system

Abstract

We provide the system. [Solution] Means of obtaining weather information from external information providers, A means for analyzing weather information using artificial intelligence that automatically generates agricultural plans and formulating work schedules, A means of remotely controlling agricultural equipment to perform agricultural work according to a set schedule, A means of collecting data after work and recording it to use in improving future agricultural plans, A system that includes this.

Description

【Technical Field】 【0001】 The technology of this disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Unexamined Patent Application Publication No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Modern agriculture is facing serious problems such as a decrease in labor force due to aging, an increase in abandoned farmland, and intensified competition with foreign agricultural products. As a result, the decline of domestic agriculture is progressing, and particularly for new entrants, the image that agriculture is difficult has strongly taken root. To break such a situation and improve the efficiency of agriculture and lower the barriers to entry, new technological solutions that do not rely on conventional experiences are required. 【Means for Solving the Problems】 【0005】 This invention provides a system in which artificial intelligence automatically generates agricultural plans and formulates work schedules based on weather information obtained from external information providers. Furthermore, this system remotely controls agricultural equipment, enables agricultural work to be performed according to the formulated schedule, and collects post-work data to be used to improve future agricultural plans. In addition, it has a function to predict the harvest time and notify the user, and allows the user to check the status of agricultural equipment in real time via a communication terminal, thereby improving agricultural productivity and making it easy for new entrants to the field. 【0006】 "Weather information" refers to weather data obtained from external sources that is necessary for planning and executing agricultural activities, and includes temperature, probability of precipitation, humidity, wind speed, etc. 【0007】 An "external information provider" refers to an organization or service that provides various types of data, including weather information, and is usually accessible via the internet. 【0008】 "Artificial intelligence" is a technology that automatically generates agricultural plans and formulates efficient farming schedules through data analysis and learning. 【0009】 An "agricultural plan" refers to a schedule and set of tasks that are tailored to the optimal agricultural work based on the growth status of crops and weather conditions. 【0010】 A "schedule" is a planned execution plan for agricultural work, indicating the specific order and timing of tasks. 【0011】 "Agricultural machinery" refers to machines and devices used to carry out agricultural work efficiently, and includes spraying equipment and automated robots. 【0012】 "Remote control" refers to operating equipment or devices from a distance using communication technology. 【0013】 "Data collection" is the act of recording the results of agricultural work performed and gathering information for improving agricultural plans and for future reference. 【0014】 "Harvest time" refers to the period when crops have completed their growth and are most suitable for harvesting. 【0015】 "Notifications" refer to a means of disseminating information to inform users about work plans, important events, and other matters. 【0016】 "User" refers to an individual or group that uses an agricultural automation system to perform farm work. 【0017】 A "communication terminal" is a device used by a user to access a system and check or operate information, and includes smartphones, computers, and other similar devices. 【0018】 "Real-time monitoring" refers to the ability to check the status of agricultural equipment and crops at the present time, meaning that information is reflected and grasped immediately. [Brief explanation of the drawing] 【0019】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7]It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Mode for Carrying Out the Invention】 【0020】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0021】 First, the language used in the following description will be explained. 【0022】 In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit). 【0023】 In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor. 【0024】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0025】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0026】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0027】 [First Embodiment] 【0028】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0029】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0030】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0031】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0032】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0033】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0034】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0035】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0036】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0037】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0038】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0039】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0040】 This invention is a system for achieving automation and efficiency in agriculture, primarily through a process in which artificial intelligence formulates agricultural plans utilizing weather information and remotely controls agricultural equipment. This system consists of three elements: a server, a terminal, and a user, each with its own unique role. 【0041】 The server periodically obtains weather information from external information providers, and based on this, artificial intelligence generates optimal farming plans for each crop. These plans include cultivation schedules, timing for watering and pesticide application, and guidelines for work procedures. The farming plans are then sent from the server to terminals, making them easily accessible to users. 【0042】 The terminal is configured to allow users to remotely control agricultural equipment. This enables drones and autonomous machines to perform planned tasks on the farm based on instructions from the terminal. For example, they can spray the appropriate amount of water according to the weather or apply fertilizer according to the growth stage of the plants. In addition, the progress of the work and the status of the equipment are fed back to the user in real time. 【0043】 Users can interact with the system via their terminals and fine-tune plans and settings as needed. For example, users can change parameters within the system if the crop type changes or if special measures are required. Furthermore, important information such as harvest time is notified from the server, enabling planned harvesting operations. 【0044】 As a concrete example, consider the case of a large-scale tomato farm in a specific region. The server retrieves the 7-day weather forecast for that region, and AI analyzes the data to formulate an appropriate daily schedule. Based on this, the terminal issues instructions to the automated irrigation system and drones for pesticide spraying, maintaining optimal conditions for tomato growth. The user can monitor these operations in real time via their smartphone and make adjustments as needed. 【0045】 In this way, by compensating for the lack of agricultural expertise and supporting efficient and effective agricultural management, a system is created that reduces the burden on those entering agriculture. 【0046】 The following describes the processing flow. 【0047】 Step 1: 【0048】 The server obtains weather information from external information providers via APIs. The data includes information such as temperature, probability of precipitation, humidity, and wind speed, and this information is stored in a database. 【0049】 Step 2: 【0050】 The server instructs artificial intelligence to analyze the stored weather data. The AI ​​uses this information to create agricultural plans tailored to the type of crop and its growth stage. These plans include timing for watering and pesticide application, as well as necessary fertilization. 【0051】 Step 3: 【0052】 The server sends the generated farming plan to the user's terminal. The user can then view the work schedule and required materials on the terminal's display. 【0053】 Step 4: 【0054】 Users can initiate operation of agricultural equipment via a terminal. The terminal sends instructions to equipment such as agricultural drones and automated irrigation systems according to a set work schedule. This ensures that watering and pesticide application are carried out as planned. 【0055】 Step 5: 【0056】 The terminal collects work status data from agricultural equipment and reports it to the server in real time. Users can check this data and monitor the situation at any time through the terminal. 【0057】 Step 6: 【0058】 After the task is completed, the server analyzes the results and records them in a database to help improve future agricultural plans. This data will be used for future AI training. 【0059】 Step 7: 【0060】 The server uses AI to predict the optimal time for harvesting crops and notifies the user's device of the result. The user receives the notification and can begin harvesting at the appropriate time. 【0061】 (Example 1) 【0062】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0063】 In modern agriculture, it is crucial to formulate rapid and accurate work plans in response to changes in weather information. However, conventional methods make it difficult to create precise plans using weather data, and efficient management of agricultural equipment is also not easy. As a result, optimizing work is difficult, and there are limitations to improving productivity. This invention aims to solve these problems and realize automation and efficiency in agriculture. 【0064】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0065】 In this invention, the server includes means for acquiring and analyzing weather information from an external information provider; means for automatically generating an agricultural plan based on the weather information using a generation AI model and formulating work schedules for each crop; and means for remotely controlling agricultural equipment via a computing device and executing agricultural work based on the formulated schedule. This makes it possible to improve the accuracy and efficiency of agricultural work and to realize the automation of agricultural operations. 【0066】 "Weather information" refers to weather-related data obtained from external information providers, including information such as temperature, precipitation, and wind speed. 【0067】 A "generative AI model" is an algorithm that uses artificial intelligence technology to analyze input data and automatically generate plans and predictions based on specific objectives. 【0068】 A "computing device" is an electronic device used to process data and perform calculations, and generally refers to computers and servers. 【0069】 "Agricultural equipment" refers to devices that perform agricultural work automatically or semi-automatically, and includes irrigation systems, pesticide spraying drones, and autonomous agricultural machinery. 【0070】 A "communication device" is a device used for sending and receiving data, and mobile terminals such as smartphones and tablets fall into this category. 【0071】 This invention is a system for automating and streamlining agriculture by utilizing three elements: a server, a terminal, and a user. The server acquires weather data from external information providers using a Web API. The Python requests library is used for this acquisition, and the data is received in JSON format, from which necessary information is extracted using a Python script. 【0072】 The server then uses TENSORFLOW® as the generation AI model and generates an agricultural plan based on the analyzed weather data. The prompts used during generation are input to the AI ​​model in the form of, for example, "Suggest the optimal irrigation schedule for tomatoes this week," and a specific schedule is formulated based on this. 【0073】 The generated farming plan is sent from the server to the terminal via the cloud. Common mobile devices such as smartphones and tablets are used as the terminal. This terminal provides the farming plan to the user through an application built using React Native. Through this application, the user can view the plan sent from the server in real time and control agricultural equipment. 【0074】 Examples of agricultural equipment include irrigation systems, drones for spraying pesticides, and autonomous agricultural machinery. These devices operate based on instructions sent from a server and can be remotely controlled by the user from a terminal. In addition, the progress of the work and the operating status of the equipment are fed back in real time and displayed on the application on the terminal. 【0075】 This system enables precise agricultural management even without specialized agricultural knowledge, contributing to improved agricultural productivity and efficiency. 【0076】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0077】 Step 1: 【0078】 The server obtains weather information from external information providers. It issues API requests as input and receives weather data in JSON format as output. Specifically, it uses the Python requests library to make HTTP requests to obtain data such as temperature, precipitation, and wind speed for the target area. The obtained data is saved in preparation for analysis in the next step. 【0079】 Step 2: 【0080】 The server inputs acquired weather information into a generating AI model to create an agricultural plan. Weather data in JSON format is provided as input to a TensorFlow model, and specific work schedules for each crop are obtained as output. In this process, the prompt "Suggest the optimal irrigation schedule for tomatoes this week" is presented to the AI ​​model, and through analysis and calculation, the optimal action plan is formulated. 