828] 4. Emotion Engine: A system that recognizes the user's emotions and uses that information to adjust how the rating results are displayed.

[1829] How to use the system

[1830] 1. Data Entry

[1831] The user uses the user terminal to input specification data for the concrete pole and the antenna. For example, the material, length, and diameter are input as specifications for the concrete pole, and the weight and wind pressure coefficient are input as specifications for the antenna.

[1832] 2. Data Transmission

[1833] The terminal converts the input specification data into JSON or XML format and sends it to the server, which then receives the data and prepares it for the next step of processing.

[1834] 3. Database Verification

[1835] The server compares the received data with its internal database to obtain strength characteristic data corresponding to the material, length, and diameter of the concrete pole, enabling it to evaluate the strength required for antenna installation.

[1836] 4. Strength calculation

[1837] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind load to the antenna's weight to calculate the total load. Next, it compares this with the maximum allowable load of the concrete pillar acquired from the database. It also applies a safety factor to make a final assessment and determine whether the antenna can be installed.

[1838] 5. Return of results

[1839] The server converts the strength calculation results into JSON or XML format and sends them back to the user's device. The evaluation results include information such as "Installation possible," "Reinforcement required," and "Installation not possible."

[1840] 6. Displaying results and using the emotion engine

[1841] The device analyzes the received results, and before displaying them, the emotion engine recognizes the user's emotional state. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify the user's emotions, and adjusts the display method based on the results.

[1842] For example, if a user wants to install a new antenna on a steel concrete pole for urban development, the user uses the terminal to enter the following specification data:

[1843] Concrete pillar specifications: iron, 10m, diameter 30cm

[1844] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[1845] This data is sent to a server, which retrieves strength characteristic data from an internal database, performs strength calculations, and returns a result of "Installation Possible" to the user's device. At this time, the emotion engine analyzes the user's facial expression and tone of voice, and if it recognizes that the user is feeling anxious, it displays the "Installation Possible" result along with detailed technical explanations and information about safety guarantees. In this way, the user's anxiety is alleviated, allowing them to proceed with the antenna installation work with peace of mind.

[1846] Example usage scenarios

[1847] For example, you can use the system with the following prompt:

[1848] "Please quickly and accurately evaluate the strength of attaching an antenna to a steel concrete pole, and adjust the way the results are displayed depending on the user's emotional state. Please perform strength calculations based on the following specifications and return the results."

[1849] Concrete pillar specifications: iron, 10m, diameter 30cm

[1850] Antenna specifications: Weight 15kg, wind pressure coefficient 1.2

[1851] This system not only enables rapid and accurate strength assessment of concrete pillars, but also provides information according to the user's emotions, ensuring the safety of the communications infrastructure.

[1852] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1853] Step 1: Data entry

[1854] The user accesses the system using a user terminal. They enter the specifications of the concrete pole and antenna into the specified form. Specifically, they enter the specifications of the concrete pole (material, length, diameter) and the antenna (weight, wind pressure coefficient). For example, the material of the concrete pole is entered as "iron," the length as "10m," and the diameter as "30cm," and the weight of the antenna as "15kg" and the wind pressure coefficient as "1.2." The user checks the information entered and clicks the send button.

[1855] Input: User input of specification data (material, length, diameter, weight, wind pressure coefficient)

[1856] Output: Formatted specification data

[1857] Step 2: Send data

[1858] The terminal takes the specification data entered by the user and converts it into JSON or XML format. The converted data is sent to the server. For example, the converted data looks like this:

[1859] json

[1860] {

[1861] "Con Pillar": {

[1862] "Material": "Iron",

[1863] "Length": "10m",

[1864] "Diameter": "30cm"

[1865] },

[1866] "antenna": {

[1867] "Weight": "15kg",

[1868] "Wind Pressure Coefficient": "1.2"

[1869] }

[1870] }

[1871] Input: Formatted specification data

[1872] Output: Data sent to the server

[1873] Step 3: Database Matching

[1874] The server receives and analyzes the data sent from the terminal. Specifically, it checks the internal database based on the material, length, and diameter of the concrete pole to obtain strength characteristic data. For example, it obtains corresponding strength characteristic data from existing data for steel concrete poles.

[1875] Input: Data sent to the server (material, length, diameter, weight, wind pressure coefficient)

[1876] Output: Strength characteristic data

[1877] Step 4: Strength calculation

[1878] The server performs strength calculations based on the acquired strength characteristic data. First, it adds the wind pressure load to the weight of the antenna to calculate the total load. Next, it compares the calculated total load with the maximum allowable load of the concrete pillar acquired from the database, and then applies a safety factor to make a final evaluation. Specifically, for example, it calculates total load = 15 kg (weight) + (1.2 x wind pressure rate) and compares it with the maximum allowable load.

