system

Abstract

Provide a system. A method for collecting environmental data using a sensor; A means for analyzing bee activity data; A means of artificially assisted pollination; a means for storing and analyzing the data on a central server; A system including:

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 modern agriculture, the decline in honeybee populations leads to a decline in pollination efficiency, seriously affecting crop productivity. The pollination activity of honeybees is important for many crops, and their decline poses a direct risk to food supply. This invention aims to solve the problem of declining pollination efficiency caused by the decline in honeybee populations and to realize sustainable agriculture. [Means for solving the problem]

[0005] The present invention provides the following means.

[0006] 1. A means of collecting environmental data (temperature and humidity) with sensors.

[0007] 2. A means of analyzing bee activity data to determine whether activity is high or low and whether pollination support is needed.

[0008] 3. Robotic artificial pollination assistance, if necessary.

[0009] 4. A means of storing data on a central server for analysis and report generation.

[0010] This provides a system that allows efficient pollination support by robots even during periods of low bee activity, enabling stable crop production.

[0011] A "sensor" is a device for collecting environmental data such as temperature and humidity.

[0012] "Environmental data" refers to information related to the growing environment of the crop, specifically temperature and humidity.

[0013] "Honeybees" refer to insects that mediate pollination and are involved in the pollination of crops.

[0014] "Activity data" refers to information measured and recorded about the behavior and movements of bees.

[0015] "Analysis tools" refers to software and algorithms used to determine bee activity based on collected data.

[0016] "Assisted pollination" refers to the process of artificially assisting natural pollination activities.

[0017] A "robot" refers to a machine that operates autonomously based on programmed instructions and assists with pollination.

[0018] "Central server" refers to a computer system that centrally manages various data, analyzes and stores it, and generates reports.

[0019] "Database" refers to the system for storing and managing collected environmental data and bee activity data.

[0020] "Report" refers to a document created based on collected and analyzed data, and is information provided to farmers and related institutions. [Brief explanation of the drawings]

[0021] [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

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] The present invention is a system in which an agricultural robot utilizes artificial intelligence to cooperate with honeybees and assist in the pollination of agricultural crops. Details for implementing the present invention in a specific embodiment are described below.

[0043] System Overview

[0044] The system uses sensors to collect data related to the crop's growing environment (temperature and humidity), analyzes data on the bees' activity, and, if necessary, a robot assists in artificial pollination. All data is stored on a central server for analysis and report generation.

[0045] 1. Environmental data collection

[0046] Sensors measure the growing environment of crops in real time. The sensors periodically measure temperature and humidity and transmit the data to a terminal. The terminal preprocesses the received data and sends it to a central server.

[0047] The terminal receives data from the sensors at regular intervals and forwards it to a central server, which stores the received data in a database and checks the consistency of the data required for each processing step.

[0048] 2. Analysis of honeybee activity

[0049] The user sets up the bee monitoring device and collects bee activity data. The collected data is sent to a terminal. The terminal passes the received bee activity data to an analysis module, and the analysis results are sent to a server.

[0050] The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination assistance is necessary.

[0051] 3. Implementing pollination support

[0052] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends instructions to the robot. The robot moves to the specified location and performs artificial pollination assistance.

[0053] 4. Data Management and Report Generation

[0054] The server centralizes the collected environmental data and bee activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to farmers and related organizations.

[0055] Specific examples

[0056] Example 1:

[0057] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[0058] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0059] The server analyzes the bee activity and determines that "bee activity is high."

[0060] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[0061] Example 2:

[0062] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0063] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0064] The server analyzes bee activity and determines that there is little bee activity.

[0065] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[0066] The robot moves to the location of the crop and assists with pollination, storing the data and generating a corresponding report.

[0067] In this way, this system uses AI and robots to address the problem of declining honeybee populations and provide pollination support to maintain crop productivity.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] Sensors measure and collect environmental data (temperature and humidity).

[0071] Step 2:

[0072] The device receives environmental data from the sensors at regular intervals and preprocesses the data, which is then prepared for transmission to the server.

[0073] Step 3:

[0074] The server receives the environmental data sent from the device, stores the data in a database, and verifies that the data is consistent.

[0075] Step 4:

[0076] The user sets up the bee monitoring device, collects bee activity data, and transmits it to the terminal.

[0077] Step 5:

[0078] The terminal receives the bee activity data sent by the user and passes the data to the analysis module.

[0079] Step 6:

[0080] The server analyzes the bee activity data and applies an algorithm to determine whether bee activity is high or low.

[0081] Step 7:

[0082] The server determines whether pollination assistance is necessary based on the analysis results. If activity is low, it determines that pollination assistance is necessary.

[0083] Step 8:

[0084] If it is determined that pollination assistance is needed, the server sends instructions to the robot via the terminal.

[0085] Step 9:

[0086] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[0087] Step 10:

[0088] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[0089] Step 11:

[0090] The server collects and organizes all data, analyzes it periodically, and generates reports based on the analysis results.

[0091] Step 12:

[0092] The server sends the generated report to the user, who then checks the report and considers how to proceed.

[0093] Example 1

[0094] 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."

[0095] In modern agriculture, the decline in honeybee populations has become a major problem, resulting in insufficient pollination of crops. Furthermore, there is a lack of systems that can monitor environmental conditions and honeybee activity in real time and provide pollination support based on that information. A system that can address these issues and maintain crop productivity is needed.

[0096] 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.

[0097] In this invention, the server includes means for collecting environmental data with sensors and measuring temperature and humidity, means for collecting bee activity data and sending it to a terminal, means for preprocessing the collected data on the terminal and sending it to a central server, means for analyzing the received data on the central server and determining whether bee activity is high or low, means for determining the need for pollination assistance based on the analysis results on the central server, means for sending instructions to the robot via the terminal when the central server determines that pollination assistance is necessary, means for the robot to move to a specified location and perform artificial pollination assistance, and means for storing the data collected and analyzed by the central server in a database and generating a report. This makes it possible to efficiently and automatically provide pollination assistance based on the bee activity status and environmental data.

[0098] A "sensor" is a device for collecting environmental data and measuring physical quantities such as temperature and humidity.

[0099] "Environmental data" refers to data related to the growing environment of agricultural crops, and mainly refers to temperature and humidity.

[0100] "Terminal" is a device that receives data collected from sensors and bee monitoring devices, pre-processes it and transmits it to a central server.

[0101] The "central server" is a computer system that centrally manages, analyzes, and stores various collected data.

[0102] A "bee monitoring device" is a device for collecting data on bee activity.

[0103] "Assisted pollination" is the process by which robots artificially pollinate crops.

[0104] A "database" is an information management system for systematically storing and managing collected data.

[0105] A "report" is a document that is periodically produced based on collected and analyzed data, and is intended to provide information to farmers and related institutions.

[0106] "Analysis" is the process of evaluating bee activity and environmental conditions based on collected data and determining the need for pollination support.

[0107] A "robot" is an automated mechanical device that moves to the location of crops based on instructions from a server and assists in artificial pollination.

[0108] "Preprocessing" refers to processes that remove noise from collected data and correct outliers to improve the accuracy and reliability of the data.

[0109] An "instruction" is an operation command sent from a central server to a robot via a terminal.

[0110] This invention is an agricultural robot system that efficiently supports the pollination of agricultural crops through the cooperative operation of sensors, terminals, a central server, and robots.

[0111] First, sensors monitor the growing environment of agricultural crops. Specifically, they measure temperature and humidity in real time and send the data to a terminal. Temperature and humidity sensors are generally used. This data is important for maintaining an optimal growing environment for agricultural crops.

[0112] The terminal receives data from the sensors at regular intervals and performs preprocessing. Specifically, it removes noise from the data, corrects outliers, and converts the data format into a suitable format for the database. The preprocessed data is then sent to a central server.

[0113] The server stores the received data in a database and checks the consistency of the data required at each processing step. Furthermore, the server also analyzes the bee activity data. Specifically, the server passes the bee activity data collected by the user using the bee monitoring device to the analysis module, which determines whether the activity is high or low. A generative AI model is used for this analysis, allowing for fast and accurate judgments.

[0114] Based on the analysis results and environmental data, the server determines whether pollination assistance is necessary. If it is determined that pollination assistance is necessary, instructions are sent to the robot via the terminal. Instructions include, for example, "Move to the location of the crop and begin pollination assistance."

[0115] The robot moves to a designated location and assists in artificial pollination. Typically, the robot's arm touches the flowers of the crops to promote pollination.

[0116] Finally, the server centralizes the collected environmental data and bee activity data, and periodically generates reports containing monthly data analysis results and a history of pollination support activities, which are provided to farmers and related organizations.

[0117] Specific examples

[0118] Example 1:

[0119] The sensor measures the temperature at 22 degrees and the humidity at 55% and collects the data.

[0120] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "100 flights per day."

[0121] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that the bees are active.

[0122] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[0123] Example 2:

[0124] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0125] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "10 flights per day."

[0126] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that there is little bee activity.

[0127] The server determines that pollination assistance is needed, and the terminal sends instructions to the robot.

[0128] The robot moves to the location of the crop and assists with pollination. The robot touches the flowers of the crop.

[0129] The server generates a corresponding report and sends it to the user.

[0130] The system uses AI and robots to address the declining honeybee population and provide pollination assistance to maintain crop productivity.

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

[0132] Step 1:

[0133] The sensor collects environmental data. Specifically, the sensor measures temperature and humidity in real time, obtaining data such as "temperature 22 degrees, humidity 55%." This collected data is sent to the device as environmental data.

[0134] Input: Environmental data (temperature, humidity)

[0135] Output: Environmental data sent to the device

[0136] Step 2:

[0137] The device receives environmental data from the sensor and performs preprocessing. Specifically, the device removes noise and corrects outliers, and converts the data format into a format suitable for the database. For example, a measured value of "temperature 22 degrees, humidity 55%" is preprocessed and converted into a database format.

[0138] Input: Environmental data from sensors

[0139] Output: Preprocessed environmental data (database format)

[0140] Step 3:

[0141] The device sends the preprocessed environmental data to the central server. Specifically, the preprocessed data is packaged into packets and sent to a specific IP address on the central server. For example, data such as "temperature 22 degrees, humidity 55%" is sent as a packet.

[0142] Input: Preprocessed environmental data

[0143] Output: Data packets sent to the central server

[0144] Step 4:

[0145] The environmental data received by the server is stored in a database. Specifically, a database management system (e.g., MySQL (registered trademark)) is used to check for data duplication and consistency, and if there are no problems, the data is stored. For example, data such as "temperature 22 degrees, humidity 55%" is saved in the database.

[0146] Input: Data packet sent to the central server

[0147] Output: Environmental data stored in a database

[0148] Step 5:

[0149] The user sets up a bee monitoring device and collects bee activity data. For example, a sensor device installed in a hive collects data such as "100 bee flights per day." This activity data is sent to a terminal.

[0150] Input: Bee activity data (number of flights)

[0151] Output: Bee activity data sent to the terminal

[0152] Step 6:

[0153] The terminal receives the bee activity data and passes it to the preprocessing and analysis module. Specifically, the data is cleansed and standardized into a format that is easy to analyze. For example, "100 flights" is converted into data for analysis.

[0154] Input: Bee activity data sent to the terminal

[0155] Output: Preprocessed data passed to the analysis module

[0156] Step 7:

[0157] The server analyzes the bee activity data and determines whether the activity is high or low. Specifically, it uses a generative AI model (e.g., TENSORFLOW (registered trademark)). For example, if the number of bee flights is low, it is determined that there is "low bee activity."

[0158] Input: Preprocessed data passed to the analysis module

[0159] Output: Activity evaluation result (high / low)

[0160] Step 8:

[0161] The server determines whether pollination support is necessary based on the analysis results and environmental data. Specifically, it uses an AI algorithm to comprehensively evaluate each piece of data. For example, if it determines that "the temperature is 20 degrees, the humidity is 50%, and there is little bee activity," pollination support is necessary.

[0162] Input: Activity evaluation results, environmental data

[0163] Output: Pollination support decision (necessary / unnecessary)

[0164] Step 9:

[0165] The terminal sends instructions for pollination assistance to the robot. For example, it sends a packet containing instructions to the robot to "move to the location of the crop and start pollination assistance."

[0166] Input: Pollination support judgment

[0167] Output: Instruction packet to the robot

[0168] Step 10:

[0169] The robot moves to a designated location and assists in artificial pollination. Specifically, the robot's arm touches the flowers of the crops to promote pollination. For example, it performs a "flower touching action."

[0170] Input: Instruction packet to the robot

[0171] Output: Record of assisted pollination performed

[0172] Step 11:

[0173] The server centrally manages the collected environmental data and bee activity data and stores it in a database. Furthermore, the server periodically analyzes the data and generates reports to provide to farmers and related organizations. For example, it creates a report based on this month's bee activity and environmental data.

[0174] Input: Environmental data, bee activity data

[0175] Output: Report

[0176] (Application example 1)

[0177] 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."

[0178] Conventional factory production lines lacked systems that could monitor environmental data and equipment activity data in real time and respond quickly. As a result, responses to environmental changes and equipment abnormalities were often delayed, resulting in reduced productivity and quality issues. Furthermore, data collection and analysis were not carried out efficiently, and report creation took a long time.

[0179] 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.

[0180] In this invention, the server includes a means for collecting environmental data with sensors, a means for analyzing activity data of production equipment, a means for automatically adjusting the production line, and a means for storing the data in the central server, analyzing it, and generating reports, thereby enabling real-time monitoring and rapid adjustment of the production line, as well as efficient data management and rapid report generation.

[0181] A "sensor" is a device that measures environmental data in real time and transmits that data to a terminal.

[0182] "Environmental data" refers to physical data such as temperature, humidity, vibration, and noise inside the factory.

[0183] "Production equipment activity data" refers to data relating to the operating status and operational status of production line equipment.

[0184] "Analysis" is the process of analyzing collected data and determining whether activity is normal or abnormal.

[0185] "Central Server" refers to a central computer server that stores collected environmental data and production equipment activity data, analyzes them, and generates reports.

[0186] A "report" is a document provided to interested parties based on collected and analyzed data.

[0187] "Adjustment" refers to the task of a robot changing the settings and arrangement of equipment on a production line.

[0188] "Real time" refers to information being processed almost simultaneously.

[0189] The present invention relates to a system for collecting and analyzing environmental data and activity data of production equipment within a factory, and making necessary adjustments based on the data. Details for specifically implementing the present invention will be described below.

[0190] 1. Environmental data collection

[0191] The server uses sensors to collect environmental data within the factory in real time. The sensors periodically measure temperature, humidity, vibration, and noise and send the data to terminals. The terminals preprocess the received data and send it to the central server. The central server stores the received data in a database and checks the consistency of the data required at each processing step.

[0192] 2. Analysis of production equipment activity data

[0193] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to the terminal. The terminal passes the received equipment activity data to the analysis module and sends the analysis results to the central server. The server analyzes the equipment activity data and determines whether the activity is normal or abnormal. Based on the analysis results, it determines whether adjustments are necessary.

[0194] 3. Implement production line adjustments

[0195] The server determines that adjustments to the production line are necessary based on the analysis results and environmental data. If adjustments are determined to be necessary, the terminal sends instructions to the robot. The robot moves to the specified location and automatically adjusts the production line or handles any problems. After the robot completes the adjustment work, it sends the data to the terminal, which then stores it on the central server.

[0196] 4. Data Management and Report Generation

[0197] The server centrally manages the collected environmental data and production equipment activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to production managers and related organizations.

[0198] Hardware and software used

[0199] Sensors: Temperature sensor, humidity sensor, vibration sensor, microphone

[0200] Terminal: IoT device for data collection and transmission

[0201] Central server: A computer server that runs the database and analysis modules

[0202] Robot: Autonomous robot for production line adjustment

[0203] Software: Database management systems, analysis software, robot control systems

[0204] Specific examples

[0205] Example 1:

[0206] The sensors measure temperature at 25 degrees, humidity at 60%, and vibration level at 2.0 and collect data.

[0207] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[0208] The server analyzes the device activity and determines that the activity is normal.

[0209] The server determines that no adjustment is necessary and saves the data. A report on the operation status of the production line is generated.

[0210] Example 2:

[0211] The sensors measure a temperature of 30 degrees, humidity of 50%, and vibration level of 3.5 and collect data.

[0212] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[0213] The server analyzes the device activity and determines that the activity is abnormal.

[0214] The server determines that adjustments are necessary, and the terminal sends instructions to the robot.

[0215] The robot moves to its working position, adjusts the production line, stores the data and generates a corresponding report.

[0216] Prompt Sentence Examples

[0217] Prompt: Generate a procedure for adjusting the production line if the temperature measured by sensors in the factory is 30 degrees and the vibration level is 3.5.

[0218] Output procedure: Analyze data from sensors and send it to a central server. The server detects anomalies. The robot moves to the specified position and initiates adjustments. The data is saved and a report is generated.

[0219] The system of the present invention aims to improve the efficiency of management and adjustment of production lines within a factory, thereby improving productivity and optimizing quality control.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] The server collects environmental data from sensors. The sensors periodically measure the temperature, humidity, vibration, and noise levels in the factory and send the data to terminals. The terminals then format the received data and send it to the central server. The input is the environmental data sent by the sensors, and the output is the formatted data. Specifically, the temperature sensor measures 25 degrees, and the data is sent by the terminal to the central server.

[0223] Step 2:

[0224] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to a terminal. The terminal passes the received equipment data to an analysis module, which then sends the analysis results to a central server. The input is the equipment activity data, and the output is the analyzed status data. Specifically, the monitoring device confirms that the equipment is operating normally, and the data is sent to the server.

[0225] Step 3:

[0226] The server analyzes the device's activity data and determines whether the activity is normal or abnormal. The input is the received activity data, and the output is the analysis result. Specific calculations detect abnormalities by comparing it with normal activity patterns. For example, if the vibration level is abnormally high, it is determined to be abnormal.

[0227] Step 4:

[0228] The server determines whether adjustments to the production line are necessary based on the analysis results and environmental data. If it determines that adjustments are necessary, the terminal sends instructions to the robot. The input is the analysis results and environmental data, and the output is instructions to the robot. Specifically, if it determines that the temperature and vibration levels are abnormally high, an adjustment instruction is sent to the robot.

[0229] Step 5:

[0230] The robot receives instructions, moves to the designated location, and automatically adjusts the production line and handles problems. The input is the adjustment instruction from the server, and the output is the improved activity data after the adjustment. A specific example of the robot's operation is readjusting equipment to suppress abnormal vibrations.

[0231] Step 6:

[0232] The server receives the adjusted data sent from the robot and stores it in a database. It also periodically analyzes the data and generates a report. The input is the adjusted data and the output is the report. The specific operation is to generate a report and provide it to the production manager.

[0233] This enables real-time monitoring of production lines within factories and rapid adjustments, resulting in improved productivity and quality.

[0234] 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.