【0081】 Step 3: 【0082】 The server sends the generated farming plan to the terminal. The created work schedule is uploaded to cloud storage as input, and a push notification is sent to the terminal as output. Here, settings are configured to access the database via the cloud service and reflect the data on the terminal in real time. 【0083】 Step 4: 【0084】 The terminal assists users in operating agricultural equipment based on the received farming plan. It receives plan information sent from the server as input and displays an operation screen via a user interface as output. Specifically, a React Native mobile app provides instructions based on the plan, and the user remotely controls the equipment through this app. For example, it can activate an irrigation system at a specified time. 【0085】 Step 5: 【0086】 The terminal displays feedback on work progress and equipment status obtained from agricultural machinery. It receives status data from the equipment as input and outputs the situation to the user in an easy-to-understand manner. This allows the user to grasp the progress of work in real time and make adjustments to the plan as needed. 【0087】 (Application Example 1) 【0088】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0089】 Agricultural activities in urban areas require efficient and effective management in response to population growth and changes in land use. However, many urban residents lack specialized knowledge about agriculture, making it difficult to operate farms in a sustainable manner. Furthermore, planning must take into account weather uncertainties and limited resources. This complicates farmland management and places a significant burden on residents promoting agriculture in community gardens and shared farmlands. To address these challenges, there is a need to provide a system that allows urban residents to easily engage in agricultural activities and manage them efficiently. 【0090】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0091】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating an environmental schedule, and means for remotely controlling agricultural equipment and executing agricultural work based on the formulated schedule. This makes it possible for urban residents to efficiently manage and sustainably operate agricultural activities in community gardens and shared farmland, even without specialized knowledge. 【0092】 "Weather information" refers to data on atmospheric conditions such as precipitation, temperature, humidity, and wind speed, which are necessary for agricultural planning and environmental management. 【0093】 An "external information provider" is a third-party organization that provides weather information and other necessary data to the system. 【0094】 An "agricultural plan" is a schedule and procedure of work created to optimize the efficiency of crop production. 【0095】 "Artificial intelligence" is a program or system that analyzes large amounts of data, identifies patterns, and makes predictions. 【0096】 An "environmental schedule" is a plan set up to carry out tasks at the appropriate time in urban agriculture and environmental management activities. 【0097】 "Agricultural equipment" refers to all types of machinery and devices used to assist in agricultural work. 【0098】 "Remote control" refers to the means of operating or managing equipment from a physically distant location using communication technology. 【0099】 An "interface" is a means for a user to interact with a system, and includes an operation screen and control functions that enable the input and output of information. 【0100】 An "administrator" is a person or role responsible for operating and monitoring a system or environment, and for adjusting plans as needed. 【0101】 "Real-time" refers to processing and reactions occurring at nearly the same speed as actual time. 【0102】 The system for implementing this invention supports the efficient management of urban agriculture and community gardens. It primarily consists of three elements: a server, a terminal, and a user, and operates as follows: 【0103】 The server first periodically acquires weather information from external information providers. This weather information is analyzed using a generative AI model to generate optimal agricultural plans for each crop. For example, it adjusts water and fertilizer application schedules according to fluctuations in rainfall and temperature. This plan is then transmitted to terminals in the form of an environmental schedule. 【0104】 The terminal has the means to remotely control agricultural equipment in real time. Based on the plan received from the server, the terminal can appropriately execute the necessary agricultural tasks. This ensures that agricultural equipment operates according to schedule and performs the prescribed tasks. For example, it is possible to set up an irrigation system to operate automatically according to weather conditions. 【0105】 Users can interact with the system through an interface via their terminal. The system provides users with real-time information on the status of farmland, allowing them to adjust plans as needed. This improves the efficiency and sustainability of agricultural activities in urban areas. 【0106】 For example, if a community garden manager checks the weekend rain forecast and the system determines that it will be sunny on Saturday and Sunday, it can adjust the irrigation schedule and notify the manager via the device. 【0107】 An example of a prompt message is expected to be something like, "Generate an irrigation schedule to optimize tomato growth based on next week's weather." This is how the AI ​​model would be instructed. 【0108】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0109】 Step 1: 【0110】 The server periodically retrieves weather information from external information providers. The input is weather forecast data, and the output is weather information ready for analysis. This updates the weather database with the latest information. Specifically, the server automatically downloads weather information using a defined API. 【0111】 Step 2: 【0112】 The server uses a generative AI model to generate agricultural plans based on acquired weather information. The input is weather information, and the output is the optimal environmental schedule for each crop. In this process, weather data is analyzed, and based on the results, the AI ​​proposes irrigation and fertilization schedules. Specifically, the AI ​​model refers to past weather patterns and crop growth history to formulate an optimized plan. 【0113】 Step 3: 【0114】 The terminal receives the agricultural plan transmitted from the server. The input is the generated agricultural plan, and the output is the latest schedule information held by the terminal. Based on this information, the terminal updates the control program for agricultural equipment located remotely. Specifically, the terminal converts the received plan into operation commands for the equipment and prepares it for execution. 【0115】 Step 4: 【0116】 Users monitor the operating status of agricultural equipment via a terminal and adjust plans as needed. Inputs are equipment operating data and feedback from the system, while outputs are adjusted equipment control instructions. Users can change schedules and issue immediate instructions through the application interface. Specifically, users fine-tune plans using their smartphone's touchscreen. 【0117】 Step 5: 【0118】 The terminal controls agricultural equipment based on user or program instructions, performing tasks according to a predetermined plan. Input is adjusted schedule information, and output is a work completion report. Specifically, the terminal monitors the machine's status in real time and issues commands to perform the necessary agricultural tasks. 【0119】 Step 6: 【0120】 The server collects data after work is completed and records it for future planning improvements. The input is work completion report data, and the output is an updated system database. Specifically, the server compares work results with weather forecasts to improve the accuracy of plans. 【0121】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0122】 This invention provides an automated agricultural planning system that utilizes weather information, and also offers a system that recognizes user emotions to provide further adaptability. By incorporating an emotion engine, this system can adjust work plans and optimize notification content while considering the user's emotional state. The system consists of server, terminal, and user elements. 【0123】 The server uses weather information obtained from external information providers to generate agricultural plans using artificial intelligence. In addition, the server is equipped with an emotion engine that can analyze the user's stress and fatigue levels. The emotion engine determines the user's emotions based on user input and data obtained from terminal sensors, and suggests appropriate responses. Therefore, the pace and content of the planned farm work may be adjusted according to the user's emotions. 【0124】 The device receives the results of the emotion engine's analysis and adjusts the content of notifications to the user and the display on the interface. For example, if it determines that the user is tired, it can send a notification suggesting that the user take a break from work. The device also provides an interface for operating agricultural equipment and plays a role in remotely controlling the equipment according to a plan. 【0125】 Users interact with the system via their devices. An emotion engine suggests crops based on the user's interests and preferences, allowing them to choose crops that align with their emotions and proceed with farming while feeling a sense of fulfillment. This emotion-based suggestion has the effect of increasing motivation in farming. 【0126】 As a concrete example, consider a case where a user has just started growing corn. The server collects local weather forecasts, and the AI ​​creates an optimal growing plan. At that time, the emotion engine analyzes the user's current stress level, and if the user is in a high-stress state, it can suggest a work schedule with more leeway. Furthermore, if the user has shown interest in crops other than corn, it can also suggest alternative options accordingly. 【0127】 In this way, this system combines emotional understanding with agricultural efficiency to provide a more humane agricultural experience, aiming to reduce the burden on newcomers to agriculture while improving the quality of work. 【0128】 The following describes the processing flow. 【0129】 Step 1: 【0130】 The server obtains weather information for each region through APIs from external information providers. This includes temperature, humidity, wind speed, and probability of precipitation, and the obtained data is stored in an internal database. 【0131】 Step 2: 【0132】 The server sends stored weather information to artificial intelligence to generate an optimal farming plan for each crop. This plan includes water and pesticide application schedules based on soil conditions and growth stage. 【0133】 Step 3: 【0134】 The emotion engine installed on the server receives user emotion data from the terminal and analyzes stress and fatigue levels. Using this analysis, the agricultural work schedule is adjusted as needed. 【0135】 Step 4: 【0136】 The terminal notifies the user of the adjusted farming plan and sentiment analysis results received from the server. This may include progress reports tailored to the user's condition and recommendations for rest. 【0137】 Step 5: 【0138】 Users can remotely control agricultural equipment using the terminal interface and initiate work based on a created schedule. Equipment operation includes automated water and pesticide spraying, as well as machine operation at specified times. 【0139】 Step 6: 【0140】 The terminal transmits feedback from agricultural equipment and work completion data to the server in real time. This allows users to check work progress and re-evaluate the schedule as needed. 【0141】 Step 7: 【0142】 The server predicts the harvest time based on an analysis of crop growth and current conditions. As the harvest time approaches, a notification is sent to the user's device, and the optimal harvesting method is suggested. 【0143】 Step 8: 【0144】 The emotion engine analyzes emotional data obtained through work and uses it to improve long-term farming plans. It also generates suggestions for the user's next crops and tasks based on this data. 【0145】 (Example 2) 【0146】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0147】 In recent years, changes in weather conditions have a significant impact on work schedules in agriculture, necessitating efficient planning. However, conventional systems fail to adequately alleviate users' mental burden because they do not consider the emotional state of the users. Furthermore, there is room for improvement in the remote operation of agricultural equipment and the utilization of data after work. To address these challenges, there is a need to provide flexible and efficient agricultural planning that reflects the individual circumstances of each user. 【0148】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0149】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating a work schedule, and means for analyzing the user's emotional state and adjusting the work schedule based on the analysis. This makes it possible to formulate and execute flexible agricultural plans that respond to weather conditions and the user's emotional state. 【0150】 "Weather information" refers to data on environmental conditions such as local temperature, humidity, rainfall, and sunshine duration, obtained from external information providers. 【0151】 An "agricultural plan" is a series of plans for crop cultivation and work schedules that are automatically created by artificial intelligence based on weather information. 【0152】 "Artificial intelligence" is a technology used in computer systems to mimic human intellectual work, analyze data, and make optimal decisions. 【0153】 "Emotional state" is an indicator that shows the mental and emotional condition of the user, and is an assessment that includes stress levels and fatigue levels. 