[1879] Input: Strength characteristics data and input specification data

[1880] Output: Strength evaluation result (Installable, Reinforcement required, Uninstallable)

[1881] Step 5: Returning the results

[1882] The server converts the results of the strength calculation into JSON or XML format and sends it back to the user device. For example, the result data looks like this:

[1883] json

[1884] {

[1885] "Evaluation result": "Installable"

[1886] }

[1887] Input: Strength evaluation results

[1888] Output: Evaluation results sent to the user's device

[1889] Step 6: Displaying the results and using the emotion engine

[1890] The device receives the result data returned from the server and activates the emotion engine before analyzing it. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state. Based on the results, the display of the evaluation results can be adjusted. For example, if the user is feeling anxious, the device will display the "Installable" result along with technical details and safety guarantees. On the other hand, if the user is relaxed, only the basic results will be displayed.

[1891] Input: Evaluation results and user's emotional state

[1892] Output: Evaluation results in a tailored display format

[1893] Step 7: Logging the user's emotional state

[1894] The emotion engine records the user's emotional state as log data and feeds it back into future evaluations and display adjustments. This allows the system to learn the user's usage patterns and emotional responses, enabling more accurate emotion recognition and display results in the future.

[1895] Input: User's emotional state

[1896] Output: Log data and feedback information

[1897] (Application example 2)

[1898] 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."

[1899] In the past, logistics center workers lacked a system for obtaining information on how to handle packages and taking appropriate measures immediately. Furthermore, there was a lack of information provided based on the strength assessment of package handling and the emotional state of the workers, resulting in issues with safety and efficiency. The present invention aims to solve these issues and improve the safety and efficiency of workers at logistics centers.

[1900] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1901] In this invention, the server includes: means for inputting specification data of the concrete pole; means for inputting specification data of the communication device; means for transmitting the input data to a central computer; means for comparing the transmitted data with an internal database to obtain strength characteristics of the concrete pole; means for evaluating the feasibility of attaching the communication device based on the obtained strength characteristics; means for returning the evaluation results to a user terminal; means for displaying the evaluation results on the terminal; means for recognizing the emotional state of the user and adjusting the display method of the evaluation results; and means for enabling a user at a logistics center to use smart glasses to check how to handle packages and providing help information and warnings according to the user's emotional state. This allows workers at the logistics center to instantly check how to handle packages and improves safety and efficiency.

[1902] A "concrete pole" is a column-shaped structural member used to install and secure communication devices and other equipment.

[1903] A "communication device" is a device for sending and receiving data, and refers to a wide range of equipment including antennas and sensors.

[1904] "Specification data" refers to information that indicates the characteristics of concrete pillars and communication devices, such as their materials, dimensions, weight, and wind pressure coefficients.

[1905] A "central computer" is a computer system that centralizes data processing and typically functions as a server.

[1906] "Internal Database" means a data storage device that can store, search, and use required characteristic data.

[1907] "Strength properties" are physical characteristics that indicate how much load or pressure a material or structure can withstand.

[1908] "Attachability" is an index that evaluates whether a communication device can be attached safely and effectively to a concrete pole.

[1909] "User terminal" refers to a device used by a user to receive and display evaluation results, and includes smartphones, tablets, etc.

[1910] "Emotional state" indicates the user's current psychological and emotional state and is identified through facial expressions, tone of voice, etc.

[1911] "Smart glasses" are eyeglass-type devices that have the function of displaying information and are based on augmented reality (AR) technology.

[1912] "Help information" refers to support information that can be referred to when a worker performs a required operation.

[1913] "Caution" refers to information that provides warnings or advice to workers about specific actions or situations.

[1914] A "logistics center" is a facility that centralizes operations such as storing, sorting, and shipping goods.

[1915] The system for carrying out the present invention aims to improve the efficiency and safety of work in a logistics center. The system configuration is as follows.

[1916] System Configuration

[1917] 1. User device (smart glasses):

[1918] This is a device that allows users to input data and check the displayed results. Workers wear smart glasses and check how to handle packages and important points to note.

[1919] 2. Central computer (server):

[1920] This is the central computer that receives data, processes it, and returns the results. It evaluates the strength of the package and displays the results.

[1921] 3. Internal database:

[1922] This is a database that stores various strength data and characteristic data stored in the server.

[1923] 4. Emotion Engine:

[1924] This system recognizes the user's emotions and adjusts the way evaluation results are displayed based on that information.

[1925] Data Entry

[1926] The user uses the smart glasses to input package specifications, such as package type, weight, and dimensions, using voice commands or touch operations. A form is used as the input interface.

[1927] Data transmission

[1928] The device converts the input specification data into JSON or XML format and sends it to the server, where the smart glasses send the data to the server via Wi-Fi or Bluetooth.