[0235] The present invention combines a system that collects environmental data, analyzes bee activity data, and artificially supports pollination with an emotion engine that recognizes the user's emotions. Details for implementing the present invention in a specific form are described below.

[0236] System Overview

[0237] The system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect data related to the crop's growing environment (temperature and humidity), analyze the bee activity data, and the robot assists with artificial pollination as needed. Furthermore, the emotion engine analyzes the user's emotional state and optimizes the system's operation based on this.

[0238] 1. Environmental data collection

[0239] The sensors measure the crop growth environment (temperature and humidity) in real time, periodically collecting this data and sending it to the terminal.

[0240] The devices preprocess the environmental data received from the sensors and send it to a central server, which receives it, stores it in a database, and checks the integrity of the data.

[0241] 2. Analysis of honeybee activity

[0242] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal, which receives the data and passes it to the analysis module.

[0243] The server analyzes the bee activity data and determines whether the activity is high or low, and based on the analysis results, decides whether pollination assistance is needed.

[0244] 3. Implementing pollination support

[0245] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions to the robot to assist pollination. The robot then moves to the specified location and performs artificial pollination assistance.

[0246] 4. Incorporating an Emotional Engine

[0247] To monitor the user's emotional state, the user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and transmits the data to the device. The device receives the emotion data and analyzes it using an emotion engine.

[0248] The server optimizes the overall operation of the system based on the user's emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will adjust the timing of pollination assistance to reduce the user's burden.

[0249] 5. Data Management and Report Generation

[0250] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[0251] Specific examples

[0252] Example 1:

[0253] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[0254] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0255] Based on the data sent from the device, the server determines that bee activity is high and therefore does not provide pollination support.

[0256] Since the emotion engine has determined that the user is not feeling stressed, the default processing continues.

[0257] Example 2:

[0258] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0259] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0260] The server analyzes bee activity and determines that there is little bee activity.

[0261] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[0262] The robot moves based on instructions and assists with pollination.

[0263] Because the emotion engine determines that the user is stressed, the system expedites report generation and provides immediate feedback to the user.

[0264] In this way, the system uses AI, robots, and an emotion engine to assist with pollination to maintain crop productivity, and also optimizes the operation of the entire system by taking into account the user's emotional state.

[0265] The processing flow will be explained below.

[0266] Step 1:

[0267] Sensors measure and collect environmental data (temperature and humidity).

[0268] Step 2:

[0269] The terminal receives environmental data from sensors at regular intervals, preprocesses the data, and sends it to a central server.

[0270] Step 3:

[0271] The server receives the environmental data sent from the device, stores it in a database, and checks the integrity of the data.

[0272] Step 4:

[0273] A user uses a bee monitoring device to collect bee activity data and transmit it to a terminal.

[0274] Step 5:

[0275] The terminal receives the bee activity data sent by the user and passes it to the analysis module.

[0276] Step 6:

[0277] The server analyzes the bee activity data and runs an algorithm to determine whether activity is high or low.

[0278] Step 7:

[0279] The server determines whether pollination assistance is necessary based on the analysis results, and generates instructions for pollination assistance if necessary.

[0280] Step 8:

[0281] If the server determines that pollination assistance is necessary, it sends instructions to the terminal and prepares instructions for the robot to move and for pollination assistance.

[0282] Step 9:

[0283] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[0284] Step 10:

[0285] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[0286] Step 11:

[0287] A user uses an emotion recognition device to collect his / her own emotion data and transmits it to a terminal.

[0288] Step 12:

[0289] The terminal receives the user's emotion data and passes the data to the emotion engine.

[0290] Step 13:

[0291] The server uses an emotion engine to analyze the user's emotional data and adjusts the operation of the entire system based on the results.

[0292] Step 14:

[0293] The server stores all data (environmental data, bee activity data, emotion data) in a database and manages them centrally.

[0294] Step 15:

[0295] The server periodically analyzes the data and generates reports based on the results.

[0296] Step 16:

[0297] The server generates a report, which is then sent to the user, which then reviews it. The report includes environmental data, bee activity, pollination support status, and emotional state analysis.

[0298] Example 2

[0299] 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."

[0300] The present invention aims to provide a method for optimizing the operation of a system that uses environmental data and bee activity data to support the pollination of agricultural crops, taking into account the emotional state of the user, thereby improving the efficiency of pollination support and reducing the stress and burden on the user.

[0301] 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.

[0302] In this invention, the server includes means for collecting environmental data with sensors, means for analyzing bee activity data, means for artificially supporting pollination, means for storing and analyzing data in a central server, means for collecting and analyzing emotion data using an emotion engine that recognizes user emotions, and means for optimizing system operation based on the analyzed emotion data. This enables comprehensive pollination support that takes into account not only conventional environmental data and bee activity data, but also user emotion data.

[0303] A "sensor" is a device that measures a physical condition, such as temperature or humidity, to collect environmental data.

[0304] "Bee activity data" is data that records the movements of bees, such as their comings and goings and flight activities.

[0305] "Artificial pollination assistance" is a method of artificially moving pollen using devices such as robots.

[0306] "Central Server" is a computer system that stores and analyzes collected data.

[0307] An "emotion engine" is software that recognizes a user's emotions and analyzes that emotional data.

[0308] "Emotional Data" is data about a user's emotional state that is collected and analyzed by the emotion engine.

[0309] "Optimizing system operation" refers to optimally adjusting the performance of various system functions based on collected data.

[0310] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination as needed, and further combines it with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present invention.

[0311] System configuration

[0312] This system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect temperature and humidity data related to the crop growth environment. The terminals preprocess the data received from the sensors and send it to the central server. The central server receives, stores, and analyzes the data. It also issues instructions to the robots that assist with pollination. The emotion engine analyzes the user's emotional state and optimizes the system's operation.

[0313] Environmental data collection

[0314] Sensors measure the crops' environmental data (temperature and humidity) in real time. These sensors periodically collect data and send it to the terminal. For example, the sensor collects data of 22 degrees Celsius and 55% humidity every 5 minutes and sends it to the terminal.

[0315] The device preprocesses the environmental data received from the sensor and sends it to the central server. As part of the preprocessing, the device organizes the data and checks for any abnormal values. The organized data is then sent to the central server. The server receives the data, stores it in a database, and checks the integrity of the data.

[0316] Analysis of honeybee activity

[0317] A user sets up a monitoring device to collect bee activity data, and the collected data is sent to a terminal. For example, the user sends data recording the bees' entry and exit and flight activity to the terminal.

[0318] The terminal passes the received bee activity data to an analysis module, which then sends it to a central server. The central server analyzes the bee activity data and determines whether activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination assistance is necessary.

[0319] Pollination support

[0320] The central server determines whether pollination assistance is necessary based on the analysis results. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination.

[0321] Incorporating an emotion engine

[0322] The user uses an emotion recognition device, which collects emotional data from facial expressions and voice and sends it to the terminal. The terminal receives the emotional data and passes it to the emotion engine. The emotion engine determines the user's current emotional state and sends the data to the central server. The central server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it may change the timing of pollination assistance.

[0323] Specific examples

[0324] As a concrete example, a sensor collects data on a temperature of 20 degrees and humidity of 50%, and a user collects data on bee activity using a monitoring device and sends this data to a terminal. The terminal then sends this data to a server, which determines that "bee activity is low." The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot to move and pollinate. The robot moves to the instructed location and assists with pollination. Furthermore, if the emotion engine determines that the user is feeling stressed, the system will quickly generate a report and provide the user with immediate feedback.

[0325] Prompt Sentence Examples

[0326] "What steps can we take to optimize pollination support based on user sentiment and environmental data?"

[0327] In this way, the system uses AI, robots, and an emotion engine to maintain crop productivity and optimize the operation of the entire system by taking into account the user's emotional state.

[0328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0329] Step 1:

[0330] Sensors collect environmental data

[0331] The sensors measure the temperature and humidity around the crops in real time. For example, the sensors collect data every five minutes showing a temperature of 22°C and humidity of 55%.

[0332] Input: Ambient environmental conditions (temperature, humidity)

[0333] Output: Measured temperature and humidity data

[0334] Step 2:

[0335] The device preprocesses the data and sends it to a central server

[0336] The device processes the environmental data received from the sensors, checks for abnormal values, aggregates this data, and sends it to a central server.

[0337] Input: Temperature and humidity data from sensors

[0338] Output: Preprocessed environmental data (temperature and humidity)

[0339] Step 3:

[0340] The server stores the data and checks its integrity

[0341] The server receives the preprocessed environmental data and stores it in a database. After storing it, it checks the integrity of the data and verifies that there are no abnormalities.

[0342] Input: Preprocessed environmental data

[0343] Output: Environmental data stored in a database

[0344] Step 4:

[0345] The user collects bee activity data and sends it to the device.

[0346] Users collect bee activity data using a monitoring device, which records the bees' entry and exit and flight activity and transmits the data to a terminal.

[0347] Input: Bee activity (entering and exiting, flight activity)

[0348] Output: Collected bee activity data

[0349] Step 5:

[0350] The device passes the bee activity data to the analysis module and sends it to the server.

[0351] The terminal passes the bee activity data received from the user to the analysis module, which then transmits it to the central server.

[0352] Input: Collected bee activity data

[0353] Output: Bee activity data passed to the analysis module

[0354] Step 6:

[0355] The server analyzes bee activity data and determines whether pollination assistance is needed.

[0356] The server's analysis module analyzes the bee activity data and determines whether the activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination support is necessary.

[0357] Input: Bee activity data passed to the analysis module

[0358] Output: Analysis result (determining whether activity is high or low)

[0359] Step 7:

[0360] The server determines the need for pollination assistance and sends instructions to the device.

[0361] The server then reconfirms whether pollination assistance is necessary based on the analysis results and environmental data, and if so, sends instructions to the terminal for the robot to move and assist with pollination.

[0362] Input: Analysis results and environmental data

[0363] Output: Instructions to terminal (movement and pollination assistance)

[0364] Step 8:

[0365] The terminal sends instructions to the robot to carry out pollination assistance.

[0366] The terminal sends instructions to the robot to assist with pollination, and the robot moves to the specified location and performs artificial pollination.

[0367] Input: Instructions from the server (movement and pollination assistance)

[0368] Output: Robot behavior (movement and pollination assistance)

[0369] Step 9:

[0370] A user uses an emotion recognition device to collect emotion data.

[0371] The user uses an emotion recognition device, which collects emotion data from facial expressions and voice and transmits it to the terminal.

[0372] Input: User's facial expressions and voice

[0373] Output: Collected emotion data

[0374] Step 10:

[0375] The device receives emotion data and analyzes it with an emotion engine.

[0376] The device receives the emotion data and passes it to the emotion engine in real time to analyze the user's emotional state.

[0377] Input: Collected emotion data

[0378] Output: Analyzed user emotion data

[0379] Step 11:

[0380] The server optimizes system operation based on emotion data

[0381] The server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it changes the timing of pollination assistance.

[0382] Input: Parsed user emotion data

[0383] Output: Optimized system behavior

[0384] Step 12:

[0385] The server manages all the data and generates reports

[0386] The server centrally manages environmental data, bee activity data, and emotion data, and periodically analyzes the data to generate reports.

[0387] Input: Environmental data, bee activity data, emotion data

[0388] Output: Data analysis results and generated reports

[0389] (Application example 2)

[0390] 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."

[0391] Conventional agricultural support systems and factory robot systems were unable to perform optimal operations by taking into account environmental data and the emotional state of workers. As a result, it was difficult to maintain efficient production activities, and there were problems with productivity decline, particularly due to delayed responses to environmental changes and worker emotional stress. Furthermore, as pollination support relies on the activity of honeybees, artificial pollination support was sometimes not performed appropriately.

[0392] 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.

[0393] In this invention, the server includes a means for collecting environmental data using sensors, a means for analyzing bee activity data, a means for artificially supporting pollination, a means for analyzing the user's emotional state, a means for storing and analyzing data in a central server, and a means for optimizing system operation based on the worker's emotional data. This enables real-time monitoring and analysis of the production environment, enabling optimization of pollination support and production activities. Furthermore, by taking the worker's emotional state into consideration, it is possible to improve work efficiency and ensure safety.

[0394] A "sensor" is a device for collecting environmental data, and is responsible for obtaining information such as temperature and humidity in real time.

[0395] "Bee activity data" is data used to measure and analyze the activity status of bees, and is information used to determine the need for pollination support.

[0396] "Means of artificially assisted pollination" refers to a method of artificially pollinating plants using robots or other devices instead of the natural pollination performed by bees.

[0397] "Means for analyzing the user's emotional state" refers to technology for recognizing and analyzing the user's emotions from facial expressions, voice, etc., and refers to devices or software that optimize the system's operation based on emotional data.

[0398] "Means for storing and analyzing data on a central server" refers to a means for centrally managing and analyzing collected environmental data, bee activity data, and emotional data.

[0399] "Worker emotional data" is data related to the emotional state of a worker, and is information that can be used to analyze stress, fatigue, etc., and to optimize production activities.

[0400] "Means for optimizing system operation" refers to the means for determining the current situation based on collected data and maintaining the operation of the entire system in an optimal state.

[0401] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination, as well as a system that analyzes the emotional state of workers and optimizes production activities. Specific embodiments of the present invention are described in detail below.

[0402] System Overview

[0403] The system consists of sensors, terminals, robots, an emotion engine, and a central server. The sensors collect environmental data (temperature and humidity) within the factory and analyze the activity data of the bees. Furthermore, the system monitors and analyzes the user's emotional state, optimizing the operation of the entire system based on this data.

[0404] 1. Environmental data collection

[0405] Sensors measure the temperature and humidity in the factory in real time. The sensors periodically collect this data and send it to the terminal. The terminal preprocesses the environmental data received from the sensors and sends it to the central server. The server receives it, stores it in a database, and checks the integrity of the data.

[0406] 2. Analysis of honeybee activity

[0407] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal. The terminal receives this data and passes it to the analysis module. The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination support is necessary.

[0408] 3. Implementing pollination support

[0409] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination assistance.

[0410] 4. Incorporating an Emotional Engine

[0411] The user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and sends the data to the terminal. The terminal receives the emotion data and analyzes it using an emotion engine. The server optimizes the operation of the entire system based on the user's emotion data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will pause the production line, adjust the environment, and offer the user a break.

[0412] 5. Data Management and Report Generation

[0413] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[0414] Specific examples

[0415] 1. The sensor measures a temperature of 22°C and humidity of 55%, and collects the data. The user uses a monitoring device to collect bee activity data and sends it to the device. Based on the data sent from the device, the server determines that the bees are active, so pollination assistance is not provided. The emotion engine determines that the user is not feeling stressed, so the default processing continues.

[0416] 2. The sensor measures a temperature of 20 degrees and humidity of 50% and collects the data. The user collects bee activity data using a monitoring device and sends it to the terminal. The server analyzes the bee activity and determines that there is little bee activity. The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot. The robot moves based on the instructions and assists with pollination. Because the emotion engine determines that the user is feeling stressed, the system quickly generates a report and provides the user with immediate feedback.

[0417] Prompt Sentence Examples

[0418] "We want to build a system that uses sensors and emotion recognition devices installed in factories to collect data on the status of the production line and the emotions of workers, and optimize factory operations in real time. We envision a system that continues normal processes only when the temperature is above 20 degrees and the humidity is below 60%, and otherwise adjusts the environment and takes necessary action on workers based on the emotional data."

[0419] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0420] Step 1:

[0421] Sensors collect environmental data within the factory and send it to a terminal.

[0422] Specifically, the sensors measure the temperature and humidity inside the factory in real time and send the data to the terminal.

[0423] Input: Environmental conditions in the factory (temperature, humidity).

[0424] Output: Environmental data sent to the device.

[0425] Step 2:

[0426] The terminal preprocesses the received environmental data and sends it to a central server.

[0427] Specifically, the terminal checks the integrity of the data received from the sensor, pre-processes it, converts it into an appropriate format, and sends it to the central server.

[0428] Input: Environmental data sent from sensors.

[0429] Output: Preprocessed environmental data sent to a central server.

[0430] Step 3:

[0431] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0432] Specifically, the user operates a device to acquire bee activity data, collects the data, and transmits it to a terminal.

[0433] Input: Bee activity data.

[0434] Output: Bee activity data sent to the device.

[0435] Step 4:

[0436] The terminal passes the bee activity data to an analysis module, which then sends the analysis results to a central server.

[0437] Specifically, the terminal inputs the bee activity data into an analysis module and sends the results to a central server.

[0438] Input: Bee activity data.

[0439] Output: Analysis results sent to a central server.

[0440] Step 5:

[0441] The server determines the need for pollination support based on the analysis results and environmental data.

[0442] Specifically, the server compares the analysis results with environmental data and determines whether pollination assistance is needed if bee activity is declining.

[0443] Input: Analysis results, environmental data.

[0444] Output: Determination of the need for pollination support.

[0445] Step 6:

[0446] If the server determines that pollination assistance is necessary, it sends instructions to the robot to move and to assist with pollination via the terminal.

[0447] Specifically, the server confirms the need for pollination assistance and then sends specific instructions to the robot via the terminal, including its destination and how to provide pollination assistance.

[0448] Input: Results of pollination support need determination.

[0449] Output: Movement instructions and pollination assistance instructions to the robot.

[0450] Step 7:

[0451] The robot assists with pollination based on instructions.

[0452] Specifically, the robot moves to a designated location and assists with artificial pollination in its assigned area.

[0453] Input: Instructions to the robot.

[0454] Output: Assisted pollination performed.

[0455] Step 8:

[0456] A user uses an emotion recognition device to collect emotion data.

[0457] Specifically, the user uses an emotion recognition device to obtain emotion data from facial expressions, voice, etc., and sends it to the terminal.

[0458] Input: The user's emotional state.

[0459] Output: Emotion data sent to the device.

[0460] Step 9:

[0461] The device analyzes the emotional data using an emotion engine and sends the results to a central server.

[0462] Specifically, the device analyzes the user's emotional data using an emotion engine and sends the results to a central server.

[0463] Input: User emotion data.

[0464] Output: Analysis results sent to a central server.

[0465] Step 10:

[0466] The server optimizes the operation of the entire system based on emotional data.

[0467] Specifically, the server optimizes the system's operation by, for example, adjusting the production line or suggesting breaks for workers based on the results of analyzing the emotional data.

[0468] Input: Parsed emotion data.

[0469] Output: Optimized system operating instructions.

[0470] 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.

[0471] 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.

[0472] 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.

[0473] [Second embodiment]

[0474] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0475] 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.

[0476] 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).

[0477] 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.

[0478] 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.

[0479] 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).

[0480] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0481] 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.

[0482] 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.

[0483] 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.

[0484] 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.

[0485] 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."

[0486] The present invention is a system in which an agricultural robot utilizes artificial intelligence to cooperate with honeybees and assist in the pollination of agricultural crops. Details for implementing the present invention in a specific embodiment are described below.