【0154】 "Agricultural machinery" refers to machines and devices used to carry out agricultural work, and this includes equipment such as tractors and irrigation systems. 【0155】 "Remote control" is a technology that allows you to operate machinery and equipment from a distance using electrical or electronic means, without physically touching the equipment. 【0156】 "Adjustment" is the process of modifying or optimizing pre-planned schedules and tasks, taking into account the emotional state of the users. 【0157】 A "notification" is information sent from the system to the user, and includes scheduled actions and urgent suggestions. 【0158】 "Analysis" is the process of extracting useful information from complex data and expressing it in an easily understandable format. 【0159】 Modes for carrying out the invention 【0160】 This invention is a system that automates agricultural planning using weather information and further proposes effective plans by incorporating the user's emotional state. The hardware used includes a server for managing information, user devices as terminals, and agricultural equipment requested by the user. The software integrates a generative AI model and an emotion analysis engine, enabling advanced data processing. 【0161】 The server obtains real-time weather information from external information providers via API and uses this information to develop appropriate agricultural plans using a generated AI model. Furthermore, the server is equipped with an emotion analysis engine that can analyze user emotion data based on information obtained from the terminal. Based on this analysis, the server flexibly adjusts the work schedule and plan content. 【0162】 The terminal functions as an interface between the user and the system, displaying information received from the server and sending notifications. Specifically, if the user is under high stress, it will send an alert such as "You should take a break." The terminal is also equipped with an interface for the user to remotely control agricultural equipment, enabling planned equipment operation. 【0163】 Users can interact with this system through their devices and receive crop selection suggestions based on sentiment analysis. This allows users to choose crops they are interested in and perform farming tasks with a sense of satisfaction. For example, when a user plans to cultivate corn, the server collects local weather data and uses AI to create a cultivation plan. In doing so, it suggests a schedule with buffer time if necessary, based on sentiment analysis. 【0164】 An example of a prompt message that could be input to the generating AI model is: "Based on the current weather information and the user's stress level, please suggest the optimal corn cultivation plan. Also, if the user is interested in sunflowers, please include a cultivation plan for those as well." 【0165】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0166】 Step 1: 【0167】 The server obtains weather information through APIs from external information providers. It sends region-based requests to the API as input and receives data on temperature, humidity, rainfall, and sunshine duration for the specified region as output. This data is then organized and stored for input into a generating AI model. 【0168】 Step 2: 【0169】 The server uses a generative AI model to analyze acquired weather information data and generate a farming plan. The input includes weather information and a prompt message such as "Generate optimal cultivation plan." The AI ​​model analyzes this information and generates a farming plan as output, which may include, for example, appropriate planting dates and irrigation schedules for corn. 【0170】 Step 3: 【0171】 The device acquires information about the user's emotional state, such as heart rate and input data. Inputs include wearable devices and direct input. The output is the integration of this information to obtain numerical data representing the user's stress level and fatigue level. 【0172】 Step 4: 【0173】 The server adjusts existing farming plans based on emotional state data acquired from the terminal. The inputs are the generated farming plan and the user's emotional state data. This data is processed by an emotional analysis engine, which then outputs an adjusted work schedule adapted to the user's emotions. 【0174】 Step 5: 【0175】 The terminal displays the adjusted work schedule sent from the server on its screen and notifies the user. Input includes the adjusted schedule and a template message to send to the user. Output generates specific notifications, such as "We recommend taking a break today," and presents them visually to the user. 【0176】 Step 6: 【0177】 Users can review proposed plans and crops via their terminal and approve, reject, or modify them. Input includes the displayed information and the user's decisions. Output is the data returned to the server as the selected work plan or modification request. 【0178】 Step 7: 【0179】 The server stores user selections and feedback in a database, which is then used for future analyses and plan generation. Inputs consist of user selections and work progress data. Based on this, the output is accumulated as data that contributes to improving the accuracy of agricultural planning and sentiment analysis. 【0180】 (Application Example 2) 【0181】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0182】 Agricultural activities in modern urban environments require efficient operations while considering the physical and mental state of workers. However, conventional systems struggle to take workers' emotions into account, resulting in inappropriate work plans and a decline in work efficiency and sustainability. Furthermore, a system capable of real-time situation monitoring and immediate response is needed. Therefore, a system is required that can adaptively adjust agricultural plans while considering workers' emotions. 【0183】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0184】 In this invention, the server includes means for acquiring weather information from an external organization and processing input data for recognizing emotional states; means for analyzing weather information and emotional data using artificial intelligence and an emotion engine to automatically generate agricultural plans and formulate work schedules; and means for remotely operating agricultural equipment to perform agricultural work based on the formulated schedule, as well as adjusting notifications and suggestions according to the user's emotional state. This makes it possible to formulate and execute agricultural plans that take into account the emotional state of the workers, thereby achieving both improved work efficiency and worker comfort. 【0185】 "Weather information" refers to data on the natural environment that affects agricultural planning, such as weather, temperature, precipitation, and wind speed. 【0186】 An "external organization" refers to an organization or system that provides weather information or other data. 【0187】 "Emotional state" refers to information that indicates the user's mental and psychological state, including stress and fatigue. 【0188】 "Input data" refers to data obtained from the user, including their emotional state, as well as environmental information. 【0189】 "Artificial intelligence" is a computer technology that uses machine learning and data analysis techniques to automatically generate agricultural plans. 【0190】 An "emotion engine" is a technology that analyzes a user's emotional state and provides appropriate work plans and notifications based on that analysis. 【0191】 "Agricultural equipment" refers to devices and machines used to support or automate agricultural work. 【0192】 "Remote control" refers to the means of controlling equipment or systems from a distance. 【0193】 A "schedule" refers to a plan or schedule that is carried out based on time and order. 【0194】 A "notification" is a message or alert used to inform a user of information. 【0195】 A "suggestion" is something that presents the optimal action or choice based on the user's state and environment. 【0196】 The system in this invention is built using a smartphone and a server. The server obtains weather information from an external organization via the internet. Next, the server uses an emotion engine to analyze the user's emotional state based on sensor data obtained from the smartphone's camera and microphone. This analysis can utilize open-source libraries such as OpenCV and Google's Cloud Speech-to-Text API for speech analysis. 【0197】 The server uses artificial intelligence technology to automatically generate farming plans that take into account weather information and the user's emotional state. Based on the generated plan, a work schedule is created, and this information is sent to the terminal. The terminal receives this information and notifies the user in a timely manner. These notifications may include suggestions for taking a break if the user is fatigued, or suggestions for carrying out the planned farming tasks. 【0198】 The terminal also has an interface for remotely operating agricultural equipment and performing tasks according to a plan. Furthermore, data obtained after agricultural activities are returned to the server and used for future planning. 【0199】 For example, when a user starts growing a new crop, the server can obtain local weather forecast data, perform sentiment analysis, and then propose a less stressful and more efficient work plan. 【0200】 Example of a prompt: 【0201】 "If a user is relaxing and tending to lavender with birdsong in the background, and is feeling a little tired, please suggest the optimal work plan." 【0202】 In this way, the server integrates and analyzes weather information and sentiment data to provide users with the optimal agricultural experience. 【0203】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0204】 Step 1: 【0205】 The server obtains weather information from external organizations via the internet. It sends requests based on region and time period as input, and receives data such as weather, temperature, and precipitation as output. This makes it possible to understand local climate conditions. 【0206】 Step 2: 【0207】 The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. It collects real-time audio and video data as input and generates data indicating the user's emotional state as output. This provides a basis for analyzing the user's stress and fatigue levels. 【0208】 Step 3: 【0209】 The server uses artificial intelligence to generate agricultural plans based on acquired weather information and sentiment data. It integrates the data obtained in steps 1 and 2 as input and performs data calculations. As output, it provides an optimal work schedule. This creates a plan that takes weather conditions and user sentiment into account. 【0210】 Step 4: 【0211】 The terminal receives the work schedule sent from the server and notifies the user. It receives the generated schedule as input and sends visual and auditory notifications to the user as output. These notifications are optimized for the user's emotional state and include suggestions to improve work efficiency. 【0212】 Step 5: 【0213】 The user operates a terminal to remotely control agricultural equipment. The system controls the equipment based on work schedules and terminal operation instructions as input, and performs agricultural tasks as output. This allows for efficient farming even from remote locations. 【0214】 Step 6: 【0215】 After completing a task, the terminal sends the data of the executed task to the server. It collects task execution result data as input and sends that data to the server as output. This allows for the accumulation of data that can be used to inform future agricultural planning. 【0216】 The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data. 【0217】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0218】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0219】 [Second Embodiment] 【0220】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0221】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0222】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0223】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0224】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0225】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0226】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0227】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0228】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0229】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0230】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0231】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0232】 This invention is a system for achieving automation and efficiency in agriculture, primarily through a process in which artificial intelligence formulates agricultural plans utilizing weather information and remotely controls agricultural equipment. This system consists of three elements: a server, a terminal, and a user, each with its own unique role. 【0233】 The server periodically obtains weather information from external information providers, and based on this, artificial intelligence generates optimal farming plans for each crop. These plans include cultivation schedules, timing for watering and pesticide application, and guidelines for work procedures. The farming plans are then sent from the server to terminals, making them easily accessible to users. 【0234】 The terminal is configured to allow users to remotely control agricultural equipment. This enables drones and autonomous machines to perform planned tasks on the farm based on instructions from the terminal. For example, they can spray the appropriate amount of water according to the weather or apply fertilizer according to the growth stage of the plants. In addition, the progress of the work and the status of the equipment are fed back to the user in real time. 【0235】 Users can interact with the system via their terminals and fine-tune plans and settings as needed. For example, users can change parameters within the system if the crop type changes or if special measures are required. Furthermore, important information such as harvest time is notified from the server, enabling planned harvesting operations. 