[1929] Database collation

[1930] The server compares the received data with an internal database to obtain the strength characteristics data of the package, which contains the package's material, dimensions, and strength characteristics.

[1931] strength calculation

[1932] The server performs strength calculations based on the acquired strength characteristic data. First, it calculates the total load based on the weight of the package, then compares it with the maximum allowable load of the package acquired from the database, and applies a safety factor to make a final assessment and determine whether the package can be handled.

[1933] Results display

[1934] The server converts the strength calculation results into JSON or XML format and sends them back to the device. The evaluation results include information such as "Can be handled," "Caution required," and "Cannot be handled."

[1935] Use of emotion engine

[1936] The device analyzes the received results, and an emotion engine recognizes the user's emotional state before displaying them. It uses a camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotions. It adjusts the display method based on the results. For example, if the user has concerns or questions about the assessment results, it provides a detailed explanation and support options for the "Caution Required" result.

[1937] Logging the user's emotional state

[1938] The emotion engine logs the user's emotional state and feeds it back into subsequent evaluations, allowing the system to learn the user's usage patterns and emotional responses, resulting in more accurate emotion recognition and display results.

[1939] Specific examples

[1940] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[1941] Prompt Sentence Examples

[1942] "What is the maximum weight allowable for this luggage?"

[1943] "Please tell me the steps to safely transport this package."

[1944] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1945] Step 1:

[1946] The user uses the smart glasses to input package specifications (package type, weight, dimensions) using voice commands or touch operations. The input data is acquired by a voice recognition system or touch sensor and converted into JSON or XML format within the device.

[1947] Input: Package type, weight, dimensions

[1948] Output: Package specification data in JSON or XML format

[1949] Step 2:

[1950] The terminal sends the converted specification data to the server via Wi-Fi or Bluetooth, using the communication module of the smart glasses.

[1951] Input: Package specification data in JSON or XML format

[1952] Output: Send data to the server

[1953] Step 3:

[1954] The server analyzes the received data and retrieves the strength characteristics data of the package by checking the data against its internal database. A database query module in the server is used.

[1955] Input: Package specification data sent by the user

[1956] Output: Strength characteristics data of the luggage

[1957] Step 4:

[1958] The server performs strength calculations based on the acquired strength characteristic data. The calculation module uses data such as weight, dimensions, and wind pressure coefficients to calculate the total load, compare it with the maximum allowable load, and apply a safety factor.

[1959] Input: Package strength characteristics data

[1960] Output: Evaluation result of the cargo handling feasibility

[1961] Step 5:

[1962] The server converts the evaluation results into JSON or XML format and sends them back to the device. The evaluation module is responsible for converting the results.

[1963] Input: Evaluation result of the cargo's feasibility

[1964] Output: Evaluation results in JSON or XML format

[1965] Step 6:

[1966] The terminal receives the evaluation results and parses the data. An analysis module interprets the data format and prepares it for display.

[1967] Input: Evaluation result returned from the server

[1968] Output: Analyzed evaluation result data

[1969] Step 7:

[1970] The device's emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to identify their emotional state, and emotion recognition algorithms are used to generate the user's emotion data.

[1971] Input: User's facial expression, tone of voice

[1972] Output: User emotion data

[1973] Step 8:

[1974] The emotion engine adjusts the way the rating results are displayed based on the user's emotional state. For example, if the user is feeling anxious, it might display additional detailed explanations or support options. The display module is used.

[1975] Input: Analyzed evaluation result data, user emotion data

[1976] Output: Adjusted evaluation results

[1977] Step 9:

[1978] The terminal then displays the adjusted evaluation results on the smart glasses' display, allowing the worker to check how to handle the package and proceed with the work safely and efficiently.

[1979] Input: Adjusted evaluation results display

[1980] Output: Evaluation results displayed on the smart glasses display

[1981] Examples:

[1982] In logistics centers, workers picking heavy packages use smart glasses to confirm how to handle them. For example, if a worker asks, "What is the maximum allowable weight for this package?", the system responds by displaying package handling instructions and safety procedures. If the user feels unsure, the application can provide additional safety procedures and reinforcement information.

[1983] Example prompt sentence:

[1984] "What is the maximum weight allowable for this luggage?"

[1985] "Please tell me the steps to safely transport this package."

[1986] 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.

[1987] 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.

[1988] 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.

[1989] 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.

[1990] 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.

[1991] 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.

[1992] 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).

[1993] 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.

[1994] 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."

[1995] 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.

[1996] 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).

[1997] 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.

[1998] 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.

[1999] 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.

[2000] 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.

[2001] 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.

[2002] 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.

[2003] 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.

[2004] 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.

[2005] 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.

[2006] 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.

[2007] The following is further disclosed regarding the above embodiment.