[0487] System Overview

[0488] The system uses sensors to collect data related to the crop's growing environment (temperature and humidity), analyzes data on the bees' activity, and, if necessary, a robot assists in artificial pollination. All data is stored on a central server for analysis and report generation.

[0489] 1. Environmental data collection

[0490] Sensors measure the growing environment of crops in real time. The sensors periodically measure temperature and humidity and transmit the data to a terminal. The terminal preprocesses the received data and sends it to a central server.

[0491] The terminal receives data from the sensors at regular intervals and forwards it to a central server, which stores the received data in a database and checks the consistency of the data required for each processing step.

[0492] 2. Analysis of honeybee activity

[0493] The user sets up the bee monitoring device and collects bee activity data. The collected data is sent to a terminal. The terminal passes the received bee activity data to an analysis module, and the analysis results are sent to a server.

[0494] The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination assistance is necessary.

[0495] 3. Implementing pollination support

[0496] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends instructions to the robot. The robot moves to the specified location and performs artificial pollination assistance.

[0497] 4. Data Management and Report Generation

[0498] The server centralizes the collected environmental data and bee activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to farmers and related organizations.

[0499] Specific examples

[0500] Example 1:

[0501] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[0502] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0503] The server analyzes the bee activity and determines that "bee activity is high."

[0504] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[0505] Example 2:

[0506] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0507] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0508] The server analyzes bee activity and determines that there is little bee activity.

[0509] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[0510] The robot moves to the location of the crop and assists with pollination, storing the data and generating a corresponding report.

[0511] In this way, this system uses AI and robots to address the problem of declining honeybee populations and provide pollination support to maintain crop productivity.

[0512] The processing flow will be explained below.

[0513] Step 1:

[0514] Sensors measure and collect environmental data (temperature and humidity).

[0515] Step 2:

[0516] The device receives environmental data from the sensors at regular intervals and preprocesses the data, which is then prepared for transmission to the server.

[0517] Step 3:

[0518] The server receives the environmental data sent from the device, stores the data in a database, and verifies that the data is consistent.

[0519] Step 4:

[0520] The user sets up the bee monitoring device, collects bee activity data, and transmits it to the terminal.

[0521] Step 5:

[0522] The terminal receives the bee activity data sent by the user and passes the data to the analysis module.

[0523] Step 6:

[0524] The server analyzes the bee activity data and applies an algorithm to determine whether bee activity is high or low.

[0525] Step 7:

[0526] The server determines whether pollination assistance is necessary based on the analysis results. If activity is low, it determines that pollination assistance is necessary.

[0527] Step 8:

[0528] If it is determined that pollination assistance is needed, the server sends instructions to the robot via the terminal.

[0529] Step 9:

[0530] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[0531] Step 10:

[0532] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[0533] Step 11:

[0534] The server collects and organizes all data, analyzes it periodically, and generates reports based on the analysis results.

[0535] Step 12:

[0536] The server sends the generated report to the user, who then checks the report and considers how to proceed.

[0537] Example 1

[0538] 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."

[0539] In modern agriculture, the decline in honeybee populations has become a major problem, resulting in insufficient pollination of crops. Furthermore, there is a lack of systems that can monitor environmental conditions and honeybee activity in real time and provide pollination support based on that information. A system that can address these issues and maintain crop productivity is needed.

[0540] 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.

[0541] In this invention, the server includes means for collecting environmental data with sensors and measuring temperature and humidity, means for collecting bee activity data and sending it to a terminal, means for preprocessing the collected data on the terminal and sending it to a central server, means for analyzing the received data on the central server and determining whether bee activity is high or low, means for determining the need for pollination assistance based on the analysis results on the central server, means for sending instructions to the robot via the terminal when the central server determines that pollination assistance is necessary, means for the robot to move to a specified location and perform artificial pollination assistance, and means for storing the data collected and analyzed by the central server in a database and generating a report. This makes it possible to efficiently and automatically provide pollination assistance based on the bee activity status and environmental data.

[0542] A "sensor" is a device for collecting environmental data and measuring physical quantities such as temperature and humidity.

[0543] "Environmental data" refers to data related to the growing environment of agricultural crops, and mainly refers to temperature and humidity.

[0544] "Terminal" is a device that receives data collected from sensors and bee monitoring devices, pre-processes it and transmits it to a central server.

[0545] The "central server" is a computer system that centrally manages, analyzes, and stores various collected data.

[0546] A "bee monitoring device" is a device for collecting data on bee activity.

[0547] "Assisted pollination" is the process by which robots artificially pollinate crops.

[0548] A "database" is an information management system for systematically storing and managing collected data.

[0549] A "report" is a document that is periodically produced based on collected and analyzed data, and is intended to provide information to farmers and related institutions.

[0550] "Analysis" is the process of evaluating bee activity and environmental conditions based on collected data and determining the need for pollination support.

[0551] A "robot" is an automated mechanical device that moves to the location of crops based on instructions from a server and assists in artificial pollination.

[0552] "Preprocessing" refers to processes that remove noise from collected data and correct outliers to improve the accuracy and reliability of the data.

[0553] An "instruction" is an operation command sent from a central server to a robot via a terminal.

[0554] This invention is an agricultural robot system that efficiently supports the pollination of agricultural crops through the cooperative operation of sensors, terminals, a central server, and robots.

[0555] First, sensors monitor the growing environment of agricultural crops. Specifically, they measure temperature and humidity in real time and send the data to a terminal. Temperature and humidity sensors are generally used. This data is important for maintaining an optimal growing environment for agricultural crops.

[0556] The terminal receives data from the sensors at regular intervals and performs preprocessing. Specifically, it removes noise from the data, corrects outliers, and converts the data format into a suitable format for the database. The preprocessed data is then sent to a central server.

[0557] The server stores the received data in a database and checks the consistency of the data required at each processing step. Furthermore, the server also analyzes the bee activity data. Specifically, the server passes the bee activity data collected by the user using the bee monitoring device to the analysis module, which determines whether the activity is high or low. A generative AI model is used for this analysis, allowing for fast and accurate judgments.

[0558] Based on the analysis results and environmental data, the server determines whether pollination assistance is necessary. If it is determined that pollination assistance is necessary, instructions are sent to the robot via the terminal. Instructions include, for example, "Move to the location of the crop and begin pollination assistance."

[0559] The robot moves to a designated location and assists in artificial pollination. Typically, the robot's arm touches the flowers of the crops to promote pollination.

[0560] Finally, the server centralizes the collected environmental data and bee activity data, and periodically generates reports containing monthly data analysis results and a history of pollination support activities, which are provided to farmers and related organizations.

[0561] Specific examples

[0562] Example 1:

[0563] The sensor measures the temperature at 22 degrees and the humidity at 55% and collects the data.

[0564] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "100 flights per day."

[0565] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that the bees are active.

[0566] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[0567] Example 2:

[0568] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0569] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "10 flights per day."

[0570] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that there is little bee activity.

[0571] The server determines that pollination assistance is needed, and the terminal sends instructions to the robot.

[0572] The robot moves to the location of the crop and assists with pollination. The robot touches the flowers of the crop.

[0573] The server generates a corresponding report and sends it to the user.

[0574] The system uses AI and robots to address the declining honeybee population and provide pollination assistance to maintain crop productivity.

[0575] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0576] Step 1:

[0577] The sensor collects environmental data. Specifically, the sensor measures temperature and humidity in real time, obtaining data such as "temperature 22 degrees, humidity 55%." This collected data is sent to the device as environmental data.

[0578] Input: Environmental data (temperature, humidity)

[0579] Output: Environmental data sent to the device

[0580] Step 2:

[0581] The device receives environmental data from the sensor and performs preprocessing. Specifically, the device removes noise and corrects outliers, and converts the data format into a format suitable for the database. For example, a measured value of "temperature 22 degrees, humidity 55%" is preprocessed and converted into a database format.

[0582] Input: Environmental data from sensors

[0583] Output: Preprocessed environmental data (database format)

[0584] Step 3:

[0585] The device sends the preprocessed environmental data to the central server. Specifically, the preprocessed data is packaged into packets and sent to a specific IP address on the central server. For example, data such as "temperature 22 degrees, humidity 55%" is sent as a packet.

[0586] Input: Preprocessed environmental data

[0587] Output: Data packets sent to the central server

[0588] Step 4:

[0589] The environmental data received by the server is stored in a database. Specifically, a database management system (e.g., MySQL) is used to check for data duplication and consistency, and if there are no problems, the data is stored. For example, data such as "temperature 22 degrees, humidity 55%" is stored in the database.

[0590] Input: Data packet sent to the central server

[0591] Output: Environmental data stored in a database

[0592] Step 5:

[0593] The user sets up a bee monitoring device and collects bee activity data. For example, a sensor device installed in a hive collects data such as "100 bee flights per day." This activity data is sent to a terminal.

[0594] Input: Bee activity data (number of flights)

[0595] Output: Bee activity data sent to the terminal

[0596] Step 6:

[0597] The terminal receives the bee activity data and passes it to the preprocessing and analysis module. Specifically, the data is cleansed and standardized into a format that is easy to analyze. For example, "100 flights" is converted into data for analysis.

[0598] Input: Bee activity data sent to the terminal

[0599] Output: Preprocessed data passed to the analysis module

[0600] Step 7:

[0601] The server analyzes the bee activity data and determines whether the activity is high or low. Specifically, it uses a generative AI model (e.g., TensorFlow) to analyze it. For example, if the number of bee flights is low, it is determined that there is "low bee activity."

[0602] Input: Preprocessed data passed to the analysis module

[0603] Output: Activity evaluation result (high / low)

[0604] Step 8:

[0605] The server determines whether pollination support is necessary based on the analysis results and environmental data. Specifically, it uses an AI algorithm to comprehensively evaluate each piece of data. For example, if it determines that "the temperature is 20 degrees, the humidity is 50%, and there is little bee activity," pollination support is necessary.

[0606] Input: Activity evaluation results, environmental data

[0607] Output: Pollination support decision (necessary / unnecessary)

[0608] Step 9:

[0609] The terminal sends instructions for pollination assistance to the robot. For example, it sends a packet containing instructions to the robot to "move to the location of the crop and start pollination assistance."

[0610] Input: Pollination support judgment

[0611] Output: Instruction packet to the robot

[0612] Step 10:

[0613] The robot moves to a designated location and assists in artificial pollination. Specifically, the robot's arm touches the flowers of the crops to promote pollination. For example, it performs a "flower touching action."

[0614] Input: Instruction packet to the robot

[0615] Output: Record of assisted pollination performed

[0616] Step 11:

[0617] The server centrally manages the collected environmental data and bee activity data and stores it in a database. Furthermore, the server periodically analyzes the data and generates reports to provide to farmers and related organizations. For example, it creates a report based on this month's bee activity and environmental data.

[0618] Input: Environmental data, bee activity data

[0619] Output: Report

[0620] (Application example 1)

[0621] 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."

[0622] Conventional factory production lines lacked systems that could monitor environmental data and equipment activity data in real time and respond quickly. As a result, responses to environmental changes and equipment abnormalities were often delayed, resulting in reduced productivity and quality issues. Furthermore, data collection and analysis were not carried out efficiently, and report creation took a long time.

[0623] 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.

[0624] In this invention, the server includes a means for collecting environmental data with sensors, a means for analyzing activity data of production equipment, a means for automatically adjusting the production line, and a means for storing the data in the central server, analyzing it, and generating reports, thereby enabling real-time monitoring and rapid adjustment of the production line, as well as efficient data management and rapid report generation.

[0625] A "sensor" is a device that measures environmental data in real time and transmits that data to a terminal.

[0626] "Environmental data" refers to physical data such as temperature, humidity, vibration, and noise inside the factory.

[0627] "Production equipment activity data" refers to data relating to the operating status and operational status of production line equipment.

[0628] "Analysis" is the process of analyzing collected data and determining whether activity is normal or abnormal.

[0629] "Central Server" refers to a central computer server that stores collected environmental data and production equipment activity data, analyzes them, and generates reports.

[0630] A "report" is a document provided to interested parties based on collected and analyzed data.

[0631] "Adjustment" refers to the task of a robot changing the settings and arrangement of equipment on a production line.

[0632] "Real time" refers to information being processed almost simultaneously.

[0633] The present invention relates to a system for collecting and analyzing environmental data and activity data of production equipment within a factory, and making necessary adjustments based on the data. Details for specifically implementing the present invention will be described below.

[0634] 1. Environmental data collection

[0635] The server uses sensors to collect environmental data within the factory in real time. The sensors periodically measure temperature, humidity, vibration, and noise and send the data to terminals. The terminals preprocess the received data and send it to the central server. The central server stores the received data in a database and checks the consistency of the data required at each processing step.

[0636] 2. Analysis of production equipment activity data

[0637] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to the terminal. The terminal passes the received equipment activity data to the analysis module and sends the analysis results to the central server. The server analyzes the equipment activity data and determines whether the activity is normal or abnormal. Based on the analysis results, it determines whether adjustments are necessary.

[0638] 3. Implement production line adjustments

[0639] The server determines that adjustments to the production line are necessary based on the analysis results and environmental data. If adjustments are determined to be necessary, the terminal sends instructions to the robot. The robot moves to the specified location and automatically adjusts the production line or handles any problems. After the robot completes the adjustment work, it sends the data to the terminal, which then stores it on the central server.

[0640] 4. Data Management and Report Generation

[0641] The server centrally manages the collected environmental data and production equipment activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to production managers and related organizations.

[0642] Hardware and software used

[0643] Sensors: Temperature sensor, humidity sensor, vibration sensor, microphone

[0644] Terminal: IoT device for data collection and transmission

[0645] Central server: A computer server that runs the database and analysis modules

[0646] Robot: Autonomous robot for production line adjustment

[0647] Software: Database management systems, analysis software, robot control systems

[0648] Specific examples

[0649] Example 1:

[0650] The sensors measure temperature at 25 degrees, humidity at 60%, and vibration level at 2.0 and collect data.

[0651] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[0652] The server analyzes the device activity and determines that the activity is normal.

[0653] The server determines that no adjustment is necessary and saves the data. A report on the operation status of the production line is generated.

[0654] Example 2:

[0655] The sensors measure a temperature of 30 degrees, humidity of 50%, and vibration level of 3.5 and collect data.

[0656] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[0657] The server analyzes the device activity and determines that the activity is abnormal.

[0658] The server determines that adjustments are necessary, and the terminal sends instructions to the robot.

[0659] The robot moves to its working position, adjusts the production line, stores the data and generates a corresponding report.

[0660] Prompt Sentence Examples

[0661] Prompt: Generate a procedure for adjusting the production line if the temperature measured by sensors in the factory is 30 degrees and the vibration level is 3.5.

[0662] Output procedure: Analyze data from sensors and send it to a central server. The server detects anomalies. The robot moves to the specified position and initiates adjustments. The data is saved and a report is generated.

[0663] The system of the present invention aims to improve the efficiency of management and adjustment of production lines within a factory, thereby improving productivity and optimizing quality control.

[0664] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0665] Step 1:

[0666] The server collects environmental data from sensors. The sensors periodically measure the temperature, humidity, vibration, and noise levels in the factory and send the data to terminals. The terminals then format the received data and send it to the central server. The input is the environmental data sent by the sensors, and the output is the formatted data. Specifically, the temperature sensor measures 25 degrees, and the data is sent by the terminal to the central server.

[0667] Step 2:

[0668] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to a terminal. The terminal passes the received equipment data to an analysis module, which then sends the analysis results to a central server. The input is the equipment activity data, and the output is the analyzed status data. Specifically, the monitoring device confirms that the equipment is operating normally, and the data is sent to the server.

[0669] Step 3:

[0670] The server analyzes the device's activity data and determines whether the activity is normal or abnormal. The input is the received activity data, and the output is the analysis result. Specific calculations detect abnormalities by comparing it with normal activity patterns. For example, if the vibration level is abnormally high, it is determined to be abnormal.

[0671] Step 4:

[0672] The server determines whether adjustments to the production line are necessary based on the analysis results and environmental data. If it determines that adjustments are necessary, the terminal sends instructions to the robot. The input is the analysis results and environmental data, and the output is instructions to the robot. Specifically, if it determines that the temperature and vibration levels are abnormally high, an adjustment instruction is sent to the robot.

[0673] Step 5:

[0674] The robot receives instructions, moves to the designated location, and automatically adjusts the production line and handles problems. The input is the adjustment instruction from the server, and the output is the improved activity data after the adjustment. A specific example of the robot's operation is readjusting equipment to suppress abnormal vibrations.

[0675] Step 6:

[0676] The server receives the adjusted data sent from the robot and stores it in a database. It also periodically analyzes the data and generates a report. The input is the adjusted data and the output is the report. The specific operation is to generate a report and provide it to the production manager.

[0677] This enables real-time monitoring of production lines within factories and rapid adjustments, resulting in improved productivity and quality.

[0678] 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.

[0679] The present invention combines a system that collects environmental data, analyzes bee activity data, and artificially supports pollination with an emotion engine that recognizes the user's emotions. Details for implementing the present invention in a specific form are described below.

[0680] System Overview

[0681] The system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect data related to the crop's growing environment (temperature and humidity), analyze the bee activity data, and the robot assists with artificial pollination as needed. Furthermore, the emotion engine analyzes the user's emotional state and optimizes the system's operation based on this.

[0682] 1. Environmental data collection

[0683] The sensors measure the crop growth environment (temperature and humidity) in real time, periodically collecting this data and sending it to the terminal.

[0684] The devices preprocess the environmental data received from the sensors and send it to a central server, which receives it, stores it in a database, and checks the integrity of the data.

[0685] 2. Analysis of honeybee activity

[0686] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal, which receives the data and passes it to the analysis module.

[0687] The server analyzes the bee activity data and determines whether the activity is high or low, and based on the analysis results, decides whether pollination assistance is needed.

[0688] 3. Implementing pollination support

[0689] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions to the robot to assist pollination. The robot then moves to the specified location and performs artificial pollination assistance.

[0690] 4. Incorporating an Emotional Engine

[0691] To monitor the user's emotional state, the user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and transmits the data to the device. The device receives the emotion data and analyzes it using an emotion engine.

[0692] The server optimizes the overall operation of the system based on the user's emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will adjust the timing of pollination assistance to reduce the user's burden.

[0693] 5. Data Management and Report Generation

[0694] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[0695] Specific examples

[0696] Example 1:

[0697] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[0698] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0699] Based on the data sent from the device, the server determines that bee activity is high and therefore does not provide pollination support.

[0700] Since the emotion engine has determined that the user is not feeling stressed, the default processing continues.

[0701] Example 2:

[0702] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0703] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0704] The server analyzes bee activity and determines that there is little bee activity.

[0705] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[0706] The robot moves based on instructions and assists with pollination.

[0707] Because the emotion engine determines that the user is stressed, the system expedites report generation and provides immediate feedback to the user.