【0236】 As a concrete example, consider the case of a large-scale tomato farm in a specific region. The server retrieves the 7-day weather forecast for that region, and AI analyzes the data to formulate an appropriate daily schedule. Based on this, the terminal issues instructions to the automated irrigation system and drones for pesticide spraying, maintaining optimal conditions for tomato growth. The user can monitor these operations in real time via their smartphone and make adjustments as needed. 【0237】 In this way, by compensating for the lack of agricultural expertise and supporting efficient and effective agricultural management, a system is created that reduces the burden on those entering agriculture. 【0238】 The following describes the processing flow. 【0239】 Step 1: 【0240】 The server obtains weather information from external information providers via APIs. The data includes information such as temperature, probability of precipitation, humidity, and wind speed, and this information is stored in a database. 【0241】 Step 2: 【0242】 The server instructs artificial intelligence to analyze the stored weather data. The AI ​​uses this information to create agricultural plans tailored to the type and growth stage of the crops. These plans include timing for watering and pesticide application, as well as necessary fertilization. 【0243】 Step 3: 【0244】 The server sends the generated farming plan to the user's terminal. The user can then view the work schedule and required materials on the terminal's display. 【0245】 Step 4: 【0246】 Users can initiate operation of agricultural equipment via a terminal. The terminal sends instructions to equipment such as agricultural drones and automated irrigation systems according to a set work schedule. This ensures that watering and pesticide application are carried out as planned. 【0247】 Step 5: 【0248】 The terminal collects work status data from agricultural equipment and reports it to the server in real time. Users can check this data and monitor the situation at any time through the terminal. 【0249】 Step 6: 【0250】 After the task is completed, the server analyzes the results and records them in a database to help improve future farming plans. This data will be used for future AI learning. 【0251】 Step 7: 【0252】 The server uses AI to predict the optimal time for harvesting crops and notifies the user's device of the result. The user receives the notification and can begin harvesting at the appropriate time. 【0253】 (Example 1) 【0254】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0255】 In modern agriculture, it is crucial to formulate rapid and accurate work plans in response to changes in weather information. However, conventional methods make it difficult to create precise plans using weather data, and efficient management of agricultural equipment is also not easy. As a result, optimizing work is difficult, and there are limitations to improving productivity. This invention aims to solve these problems and realize automation and efficiency in agriculture. 【0256】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0257】 In this invention, the server includes means for acquiring and analyzing weather information from an external information provider; means for automatically generating an agricultural plan based on the weather information using a generation AI model and formulating work schedules for each crop; and means for remotely controlling agricultural equipment via a computing device and executing agricultural work based on the formulated schedule. This makes it possible to improve the accuracy and efficiency of agricultural work and to realize the automation of agricultural operations. 【0258】 "Weather information" refers to weather-related data obtained from external information providers, including information such as temperature, precipitation, and wind speed. 【0259】 A "generative AI model" is an algorithm that uses artificial intelligence technology to analyze input data and automatically generate plans and predictions based on specific objectives. 【0260】 A "computing device" is an electronic device used to process data and perform calculations, and generally refers to computers and servers. 【0261】 "Agricultural equipment" refers to devices that perform agricultural work automatically or semi-automatically, and includes irrigation systems, pesticide spraying drones, and autonomous agricultural machinery. 【0262】 A "communication device" is a device used for sending and receiving data, and mobile terminals such as smartphones and tablets fall into this category. 【0263】 This invention is a system for automating and streamlining agriculture by utilizing three elements: a server, a terminal, and a user. The server acquires weather data from external information providers using a Web API. The Python requests library is used for this acquisition, and the data is received in JSON format, from which necessary information is extracted using a Python script. 【0264】 The server then uses TensorFlow as the generation AI model to generate an agricultural plan based on the analyzed weather data. The prompts used during generation are input to the AI ​​model in the form of, for example, "Suggest the optimal irrigation schedule for tomatoes this week," and a specific schedule is formulated based on this. 【0265】 The generated farming plan is sent from the server to the terminal via the cloud. Common mobile devices such as smartphones and tablets are used as the terminal. This terminal provides the farming plan to the user through an application built using React Native. Through this application, the user can view the plan sent from the server in real time and control agricultural equipment. 【0266】 Examples of agricultural equipment include irrigation systems, drones for spraying pesticides, and autonomous agricultural machinery. These devices operate based on instructions sent from a server and can be remotely controlled by the user from a terminal. In addition, the progress of the work and the operating status of the equipment are fed back in real time and displayed on the application on the terminal. 【0267】 This system enables precise agricultural management even without specialized agricultural knowledge, contributing to improved agricultural productivity and efficiency. 【0268】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0269】 Step 1: 【0270】 The server obtains weather information from external information providers. It issues API requests as input and receives weather data in JSON format as output. Specifically, it uses the Python requests library to make HTTP requests to obtain data such as temperature, precipitation, and wind speed for the target area. The obtained data is saved in preparation for analysis in the next step. 【0271】 Step 2: 【0272】 The server inputs acquired weather information into a generating AI model to create an agricultural plan. Weather data in JSON format is provided as input to a TensorFlow model, and specific work schedules for each crop are obtained as output. In this process, the prompt "Suggest the optimal irrigation schedule for tomatoes this week" is presented to the AI ​​model, and through analysis and calculation, the optimal action plan is formulated. 【0273】 Step 3: 【0274】 The server sends the generated farming plan to the terminal. The created work schedule is uploaded to cloud storage as input, and a push notification is sent to the terminal as output. Here, settings are configured to access the database via the cloud service and reflect the data on the terminal in real time. 【0275】 Step 4: 【0276】 The terminal assists users in operating agricultural equipment based on the received farming plan. It receives plan information sent from the server as input and displays an operation screen via a user interface as output. Specifically, a React Native mobile app provides instructions based on the plan, and the user remotely controls the equipment through this app. For example, it can activate an irrigation system at a specified time. 【0277】 Step 5: 【0278】 The terminal displays feedback on work progress and equipment status obtained from agricultural machinery. It receives status data from the equipment as input and outputs the situation to the user in an easy-to-understand manner. This allows the user to grasp the progress of work in real time and make adjustments to the plan as needed. 【0279】 (Application Example 1) 【0280】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0281】 Agricultural activities in urban areas require efficient and effective management in response to population growth and changes in land use. However, many urban residents lack specialized knowledge about agriculture, making it difficult to operate farms in a sustainable manner. Furthermore, planning must take into account weather uncertainties and limited resources. This complicates farmland management and places a significant burden on residents promoting agriculture in community gardens and shared farmlands. To address these challenges, there is a need to provide a system that allows urban residents to easily engage in agricultural activities and manage them efficiently. 【0282】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0283】 In this invention, the server includes means for obtaining meteorological information from an external information provider, means for analyzing the meteorological information using artificial intelligence that automatically generates an agricultural plan, means for formulating an environmental schedule, and means for remotely controlling agricultural devices to perform farming operations based on the formulated schedule. As a result, even if urban residents do not have specialized knowledge, they can efficiently manage agricultural activities in community gardens or shared farmlands and operate them in a sustainable manner. 【0284】 "Meteorological information" refers to data on the state of the atmosphere such as precipitation, temperature, humidity, wind speed, etc., which are necessary for agricultural planning and environmental management. 【0285】 "External information provider" refers to a third-party organization that provides meteorological information and other necessary data to the system. 【0286】 "Agricultural plan" refers to a work schedule and procedure created to optimize the production efficiency of agricultural crops. 【0287】 "Artificial intelligence" refers to a program or system for analyzing a large amount of data, identifying patterns, and making predictions. 【0288】 "Environmental schedule" refers to a plan set to execute work at an appropriate timing in urban agriculture and environmental management activities. 【0289】 "Agricultural devices" refers to all kinds of machinery and devices used to assist farming operations. 【0290】 "Remote control" refers to means for operating or managing a device from a physically distant location using communication technology. 【0291】 "Interface" refers to means for a user to interact with the system, including an operation screen and control functions for enabling input and output of information. 【0292】 An "administrator" is a person or role responsible for operating and monitoring a system or environment, and for adjusting plans as needed. 【0293】 "Real-time" refers to processing and reactions occurring at nearly the same speed as actual time. 【0294】 The system for implementing this invention supports the efficient management of urban agriculture and community gardens. It primarily consists of three elements: a server, a terminal, and a user, and operates as follows: 【0295】 The server first periodically acquires weather information from external information providers. This weather information is analyzed using a generative AI model to generate optimal agricultural plans for each crop. For example, it adjusts water and fertilizer application schedules according to fluctuations in rainfall and temperature. This plan is then transmitted to terminals in the form of an environmental schedule. 【0296】 The terminal has the means to remotely control agricultural equipment in real time. Based on the plan received from the server, the terminal can appropriately execute the necessary agricultural tasks. This ensures that agricultural equipment operates according to schedule and performs the prescribed tasks. For example, it is possible to set up an irrigation system to operate automatically according to weather conditions. 【0297】 Users can interact with the system through an interface via their terminal. The system provides users with real-time information on the status of farmland, allowing them to adjust plans as needed. This improves the efficiency and sustainability of agricultural activities in urban areas. 【0298】 For example, if a community garden manager checks the weekend rain forecast and the system determines that it will be sunny on Saturday and Sunday, it can adjust the irrigation schedule and notify the manager via the device. 【0299】 As an example of a prompt sentence, it is assumed that an instruction is given to the generative AI model in the form of "Please generate an irrigation schedule for optimizing tomato growth based on next week's weather." 【0300】 The flow of the specific process in Application Example 1 will be described using FIG. 12. 【0301】 Step 1: 【0302】 The server periodically obtains weather information from an external information provider. The input is weather forecast data, and the output is weather information in a state where analysis preparation is complete. As a result, the latest information is updated in the weather database. As a specific operation, the server automatically downloads weather information using a defined API. 【0303】 Step 2: 【0304】 The server uses the generative AI model to generate an agricultural plan based on the obtained weather information. The input is weather information, and the output is an optimal environmental schedule for each crop. In this process, the weather data is analyzed, and based on the results, the AI proposes irrigation and fertilization schedules. As a specific operation, the AI model refers to past weather patterns and crop growth histories to formulate an optimized plan. 【0305】 Step 3: 【0306】 The terminal receives the agricultural plan sent from the server. The input is the generated agricultural plan, and the output is the latest schedule information held by the terminal. Based on this information, the terminal updates the control program of the agricultural device located remotely. As a specific operation, the terminal converts the received plan into an operation instruction for the device and prepares for execution. 