[2008] (Claim 1)

[2009] A means for inputting concrete column specification data,

[2010] a means for inputting antenna specification data;

[2011] means for transmitting the input data to a server;

[2012] A means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the concrete pillar;

[2013] a means for evaluating the feasibility of attaching the antenna based on the acquired strength characteristics;

[2014] means for returning the evaluation result to the user terminal;

[2015] The system includes means for displaying the evaluation results on a terminal.

[2016] (Claim 2)

[2017] 10. The system of claim 1, including means for inputting material, length, and diameter specification data for the concrete pole.

[2018] (Claim 3)

[2019] 10. The system of claim 1, including means for inputting weight and wind coefficient specification data for the antenna.

[2020] "Example 1"

[2021] (Claim 1)

[2022] A means for receiving specification data of the pole and the antenna input by a user;

[2023] A means of converting input specification data into JSON or XML format;

[2024] means for transmitting the converted data to a server;

[2025] A means for collating the data received by the server with an internal database to obtain strength characteristic data of the concrete pillar;

[2026] a means for evaluating the feasibility of attaching an antenna based on the acquired strength characteristic data;

[2027] A means for converting the evaluation results into JSON or XML format and returning them to the user terminal;

[2028] A system including a means for a user terminal to visually display the evaluation results and present appropriate guidelines to the user.

[2029] (Claim 2)

[2030] 10. The system of claim 1, including means for inputting material, length, and diameter specification data for the concrete pole.

[2031] (Claim 3)

[2032] 10. The system of claim 1, including means for inputting weight and wind coefficient specification data for the antenna.

[2033] "Application Example 1"

[2034] (Claim 1)

[2035] A means for inputting concrete column specification data,

[2036] A means for inputting specification data of the installation structure;

[2037] means for transmitting the input data to a server;

[2038] means for checking an internal database based on the transmitted data to obtain strength characteristics of the structure;

[2039] A means for evaluating the attachability of the equipment based on the acquired strength characteristics;

[2040] means for returning the evaluation results to the user terminal and the operation device;

[2041] The system includes a terminal and a means for displaying the evaluation results on an operating device.

[2042] (Claim 2)

[2043] 10. The system of claim 1, including means for inputting material, length, and dimension specification data.

[2044] (Claim 3)

[2045] 10. The system of claim 1, including means for inputting weight and pressure coefficient specification data.

[2046] "Example 2: Combining Emotion Engines"

[2047] (Claim 1)

[2048] A means for inputting concrete column specification data,

[2049] a means for inputting antenna specification data;

[2050] means for transmitting the entered data to a central computing device;

[2051] A means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the concrete pillar;

[2052] a means for evaluating the feasibility of attaching the antenna based on the acquired strength characteristics;

[2053] means for returning the evaluation result to the user terminal;

[2054] means for displaying the evaluation results on the terminal;

[2055] A system including an emotion engine that recognizes user emotions and adjusts how evaluation results are displayed.

[2056] (Claim 2)

[2057] 10. The system of claim 1, including means for inputting material, length, and diameter specification data for the concrete pole.

[2058] (Claim 3)

[2059] 10. The system of claim 1, including means for inputting weight and wind coefficient specification data for the antenna.

[2060] "Application example 2 when combining emotion engines"

[2061] (Claim 1)

[2062] A means for inputting concrete column specification data,

[2063] means for inputting specification data of a communication device;

[2064] means for transmitting the entered data to a central computer;

[2065] A means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the concrete pillar;

[2066] means for evaluating the attachability of the communication device based on the acquired strength characteristics;

[2067] means for returning the evaluation result to the user terminal;

[2068] a means for displaying the evaluation results on the terminal;

[2069] a means for recognizing the user's emotional state and adjusting the display method of the evaluation results;

[2070] A means including an application in which a user uses smart glasses in a logistics center to check how to handle luggage and provides help information and warnings according to the user's emotional state;

[2071] A system including:

[2072] (Claim 2)

[2073] 10. The system of claim 1, including means for inputting material, length, and diameter specification data for the concrete pole.

[2074] (Claim 3)

[2075] 10. The system of claim 1, further comprising means for inputting weight and wind coefficient specification data for the communication device. [Explanation of symbols]

[2076] 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 means for inputting concrete column specification data, a means for inputting antenna specification data; means for transmitting the input data to a server; A means for comparing the transmitted data with an internal database and acquiring the strength characteristics of the concrete pillar; a means for evaluating the feasibility of attaching the antenna based on the acquired strength characteristics; means for returning the evaluation result to the user terminal; The system includes means for displaying the evaluation results on a terminal.

2. 2. The system of claim 1, further comprising means for inputting material, length, and diameter specification data for the concrete pole.

3. 2. The system of claim 1, further comprising means for inputting weight and wind coefficient specification data for the antenna.

Images