[0708] In this way, the system uses AI, robots, and an emotion engine to assist with pollination to maintain crop productivity, and also optimizes the operation of the entire system by taking into account the user's emotional state.

[0709] The processing flow will be explained below.

[0710] Step 1:

[0711] Sensors measure and collect environmental data (temperature and humidity).

[0712] Step 2:

[0713] The terminal receives environmental data from sensors at regular intervals, preprocesses the data, and sends it to a central server.

[0714] Step 3:

[0715] The server receives the environmental data sent from the device, stores it in a database, and checks the integrity of the data.

[0716] Step 4:

[0717] A user uses a bee monitoring device to collect bee activity data and transmit it to a terminal.

[0718] Step 5:

[0719] The terminal receives the bee activity data sent by the user and passes it to the analysis module.

[0720] Step 6:

[0721] The server analyzes the bee activity data and runs an algorithm to determine whether activity is high or low.

[0722] Step 7:

[0723] The server determines whether pollination assistance is necessary based on the analysis results, and generates instructions for pollination assistance if necessary.

[0724] Step 8:

[0725] If the server determines that pollination assistance is necessary, it sends instructions to the terminal and prepares instructions for the robot to move and for pollination assistance.

[0726] Step 9:

[0727] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[0728] Step 10:

[0729] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[0730] Step 11:

[0731] A user uses an emotion recognition device to collect his / her own emotion data and transmits it to a terminal.

[0732] Step 12:

[0733] The terminal receives the user's emotion data and passes the data to the emotion engine.

[0734] Step 13:

[0735] The server uses an emotion engine to analyze the user's emotional data and adjusts the operation of the entire system based on the results.

[0736] Step 14:

[0737] The server stores all data (environmental data, bee activity data, emotion data) in a database and manages them centrally.

[0738] Step 15:

[0739] The server periodically analyzes the data and generates reports based on the results.

[0740] Step 16:

[0741] The server generates a report, which is then sent to the user, which then reviews it. The report includes environmental data, bee activity, pollination support status, and emotional state analysis.

[0742] Example 2

[0743] 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."

[0744] The present invention aims to provide a method for optimizing the operation of a system that uses environmental data and bee activity data to support the pollination of agricultural crops, taking into account the emotional state of the user, thereby improving the efficiency of pollination support and reducing the stress and burden on the user.

[0745] 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.

[0746] In this invention, the server includes means for collecting environmental data with sensors, means for analyzing bee activity data, means for artificially supporting pollination, means for storing and analyzing data in a central server, means for collecting and analyzing emotion data using an emotion engine that recognizes user emotions, and means for optimizing system operation based on the analyzed emotion data. This enables comprehensive pollination support that takes into account not only conventional environmental data and bee activity data, but also user emotion data.

[0747] A "sensor" is a device that measures a physical condition, such as temperature or humidity, to collect environmental data.

[0748] "Bee activity data" is data that records the movements of bees, such as their comings and goings and flight activities.

[0749] "Artificial pollination assistance" is a method of artificially moving pollen using devices such as robots.

[0750] "Central Server" is a computer system that stores and analyzes collected data.

[0751] An "emotion engine" is software that recognizes a user's emotions and analyzes that emotional data.

[0752] "Emotional Data" is data about a user's emotional state that is collected and analyzed by the emotion engine.

[0753] "Optimizing system operation" refers to optimally adjusting the performance of various system functions based on collected data.

[0754] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination as needed, and further combines it with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present invention.

[0755] System configuration

[0756] This system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect temperature and humidity data related to the crop growth environment. The terminals preprocess the data received from the sensors and send it to the central server. The central server receives, stores, and analyzes the data. It also issues instructions to the robots that assist with pollination. The emotion engine analyzes the user's emotional state and optimizes the system's operation.

[0757] Environmental data collection

[0758] Sensors measure the crops' environmental data (temperature and humidity) in real time. These sensors periodically collect data and send it to the terminal. For example, the sensor collects data of 22 degrees Celsius and 55% humidity every 5 minutes and sends it to the terminal.

[0759] The device preprocesses the environmental data received from the sensor and sends it to the central server. As part of the preprocessing, the device organizes the data and checks for any abnormal values. The organized data is then sent to the central server. The server receives the data, stores it in a database, and checks the integrity of the data.

[0760] Analysis of honeybee activity

[0761] A user sets up a monitoring device to collect bee activity data, and the collected data is sent to a terminal. For example, the user sends data recording the bees' entry and exit and flight activity to the terminal.

[0762] The terminal passes the received bee activity data to an analysis module, which then sends it to a central server. The central server analyzes the bee activity data and determines whether activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination assistance is necessary.

[0763] Pollination support

[0764] The central server determines whether pollination assistance is necessary based on the analysis results. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination.

[0765] Incorporating an emotion engine

[0766] The user uses an emotion recognition device, which collects emotional data from facial expressions and voice and sends it to the terminal. The terminal receives the emotional data and passes it to the emotion engine. The emotion engine determines the user's current emotional state and sends the data to the central server. The central server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it may change the timing of pollination assistance.

[0767] Specific examples

[0768] As a concrete example, a sensor collects data on a temperature of 20 degrees and humidity of 50%, and a user collects data on bee activity using a monitoring device and sends this data to a terminal. The terminal then sends this data to a server, which determines that "bee activity is low." The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot to move and pollinate. The robot moves to the instructed location and assists with pollination. Furthermore, if the emotion engine determines that the user is feeling stressed, the system will quickly generate a report and provide the user with immediate feedback.

[0769] Prompt Sentence Examples

[0770] "What steps can we take to optimize pollination support based on user sentiment and environmental data?"

[0771] In this way, the system uses AI, robots, and an emotion engine to maintain crop productivity and optimize the operation of the entire system by taking into account the user's emotional state.

[0772] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0773] Step 1:

[0774] Sensors collect environmental data

[0775] The sensors measure the temperature and humidity around the crops in real time. For example, the sensors collect data every five minutes showing a temperature of 22°C and humidity of 55%.

[0776] Input: Ambient environmental conditions (temperature, humidity)

[0777] Output: Measured temperature and humidity data

[0778] Step 2:

[0779] The device preprocesses the data and sends it to a central server

[0780] The device processes the environmental data received from the sensors, checks for abnormal values, aggregates this data, and sends it to a central server.

[0781] Input: Temperature and humidity data from sensors

[0782] Output: Preprocessed environmental data (temperature and humidity)

[0783] Step 3:

[0784] The server stores the data and checks its integrity

[0785] The server receives the preprocessed environmental data and stores it in a database. After storing it, it checks the integrity of the data and verifies that there are no abnormalities.

[0786] Input: Preprocessed environmental data

[0787] Output: Environmental data stored in a database

[0788] Step 4:

[0789] The user collects bee activity data and sends it to the device.

[0790] Users collect bee activity data using a monitoring device, which records the bees' entry and exit and flight activity and transmits the data to a terminal.

[0791] Input: Bee activity (entering and exiting, flight activity)

[0792] Output: Collected bee activity data

[0793] Step 5:

[0794] The device passes the bee activity data to the analysis module and sends it to the server.

[0795] The terminal passes the bee activity data received from the user to the analysis module, which then transmits it to the central server.

[0796] Input: Collected bee activity data

[0797] Output: Bee activity data passed to the analysis module

[0798] Step 6:

[0799] The server analyzes bee activity data and determines whether pollination assistance is needed.

[0800] The server's analysis module analyzes the bee activity data and determines whether the activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination support is necessary.

[0801] Input: Bee activity data passed to the analysis module

[0802] Output: Analysis result (determining whether activity is high or low)

[0803] Step 7:

[0804] The server determines the need for pollination assistance and sends instructions to the device.

[0805] The server then reconfirms whether pollination assistance is necessary based on the analysis results and environmental data, and if so, sends instructions to the terminal for the robot to move and assist with pollination.

[0806] Input: Analysis results and environmental data

[0807] Output: Instructions to terminal (movement and pollination assistance)

[0808] Step 8:

[0809] The terminal sends instructions to the robot to carry out pollination assistance.

[0810] The terminal sends instructions to the robot to assist with pollination, and the robot moves to the specified location and performs artificial pollination.

[0811] Input: Instructions from the server (movement and pollination assistance)

[0812] Output: Robot behavior (movement and pollination assistance)

[0813] Step 9:

[0814] A user uses an emotion recognition device to collect emotion data.

[0815] The user uses an emotion recognition device, which collects emotion data from facial expressions and voice and transmits it to the terminal.

[0816] Input: User's facial expressions and voice

[0817] Output: Collected emotion data

[0818] Step 10:

[0819] The device receives emotion data and analyzes it with an emotion engine.

[0820] The device receives the emotion data and passes it to the emotion engine in real time to analyze the user's emotional state.

[0821] Input: Collected emotion data

[0822] Output: Analyzed user emotion data

[0823] Step 11:

[0824] The server optimizes system operation based on emotion data

[0825] The server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it changes the timing of pollination assistance.

[0826] Input: Parsed user emotion data

[0827] Output: Optimized system behavior

[0828] Step 12:

[0829] The server manages all the data and generates reports

[0830] The server centrally manages environmental data, bee activity data, and emotion data, and periodically analyzes the data to generate reports.

[0831] Input: Environmental data, bee activity data, emotion data

[0832] Output: Data analysis results and generated reports

[0833] (Application example 2)

[0834] 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."

[0835] Conventional agricultural support systems and factory robot systems were unable to perform optimal operations by taking into account environmental data and the emotional state of workers. As a result, it was difficult to maintain efficient production activities, and there were problems with productivity decline, particularly due to delayed responses to environmental changes and worker emotional stress. Furthermore, as pollination support relies on the activity of honeybees, artificial pollination support was sometimes not performed appropriately.

[0836] 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.

[0837] In this invention, the server includes a means for collecting environmental data using sensors, a means for analyzing bee activity data, a means for artificially supporting pollination, a means for analyzing the user's emotional state, a means for storing and analyzing data in a central server, and a means for optimizing system operation based on the worker's emotional data. This enables real-time monitoring and analysis of the production environment, enabling optimization of pollination support and production activities. Furthermore, by taking the worker's emotional state into consideration, it is possible to improve work efficiency and ensure safety.

[0838] A "sensor" is a device for collecting environmental data, and is responsible for obtaining information such as temperature and humidity in real time.

[0839] "Bee activity data" is data used to measure and analyze the activity status of bees, and is information used to determine the need for pollination support.

[0840] "Means of artificially assisted pollination" refers to a method of artificially pollinating plants using robots or other devices instead of the natural pollination performed by bees.

[0841] "Means for analyzing the user's emotional state" refers to technology for recognizing and analyzing the user's emotions from facial expressions, voice, etc., and refers to devices or software that optimize the system's operation based on emotional data.

[0842] "Means for storing and analyzing data on a central server" refers to a means for centrally managing and analyzing collected environmental data, bee activity data, and emotional data.

[0843] "Worker emotional data" is data related to the emotional state of a worker, and is information that can be used to analyze stress, fatigue, etc., and to optimize production activities.

[0844] "Means for optimizing system operation" refers to the means for determining the current situation based on collected data and maintaining the operation of the entire system in an optimal state.

[0845] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination, as well as a system that analyzes the emotional state of workers and optimizes production activities. Specific embodiments of the present invention are described in detail below.

[0846] System Overview

[0847] The system consists of sensors, terminals, robots, an emotion engine, and a central server. The sensors collect environmental data (temperature and humidity) within the factory and analyze the activity data of the bees. Furthermore, the system monitors and analyzes the user's emotional state, optimizing the operation of the entire system based on this data.

[0848] 1. Environmental data collection

[0849] Sensors measure the temperature and humidity in the factory in real time. The sensors periodically collect this data and send it to the terminal. The terminal preprocesses the environmental data received from the sensors and sends it to the central server. The server receives it, stores it in a database, and checks the integrity of the data.

[0850] 2. Analysis of honeybee activity

[0851] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal. The terminal receives this data and passes it to the analysis module. The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination support is necessary.

[0852] 3. Implementing pollination support

[0853] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination assistance.

[0854] 4. Incorporating an Emotional Engine

[0855] The user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and sends the data to the terminal. The terminal receives the emotion data and analyzes it using an emotion engine. The server optimizes the operation of the entire system based on the user's emotion data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will pause the production line, adjust the environment, and offer the user a break.

[0856] 5. Data Management and Report Generation

[0857] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[0858] Specific examples

[0859] 1. The sensor measures a temperature of 22°C and humidity of 55%, and collects the data. The user uses a monitoring device to collect bee activity data and sends it to the device. Based on the data sent from the device, the server determines that the bees are active, so pollination assistance is not provided. The emotion engine determines that the user is not feeling stressed, so the default processing continues.

[0860] 2. The sensor measures a temperature of 20 degrees and humidity of 50% and collects the data. The user collects bee activity data using a monitoring device and sends it to the terminal. The server analyzes the bee activity and determines that there is little bee activity. The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot. The robot moves based on the instructions and assists with pollination. Because the emotion engine determines that the user is feeling stressed, the system quickly generates a report and provides the user with immediate feedback.

[0861] Prompt Sentence Examples

[0862] "We want to build a system that uses sensors and emotion recognition devices installed in factories to collect data on the status of the production line and the emotions of workers, and optimize factory operations in real time. We envision a system that continues normal processes only when the temperature is above 20 degrees and the humidity is below 60%, and otherwise adjusts the environment and takes necessary action on workers based on the emotional data."

[0863] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0864] Step 1:

[0865] Sensors collect environmental data within the factory and send it to a terminal.

[0866] Specifically, the sensors measure the temperature and humidity inside the factory in real time and send the data to the terminal.

[0867] Input: Environmental conditions in the factory (temperature, humidity).

[0868] Output: Environmental data sent to the device.

[0869] Step 2:

[0870] The terminal preprocesses the received environmental data and sends it to a central server.

[0871] Specifically, the terminal checks the integrity of the data received from the sensor, pre-processes it, converts it into an appropriate format, and sends it to the central server.

[0872] Input: Environmental data sent from sensors.

[0873] Output: Preprocessed environmental data sent to a central server.

[0874] Step 3:

[0875] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0876] Specifically, the user operates a device to acquire bee activity data, collects the data, and transmits it to a terminal.

[0877] Input: Bee activity data.

[0878] Output: Bee activity data sent to the device.

[0879] Step 4:

[0880] The terminal passes the bee activity data to an analysis module, which then sends the analysis results to a central server.

[0881] Specifically, the terminal inputs the bee activity data into an analysis module and sends the results to a central server.

[0882] Input: Bee activity data.

[0883] Output: Analysis results sent to a central server.

[0884] Step 5:

[0885] The server determines the need for pollination support based on the analysis results and environmental data.

[0886] Specifically, the server compares the analysis results with environmental data and determines whether pollination assistance is needed if bee activity is declining.

[0887] Input: Analysis results, environmental data.

[0888] Output: Determination of the need for pollination support.

[0889] Step 6:

[0890] If the server determines that pollination assistance is necessary, it sends instructions to the robot to move and to assist with pollination via the terminal.

[0891] Specifically, the server confirms the need for pollination assistance and then sends specific instructions to the robot via the terminal, including its destination and how to provide pollination assistance.

[0892] Input: Results of pollination support need determination.

[0893] Output: Movement instructions and pollination assistance instructions to the robot.

[0894] Step 7:

[0895] The robot assists with pollination based on instructions.

[0896] Specifically, the robot moves to a designated location and assists with artificial pollination in its assigned area.

[0897] Input: Instructions to the robot.

[0898] Output: Assisted pollination performed.

[0899] Step 8:

[0900] A user uses an emotion recognition device to collect emotion data.

[0901] Specifically, the user uses an emotion recognition device to obtain emotion data from facial expressions, voice, etc., and sends it to the terminal.

[0902] Input: The user's emotional state.

[0903] Output: Emotion data sent to the device.

[0904] Step 9:

[0905] The device analyzes the emotional data using an emotion engine and sends the results to a central server.

[0906] Specifically, the device analyzes the user's emotional data using an emotion engine and sends the results to a central server.

[0907] Input: User emotion data.

[0908] Output: Analysis results sent to a central server.

[0909] Step 10:

[0910] The server optimizes the operation of the entire system based on emotional data.

[0911] Specifically, the server optimizes the system's operation by, for example, adjusting the production line or suggesting breaks for workers based on the results of analyzing the emotional data.

[0912] Input: Parsed emotion data.

[0913] Output: Optimized system operating instructions.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] [Third embodiment]

[0918] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0919] 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.

[0920] 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).

[0921] 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.

[0922] 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.

[0923] 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).

[0924] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0925] 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.

[0926] 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.

[0927] 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.

[0928] 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.

[0929] 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."

[0930] The present invention is a system in which an agricultural robot utilizes artificial intelligence to cooperate with honeybees and assist in the pollination of agricultural crops. Details for implementing the present invention in a specific embodiment are described below.

[0931] System Overview

[0932] The system uses sensors to collect data related to the crop's growing environment (temperature and humidity), analyzes data on the bees' activity, and, if necessary, a robot assists in artificial pollination. All data is stored on a central server for analysis and report generation.

[0933] 1. Environmental data collection

[0934] Sensors measure the growing environment of crops in real time. The sensors periodically measure temperature and humidity and transmit the data to a terminal. The terminal preprocesses the received data and sends it to a central server.

[0935] The terminal receives data from the sensors at regular intervals and forwards it to a central server, which stores the received data in a database and checks the consistency of the data required for each processing step.

[0936] 2. Analysis of honeybee activity

[0937] The user sets up the bee monitoring device and collects bee activity data. The collected data is sent to a terminal. The terminal passes the received bee activity data to an analysis module, and the analysis results are sent to a server.

[0938] The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination assistance is necessary.

[0939] 3. Implementing pollination support

[0940] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends instructions to the robot. The robot moves to the specified location and performs artificial pollination assistance.

[0941] 4. Data Management and Report Generation

[0942] The server centralizes the collected environmental data and bee activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to farmers and related organizations.

[0943] Specific examples

[0944] Example 1:

[0945] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[0946] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0947] The server analyzes the bee activity and determines that "bee activity is high."

[0948] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[0949] Example 2:

[0950] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[0951] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[0952] The server analyzes bee activity and determines that there is little bee activity.

[0953] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[0954] The robot moves to the location of the crop and assists with pollination, storing the data and generating a corresponding report.

[0955] In this way, this system uses AI and robots to address the problem of declining honeybee populations and provide pollination support to maintain crop productivity.

[0956] The processing flow will be explained below.

[0957] Step 1:

[0958] Sensors measure and collect environmental data (temperature and humidity).

[0959] Step 2:

[0960] The device receives environmental data from the sensors at regular intervals and preprocesses the data, which is then prepared for transmission to the server.

[0961] Step 3:

[0962] The server receives the environmental data sent from the device, stores the data in a database, and verifies that the data is consistent.