【0307】 Step 4: 【0308】 Users monitor the operating status of agricultural equipment via a terminal and adjust plans as needed. Inputs are equipment operating data and feedback from the system, while outputs are adjusted equipment control instructions. Users can change schedules and issue immediate instructions through the application interface. Specifically, users fine-tune plans using their smartphone's touchscreen. 【0309】 Step 5: 【0310】 The terminal controls agricultural equipment based on user or program instructions, performing tasks according to a predetermined plan. Input is adjusted schedule information, and output is a work completion report. Specifically, the terminal monitors the machine's status in real time and issues commands to perform the necessary agricultural tasks. 【0311】 Step 6: 【0312】 The server collects data after work is completed and records it for future planning improvements. The input is work completion report data, and the output is an updated system database. Specifically, the server compares work results with weather forecasts to improve the accuracy of plans. 【0313】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0314】 This invention provides an automated agricultural planning system that utilizes weather information, and also offers a system that recognizes user emotions to provide further adaptability. By incorporating an emotion engine, this system can adjust work plans and optimize notification content while considering the user's emotional state. The system consists of server, terminal, and user elements. 【0315】 The server uses weather information obtained from external information providers to generate agricultural plans using artificial intelligence. In addition, the server is equipped with an emotion engine that can analyze the user's stress and fatigue levels. The emotion engine determines the user's emotions based on user input and data obtained from terminal sensors, and suggests appropriate responses. Therefore, the pace and content of the planned farm work may be adjusted according to the user's emotions. 【0316】 The device receives the results of the emotion engine's analysis and adjusts the content of notifications to the user and the display on the interface. For example, if it determines that the user is tired, it can send a notification suggesting that the user take a break from work. The device also provides an interface for operating agricultural equipment and plays a role in remotely controlling the equipment according to a plan. 【0317】 Users interact with the system via their devices. An emotion engine suggests crops based on the user's interests and preferences, allowing them to choose crops that align with their emotions and proceed with farming while feeling a sense of fulfillment. This emotion-based suggestion has the effect of increasing motivation in farming. 【0318】 As a concrete example, consider a case where a user has just started growing corn. The server collects local weather forecasts, and the AI ​​creates an optimal growing plan. At that time, the emotion engine analyzes the user's current stress level, and if the user is in a high-stress state, it can suggest a work schedule with more leeway. Furthermore, if the user has shown interest in crops other than corn, it can also suggest alternative options accordingly. 【0319】 In this way, this system combines emotional understanding with agricultural efficiency to provide a more humane agricultural experience, aiming to reduce the burden on newcomers to agriculture while improving the quality of work. 【0320】 The following describes the processing flow. 【0321】 Step 1: 【0322】 The server obtains weather information for each region through APIs from external information providers. This includes temperature, humidity, wind speed, and probability of precipitation, and the obtained data is stored in an internal database. 【0323】 Step 2: 【0324】 The server sends stored weather information to artificial intelligence to generate an optimal farming plan for each crop. This plan includes water and pesticide application schedules based on soil conditions and growth stage. 【0325】 Step 3: 【0326】 The emotion engine installed on the server receives user emotion data from the terminal and analyzes stress and fatigue levels. Using this analysis, the agricultural work schedule is adjusted as needed. 【0327】 Step 4: 【0328】 The terminal notifies the user of the adjusted farming plan and sentiment analysis results received from the server. This may include progress reports tailored to the user's condition and recommendations for rest. 【0329】 Step 5: 【0330】 Users can remotely control agricultural equipment using the terminal interface and initiate work based on a created schedule. Equipment operation includes automated water and pesticide spraying, as well as machine operation at specified times. 【0331】 Step 6: 【0332】 The terminal transmits feedback from agricultural equipment and work completion data to the server in real time. This allows users to check work progress and re-evaluate the schedule as needed. 【0333】 Step 7: 【0334】 The server predicts the harvest time based on an analysis of crop growth and current conditions. As the harvest time approaches, a notification is sent to the user's device, and the optimal harvesting method is suggested. 【0335】 Step 8: 【0336】 The emotion engine analyzes emotional data obtained through work and uses it to improve long-term farming plans. It also generates suggestions for the user's next crops and tasks based on this data. 【0337】 (Example 2) 【0338】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0339】 In recent years, changes in weather conditions have a significant impact on work schedules in agriculture, necessitating efficient planning. However, conventional systems fail to adequately alleviate users' mental burden because they do not consider the emotional state of the users. Furthermore, there is room for improvement in the remote operation of agricultural equipment and the utilization of data after work. To address these challenges, there is a need to provide flexible and efficient agricultural planning that reflects the individual circumstances of each user. 【0340】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0341】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating a work schedule, and means for analyzing the user's emotional state and adjusting the work schedule based on the analysis. This makes it possible to formulate and execute flexible agricultural plans that respond to weather conditions and the user's emotional state. 【0342】 "Weather information" refers to data on environmental conditions such as local temperature, humidity, rainfall, and sunshine duration, obtained from external information providers. 【0343】 An "agricultural plan" is a series of plans for crop cultivation and work schedules that are automatically created by artificial intelligence based on weather information. 【0344】 "Artificial intelligence" is a technology used in computer systems to mimic human intellectual work, analyze data, and make optimal decisions. 【0345】 "Emotional state" is an indicator that shows the mental and emotional condition of the user, and is an assessment that includes stress levels and fatigue levels. 【0346】 "Agricultural machinery" refers to machines and devices used to carry out agricultural work, and this includes equipment such as tractors and irrigation systems. 【0347】 "Remote control" is a technology that allows you to operate machinery and equipment from a distance using electrical or electronic means, without physically touching the equipment. 【0348】 "Adjustment" is the process of modifying or optimizing pre-planned schedules and tasks, taking into account the emotional state of the users. 【0349】 A "notification" is information sent from the system to the user, and includes scheduled actions and urgent suggestions. 【0350】 "Analysis" is the process of extracting useful information from complex data and expressing it in an easily understandable format. 【0351】 Modes for carrying out the invention 【0352】 This invention is a system that automates agricultural planning using weather information and further proposes effective plans by incorporating the user's emotional state. The hardware used includes a server for managing information, user devices as terminals, and agricultural equipment requested by the user. The software integrates a generative AI model and an emotion analysis engine, enabling advanced data processing. 【0353】 The server obtains real-time weather information from external information providers via API and uses this information to develop appropriate agricultural plans using a generated AI model. Furthermore, the server is equipped with an emotion analysis engine that can analyze user emotion data based on information obtained from the terminal. Based on this analysis, the server flexibly adjusts the work schedule and plan content. 【0354】 The terminal functions as an interface between the user and the system, displaying information received from the server and sending notifications. Specifically, if the user is under high stress, it will send an alert such as "You should take a break." The terminal is also equipped with an interface for the user to remotely control agricultural equipment, enabling planned equipment operation. 【0355】 Users can interact with this system through their devices and receive crop selection suggestions based on sentiment analysis. This allows users to choose crops they are interested in and perform farming tasks with a sense of satisfaction. For example, when a user plans to cultivate corn, the server collects local weather data and uses AI to create a cultivation plan. In doing so, it suggests a schedule with buffer time if necessary, based on sentiment analysis. 【0356】 An example of a prompt message that could be input to the generating AI model is: "Based on the current weather information and the user's stress level, please suggest the optimal corn cultivation plan. Also, if the user is interested in sunflowers, please include a cultivation plan for those as well." 【0357】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0358】 Step 1: 【0359】 The server obtains weather information through APIs from external information providers. It sends region-based requests to the API as input and receives data on temperature, humidity, rainfall, and sunshine duration for the specified region as output. This data is then organized and stored for input into a generating AI model. 【0360】 Step 2: 【0361】 The server uses a generative AI model to analyze acquired weather information data and generate a farming plan. The input includes weather information and a prompt message such as "Generate optimal cultivation plan." The AI ​​model analyzes this information and generates a farming plan as output, which may include, for example, appropriate planting dates and irrigation schedules for corn. 【0362】 Step 3: 【0363】 The device acquires information about the user's emotional state, such as heart rate and input data. Inputs include wearable devices and direct input. The output is the integration of this information to obtain numerical data representing the user's stress level and fatigue level. 【0364】 Step 4: 【0365】 The server adjusts existing farming plans based on emotional state data acquired from the terminal. The inputs are the generated farming plan and the user's emotional state data. This data is processed by an emotional analysis engine, which then outputs an adjusted work schedule adapted to the user's emotions. 【0366】 Step 5: 【0367】 The terminal displays the adjusted work schedule sent from the server on its screen and notifies the user. Input includes the adjusted schedule and a template message to send to the user. Output generates specific notifications, such as "We recommend taking a break today," and presents them visually to the user. 【0368】 Step 6: 【0369】 Users can review proposed plans and crops via their terminal and approve, reject, or modify them. Input includes the displayed information and the user's decisions. Output is the data returned to the server as the selected work plan or modification request. 【0370】 Step 7: 【0371】 The server stores user selections and feedback in a database, which is then used for future analyses and plan generation. Inputs consist of user selections and work progress data. Based on this, the output is accumulated as data that contributes to improving the accuracy of agricultural planning and sentiment analysis. 【0372】 (Application Example 2) 【0373】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal". 【0374】 Agricultural activities in modern urban environments require efficient operations while considering the physical and mental state of workers. However, conventional systems struggle to take workers' emotions into account, resulting in inappropriate work plans and a decline in work efficiency and sustainability. Furthermore, a system capable of real-time situation monitoring and immediate response is needed. Therefore, a system is required that can adaptively adjust agricultural plans while considering workers' emotions. 【0375】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0376】 In this invention, the server includes means for acquiring weather information from an external organization and processing input data for recognizing emotional states; means for analyzing weather information and emotional data using artificial intelligence and an emotion engine to automatically generate agricultural plans and formulate work schedules; and means for remotely operating agricultural equipment to perform agricultural work based on the formulated schedule, as well as adjusting notifications and suggestions according to the user's emotional state. This makes it possible to formulate and execute agricultural plans that take into account the emotional state of the workers, thereby achieving both improved work efficiency and worker comfort. 【0377】 "Weather information" refers to data on the natural environment that affects agricultural planning, such as weather, temperature, precipitation, and wind speed. 