[0963] Step 4:

[0964] The user sets up the bee monitoring device, collects bee activity data, and transmits it to the terminal.

[0965] Step 5:

[0966] The terminal receives the bee activity data sent by the user and passes the data to the analysis module.

[0967] Step 6:

[0968] The server analyzes the bee activity data and applies an algorithm to determine whether bee activity is high or low.

[0969] Step 7:

[0970] The server determines whether pollination assistance is necessary based on the analysis results. If activity is low, it determines that pollination assistance is necessary.

[0971] Step 8:

[0972] If it is determined that pollination assistance is needed, the server sends instructions to the robot via the terminal.

[0973] Step 9:

[0974] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[0975] Step 10:

[0976] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[0977] Step 11:

[0978] The server collects and organizes all data, analyzes it periodically, and generates reports based on the analysis results.

[0979] Step 12:

[0980] The server sends the generated report to the user, who then checks the report and considers how to proceed.

[0981] Example 1

[0982] 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."

[0983] In modern agriculture, the decline in honeybee populations has become a major problem, resulting in insufficient pollination of crops. Furthermore, there is a lack of systems that can monitor environmental conditions and honeybee activity in real time and provide pollination support based on that information. A system that can address these issues and maintain crop productivity is needed.

[0984] 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.

[0985] In this invention, the server includes means for collecting environmental data with sensors and measuring temperature and humidity, means for collecting bee activity data and sending it to a terminal, means for preprocessing the collected data on the terminal and sending it to a central server, means for analyzing the received data on the central server and determining whether bee activity is high or low, means for determining the need for pollination assistance based on the analysis results on the central server, means for sending instructions to the robot via the terminal when the central server determines that pollination assistance is necessary, means for the robot to move to a specified location and perform artificial pollination assistance, and means for storing the data collected and analyzed by the central server in a database and generating a report. This makes it possible to efficiently and automatically provide pollination assistance based on the bee activity status and environmental data.

[0986] A "sensor" is a device for collecting environmental data and measuring physical quantities such as temperature and humidity.

[0987] "Environmental data" refers to data related to the growing environment of agricultural crops, and mainly refers to temperature and humidity.

[0988] "Terminal" is a device that receives data collected from sensors and bee monitoring devices, pre-processes it and transmits it to a central server.

[0989] The "central server" is a computer system that centrally manages, analyzes, and stores various collected data.

[0990] A "bee monitoring device" is a device for collecting data on bee activity.

[0991] "Assisted pollination" is the process by which robots artificially pollinate crops.

[0992] A "database" is an information management system for systematically storing and managing collected data.

[0993] A "report" is a document that is periodically produced based on collected and analyzed data, and is intended to provide information to farmers and related institutions.

[0994] "Analysis" is the process of evaluating bee activity and environmental conditions based on collected data and determining the need for pollination support.

[0995] A "robot" is an automated mechanical device that moves to the location of crops based on instructions from a server and assists in artificial pollination.

[0996] "Preprocessing" refers to processes that remove noise from collected data and correct outliers to improve the accuracy and reliability of the data.

[0997] An "instruction" is an operation command sent from a central server to a robot via a terminal.

[0998] This invention is an agricultural robot system that efficiently supports the pollination of agricultural crops through the cooperative operation of sensors, terminals, a central server, and robots.

[0999] First, sensors monitor the growing environment of agricultural crops. Specifically, they measure temperature and humidity in real time and send the data to a terminal. Temperature and humidity sensors are generally used. This data is important for maintaining an optimal growing environment for agricultural crops.

[1000] The terminal receives data from the sensors at regular intervals and performs preprocessing. Specifically, it removes noise from the data, corrects outliers, and converts the data format into a suitable format for the database. The preprocessed data is then sent to a central server.

[1001] The server stores the received data in a database and checks the consistency of the data required at each processing step. Furthermore, the server also analyzes the bee activity data. Specifically, the server passes the bee activity data collected by the user using the bee monitoring device to the analysis module, which determines whether the activity is high or low. A generative AI model is used for this analysis, allowing for fast and accurate judgments.

[1002] Based on the analysis results and environmental data, the server determines whether pollination assistance is necessary. If it is determined that pollination assistance is necessary, instructions are sent to the robot via the terminal. Instructions include, for example, "Move to the location of the crop and begin pollination assistance."

[1003] The robot moves to a designated location and assists in artificial pollination. Typically, the robot's arm touches the flowers of the crops to promote pollination.

[1004] Finally, the server centralizes the collected environmental data and bee activity data, and periodically generates reports containing monthly data analysis results and a history of pollination support activities, which are provided to farmers and related organizations.

[1005] Specific examples

[1006] Example 1:

[1007] The sensor measures the temperature at 22 degrees and the humidity at 55% and collects the data.

[1008] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "100 flights per day."

[1009] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that the bees are active.

[1010] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[1011] Example 2:

[1012] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[1013] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "10 flights per day."

[1014] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that there is little bee activity.

[1015] The server determines that pollination assistance is needed, and the terminal sends instructions to the robot.

[1016] The robot moves to the location of the crop and assists with pollination. The robot touches the flowers of the crop.

[1017] The server generates a corresponding report and sends it to the user.

[1018] The system uses AI and robots to address the declining honeybee population and provide pollination assistance to maintain crop productivity.

[1019] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1020] Step 1:

[1021] The sensor collects environmental data. Specifically, the sensor measures temperature and humidity in real time, obtaining data such as "temperature 22 degrees, humidity 55%." This collected data is sent to the device as environmental data.

[1022] Input: Environmental data (temperature, humidity)

[1023] Output: Environmental data sent to the device

[1024] Step 2:

[1025] The device receives environmental data from the sensor and performs preprocessing. Specifically, the device removes noise and corrects outliers, and converts the data format into a format suitable for the database. For example, a measured value of "temperature 22 degrees, humidity 55%" is preprocessed and converted into a database format.

[1026] Input: Environmental data from sensors

[1027] Output: Preprocessed environmental data (database format)

[1028] Step 3:

[1029] The device sends the preprocessed environmental data to the central server. Specifically, the preprocessed data is packaged into packets and sent to a specific IP address on the central server. For example, data such as "temperature 22 degrees, humidity 55%" is sent as a packet.

[1030] Input: Preprocessed environmental data

[1031] Output: Data packets sent to the central server

[1032] Step 4:

[1033] The environmental data received by the server is stored in a database. Specifically, a database management system (e.g., MySQL) is used to check for data duplication and consistency, and if there are no problems, the data is stored. For example, data such as "temperature 22 degrees, humidity 55%" is stored in the database.

[1034] Input: Data packet sent to the central server

[1035] Output: Environmental data stored in a database

[1036] Step 5:

[1037] The user sets up a bee monitoring device and collects bee activity data. For example, a sensor device installed in a hive collects data such as "100 bee flights per day." This activity data is sent to a terminal.

[1038] Input: Bee activity data (number of flights)

[1039] Output: Bee activity data sent to the terminal

[1040] Step 6:

[1041] The terminal receives the bee activity data and passes it to the preprocessing and analysis module. Specifically, the data is cleansed and standardized into a format that is easy to analyze. For example, "100 flights" is converted into data for analysis.

[1042] Input: Bee activity data sent to the terminal

[1043] Output: Preprocessed data passed to the analysis module

[1044] Step 7:

[1045] The server analyzes the bee activity data and determines whether the activity is high or low. Specifically, it uses a generative AI model (e.g., TensorFlow) to analyze it. For example, if the number of bee flights is low, it is determined that there is "low bee activity."

[1046] Input: Preprocessed data passed to the analysis module

[1047] Output: Activity evaluation result (high / low)

[1048] Step 8:

[1049] The server determines whether pollination support is necessary based on the analysis results and environmental data. Specifically, it uses an AI algorithm to comprehensively evaluate each piece of data. For example, if it determines that "the temperature is 20 degrees, the humidity is 50%, and there is little bee activity," pollination support is necessary.

[1050] Input: Activity evaluation results, environmental data

[1051] Output: Pollination support decision (necessary / unnecessary)

[1052] Step 9:

[1053] The terminal sends instructions for pollination assistance to the robot. For example, it sends a packet containing instructions to the robot to "move to the location of the crop and start pollination assistance."

[1054] Input: Pollination support judgment

[1055] Output: Instruction packet to the robot

[1056] Step 10:

[1057] The robot moves to a designated location and assists in artificial pollination. Specifically, the robot's arm touches the flowers of the crops to promote pollination. For example, it performs a "flower touching action."

[1058] Input: Instruction packet to the robot

[1059] Output: Record of assisted pollination performed

[1060] Step 11:

[1061] The server centrally manages the collected environmental data and bee activity data and stores it in a database. Furthermore, the server periodically analyzes the data and generates reports to provide to farmers and related organizations. For example, it creates a report based on this month's bee activity and environmental data.

[1062] Input: Environmental data, bee activity data

[1063] Output: Report

[1064] (Application example 1)

[1065] 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."

[1066] Conventional factory production lines lacked systems that could monitor environmental data and equipment activity data in real time and respond quickly. As a result, responses to environmental changes and equipment abnormalities were often delayed, resulting in reduced productivity and quality issues. Furthermore, data collection and analysis were not carried out efficiently, and report creation took a long time.

[1067] 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.

[1068] In this invention, the server includes a means for collecting environmental data with sensors, a means for analyzing activity data of production equipment, a means for automatically adjusting the production line, and a means for storing the data in the central server, analyzing it, and generating reports, thereby enabling real-time monitoring and rapid adjustment of the production line, as well as efficient data management and rapid report generation.

[1069] A "sensor" is a device that measures environmental data in real time and transmits that data to a terminal.

[1070] "Environmental data" refers to physical data such as temperature, humidity, vibration, and noise inside the factory.

[1071] "Production equipment activity data" refers to data relating to the operating status and operational status of production line equipment.

[1072] "Analysis" is the process of analyzing collected data and determining whether activity is normal or abnormal.

[1073] "Central Server" refers to a central computer server that stores collected environmental data and production equipment activity data, analyzes them, and generates reports.

[1074] A "report" is a document provided to interested parties based on collected and analyzed data.

[1075] "Adjustment" refers to the task of a robot changing the settings and arrangement of equipment on a production line.

[1076] "Real time" refers to information being processed almost simultaneously.

[1077] The present invention relates to a system for collecting and analyzing environmental data and activity data of production equipment within a factory, and making necessary adjustments based on the data. Details for specifically implementing the present invention will be described below.

[1078] 1. Environmental data collection

[1079] The server uses sensors to collect environmental data within the factory in real time. The sensors periodically measure temperature, humidity, vibration, and noise and send the data to terminals. The terminals preprocess the received data and send it to the central server. The central server stores the received data in a database and checks the consistency of the data required at each processing step.

[1080] 2. Analysis of production equipment activity data

[1081] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to the terminal. The terminal passes the received equipment activity data to the analysis module and sends the analysis results to the central server. The server analyzes the equipment activity data and determines whether the activity is normal or abnormal. Based on the analysis results, it determines whether adjustments are necessary.

[1082] 3. Implement production line adjustments

[1083] The server determines that adjustments to the production line are necessary based on the analysis results and environmental data. If adjustments are determined to be necessary, the terminal sends instructions to the robot. The robot moves to the specified location and automatically adjusts the production line or handles any problems. After the robot completes the adjustment work, it sends the data to the terminal, which then stores it on the central server.

[1084] 4. Data Management and Report Generation

[1085] The server centrally manages the collected environmental data and production equipment activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to production managers and related organizations.

[1086] Hardware and software used

[1087] Sensors: Temperature sensor, humidity sensor, vibration sensor, microphone

[1088] Terminal: IoT device for data collection and transmission

[1089] Central server: A computer server that runs the database and analysis modules

[1090] Robot: Autonomous robot for production line adjustment

[1091] Software: Database management systems, analysis software, robot control systems

[1092] Specific examples

[1093] Example 1:

[1094] The sensors measure temperature at 25 degrees, humidity at 60%, and vibration level at 2.0 and collect data.

[1095] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[1096] The server analyzes the device activity and determines that the activity is normal.

[1097] The server determines that no adjustment is necessary and saves the data. A report on the operation status of the production line is generated.

[1098] Example 2:

[1099] The sensors measure a temperature of 30 degrees, humidity of 50%, and vibration level of 3.5 and collect data.

[1100] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[1101] The server analyzes the device activity and determines that the activity is abnormal.

[1102] The server determines that adjustments are necessary, and the terminal sends instructions to the robot.

[1103] The robot moves to its working position, adjusts the production line, stores the data and generates a corresponding report.

[1104] Prompt Sentence Examples

[1105] Prompt: Generate a procedure for adjusting the production line if the temperature measured by sensors in the factory is 30 degrees and the vibration level is 3.5.

[1106] Output procedure: Analyze data from sensors and send it to a central server. The server detects anomalies. The robot moves to the specified position and initiates adjustments. The data is saved and a report is generated.

[1107] The system of the present invention aims to improve the efficiency of management and adjustment of production lines within a factory, thereby improving productivity and optimizing quality control.

[1108] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1109] Step 1:

[1110] The server collects environmental data from sensors. The sensors periodically measure the temperature, humidity, vibration, and noise levels in the factory and send the data to terminals. The terminals then format the received data and send it to the central server. The input is the environmental data sent by the sensors, and the output is the formatted data. Specifically, the temperature sensor measures 25 degrees, and the data is sent by the terminal to the central server.

[1111] Step 2:

[1112] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to a terminal. The terminal passes the received equipment data to an analysis module, which then sends the analysis results to a central server. The input is the equipment activity data, and the output is the analyzed status data. Specifically, the monitoring device confirms that the equipment is operating normally, and the data is sent to the server.

[1113] Step 3:

[1114] The server analyzes the device's activity data and determines whether the activity is normal or abnormal. The input is the received activity data, and the output is the analysis result. Specific calculations detect abnormalities by comparing it with normal activity patterns. For example, if the vibration level is abnormally high, it is determined to be abnormal.

[1115] Step 4:

[1116] The server determines whether adjustments to the production line are necessary based on the analysis results and environmental data. If it determines that adjustments are necessary, the terminal sends instructions to the robot. The input is the analysis results and environmental data, and the output is instructions to the robot. Specifically, if it determines that the temperature and vibration levels are abnormally high, an adjustment instruction is sent to the robot.

[1117] Step 5:

[1118] The robot receives instructions, moves to the designated location, and automatically adjusts the production line and handles problems. The input is the adjustment instruction from the server, and the output is the improved activity data after the adjustment. A specific example of the robot's operation is readjusting equipment to suppress abnormal vibrations.

[1119] Step 6:

[1120] The server receives the adjusted data sent from the robot and stores it in a database. It also periodically analyzes the data and generates a report. The input is the adjusted data and the output is the report. The specific operation is to generate a report and provide it to the production manager.

[1121] This enables real-time monitoring of production lines within factories and rapid adjustments, resulting in improved productivity and quality.

[1122] 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.

[1123] The present invention combines a system that collects environmental data, analyzes bee activity data, and artificially supports pollination with an emotion engine that recognizes the user's emotions. Details for implementing the present invention in a specific form are described below.

[1124] System Overview

[1125] The system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect data related to the crop's growing environment (temperature and humidity), analyze the bee activity data, and the robot assists with artificial pollination as needed. Furthermore, the emotion engine analyzes the user's emotional state and optimizes the system's operation based on this.

[1126] 1. Environmental data collection

[1127] The sensors measure the crop growth environment (temperature and humidity) in real time, periodically collecting this data and sending it to the terminal.

[1128] The devices preprocess the environmental data received from the sensors and send it to a central server, which receives it, stores it in a database, and checks the integrity of the data.

[1129] 2. Analysis of honeybee activity

[1130] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal, which receives the data and passes it to the analysis module.

[1131] The server analyzes the bee activity data and determines whether the activity is high or low, and based on the analysis results, decides whether pollination assistance is needed.

[1132] 3. Implementing pollination support

[1133] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions to the robot to assist pollination. The robot then moves to the specified location and performs artificial pollination assistance.

[1134] 4. Incorporating an Emotional Engine

[1135] To monitor the user's emotional state, the user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and transmits the data to the device. The device receives the emotion data and analyzes it using an emotion engine.

[1136] The server optimizes the overall operation of the system based on the user's emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will adjust the timing of pollination assistance to reduce the user's burden.

[1137] 5. Data Management and Report Generation

[1138] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[1139] Specific examples

[1140] Example 1:

[1141] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[1142] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1143] Based on the data sent from the device, the server determines that bee activity is high and therefore does not provide pollination support.

[1144] Since the emotion engine has determined that the user is not feeling stressed, the default processing continues.

[1145] Example 2:

[1146] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[1147] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1148] The server analyzes bee activity and determines that there is little bee activity.

[1149] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[1150] The robot moves based on instructions and assists with pollination.

[1151] Because the emotion engine determines that the user is stressed, the system expedites report generation and provides immediate feedback to the user.

[1152] In this way, the system uses AI, robots, and an emotion engine to assist with pollination to maintain crop productivity, and also optimizes the operation of the entire system by taking into account the user's emotional state.

[1153] The processing flow will be explained below.

[1154] Step 1:

[1155] Sensors measure and collect environmental data (temperature and humidity).

[1156] Step 2:

[1157] The terminal receives environmental data from sensors at regular intervals, preprocesses the data, and sends it to a central server.

[1158] Step 3:

[1159] The server receives the environmental data sent from the device, stores it in a database, and checks the integrity of the data.

[1160] Step 4:

[1161] A user uses a bee monitoring device to collect bee activity data and transmit it to a terminal.

[1162] Step 5:

[1163] The terminal receives the bee activity data sent by the user and passes it to the analysis module.

[1164] Step 6:

[1165] The server analyzes the bee activity data and runs an algorithm to determine whether activity is high or low.

[1166] Step 7:

[1167] The server determines whether pollination assistance is necessary based on the analysis results, and generates instructions for pollination assistance if necessary.

[1168] Step 8:

[1169] If the server determines that pollination assistance is necessary, it sends instructions to the terminal and prepares instructions for the robot to move and for pollination assistance.

[1170] Step 9:

[1171] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[1172] Step 10:

[1173] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[1174] Step 11:

[1175] A user uses an emotion recognition device to collect his / her own emotion data and transmits it to a terminal.

[1176] Step 12:

[1177] The terminal receives the user's emotion data and passes the data to the emotion engine.

[1178] Step 13:

[1179] The server uses an emotion engine to analyze the user's emotional data and adjusts the operation of the entire system based on the results.

[1180] Step 14:

[1181] The server stores all data (environmental data, bee activity data, emotion data) in a database and manages them centrally.

[1182] Step 15:

[1183] The server periodically analyzes the data and generates reports based on the results.

[1184] Step 16:

[1185] The server generates a report, which is then sent to the user, which then reviews it. The report includes environmental data, bee activity, pollination support status, and emotional state analysis.

[1186] Example 2

[1187] 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."

[1188] The present invention aims to provide a method for optimizing the operation of a system that uses environmental data and bee activity data to support the pollination of agricultural crops, taking into account the emotional state of the user, thereby improving the efficiency of pollination support and reducing the stress and burden on the user.

[1189] 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.

[1190] In this invention, the server includes means for collecting environmental data with sensors, means for analyzing bee activity data, means for artificially supporting pollination, means for storing and analyzing data in a central server, means for collecting and analyzing emotion data using an emotion engine that recognizes user emotions, and means for optimizing system operation based on the analyzed emotion data. This enables comprehensive pollination support that takes into account not only conventional environmental data and bee activity data, but also user emotion data.

[1191] A "sensor" is a device that measures a physical condition, such as temperature or humidity, to collect environmental data.

[1192] "Bee activity data" is data that records the movements of bees, such as their comings and goings and flight activities.

[1193] "Artificial pollination assistance" is a method of artificially moving pollen using devices such as robots.

[1194] "Central Server" is a computer system that stores and analyzes collected data.

[1195] An "emotion engine" is software that recognizes a user's emotions and analyzes that emotional data.

[1196] "Emotional Data" is data about a user's emotional state that is collected and analyzed by the emotion engine.

[1197] "Optimizing system operation" refers to optimally adjusting the performance of various system functions based on collected data.

[1198] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination as needed, and further combines it with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present invention.

[1199] System configuration

[1200] This system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect temperature and humidity data related to the crop growth environment. The terminals preprocess the data received from the sensors and send it to the central server. The central server receives, stores, and analyzes the data. It also issues instructions to the robots that assist with pollination. The emotion engine analyzes the user's emotional state and optimizes the system's operation.

[1201] Environmental data collection

[1202] Sensors measure the crops' environmental data (temperature and humidity) in real time. These sensors periodically collect data and send it to the terminal. For example, the sensor collects data of 22 degrees Celsius and 55% humidity every 5 minutes and sends it to the terminal.

[1203] The device preprocesses the environmental data received from the sensor and sends it to the central server. As part of the preprocessing, the device organizes the data and checks for any abnormal values. The organized data is then sent to the central server. The server receives the data, stores it in a database, and checks the integrity of the data.

[1204] Analysis of honeybee activity

[1205] A user sets up a monitoring device to collect bee activity data, and the collected data is sent to a terminal. For example, the user sends data recording the bees' entry and exit and flight activity to the terminal.

[1206] The terminal passes the received bee activity data to an analysis module, which then sends it to a central server. The central server analyzes the bee activity data and determines whether activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination assistance is necessary.

[1207] Pollination support

[1208] The central server determines whether pollination assistance is necessary based on the analysis results. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination.

[1209] Incorporating an emotion engine

[1210] The user uses an emotion recognition device, which collects emotional data from facial expressions and voice and sends it to the terminal. The terminal receives the emotional data and passes it to the emotion engine. The emotion engine determines the user's current emotional state and sends the data to the central server. The central server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it may change the timing of pollination assistance.

[1211] Specific examples

[1212] As a concrete example, a sensor collects data on a temperature of 20 degrees and humidity of 50%, and a user collects data on bee activity using a monitoring device and sends this data to a terminal. The terminal then sends this data to a server, which determines that "bee activity is low." The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot to move and pollinate. The robot moves to the instructed location and assists with pollination. Furthermore, if the emotion engine determines that the user is feeling stressed, the system will quickly generate a report and provide the user with immediate feedback.

[1213] Prompt Sentence Examples

[1214] "What steps can we take to optimize pollination support based on user sentiment and environmental data?"

[1215] In this way, the system uses AI, robots, and an emotion engine to maintain crop productivity and optimize the operation of the entire system by taking into account the user's emotional state.

[1216] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1217] Step 1:

[1218] Sensors collect environmental data

[1219] The sensors measure the temperature and humidity around the crops in real time. For example, the sensors collect data every five minutes showing a temperature of 22°C and humidity of 55%.

[1220] Input: Ambient environmental conditions (temperature, humidity)

[1221] Output: Measured temperature and humidity data

[1222] Step 2:

[1223] The device preprocesses the data and sends it to a central server

[1224] The device processes the environmental data received from the sensors, checks for abnormal values, aggregates this data, and sends it to a central server.

[1225] Input: Temperature and humidity data from sensors

[1226] Output: Preprocessed environmental data (temperature and humidity)

[1227] Step 3:

[1228] The server stores the data and checks its integrity

[1229] The server receives the preprocessed environmental data and stores it in a database. After storing it, it checks the integrity of the data and verifies that there are no abnormalities.

[1230] Input: Preprocessed environmental data

[1231] Output: Environmental data stored in a database

[1232] Step 4:

[1233] The user collects bee activity data and sends it to the device.

[1234] Users collect bee activity data using a monitoring device, which records the bees' entry and exit and flight activity and transmits the data to a terminal.

[1235] Input: Bee activity (entering and exiting, flight activity)

[1236] Output: Collected bee activity data

[1237] Step 5:

[1238] The device passes the bee activity data to the analysis module and sends it to the server.

[1239] The terminal passes the bee activity data received from the user to the analysis module, which then transmits it to the central server.

[1240] Input: Collected bee activity data

[1241] Output: Bee activity data passed to the analysis module

[1242] Step 6:

[1243] The server analyzes bee activity data and determines whether pollination assistance is needed.

[1244] The server's analysis module analyzes the bee activity data and determines whether the activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination support is necessary.

[1245] Input: Bee activity data passed to the analysis module

[1246] Output: Analysis result (determining whether activity is high or low)

[1247] Step 7:

[1248] The server determines the need for pollination assistance and sends instructions to the device.

[1249] The server then reconfirms whether pollination assistance is necessary based on the analysis results and environmental data, and if so, sends instructions to the terminal for the robot to move and assist with pollination.

[1250] Input: Analysis results and environmental data

[1251] Output: Instructions to terminal (movement and pollination assistance)

[1252] Step 8:

[1253] The terminal sends instructions to the robot to carry out pollination assistance.

[1254] The terminal sends instructions to the robot to assist with pollination, and the robot moves to the specified location and performs artificial pollination.

[1255] Input: Instructions from the server (movement and pollination assistance)

[1256] Output: Robot behavior (movement and pollination assistance)

[1257] Step 9:

[1258] A user uses an emotion recognition device to collect emotion data.

[1259] The user uses an emotion recognition device, which collects emotion data from facial expressions and voice and transmits it to the terminal.

[1260] Input: User's facial expressions and voice

[1261] Output: Collected emotion data

[1262] Step 10:

[1263] The device receives emotion data and analyzes it with an emotion engine.

[1264] The device receives the emotion data and passes it to the emotion engine in real time to analyze the user's emotional state.

[1265] Input: Collected emotion data

[1266] Output: Analyzed user emotion data

[1267] Step 11:

[1268] The server optimizes system operation based on emotion data

[1269] The server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it changes the timing of pollination assistance.

[1270] Input: Parsed user emotion data

[1271] Output: Optimized system behavior

[1272] Step 12:

[1273] The server manages all the data and generates reports

[1274] The server centrally manages environmental data, bee activity data, and emotion data, and periodically analyzes the data to generate reports.

[1275] Input: Environmental data, bee activity data, emotion data

[1276] Output: Data analysis results and generated reports

[1277] (Application example 2)

[1278] 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."

[1279] Conventional agricultural support systems and factory robot systems were unable to perform optimal operations by taking into account environmental data and the emotional state of workers. As a result, it was difficult to maintain efficient production activities, and there were problems with productivity decline, particularly due to delayed responses to environmental changes and worker emotional stress. Furthermore, as pollination support relies on the activity of honeybees, artificial pollination support was sometimes not performed appropriately.

[1280] 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.

[1281] In this invention, the server includes a means for collecting environmental data using sensors, a means for analyzing bee activity data, a means for artificially supporting pollination, a means for analyzing the user's emotional state, a means for storing and analyzing data in a central server, and a means for optimizing system operation based on the worker's emotional data. This enables real-time monitoring and analysis of the production environment, enabling optimization of pollination support and production activities. Furthermore, by taking the worker's emotional state into consideration, it is possible to improve work efficiency and ensure safety.

[1282] A "sensor" is a device for collecting environmental data, and is responsible for obtaining information such as temperature and humidity in real time.

[1283] "Bee activity data" is data used to measure and analyze the activity status of bees, and is information used to determine the need for pollination support.

[1284] "Means of artificially assisted pollination" refers to a method of artificially pollinating plants using robots or other devices instead of the natural pollination performed by bees.

[1285] "Means for analyzing the user's emotional state" refers to technology for recognizing and analyzing the user's emotions from facial expressions, voice, etc., and refers to devices or software that optimize the system's operation based on emotional data.

[1286] "Means for storing and analyzing data on a central server" refers to a means for centrally managing and analyzing collected environmental data, bee activity data, and emotional data.

[1287] "Worker emotional data" is data related to the emotional state of a worker, and is information that can be used to analyze stress, fatigue, etc., and to optimize production activities.

[1288] "Means for optimizing system operation" refers to the means for determining the current situation based on collected data and maintaining the operation of the entire system in an optimal state.

[1289] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination, as well as a system that analyzes the emotional state of workers and optimizes production activities. Specific embodiments of the present invention are described in detail below.

[1290] System Overview

[1291] The system consists of sensors, terminals, robots, an emotion engine, and a central server. The sensors collect environmental data (temperature and humidity) within the factory and analyze the activity data of the bees. Furthermore, the system monitors and analyzes the user's emotional state, optimizing the operation of the entire system based on this data.

[1292] 1. Environmental data collection

[1293] Sensors measure the temperature and humidity in the factory in real time. The sensors periodically collect this data and send it to the terminal. The terminal preprocesses the environmental data received from the sensors and sends it to the central server. The server receives it, stores it in a database, and checks the integrity of the data.

[1294] 2. Analysis of honeybee activity

[1295] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal. The terminal receives this data and passes it to the analysis module. The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination support is necessary.

[1296] 3. Implementing pollination support

[1297] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination assistance.

[1298] 4. Incorporating an Emotional Engine

[1299] The user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and sends the data to the terminal. The terminal receives the emotion data and analyzes it using an emotion engine. The server optimizes the operation of the entire system based on the user's emotion data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will pause the production line, adjust the environment, and offer the user a break.

[1300] 5. Data Management and Report Generation

[1301] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[1302] Specific examples

[1303] 1. The sensor measures a temperature of 22°C and humidity of 55%, and collects the data. The user uses a monitoring device to collect bee activity data and sends it to the device. Based on the data sent from the device, the server determines that the bees are active, so pollination assistance is not provided. The emotion engine determines that the user is not feeling stressed, so the default processing continues.

[1304] 2. The sensor measures a temperature of 20 degrees and humidity of 50% and collects the data. The user collects bee activity data using a monitoring device and sends it to the terminal. The server analyzes the bee activity and determines that there is little bee activity. The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot. The robot moves based on the instructions and assists with pollination. Because the emotion engine determines that the user is feeling stressed, the system quickly generates a report and provides the user with immediate feedback.

[1305] Prompt Sentence Examples

[1306] "We want to build a system that uses sensors and emotion recognition devices installed in factories to collect data on the status of the production line and the emotions of workers, and optimize factory operations in real time. We envision a system that continues normal processes only when the temperature is above 20 degrees and the humidity is below 60%, and otherwise adjusts the environment and takes necessary action on workers based on the emotional data."

[1307] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1308] Step 1:

[1309] Sensors collect environmental data within the factory and send it to a terminal.

[1310] Specifically, the sensors measure the temperature and humidity inside the factory in real time and send the data to the terminal.

[1311] Input: Environmental conditions in the factory (temperature, humidity).

[1312] Output: Environmental data sent to the device.

[1313] Step 2:

[1314] The terminal preprocesses the received environmental data and sends it to a central server.

[1315] Specifically, the terminal checks the integrity of the data received from the sensor, pre-processes it, converts it into an appropriate format, and sends it to the central server.

[1316] Input: Environmental data sent from sensors.

[1317] Output: Preprocessed environmental data sent to a central server.

[1318] Step 3:

[1319] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1320] Specifically, the user operates a device to acquire bee activity data, collects the data, and transmits it to a terminal.

[1321] Input: Bee activity data.

[1322] Output: Bee activity data sent to the device.

[1323] Step 4:

[1324] The terminal passes the bee activity data to an analysis module, which then sends the analysis results to a central server.

[1325] Specifically, the terminal inputs the bee activity data into an analysis module and sends the results to a central server.

[1326] Input: Bee activity data.

[1327] Output: Analysis results sent to a central server.

[1328] Step 5:

[1329] The server determines the need for pollination support based on the analysis results and environmental data.

[1330] Specifically, the server compares the analysis results with environmental data and determines whether pollination assistance is needed if bee activity is declining.

[1331] Input: Analysis results, environmental data.

[1332] Output: Determination of the need for pollination support.

[1333] Step 6:

[1334] If the server determines that pollination assistance is necessary, it sends instructions to the robot to move and to assist with pollination via the terminal.

[1335] Specifically, the server confirms the need for pollination assistance and then sends specific instructions to the robot via the terminal, including its destination and how to provide pollination assistance.

[1336] Input: Results of pollination support need determination.

[1337] Output: Movement instructions and pollination assistance instructions to the robot.

[1338] Step 7:

[1339] The robot assists with pollination based on instructions.

[1340] Specifically, the robot moves to a designated location and assists with artificial pollination in its assigned area.

[1341] Input: Instructions to the robot.

[1342] Output: Assisted pollination performed.

[1343] Step 8:

[1344] A user uses an emotion recognition device to collect emotion data.

[1345] Specifically, the user uses an emotion recognition device to obtain emotion data from facial expressions, voice, etc., and sends it to the terminal.

[1346] Input: The user's emotional state.

[1347] Output: Emotion data sent to the device.

[1348] Step 9:

[1349] The device analyzes the emotional data using an emotion engine and sends the results to a central server.

[1350] Specifically, the device analyzes the user's emotional data using an emotion engine and sends the results to a central server.

[1351] Input: User emotion data.

[1352] Output: Analysis results sent to a central server.

[1353] Step 10:

[1354] The server optimizes the operation of the entire system based on emotional data.

[1355] Specifically, the server optimizes the system's operation by, for example, adjusting the production line or suggesting breaks for workers based on the results of analyzing the emotional data.

[1356] Input: Parsed emotion data.

[1357] Output: Optimized system operating instructions.

[1358] 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.

[1359] 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.

[1360] 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.

[1361] [Fourth embodiment]

[1362] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1363] 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.

[1364] 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).

[1365] 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.

[1366] 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.

[1367] 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).

[1368] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1369] 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.

[1370] 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.

[1371] 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.

[1372] 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.

[1373] 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.

[1374] 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."

[1375] The present invention is a system in which an agricultural robot utilizes artificial intelligence to cooperate with honeybees and assist in the pollination of agricultural crops. Details for implementing the present invention in a specific embodiment are described below.

[1376] System Overview

[1377] The system uses sensors to collect data related to the crop's growing environment (temperature and humidity), analyzes data on the bees' activity, and, if necessary, a robot assists in artificial pollination. All data is stored on a central server for analysis and report generation.

[1378] 1. Environmental data collection

[1379] Sensors measure the growing environment of crops in real time. The sensors periodically measure temperature and humidity and transmit the data to a terminal. The terminal preprocesses the received data and sends it to a central server.

[1380] The terminal receives data from the sensors at regular intervals and forwards it to a central server, which stores the received data in a database and checks the consistency of the data required for each processing step.

[1381] 2. Analysis of honeybee activity

[1382] The user sets up the bee monitoring device and collects bee activity data. The collected data is sent to a terminal. The terminal passes the received bee activity data to an analysis module, and the analysis results are sent to a server.

[1383] The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination assistance is necessary.

[1384] 3. Implementing pollination support

[1385] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends instructions to the robot. The robot moves to the specified location and performs artificial pollination assistance.

[1386] 4. Data Management and Report Generation

[1387] The server centralizes the collected environmental data and bee activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to farmers and related organizations.

[1388] Specific examples

[1389] Example 1:

[1390] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[1391] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1392] The server analyzes the bee activity and determines that "bee activity is high."

[1393] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[1394] Example 2:

[1395] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[1396] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1397] The server analyzes bee activity and determines that there is little bee activity.

[1398] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[1399] The robot moves to the location of the crop and assists with pollination, storing the data and generating a corresponding report.

[1400] In this way, this system uses AI and robots to address the problem of declining honeybee populations and provide pollination support to maintain crop productivity.

[1401] The processing flow will be explained below.

[1402] Step 1:

[1403] Sensors measure and collect environmental data (temperature and humidity).

[1404] Step 2:

[1405] The device receives environmental data from the sensors at regular intervals and preprocesses the data, which is then prepared for transmission to the server.

[1406] Step 3:

[1407] The server receives the environmental data sent from the device, stores the data in a database, and verifies that the data is consistent.

[1408] Step 4:

[1409] The user sets up the bee monitoring device, collects bee activity data, and transmits it to the terminal.

[1410] Step 5:

[1411] The terminal receives the bee activity data sent by the user and passes the data to the analysis module.

[1412] Step 6:

[1413] The server analyzes the bee activity data and applies an algorithm to determine whether bee activity is high or low.

[1414] Step 7:

[1415] The server determines whether pollination assistance is necessary based on the analysis results. If activity is low, it determines that pollination assistance is necessary.

[1416] Step 8:

[1417] If it is determined that pollination assistance is needed, the server sends instructions to the robot via the terminal.

[1418] Step 9:

[1419] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[1420] Step 10:

[1421] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[1422] Step 11:

[1423] The server collects and organizes all data, analyzes it periodically, and generates reports based on the analysis results.

[1424] Step 12:

[1425] The server sends the generated report to the user, who then checks the report and considers how to proceed.

[1426] Example 1

[1427] 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."

[1428] In modern agriculture, the decline in honeybee populations has become a major problem, resulting in insufficient pollination of crops. Furthermore, there is a lack of systems that can monitor environmental conditions and honeybee activity in real time and provide pollination support based on that information. A system that can address these issues and maintain crop productivity is needed.

[1429] 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.

[1430] In this invention, the server includes means for collecting environmental data with sensors and measuring temperature and humidity, means for collecting bee activity data and sending it to a terminal, means for preprocessing the collected data on the terminal and sending it to a central server, means for analyzing the received data on the central server and determining whether bee activity is high or low, means for determining the need for pollination assistance based on the analysis results on the central server, means for sending instructions to the robot via the terminal when the central server determines that pollination assistance is necessary, means for the robot to move to a specified location and perform artificial pollination assistance, and means for storing the data collected and analyzed by the central server in a database and generating a report. This makes it possible to efficiently and automatically provide pollination assistance based on the bee activity status and environmental data.

[1431] A "sensor" is a device for collecting environmental data and measuring physical quantities such as temperature and humidity.