【0378】 An "external organization" refers to an organization or system that provides weather information or other data. 【0379】 "Emotional state" refers to information that indicates the user's mental and psychological state, including stress and fatigue. 【0380】 "Input data" refers to data obtained from the user, including their emotional state, as well as environmental information. 【0381】 "Artificial intelligence" is a computer technology that uses machine learning and data analysis techniques to automatically generate agricultural plans. 【0382】 An "emotion engine" is a technology that analyzes a user's emotional state and provides appropriate work plans and notifications based on that analysis. 【0383】 "Agricultural equipment" refers to devices and machines used to support or automate agricultural work. 【0384】 "Remote control" refers to the means of controlling equipment or systems from a distance. 【0385】 A "schedule" refers to a plan or schedule that is carried out based on time and order. 【0386】 A "notification" is a message or alert used to inform a user of information. 【0387】 A "suggestion" is something that presents the optimal action or choice based on the user's state and environment. 【0388】 The system in this invention is built using a smartphone and a server. The server obtains weather information from an external organization via the internet. Next, the server uses an emotion engine to analyze the user's emotional state based on sensor data obtained from the smartphone's camera and microphone. This analysis can utilize open-source libraries such as OpenCV and the Google Cloud Speech-to-Text API for speech analysis. 【0389】 The server uses artificial intelligence technology to automatically generate farming plans that take into account weather information and the user's emotional state. Based on the generated plan, a work schedule is created, and this information is sent to the terminal. The terminal receives this information and notifies the user in a timely manner. These notifications may include suggestions for taking a break if the user is fatigued, or suggestions for carrying out the planned farming tasks. 【0390】 The terminal also has an interface for remotely operating agricultural equipment and performing tasks according to a plan. Furthermore, data obtained after agricultural activities are returned to the server and used for future planning. 【0391】 For example, when a user starts growing a new crop, the server can obtain local weather forecast data, perform sentiment analysis, and then propose a less stressful and more efficient work plan. 【0392】 Example of a prompt: 【0393】 "If a user is relaxing and tending to lavender with birdsong in the background, and is feeling a little tired, please suggest the optimal work plan." 【0394】 In this way, the server integrates and analyzes weather information and sentiment data to provide users with the optimal agricultural experience. 【0395】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0396】 Step 1: 【0397】 The server obtains weather information from external organizations via the internet. It sends requests based on region and time period as input, and receives data such as weather, temperature, and precipitation as output. This makes it possible to understand local climate conditions. 【0398】 Step 2: 【0399】 The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. It collects real-time audio and video data as input and generates data indicating the user's emotional state as output. This provides a basis for analyzing the user's stress and fatigue levels. 【0400】 Step 3: 【0401】 The server uses artificial intelligence to generate agricultural plans based on acquired weather information and sentiment data. It integrates the data obtained in steps 1 and 2 as input and performs data calculations. As output, it provides an optimal work schedule. This creates a plan that takes weather conditions and user sentiment into account. 【0402】 Step 4: 【0403】 The terminal receives the work schedule sent from the server and notifies the user. It receives the generated schedule as input and sends visual and auditory notifications to the user as output. These notifications are optimized for the user's emotional state and include suggestions to improve work efficiency. 【0404】 Step 5: 【0405】 The user operates a terminal to remotely control agricultural equipment. The system controls the equipment based on work schedules and terminal operation instructions as input, and performs agricultural tasks as output. This allows for efficient farming even from remote locations. 【0406】 Step 6: 【0407】 After completing a task, the terminal sends the data of the executed task to the server. It collects task execution result data as input and sends that data to the server as output. This allows for the accumulation of data that can be used to inform future agricultural planning. 【0408】 The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0409】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0410】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0411】 [Third Embodiment] 【0412】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0413】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0414】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0415】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0416】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0417】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0418】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0419】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0420】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0421】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0422】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0423】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0424】 This invention is a system for achieving automation and efficiency in agriculture, primarily through a process in which artificial intelligence formulates agricultural plans utilizing weather information and remotely controls agricultural equipment. This system consists of three elements: a server, a terminal, and a user, each with its own unique role. 【0425】 The server periodically obtains weather information from external information providers, and based on this, artificial intelligence generates optimal farming plans for each crop. These plans include cultivation schedules, timing for watering and pesticide application, and guidelines for work procedures. The farming plans are then sent from the server to terminals, making them easily accessible to users. 【0426】 The terminal is configured to allow users to remotely control agricultural equipment. This enables drones and autonomous machines to perform planned tasks on the farm based on instructions from the terminal. For example, they can spray the appropriate amount of water according to the weather or apply fertilizer according to the growth stage of the plants. In addition, the progress of the work and the status of the equipment are fed back to the user in real time. 【0427】 Users can interact with the system via their terminals and fine-tune plans and settings as needed. For example, users can change parameters within the system if the crop type changes or if special measures are required. Furthermore, important information such as harvest time is notified from the server, enabling planned harvesting operations. 【0428】 As a concrete example, consider the case of a large-scale tomato farm in a specific region. The server retrieves the 7-day weather forecast for that region, and AI analyzes the data to formulate an appropriate daily schedule. Based on this, the terminal issues instructions to the automated irrigation system and drones for pesticide spraying, maintaining optimal conditions for tomato growth. The user can monitor these operations in real time via their smartphone and make adjustments as needed. 【0429】 In this way, by compensating for the lack of agricultural expertise and supporting efficient and effective agricultural management, a system is created that reduces the burden on those entering agriculture. 【0430】 The following describes the processing flow. 【0431】 Step 1: 【0432】 The server obtains weather information from external information providers via APIs. The data includes information such as temperature, probability of precipitation, humidity, and wind speed, and this information is stored in a database. 【0433】 Step 2: 【0434】 The server instructs artificial intelligence to analyze the stored weather data. The AI ​​uses this information to create agricultural plans tailored to the type and growth stage of the crops. These plans include timing for watering and pesticide application, as well as necessary fertilization. 【0435】 Step 3: 【0436】 The server sends the generated farming plan to the user's terminal. The user can then view the work schedule and required materials on the terminal's display. 【0437】 Step 4: 【0438】 Users can initiate operation of agricultural equipment via a terminal. The terminal sends instructions to equipment such as agricultural drones and automated irrigation systems according to a set work schedule. This ensures that watering and pesticide application are carried out as planned. 【0439】 Step 5: 【0440】 The terminal collects work status data from agricultural equipment and reports it to the server in real time. Users can check this data and monitor the situation at any time through the terminal. 【0441】 Step 6: 【0442】 After the task is completed, the server analyzes the results and records them in a database to help improve future farming plans. This data will be used for future AI learning. 【0443】 Step 7: 【0444】 The server uses AI to predict the optimal time for harvesting crops and notifies the user's device of the result. The user receives the notification and can begin harvesting at the appropriate time. 【0445】 (Example 1) 【0446】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0447】 In modern agriculture, it is crucial to formulate rapid and accurate work plans in response to changes in weather information. However, conventional methods make it difficult to create precise plans using weather data, and efficient management of agricultural equipment is also not easy. As a result, optimizing work is difficult, and there are limitations to improving productivity. This invention aims to solve these problems and realize automation and efficiency in agriculture. 【0448】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0449】 In this invention, the server includes means for acquiring and analyzing weather information from an external information provider; means for automatically generating an agricultural plan based on the weather information using a generation AI model and formulating work schedules for each crop; and means for remotely controlling agricultural equipment via a computing device and executing agricultural work based on the formulated schedule. This makes it possible to improve the accuracy and efficiency of agricultural work and to realize the automation of agricultural operations. 【0450】 "Weather information" refers to weather-related data obtained from external information providers, including information such as temperature, precipitation, and wind speed. 【0451】 A "generative AI model" is an algorithm that uses artificial intelligence technology to analyze input data and automatically generate plans and predictions based on specific objectives. 【0452】 A "computing device" is an electronic device used to process data and perform calculations, and generally refers to computers and servers. 【0453】 "Agricultural equipment" refers to devices that perform agricultural work automatically or semi-automatically, and includes irrigation systems, pesticide spraying drones, and autonomous agricultural machinery. 【0454】 A "communication device" is a device used for sending and receiving data, and mobile terminals such as smartphones and tablets fall into this category. 【0455】 This invention is a system for automating and streamlining agriculture by utilizing three elements: a server, a terminal, and a user. The server acquires weather data from external information providers using a Web API. The Python requests library is used for this acquisition, and the data is received in JSON format, from which necessary information is extracted using a Python script. 【0456】 The server then uses TensorFlow as the generation AI model to generate an agricultural plan based on the analyzed weather data. The prompts used during generation are input to the AI ​​model in the form of, for example, "Suggest the optimal irrigation schedule for tomatoes this week," and a specific schedule is formulated based on this. 【0457】 The generated farming plan is sent from the server to the terminal via the cloud. Common mobile devices such as smartphones and tablets are used as the terminal. This terminal provides the farming plan to the user through an application built using React Native. Through this application, the user can view the plan sent from the server in real time and control agricultural equipment. 【0458】 Examples of agricultural equipment include irrigation systems, drones for spraying pesticides, and autonomous agricultural machinery. These devices operate based on instructions sent from a server and can be remotely controlled by the user from a terminal. In addition, the progress of the work and the operating status of the equipment are fed back in real time and displayed on the application on the terminal. 【0459】 This system enables precise agricultural management even without specialized agricultural knowledge, contributing to improved agricultural productivity and efficiency. 【0460】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0461】 Step 1: 【0462】 The server obtains weather information from external information providers. It issues API requests as input and receives weather data in JSON format as output. Specifically, it uses the Python requests library to make HTTP requests to obtain data such as temperature, precipitation, and wind speed for the target area. The obtained data is saved in preparation for analysis in the next step. 