[1432] "Environmental data" refers to data related to the growing environment of agricultural crops, and mainly refers to temperature and humidity.

[1433] "Terminal" is a device that receives data collected from sensors and bee monitoring devices, pre-processes it and transmits it to a central server.

[1434] The "central server" is a computer system that centrally manages, analyzes, and stores various collected data.

[1435] A "bee monitoring device" is a device for collecting data on bee activity.

[1436] "Assisted pollination" is the process by which robots artificially pollinate crops.

[1437] A "database" is an information management system for systematically storing and managing collected data.

[1438] A "report" is a document that is periodically produced based on collected and analyzed data, and is intended to provide information to farmers and related institutions.

[1439] "Analysis" is the process of evaluating bee activity and environmental conditions based on collected data and determining the need for pollination support.

[1440] A "robot" is an automated mechanical device that moves to the location of crops based on instructions from a server and assists in artificial pollination.

[1441] "Preprocessing" refers to processes that remove noise from collected data and correct outliers to improve the accuracy and reliability of the data.

[1442] An "instruction" is an operation command sent from a central server to a robot via a terminal.

[1443] This invention is an agricultural robot system that efficiently supports the pollination of agricultural crops through the cooperative operation of sensors, terminals, a central server, and robots.

[1444] First, sensors monitor the growing environment of agricultural crops. Specifically, they measure temperature and humidity in real time and send the data to a terminal. Temperature and humidity sensors are generally used. This data is important for maintaining an optimal growing environment for agricultural crops.

[1445] The terminal receives data from the sensors at regular intervals and performs preprocessing. Specifically, it removes noise from the data, corrects outliers, and converts the data format into a suitable format for the database. The preprocessed data is then sent to a central server.

[1446] The server stores the received data in a database and checks the consistency of the data required at each processing step. Furthermore, the server also analyzes the bee activity data. Specifically, the server passes the bee activity data collected by the user using the bee monitoring device to the analysis module, which determines whether the activity is high or low. A generative AI model is used for this analysis, allowing for fast and accurate judgments.

[1447] Based on the analysis results and environmental data, the server determines whether pollination assistance is necessary. If it is determined that pollination assistance is necessary, instructions are sent to the robot via the terminal. Instructions include, for example, "Move to the location of the crop and begin pollination assistance."

[1448] The robot moves to a designated location and assists in artificial pollination. Typically, the robot's arm touches the flowers of the crops to promote pollination.

[1449] Finally, the server centralizes the collected environmental data and bee activity data, and periodically generates reports containing monthly data analysis results and a history of pollination support activities, which are provided to farmers and related organizations.

[1450] Specific examples

[1451] Example 1:

[1452] The sensor measures the temperature at 22 degrees and the humidity at 55% and collects the data.

[1453] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "100 flights per day."

[1454] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that the bees are active.

[1455] The server does not assist with pollination but stores the data. It generates reports on crop growth-related data.

[1456] Example 2:

[1457] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[1458] The user collects bee activity data using a monitoring device and sends it to a terminal, such as "10 flights per day."

[1459] The device preprocesses the received data and sends it to the server, which analyzes the bee activity and determines that there is little bee activity.

[1460] The server determines that pollination assistance is needed, and the terminal sends instructions to the robot.

[1461] The robot moves to the location of the crop and assists with pollination. The robot touches the flowers of the crop.

[1462] The server generates a corresponding report and sends it to the user.

[1463] The system uses AI and robots to address the declining honeybee population and provide pollination assistance to maintain crop productivity.

[1464] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1465] Step 1:

[1466] The sensor collects environmental data. Specifically, the sensor measures temperature and humidity in real time, obtaining data such as "temperature 22 degrees, humidity 55%." This collected data is sent to the device as environmental data.

[1467] Input: Environmental data (temperature, humidity)

[1468] Output: Environmental data sent to the device

[1469] Step 2:

[1470] The device receives environmental data from the sensor and performs preprocessing. Specifically, the device removes noise and corrects outliers, and converts the data format into a format suitable for the database. For example, a measured value of "temperature 22 degrees, humidity 55%" is preprocessed and converted into a database format.

[1471] Input: Environmental data from sensors

[1472] Output: Preprocessed environmental data (database format)

[1473] Step 3:

[1474] The device sends the preprocessed environmental data to the central server. Specifically, the preprocessed data is packaged into packets and sent to a specific IP address on the central server. For example, data such as "temperature 22 degrees, humidity 55%" is sent as a packet.

[1475] Input: Preprocessed environmental data

[1476] Output: Data packets sent to the central server

[1477] Step 4:

[1478] The environmental data received by the server is stored in a database. Specifically, a database management system (e.g., MySQL) is used to check for data duplication and consistency, and if there are no problems, the data is stored. For example, data such as "temperature 22 degrees, humidity 55%" is stored in the database.

[1479] Input: Data packet sent to the central server

[1480] Output: Environmental data stored in a database

[1481] Step 5:

[1482] The user sets up a bee monitoring device and collects bee activity data. For example, a sensor device installed in a hive collects data such as "100 bee flights per day." This activity data is sent to a terminal.

[1483] Input: Bee activity data (number of flights)

[1484] Output: Bee activity data sent to the terminal

[1485] Step 6:

[1486] The terminal receives the bee activity data and passes it to the preprocessing and analysis module. Specifically, the data is cleansed and standardized into a format that is easy to analyze. For example, "100 flights" is converted into data for analysis.

[1487] Input: Bee activity data sent to the terminal

[1488] Output: Preprocessed data passed to the analysis module

[1489] Step 7:

[1490] The server analyzes the bee activity data and determines whether the activity is high or low. Specifically, it uses a generative AI model (e.g., TensorFlow) to analyze it. For example, if the number of bee flights is low, it is determined that there is "low bee activity."

[1491] Input: Preprocessed data passed to the analysis module

[1492] Output: Activity evaluation result (high / low)

[1493] Step 8:

[1494] The server determines whether pollination support is necessary based on the analysis results and environmental data. Specifically, it uses an AI algorithm to comprehensively evaluate each piece of data. For example, if it determines that "the temperature is 20 degrees, the humidity is 50%, and there is little bee activity," pollination support is necessary.

[1495] Input: Activity evaluation results, environmental data

[1496] Output: Pollination support decision (necessary / unnecessary)

[1497] Step 9:

[1498] The terminal sends instructions for pollination assistance to the robot. For example, it sends a packet containing instructions to the robot to "move to the location of the crop and start pollination assistance."

[1499] Input: Pollination support judgment

[1500] Output: Instruction packet to the robot

[1501] Step 10:

[1502] The robot moves to a designated location and assists in artificial pollination. Specifically, the robot's arm touches the flowers of the crops to promote pollination. For example, it performs a "flower touching action."

[1503] Input: Instruction packet to the robot

[1504] Output: Record of assisted pollination performed

[1505] Step 11:

[1506] The server centrally manages the collected environmental data and bee activity data and stores it in a database. Furthermore, the server periodically analyzes the data and generates reports to provide to farmers and related organizations. For example, it creates a report based on this month's bee activity and environmental data.

[1507] Input: Environmental data, bee activity data

[1508] Output: Report

[1509] (Application example 1)

[1510] 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."

[1511] Conventional factory production lines lacked systems that could monitor environmental data and equipment activity data in real time and respond quickly. As a result, responses to environmental changes and equipment abnormalities were often delayed, resulting in reduced productivity and quality issues. Furthermore, data collection and analysis were not carried out efficiently, and report creation took a long time.

[1512] 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.

[1513] In this invention, the server includes a means for collecting environmental data with sensors, a means for analyzing activity data of production equipment, a means for automatically adjusting the production line, and a means for storing the data in the central server, analyzing it, and generating reports, thereby enabling real-time monitoring and rapid adjustment of the production line, as well as efficient data management and rapid report generation.

[1514] A "sensor" is a device that measures environmental data in real time and transmits that data to a terminal.

[1515] "Environmental data" refers to physical data such as temperature, humidity, vibration, and noise inside the factory.

[1516] "Production equipment activity data" refers to data relating to the operating status and operational status of production line equipment.

[1517] "Analysis" is the process of analyzing collected data and determining whether activity is normal or abnormal.

[1518] "Central Server" refers to a central computer server that stores collected environmental data and production equipment activity data, analyzes them, and generates reports.

[1519] A "report" is a document provided to interested parties based on collected and analyzed data.

[1520] "Adjustment" refers to the task of a robot changing the settings and arrangement of equipment on a production line.

[1521] "Real time" refers to information being processed almost simultaneously.

[1522] The present invention relates to a system for collecting and analyzing environmental data and activity data of production equipment within a factory, and making necessary adjustments based on the data. Details for specifically implementing the present invention will be described below.

[1523] 1. Environmental data collection

[1524] The server uses sensors to collect environmental data within the factory in real time. The sensors periodically measure temperature, humidity, vibration, and noise and send the data to terminals. The terminals preprocess the received data and send it to the central server. The central server stores the received data in a database and checks the consistency of the data required at each processing step.

[1525] 2. Analysis of production equipment activity data

[1526] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to the terminal. The terminal passes the received equipment activity data to the analysis module and sends the analysis results to the central server. The server analyzes the equipment activity data and determines whether the activity is normal or abnormal. Based on the analysis results, it determines whether adjustments are necessary.

[1527] 3. Implement production line adjustments

[1528] The server determines that adjustments to the production line are necessary based on the analysis results and environmental data. If adjustments are determined to be necessary, the terminal sends instructions to the robot. The robot moves to the specified location and automatically adjusts the production line or handles any problems. After the robot completes the adjustment work, it sends the data to the terminal, which then stores it on the central server.

[1529] 4. Data Management and Report Generation

[1530] The server centrally manages the collected environmental data and production equipment activity data, stores them in a database, and periodically analyzes the data to generate reports that can be provided to production managers and related organizations.

[1531] Hardware and software used

[1532] Sensors: Temperature sensor, humidity sensor, vibration sensor, microphone

[1533] Terminal: IoT device for data collection and transmission

[1534] Central server: A computer server that runs the database and analysis modules

[1535] Robot: Autonomous robot for production line adjustment

[1536] Software: Database management systems, analysis software, robot control systems

[1537] Specific examples

[1538] Example 1:

[1539] The sensors measure temperature at 25 degrees, humidity at 60%, and vibration level at 2.0 and collect data.

[1540] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[1541] The server analyzes the device activity and determines that the activity is normal.

[1542] The server determines that no adjustment is necessary and saves the data. A report on the operation status of the production line is generated.

[1543] Example 2:

[1544] The sensors measure a temperature of 30 degrees, humidity of 50%, and vibration level of 3.5 and collect data.

[1545] The user collects production line equipment data using a monitoring device and sends it to a terminal.

[1546] The server analyzes the device activity and determines that the activity is abnormal.

[1547] The server determines that adjustments are necessary, and the terminal sends instructions to the robot.

[1548] The robot moves to its working position, adjusts the production line, stores the data and generates a corresponding report.

[1549] Prompt Sentence Examples

[1550] Prompt: Generate a procedure for adjusting the production line if the temperature measured by sensors in the factory is 30 degrees and the vibration level is 3.5.

[1551] Output procedure: Analyze data from sensors and send it to a central server. The server detects anomalies. The robot moves to the specified position and initiates adjustments. The data is saved and a report is generated.

[1552] The system of the present invention aims to improve the efficiency of management and adjustment of production lines within a factory, thereby improving productivity and optimizing quality control.

[1553] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1554] Step 1:

[1555] The server collects environmental data from sensors. The sensors periodically measure the temperature, humidity, vibration, and noise levels in the factory and send the data to terminals. The terminals then format the received data and send it to the central server. The input is the environmental data sent by the sensors, and the output is the formatted data. Specifically, the temperature sensor measures 25 degrees, and the data is sent by the terminal to the central server.

[1556] Step 2:

[1557] The user sets up a production monitoring device to collect activity data from equipment on the production line. The collected data is sent to a terminal. The terminal passes the received equipment data to an analysis module, which then sends the analysis results to a central server. The input is the equipment activity data, and the output is the analyzed status data. Specifically, the monitoring device confirms that the equipment is operating normally, and the data is sent to the server.

[1558] Step 3:

[1559] The server analyzes the device's activity data and determines whether the activity is normal or abnormal. The input is the received activity data, and the output is the analysis result. Specific calculations detect abnormalities by comparing it with normal activity patterns. For example, if the vibration level is abnormally high, it is determined to be abnormal.

[1560] Step 4:

[1561] The server determines whether adjustments to the production line are necessary based on the analysis results and environmental data. If it determines that adjustments are necessary, the terminal sends instructions to the robot. The input is the analysis results and environmental data, and the output is instructions to the robot. Specifically, if it determines that the temperature and vibration levels are abnormally high, an adjustment instruction is sent to the robot.

[1562] Step 5:

[1563] The robot receives instructions, moves to the designated location, and automatically adjusts the production line and handles problems. The input is the adjustment instruction from the server, and the output is the improved activity data after the adjustment. A specific example of the robot's operation is readjusting equipment to suppress abnormal vibrations.

[1564] Step 6:

[1565] The server receives the adjusted data sent from the robot and stores it in a database. It also periodically analyzes the data and generates a report. The input is the adjusted data and the output is the report. The specific operation is to generate a report and provide it to the production manager.

[1566] This enables real-time monitoring of production lines within factories and rapid adjustments, resulting in improved productivity and quality.

[1567] 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.

[1568] The present invention combines a system that collects environmental data, analyzes bee activity data, and artificially supports pollination with an emotion engine that recognizes the user's emotions. Details for implementing the present invention in a specific form are described below.

[1569] System Overview

[1570] The system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect data related to the crop's growing environment (temperature and humidity), analyze the bee activity data, and the robot assists with artificial pollination as needed. Furthermore, the emotion engine analyzes the user's emotional state and optimizes the system's operation based on this.

[1571] 1. Environmental data collection

[1572] The sensors measure the crop growth environment (temperature and humidity) in real time, periodically collecting this data and sending it to the terminal.

[1573] The devices preprocess the environmental data received from the sensors and send it to a central server, which receives it, stores it in a database, and checks the integrity of the data.

[1574] 2. Analysis of honeybee activity

[1575] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal, which receives the data and passes it to the analysis module.

[1576] The server analyzes the bee activity data and determines whether the activity is high or low, and based on the analysis results, decides whether pollination assistance is needed.

[1577] 3. Implementing pollination support

[1578] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions to the robot to assist pollination. The robot then moves to the specified location and performs artificial pollination assistance.

[1579] 4. Incorporating an Emotional Engine

[1580] To monitor the user's emotional state, the user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and transmits the data to the device. The device receives the emotion data and analyzes it using an emotion engine.

[1581] The server optimizes the overall operation of the system based on the user's emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will adjust the timing of pollination assistance to reduce the user's burden.

[1582] 5. Data Management and Report Generation

[1583] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[1584] Specific examples

[1585] Example 1:

[1586] The sensors measure the temperature at 22 degrees and the humidity at 55% and collect the data.

[1587] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1588] Based on the data sent from the device, the server determines that bee activity is high and therefore does not provide pollination support.

[1589] Since the emotion engine has determined that the user is not feeling stressed, the default processing continues.

[1590] Example 2:

[1591] The sensor measures the temperature at 20 degrees and the humidity at 50% and collects the data.

[1592] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1593] The server analyzes bee activity and determines that there is little bee activity.

[1594] The server determines that pollination assistance is required, and the terminal sends instructions to the robot.

[1595] The robot moves based on instructions and assists with pollination.

[1596] Because the emotion engine determines that the user is stressed, the system expedites report generation and provides immediate feedback to the user.

[1597] In this way, the system uses AI, robots, and an emotion engine to assist with pollination to maintain crop productivity, and also optimizes the operation of the entire system by taking into account the user's emotional state.

[1598] The processing flow will be explained below.

[1599] Step 1:

[1600] Sensors measure and collect environmental data (temperature and humidity).

[1601] Step 2:

[1602] The terminal receives environmental data from sensors at regular intervals, preprocesses the data, and sends it to a central server.

[1603] Step 3:

[1604] The server receives the environmental data sent from the device, stores it in a database, and checks the integrity of the data.

[1605] Step 4:

[1606] A user uses a bee monitoring device to collect bee activity data and transmit it to a terminal.

[1607] Step 5:

[1608] The terminal receives the bee activity data sent by the user and passes it to the analysis module.

[1609] Step 6:

[1610] The server analyzes the bee activity data and runs an algorithm to determine whether activity is high or low.

[1611] Step 7:

[1612] The server determines whether pollination assistance is necessary based on the analysis results, and generates instructions for pollination assistance if necessary.

[1613] Step 8:

[1614] If the server determines that pollination assistance is necessary, it sends instructions to the terminal and prepares instructions for the robot to move and for pollination assistance.

[1615] Step 9:

[1616] The terminal receives instructions from the server and sends movement instructions and pollination assistance instructions to the robot.

[1617] Step 10:

[1618] Based on the instructions received, the robot moves to the specified location and performs artificial pollination assistance.

[1619] Step 11:

[1620] A user uses an emotion recognition device to collect his / her own emotion data and transmits it to a terminal.

[1621] Step 12:

[1622] The terminal receives the user's emotion data and passes the data to the emotion engine.

[1623] Step 13:

[1624] The server uses an emotion engine to analyze the user's emotional data and adjusts the operation of the entire system based on the results.

[1625] Step 14:

[1626] The server stores all data (environmental data, bee activity data, emotion data) in a database and manages them centrally.

[1627] Step 15:

[1628] The server periodically analyzes the data and generates reports based on the results.

[1629] Step 16:

[1630] The server generates a report, which is then sent to the user, which then reviews it. The report includes environmental data, bee activity, pollination support status, and emotional state analysis.

[1631] Example 2

[1632] 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."

[1633] The present invention aims to provide a method for optimizing the operation of a system that uses environmental data and bee activity data to support the pollination of agricultural crops, taking into account the emotional state of the user, thereby improving the efficiency of pollination support and reducing the stress and burden on the user.

[1634] 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.

[1635] In this invention, the server includes means for collecting environmental data with sensors, means for analyzing bee activity data, means for artificially supporting pollination, means for storing and analyzing data in a central server, means for collecting and analyzing emotion data using an emotion engine that recognizes user emotions, and means for optimizing system operation based on the analyzed emotion data. This enables comprehensive pollination support that takes into account not only conventional environmental data and bee activity data, but also user emotion data.

[1636] A "sensor" is a device that measures a physical condition, such as temperature or humidity, to collect environmental data.

[1637] "Bee activity data" is data that records the movements of bees, such as their comings and goings and flight activities.

[1638] "Artificial pollination assistance" is a method of artificially moving pollen using devices such as robots.

[1639] "Central Server" is a computer system that stores and analyzes collected data.

[1640] An "emotion engine" is software that recognizes a user's emotions and analyzes that emotional data.

[1641] "Emotional Data" is data about a user's emotional state that is collected and analyzed by the emotion engine.