【0463】 Step 2: 【0464】 The server inputs acquired weather information into a generating AI model to create an agricultural plan. Weather data in JSON format is provided as input to a TensorFlow model, and specific work schedules for each crop are obtained as output. In this process, the prompt "Suggest the optimal irrigation schedule for tomatoes this week" is presented to the AI ​​model, and through analysis and calculation, the optimal action plan is formulated. 【0465】 Step 3: 【0466】 The server sends the generated farming plan to the terminal. The created work schedule is uploaded to cloud storage as input, and a push notification is sent to the terminal as output. Here, settings are configured to access the database via the cloud service and reflect the data on the terminal in real time. 【0467】 Step 4: 【0468】 The terminal assists users in operating agricultural equipment based on the received farming plan. It receives plan information sent from the server as input and displays an operation screen via a user interface as output. Specifically, a React Native mobile app provides instructions based on the plan, and the user remotely controls the equipment through this app. For example, it can activate an irrigation system at a specified time. 【0469】 Step 5: 【0470】 The terminal displays feedback on work progress and equipment status obtained from agricultural machinery. It receives status data from the equipment as input and outputs the situation to the user in an easy-to-understand manner. This allows the user to grasp the progress of work in real time and make adjustments to the plan as needed. 【0471】 (Application Example 1) 【0472】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0473】 Agricultural activities in urban areas require efficient and effective management in response to population growth and changes in land use. However, many urban residents lack specialized knowledge about agriculture, making it difficult to operate farms in a sustainable manner. Furthermore, planning must take into account weather uncertainties and limited resources. This complicates farmland management and places a significant burden on residents promoting agriculture in community gardens and shared farmlands. To address these challenges, there is a need to provide a system that allows urban residents to easily engage in agricultural activities and manage them efficiently. 【0474】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0475】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating an environmental schedule, and means for remotely controlling agricultural equipment and executing agricultural work based on the formulated schedule. This makes it possible for urban residents to efficiently manage and sustainably operate agricultural activities in community gardens and shared farmland, even without specialized knowledge. 【0476】 "Weather information" refers to data on atmospheric conditions such as precipitation, temperature, humidity, and wind speed, which are necessary for agricultural planning and environmental management. 【0477】 An "external information provider" is a third-party organization that provides weather information and other necessary data to the system. 【0478】 An "agricultural plan" is a schedule and procedure of work created to optimize the efficiency of crop production. 【0479】 "Artificial intelligence" is a program or system that analyzes large amounts of data, identifies patterns, and makes predictions. 【0480】 An "environmental schedule" is a plan set up to carry out tasks at the appropriate time in urban agriculture and environmental management activities. 【0481】 "Agricultural equipment" refers to all types of machinery and devices used to assist in agricultural work. 【0482】 "Remote control" refers to the means of operating or managing equipment from a physically distant location using communication technology. 【0483】 An "interface" is a means for a user to interact with a system, and includes an operation screen and control functions that enable the input and output of information. 【0484】 An "administrator" is a person or role responsible for operating and monitoring a system or environment, and for adjusting plans as needed. 【0485】 "Real-time" refers to processing and reactions occurring at nearly the same speed as actual time. 【0486】 The system for implementing this invention supports the efficient management of urban agriculture and community gardens. It primarily consists of three elements: a server, a terminal, and a user, and operates as follows: 【0487】 The server first periodically acquires weather information from external information providers. This weather information is analyzed using a generative AI model to generate optimal agricultural plans for each crop. For example, it adjusts water and fertilizer application schedules according to fluctuations in rainfall and temperature. This plan is then transmitted to terminals in the form of an environmental schedule. 【0488】 The terminal has the means to remotely control agricultural equipment in real time. Based on the plan received from the server, the terminal can appropriately execute the necessary agricultural tasks. This ensures that agricultural equipment operates according to schedule and performs the prescribed tasks. For example, it is possible to set up an irrigation system to operate automatically according to weather conditions. 【0489】 Users can interact with the system through an interface via their terminal. The system provides users with real-time information on the status of farmland, allowing them to adjust plans as needed. This improves the efficiency and sustainability of agricultural activities in urban areas. 【0490】 For example, if a community garden manager checks the weekend rain forecast and the system determines that it will be sunny on Saturday and Sunday, it can adjust the irrigation schedule and notify the manager via the device. 【0491】 An example of a prompt message is expected to be something like, "Generate an irrigation schedule to optimize tomato growth based on next week's weather." This is how the AI ​​model would be instructed. 【0492】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0493】 Step 1: 【0494】 The server periodically retrieves weather information from external information providers. The input is weather forecast data, and the output is weather information ready for analysis. This updates the weather database with the latest information. Specifically, the server automatically downloads weather information using a defined API. 【0495】 Step 2: 【0496】 The server uses a generative AI model to generate agricultural plans based on acquired weather information. The input is weather information, and the output is the optimal environmental schedule for each crop. In this process, weather data is analyzed, and based on the results, the AI ​​proposes irrigation and fertilization schedules. Specifically, the AI ​​model refers to past weather patterns and crop growth history to formulate an optimized plan. 【0497】 Step 3: 【0498】 The terminal receives the agricultural plan transmitted from the server. The input is the generated agricultural plan, and the output is the latest schedule information held by the terminal. Based on this information, the terminal updates the control program for agricultural equipment located remotely. Specifically, the terminal converts the received plan into operation commands for the equipment and prepares it for execution. 【0499】 Step 4: 【0500】 Users monitor the operating status of agricultural equipment via a terminal and adjust plans as needed. Inputs are equipment operating data and feedback from the system, while outputs are adjusted equipment control instructions. Users can change schedules and issue immediate instructions through the application interface. Specifically, users fine-tune plans using their smartphone's touchscreen. 【0501】 Step 5: 【0502】 The terminal controls agricultural equipment based on user or program instructions, performing tasks according to a predetermined plan. Input is adjusted schedule information, and output is a work completion report. Specifically, the terminal monitors the machine's status in real time and issues commands to perform the necessary agricultural tasks. 【0503】 Step 6: 【0504】 The server collects data after work is completed and records it for future planning improvements. The input is work completion report data, and the output is an updated system database. Specifically, the server compares work results with weather forecasts to improve the accuracy of plans. 【0505】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0506】 This invention provides an automated agricultural planning system that utilizes weather information, and also offers a system that recognizes user emotions to provide further adaptability. By incorporating an emotion engine, this system can adjust work plans and optimize notification content while considering the user's emotional state. The system consists of server, terminal, and user elements. 【0507】 The server uses weather information obtained from external information providers to generate agricultural plans using artificial intelligence. In addition, the server is equipped with an emotion engine that can analyze the user's stress and fatigue levels. The emotion engine determines the user's emotions based on user input and data obtained from terminal sensors, and suggests appropriate responses. Therefore, the pace and content of the planned farm work may be adjusted according to the user's emotions. 【0508】 The device receives the results of the emotion engine's analysis and adjusts the content of notifications to the user and the display on the interface. For example, if it determines that the user is tired, it can send a notification suggesting that the user take a break from work. The device also provides an interface for operating agricultural equipment and plays a role in remotely controlling the equipment according to a plan. 【0509】 Users interact with the system via their devices. An emotion engine suggests crops based on the user's interests and preferences, allowing them to choose crops that align with their emotions and proceed with farming while feeling a sense of fulfillment. This emotion-based suggestion has the effect of increasing motivation in farming. 【0510】 As a concrete example, consider a case where a user has just started growing corn. The server collects local weather forecasts, and the AI ​​creates an optimal growing plan. At that time, the emotion engine analyzes the user's current stress level, and if the user is in a high-stress state, it can suggest a work schedule with more leeway. Furthermore, if the user has shown interest in crops other than corn, it can also suggest alternative options accordingly. 【0511】 In this way, this system combines emotional understanding with agricultural efficiency to provide a more humane agricultural experience, aiming to reduce the burden on newcomers to agriculture while improving the quality of work. 【0512】 The following describes the processing flow. 【0513】 Step 1: 【0514】 The server obtains weather information for each region through APIs from external information providers. This includes temperature, humidity, wind speed, and probability of precipitation, and the obtained data is stored in an internal database. 【0515】 Step 2: 【0516】 The server sends stored weather information to artificial intelligence to generate an optimal farming plan for each crop. This plan includes water and pesticide application schedules based on soil conditions and growth stage. 【0517】 Step 3: 【0518】 The emotion engine installed on the server receives user emotion data from the terminal and analyzes stress and fatigue levels. Using this analysis, the agricultural work schedule is adjusted as needed. 【0519】 Step 4: 【0520】 The terminal notifies the user of the adjusted farming plan and sentiment analysis results received from the server. This may include progress reports tailored to the user's condition and recommendations for rest. 【0521】 Step 5: 【0522】 Users can remotely control agricultural equipment using the terminal interface and initiate work based on a created schedule. Equipment operation includes automated water and pesticide spraying, as well as machine operation at specified times. 【0523】 Step 6: 【0524】 The terminal transmits feedback from agricultural equipment and work completion data to the server in real time. This allows users to check work progress and re-evaluate the schedule as needed. 【0525】 Step 7: 【0526】 The server predicts the harvest time based on an analysis of crop growth and current conditions. As the harvest time approaches, a notification is sent to the user's device, and the optimal harvesting method is suggested. 【0527】 Step 8: 【0528】 The emotion engine analyzes emotional data obtained through work and uses it to improve long-term farming plans. It also generates suggestions for the user's next crops and tasks based on this data. 【0529】 (Example 2) 【0530】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0531】 In recent years, changes in weather conditions have a significant impact on work schedules in agriculture, necessitating efficient planning. However, conventional systems fail to adequately alleviate users' mental burden because they do not consider the emotional state of the users. Furthermore, there is room for improvement in the remote operation of agricultural equipment and the utilization of data after work. To address these challenges, there is a need to provide flexible and efficient agricultural planning that reflects the individual circumstances of each user. 【0532】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0533】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating a work schedule, and means for analyzing the user's emotional state and adjusting the work schedule based on the analysis. This makes it possible to formulate and execute flexible agricultural plans that respond to weather conditions and the user's emotional state. 【0534】 "Weather information" refers to data on environmental conditions such as local temperature, humidity, rainfall, and sunshine duration, obtained from external information providers. 【0535】 An "agricultural plan" is a series of plans for crop cultivation and work schedules that are automatically created by artificial intelligence based on weather information. 【0536】 "Artificial intelligence" is a technology used in computer systems to mimic human intellectual work, analyze data, and make optimal decisions. 