[1642] "Optimizing system operation" refers to optimally adjusting the performance of various system functions based on collected data.

[1643] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination as needed, and further combines it with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present invention.

[1644] System configuration

[1645] This system consists of sensors, terminals, robots, a central server, and an emotion engine. The sensors collect temperature and humidity data related to the crop growth environment. The terminals preprocess the data received from the sensors and send it to the central server. The central server receives, stores, and analyzes the data. It also issues instructions to the robots that assist with pollination. The emotion engine analyzes the user's emotional state and optimizes the system's operation.

[1646] Environmental data collection

[1647] Sensors measure the crops' environmental data (temperature and humidity) in real time. These sensors periodically collect data and send it to the terminal. For example, the sensor collects data of 22 degrees Celsius and 55% humidity every 5 minutes and sends it to the terminal.

[1648] The device preprocesses the environmental data received from the sensor and sends it to the central server. As part of the preprocessing, the device organizes the data and checks for any abnormal values. The organized data is then sent to the central server. The server receives the data, stores it in a database, and checks the integrity of the data.

[1649] Analysis of honeybee activity

[1650] A user sets up a monitoring device to collect bee activity data, and the collected data is sent to a terminal. For example, the user sends data recording the bees' entry and exit and flight activity to the terminal.

[1651] The terminal passes the received bee activity data to an analysis module, which then sends it to a central server. The central server analyzes the bee activity data and determines whether activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination assistance is necessary.

[1652] Pollination support

[1653] The central server determines whether pollination assistance is necessary based on the analysis results. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination.

[1654] Incorporating an emotion engine

[1655] The user uses an emotion recognition device, which collects emotional data from facial expressions and voice and sends it to the terminal. The terminal receives the emotional data and passes it to the emotion engine. The emotion engine determines the user's current emotional state and sends the data to the central server. The central server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it may change the timing of pollination assistance.

[1656] Specific examples

[1657] As a concrete example, a sensor collects data on a temperature of 20 degrees and humidity of 50%, and a user collects data on bee activity using a monitoring device and sends this data to a terminal. The terminal then sends this data to a server, which determines that "bee activity is low." The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot to move and pollinate. The robot moves to the instructed location and assists with pollination. Furthermore, if the emotion engine determines that the user is feeling stressed, the system will quickly generate a report and provide the user with immediate feedback.

[1658] Prompt Sentence Examples

[1659] "What steps can we take to optimize pollination support based on user sentiment and environmental data?"

[1660] In this way, the system uses AI, robots, and an emotion engine to maintain crop productivity and optimize the operation of the entire system by taking into account the user's emotional state.

[1661] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1662] Step 1:

[1663] Sensors collect environmental data

[1664] The sensors measure the temperature and humidity around the crops in real time. For example, the sensors collect data every five minutes showing a temperature of 22°C and humidity of 55%.

[1665] Input: Ambient environmental conditions (temperature, humidity)

[1666] Output: Measured temperature and humidity data

[1667] Step 2:

[1668] The device preprocesses the data and sends it to a central server

[1669] The device processes the environmental data received from the sensors, checks for abnormal values, aggregates this data, and sends it to a central server.

[1670] Input: Temperature and humidity data from sensors

[1671] Output: Preprocessed environmental data (temperature and humidity)

[1672] Step 3:

[1673] The server stores the data and checks its integrity

[1674] The server receives the preprocessed environmental data and stores it in a database. After storing it, it checks the integrity of the data and verifies that there are no abnormalities.

[1675] Input: Preprocessed environmental data

[1676] Output: Environmental data stored in a database

[1677] Step 4:

[1678] The user collects bee activity data and sends it to the device.

[1679] Users collect bee activity data using a monitoring device, which records the bees' entry and exit and flight activity and transmits the data to a terminal.

[1680] Input: Bee activity (entering and exiting, flight activity)

[1681] Output: Collected bee activity data

[1682] Step 5:

[1683] The device passes the bee activity data to the analysis module and sends it to the server.

[1684] The terminal passes the bee activity data received from the user to the analysis module, which then transmits it to the central server.

[1685] Input: Collected bee activity data

[1686] Output: Bee activity data passed to the analysis module

[1687] Step 6:

[1688] The server analyzes bee activity data and determines whether pollination assistance is needed.

[1689] The server's analysis module analyzes the bee activity data and determines whether the activity is high or low. For example, if bee activity is 50% lower than normal, it determines that pollination support is necessary.

[1690] Input: Bee activity data passed to the analysis module

[1691] Output: Analysis result (determining whether activity is high or low)

[1692] Step 7:

[1693] The server determines the need for pollination assistance and sends instructions to the device.

[1694] The server then reconfirms whether pollination assistance is necessary based on the analysis results and environmental data, and if so, sends instructions to the terminal for the robot to move and assist with pollination.

[1695] Input: Analysis results and environmental data

[1696] Output: Instructions to terminal (movement and pollination assistance)

[1697] Step 8:

[1698] The terminal sends instructions to the robot to carry out pollination assistance.

[1699] The terminal sends instructions to the robot to assist with pollination, and the robot moves to the specified location and performs artificial pollination.

[1700] Input: Instructions from the server (movement and pollination assistance)

[1701] Output: Robot behavior (movement and pollination assistance)

[1702] Step 9:

[1703] A user uses an emotion recognition device to collect emotion data.

[1704] The user uses an emotion recognition device, which collects emotion data from facial expressions and voice and transmits it to the terminal.

[1705] Input: User's facial expressions and voice

[1706] Output: Collected emotion data

[1707] Step 10:

[1708] The device receives emotion data and analyzes it with an emotion engine.

[1709] The device receives the emotion data and passes it to the emotion engine in real time to analyze the user's emotional state.

[1710] Input: Collected emotion data

[1711] Output: Analyzed user emotion data

[1712] Step 11:

[1713] The server optimizes system operation based on emotion data

[1714] The server optimizes the system's operation based on the analyzed emotional data. For example, if the user is feeling stressed, it changes the timing of pollination assistance.

[1715] Input: Parsed user emotion data

[1716] Output: Optimized system behavior

[1717] Step 12:

[1718] The server manages all the data and generates reports

[1719] The server centrally manages environmental data, bee activity data, and emotion data, and periodically analyzes the data to generate reports.

[1720] Input: Environmental data, bee activity data, emotion data

[1721] Output: Data analysis results and generated reports

[1722] (Application example 2)

[1723] 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."

[1724] Conventional agricultural support systems and factory robot systems were unable to perform optimal operations by taking into account environmental data and the emotional state of workers. As a result, it was difficult to maintain efficient production activities, and there were problems with productivity decline, particularly due to delayed responses to environmental changes and worker emotional stress. Furthermore, as pollination support relies on the activity of honeybees, artificial pollination support was sometimes not performed appropriately.

[1725] 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.

[1726] In this invention, the server includes a means for collecting environmental data using sensors, a means for analyzing bee activity data, a means for artificially supporting pollination, a means for analyzing the user's emotional state, a means for storing and analyzing data in a central server, and a means for optimizing system operation based on the worker's emotional data. This enables real-time monitoring and analysis of the production environment, enabling optimization of pollination support and production activities. Furthermore, by taking the worker's emotional state into consideration, it is possible to improve work efficiency and ensure safety.

[1727] A "sensor" is a device for collecting environmental data, and is responsible for obtaining information such as temperature and humidity in real time.

[1728] "Bee activity data" is data used to measure and analyze the activity status of bees, and is information used to determine the need for pollination support.

[1729] "Means of artificially assisted pollination" refers to a method of artificially pollinating plants using robots or other devices instead of the natural pollination performed by bees.

[1730] "Means for analyzing the user's emotional state" refers to technology for recognizing and analyzing the user's emotions from facial expressions, voice, etc., and refers to devices or software that optimize the system's operation based on emotional data.

[1731] "Means for storing and analyzing data on a central server" refers to a means for centrally managing and analyzing collected environmental data, bee activity data, and emotional data.

[1732] "Worker emotional data" is data related to the emotional state of a worker, and is information that can be used to analyze stress, fatigue, etc., and to optimize production activities.

[1733] "Means for optimizing system operation" refers to the means for determining the current situation based on collected data and maintaining the operation of the entire system in an optimal state.

[1734] The present invention is a system that collects environmental data, analyzes bee activity data, and artificially supports pollination, as well as a system that analyzes the emotional state of workers and optimizes production activities. Specific embodiments of the present invention are described in detail below.

[1735] System Overview

[1736] The system consists of sensors, terminals, robots, an emotion engine, and a central server. The sensors collect environmental data (temperature and humidity) within the factory and analyze the activity data of the bees. Furthermore, the system monitors and analyzes the user's emotional state, optimizing the operation of the entire system based on this data.

[1737] 1. Environmental data collection

[1738] Sensors measure the temperature and humidity in the factory in real time. The sensors periodically collect this data and send it to the terminal. The terminal preprocesses the environmental data received from the sensors and sends it to the central server. The server receives it, stores it in a database, and checks the integrity of the data.

[1739] 2. Analysis of honeybee activity

[1740] The user sets up the bee monitoring device, collects and transmits bee activity data to the terminal. The terminal receives this data and passes it to the analysis module. The server analyzes the bee activity data and determines whether the activity is high or low. Based on the analysis results, it decides whether pollination support is necessary.

[1741] 3. Implementing pollination support

[1742] The server determines whether pollination assistance is necessary based on the analysis results and environmental data. If it is determined that pollination assistance is necessary, the terminal sends movement instructions and instructions for pollination assistance to the robot. The robot then moves to the specified location and performs artificial pollination assistance.

[1743] 4. Incorporating an Emotional Engine

[1744] The user uses an emotion recognition device. This device recognizes emotions from facial expressions and voice and sends the data to the terminal. The terminal receives the emotion data and analyzes it using an emotion engine. The server optimizes the operation of the entire system based on the user's emotion data analyzed by the emotion engine. For example, if the user is feeling stressed, the system will pause the production line, adjust the environment, and offer the user a break.

[1745] 5. Data Management and Report Generation

[1746] The server stores all data (environmental data, bee activity data, and user emotion data) in a database and manages them centrally. It periodically analyzes the data and generates reports.

[1747] Specific examples

[1748] 1. The sensor measures a temperature of 22°C and humidity of 55%, and collects the data. The user uses a monitoring device to collect bee activity data and sends it to the device. Based on the data sent from the device, the server determines that the bees are active, so pollination assistance is not provided. The emotion engine determines that the user is not feeling stressed, so the default processing continues.

[1749] 2. The sensor measures a temperature of 20 degrees and humidity of 50% and collects the data. The user collects bee activity data using a monitoring device and sends it to the terminal. The server analyzes the bee activity and determines that there is little bee activity. The server determines that pollination assistance is necessary, and the terminal sends instructions to the robot. The robot moves based on the instructions and assists with pollination. Because the emotion engine determines that the user is feeling stressed, the system quickly generates a report and provides the user with immediate feedback.

[1750] Prompt Sentence Examples

[1751] "We want to build a system that uses sensors and emotion recognition devices installed in factories to collect data on the status of the production line and the emotions of workers, and optimize factory operations in real time. We envision a system that continues normal processes only when the temperature is above 20 degrees and the humidity is below 60%, and otherwise adjusts the environment and takes necessary action on workers based on the emotional data."

[1752] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1753] Step 1:

[1754] Sensors collect environmental data within the factory and send it to a terminal.

[1755] Specifically, the sensors measure the temperature and humidity inside the factory in real time and send the data to the terminal.

[1756] Input: Environmental conditions in the factory (temperature, humidity).

[1757] Output: Environmental data sent to the device.

[1758] Step 2:

[1759] The terminal preprocesses the received environmental data and sends it to a central server.

[1760] Specifically, the terminal checks the integrity of the data received from the sensor, pre-processes it, converts it into an appropriate format, and sends it to the central server.

[1761] Input: Environmental data sent from sensors.

[1762] Output: Preprocessed environmental data sent to a central server.

[1763] Step 3:

[1764] The user collects bee activity data using a monitoring device and transmits it to a terminal.

[1765] Specifically, the user operates a device to acquire bee activity data, collects the data, and transmits it to a terminal.

[1766] Input: Bee activity data.

[1767] Output: Bee activity data sent to the device.

[1768] Step 4:

[1769] The terminal passes the bee activity data to an analysis module, which then sends the analysis results to a central server.

[1770] Specifically, the terminal inputs the bee activity data into an analysis module and sends the results to a central server.

[1771] Input: Bee activity data.

[1772] Output: Analysis results sent to a central server.

[1773] Step 5:

[1774] The server determines the need for pollination support based on the analysis results and environmental data.

[1775] Specifically, the server compares the analysis results with environmental data and determines whether pollination assistance is needed if bee activity is declining.

[1776] Input: Analysis results, environmental data.

[1777] Output: Determination of the need for pollination support.

[1778] Step 6:

[1779] If the server determines that pollination assistance is necessary, it sends instructions to the robot to move and to assist with pollination via the terminal.

[1780] Specifically, the server confirms the need for pollination assistance and then sends specific instructions to the robot via the terminal, including its destination and how to provide pollination assistance.

[1781] Input: Results of pollination support need determination.

[1782] Output: Movement instructions and pollination assistance instructions to the robot.

[1783] Step 7:

[1784] The robot assists with pollination based on instructions.

[1785] Specifically, the robot moves to a designated location and assists with artificial pollination in its assigned area.

[1786] Input: Instructions to the robot.

[1787] Output: Assisted pollination performed.

[1788] Step 8:

[1789] A user uses an emotion recognition device to collect emotion data.

[1790] Specifically, the user uses an emotion recognition device to obtain emotion data from facial expressions, voice, etc., and sends it to the terminal.

[1791] Input: The user's emotional state.

[1792] Output: Emotion data sent to the device.

[1793] Step 9:

[1794] The device analyzes the emotional data using an emotion engine and sends the results to a central server.

[1795] Specifically, the device analyzes the user's emotional data using an emotion engine and sends the results to a central server.

[1796] Input: User emotion data.

[1797] Output: Analysis results sent to a central server.

[1798] Step 10:

[1799] The server optimizes the operation of the entire system based on emotional data.

[1800] Specifically, the server optimizes the system's operation by, for example, adjusting the production line or suggesting breaks for workers based on the results of analyzing the emotional data.

[1801] Input: Parsed emotion data.

[1802] Output: Optimized system operating instructions.

[1803] 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.

[1804] 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.

[1805] 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 robot 414.

[1806] 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.

[1807] FIG. 9 illustrates 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 behaviors 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.

[1808] 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.

[1809] 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).

[1810] 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.

[1811] 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."

[1812] 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.

[1813] 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).

[1814] 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.

[1815] 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.

[1816] 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.

[1817] 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.

[1818] 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.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] 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.

[1823] 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.

[1824] The following is further disclosed regarding the above embodiment.

[1825] (Claim 1)

[1826] a means for collecting environmental data with sensors;

[1827] A means for analyzing bee activity data;

[1828] A means of artificially assisted pollination;

[1829] a means for storing and analyzing the data on a central server;

[1830] A system including:

[1831] (Claim 2)

[1832] 2. The system of claim 1, wherein the environmental data is temperature and humidity.

[1833] (Claim 3)

[1834] 10. The system of claim 1, further comprising means for determining whether bee activity is high or low and determining the need for pollination assistance.

[1835] (Claim 4)

[1836] 2. The system of claim 1, wherein the means for assisting pollination uses a robot.

[1837] (Claim 5)

[1838] 10. The system of claim 1, further comprising means for generating a report by analyzing the data.

[1839] "Example 1"

[1840] (Claim 1)

[1841] means for collecting environmental data with sensors to measure temperature and humidity;

[1842] A means for collecting and transmitting bee activity data to a terminal;

[1843] means for pre-processing the collected data on the terminal and transmitting it to a central server;

[1844] A central server analyzes the received data and determines whether bee activity is high or low.

[1845] A means for determining the need for pollination support based on the analysis results at the central server;

[1846] a means for transmitting instructions to the robot via a terminal when the central server determines that pollination assistance is necessary;

[1847] A means for the robot to move to a designated location and perform artificial pollination assistance;

[1848] a means for storing the collected and analyzed data in a database and generating reports on the central server;

[1849] A system including:

[1850] (Claim 2)

[1851] 2. The system of claim 1, wherein the environmental data is temperature and humidity.

[1852] (Claim 3)

[1853] 10. The system of claim 1, further comprising means for determining whether bee activity is high or low and determining the need for pollination assistance.

[1854] "Application Example 1"

[1855] (Claim 1)

[1856] a means for collecting environmental data with sensors;

[1857] a means for analyzing activity data of the production equipment;

[1858] means for automatically adjusting the production line;

[1859] means for storing the data on a central server and for generating analysis and reports;

[1860] A system including:

[1861] (Claim 2)

[1862] 2. The system of claim 1, wherein the environmental data is temperature, humidity, vibration, and noise.

[1863] (Claim 3)

[1864] 10. The system of claim 1, further comprising means for determining whether activity of production equipment is normal or abnormal and determining the need for adjustments to the production line.

[1865] "Example 2: Combining Emotion Engines"

[1866] (Claim 1)

[1867] a means for collecting environmental data with sensors;

[1868] A means for analyzing bee activity data;

[1869] A means of artificially assisted pollination;

[1870] a means for storing and analyzing the data on a central server;

[1871] means for collecting and analyzing emotion data using an emotion engine that recognizes user emotions;

[1872] means for optimizing the operation of the system based on the analyzed emotion data;

[1873] A system including:

[1874] (Claim 2)

[1875] 2. The system of claim 1, wherein the environmental data is temperature and humidity.

[1876] (Claim 3)

[1877] 10. The system of claim 1, further comprising means for determining whether bee activity is high or low and determining the need for pollination assistance.

[1878] "Application example 2 when combining emotion engines"

[1879] (Claim 1)

[1880] a means for collecting environmental data with sensors;

[1881] A means for analyzing bee activity data;

[1882] A means of artificially assisted pollination;

[1883] means for analyzing the emotional state of a user;

[1884] a means for storing and analyzing the data on a central server;

[1885] A means for optimizing the operation of the system based on the emotion data of the worker;

[1886] A system including:

[1887] (Claim 2)

[1888] 2. The system of claim 1, wherein the environmental data is temperature and humidity.

[1889] (Claim 3)

[1890] 10. The system of claim 1, further comprising means for determining whether bee activity is high or low and determining the need for pollination assistance. [Explanation of symbols]

[1891] 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 collecting environmental data with sensors; A means for analyzing bee activity data; A means of artificially assisted pollination; a means for storing and analyzing the data on a central server; A system including:

2. 2. The system of claim 1, wherein the environmental data is temperature and humidity.

3. 10. The system of claim 1, further comprising means for determining whether bee activity is high or low and determining the need for pollination assistance.

4. The system of claim 1 , wherein the means for assisting pollination uses a robot.

5. 10. The system of claim 1, further comprising means for generating a report by analyzing the data.

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