【0537】 "Emotional state" is an indicator that shows the mental and emotional condition of the user, and is an assessment that includes stress levels and fatigue levels. 【0538】 "Agricultural machinery" refers to machines and devices used to carry out agricultural work, and this includes equipment such as tractors and irrigation systems. 【0539】 "Remote control" is a technology that allows you to operate machinery and devices from a distance using electrical or electronic means without physically touching the equipment. 【0540】 "Adjustment" is the process of modifying or optimizing pre-planned schedules and tasks, taking into account the emotional state of the users. 【0541】 A "notification" is information sent from the system to the user, and includes scheduled actions and urgent suggestions. 【0542】 "Analysis" is the process of extracting useful information from complex data and expressing it in an easily understandable format. 【0543】 Modes for carrying out the invention 【0544】 This invention is a system that automates agricultural planning using weather information and further proposes effective plans by incorporating the user's emotional state. The hardware used includes a server for managing information, user devices as terminals, and agricultural equipment requested by the user. The software integrates a generative AI model and an emotion analysis engine, enabling advanced data processing. 【0545】 The server obtains real-time weather information from external information providers via API and uses this information to develop appropriate agricultural plans using a generated AI model. Furthermore, the server is equipped with an emotion analysis engine that can analyze user emotion data based on information obtained from the terminal. Based on this analysis, the server flexibly adjusts the work schedule and plan content. 【0546】 The terminal functions as an interface between the user and the system, displaying information received from the server and sending notifications. Specifically, if the user is under high stress, it will send an alert such as "You should take a break." The terminal is also equipped with an interface for the user to remotely control agricultural equipment, enabling planned equipment operation. 【0547】 Users can interact with this system through their devices and receive crop selection suggestions based on sentiment analysis. This allows users to choose crops they are interested in and perform farming tasks with a sense of satisfaction. For example, when a user plans to cultivate corn, the server collects local weather data and uses AI to create a cultivation plan. In doing so, it suggests a schedule with buffer time if necessary, based on sentiment analysis. 【0548】 An example of a prompt message that could be input to the generating AI model is: "Based on the current weather information and the user's stress level, please suggest the optimal corn cultivation plan. Also, if the user is interested in sunflowers, please include a cultivation plan for those as well." 【0549】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0550】 Step 1: 【0551】 The server obtains weather information through APIs from external information providers. It sends region-based requests to the API as input and receives data on temperature, humidity, rainfall, and sunshine duration for the specified region as output. This data is then organized and stored for input into a generating AI model. 【0552】 Step 2: 【0553】 The server uses a generative AI model to analyze acquired weather information data and generate a farming plan. The input includes weather information and a prompt message such as "Generate optimal cultivation plan." The AI ​​model analyzes this information and generates a farming plan as output, which may include, for example, appropriate planting dates and irrigation schedules for corn. 【0554】 Step 3: 【0555】 The device acquires information about the user's emotional state, such as heart rate and input data. Inputs include wearable devices and direct input. The output is the integration of this information to obtain numerical data representing the user's stress level and fatigue level. 【0556】 Step 4: 【0557】 The server adjusts existing farming plans based on emotional state data acquired from the terminal. The inputs are the generated farming plan and the user's emotional state data. This data is processed by an emotional analysis engine, which then outputs an adjusted work schedule adapted to the user's emotions. 【0558】 Step 5: 【0559】 The terminal displays the adjusted work schedule sent from the server on its screen and notifies the user. Input includes the adjusted schedule and a template message to send to the user. Output generates specific notifications, such as "We recommend taking a break today," and presents them visually to the user. 【0560】 Step 6: 【0561】 Users can review proposed plans and crops via their terminal and approve, reject, or modify them. Input includes the displayed information and the user's decisions. Output is the data returned to the server as the selected work plan or modification request. 【0562】 Step 7: 【0563】 The server stores user selections and feedback in a database, which is then used for future analyses and plan generation. Inputs consist of user selections and work progress data. Based on this, the output is accumulated as data that contributes to improving the accuracy of agricultural planning and sentiment analysis. 【0564】 (Application Example 2) 【0565】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0566】 Agricultural activities in modern urban environments require efficient operations while considering the physical and mental state of workers. However, conventional systems struggle to take workers' emotions into account, resulting in inappropriate work plans and a decline in work efficiency and sustainability. Furthermore, a system capable of real-time situation monitoring and immediate response is needed. Therefore, a system is required that can adaptively adjust agricultural plans while considering workers' emotions. 【0567】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0568】 In this invention, the server includes means for acquiring weather information from an external organization and processing input data for recognizing emotional states; means for analyzing weather information and emotional data using artificial intelligence and an emotion engine to automatically generate agricultural plans and formulate work schedules; and means for remotely operating agricultural equipment to perform agricultural work based on the formulated schedule, as well as adjusting notifications and suggestions according to the user's emotional state. This makes it possible to formulate and execute agricultural plans that take into account the emotional state of the workers, thereby achieving both improved work efficiency and worker comfort. 【0569】 "Weather information" refers to data on the natural environment that affects agricultural planning, such as weather, temperature, precipitation, and wind speed. 【0570】 An "external organization" refers to an organization or system that provides weather information or other data. 【0571】 "Emotional state" refers to information that indicates the user's mental and psychological state, including stress and fatigue. 【0572】 "Input data" refers to data obtained from the user, including their emotional state, as well as environmental information. 【0573】 "Artificial intelligence" is a computer technology that uses machine learning and data analysis techniques to automatically generate agricultural plans. 【0574】 An "emotion engine" is a technology that analyzes a user's emotional state and provides appropriate work plans and notifications based on that analysis. 【0575】 "Agricultural equipment" refers to devices and machines used to support or automate agricultural work. 【0576】 "Remote control" refers to the means of controlling equipment or systems from a distance. 【0577】 A "schedule" refers to a plan or schedule that is carried out based on time and order. 【0578】 A "notification" is a message or alert used to inform a user of information. 【0579】 A "suggestion" is something that presents the optimal action or choice based on the user's state and environment. 【0580】 The system in this invention is built using a smartphone and a server. The server obtains weather information from an external organization via the internet. Next, the server uses an emotion engine to analyze the user's emotional state based on sensor data obtained from the smartphone's camera and microphone. This analysis can utilize open-source libraries such as OpenCV and the Google Cloud Speech-to-Text API for speech analysis. 【0581】 The server uses artificial intelligence technology to automatically generate farming plans that take into account weather information and the user's emotional state. Based on the generated plan, a work schedule is created, and this information is sent to the terminal. The terminal receives this information and notifies the user in a timely manner. These notifications may include suggestions for taking a break if the user is fatigued, or suggestions for carrying out the planned farming tasks. 【0582】 The terminal also has an interface for remotely operating agricultural equipment and performing tasks according to a plan. Furthermore, data obtained after agricultural activities are returned to the server and used for future planning. 【0583】 For example, when a user starts growing a new crop, the server can obtain local weather forecast data, perform sentiment analysis, and then propose a less stressful and more efficient work plan. 【0584】 Example of a prompt: 【0585】 "If a user is relaxing and tending to lavender with birdsong in the background, but feeling a little tired, please suggest the optimal work plan." 【0586】 In this way, the server integrates and analyzes weather information and sentiment data to provide users with the optimal agricultural experience. 【0587】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0588】 Step 1: 【0589】 The server obtains weather information from external organizations via the internet. It sends requests based on region and time period as input, and receives data such as weather, temperature, and precipitation as output. This makes it possible to understand local climate conditions. 【0590】 Step 2: 【0591】 The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. It collects real-time audio and video data as input and generates data indicating the user's emotional state as output. This provides a basis for analyzing the user's stress and fatigue levels. 【0592】 Step 3: 【0593】 The server uses artificial intelligence to generate agricultural plans based on acquired weather information and sentiment data. It integrates the data obtained in steps 1 and 2 as input and performs data calculations. As output, it provides an optimal work schedule. This creates a plan that takes weather conditions and user sentiment into account. 【0594】 Step 4: 【0595】 The terminal receives the work schedule sent from the server and notifies the user. It receives the generated schedule as input and sends visual and auditory notifications to the user as output. These notifications are optimized for the user's emotional state and include suggestions to improve work efficiency. 【0596】 Step 5: 【0597】 The user operates a terminal to remotely control agricultural equipment. The system controls the equipment based on work schedules and terminal operation instructions as input, and performs agricultural tasks as output. This allows for efficient farming even from remote locations. 【0598】 Step 6: 【0599】 After completing a task, the terminal sends the data of the executed task to the server. It collects task execution result data as input and sends that data to the server as output. This allows for the accumulation of data that can be used to inform future agricultural planning. 【0600】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0601】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0602】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0603】 [Fourth Embodiment] 【0604】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0605】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0606】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0607】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0608】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0609】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0610】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0611】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0612】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0613】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0614】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0615】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0616】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0617】 This invention is a system for achieving automation and efficiency in agriculture, primarily through a process in which artificial intelligence formulates agricultural plans utilizing weather information and remotely controls agricultural equipment. This system consists of three elements: a server, a terminal, and a user, each with its own unique role. 【0618】 The server periodically obtains weather information from external information providers, and based on this, artificial intelligence generates optimal farming plans for each crop. These plans include cultivation schedules, timing for watering and pesticide application, and guidelines for work procedures. The farming plans are then sent from the server to terminals, making them easily accessible to users. 【0619】 The terminal is configured to allow users to remotely control agricultural equipment. This enables drones and autonomous machines to perform planned tasks on the farm based on instructions from the terminal. For example, they can spray the appropriate amount of water according to the weather or apply fertilizer according to the growth stage of the plants. In addition, the progress of the work and the status of the equipment are fed back to the user in real time. 【0620】 Users can interact with the system via their terminals and fine-tune plans and settings as needed. For example, users can change parameters within the system if the crop type changes or if special measures are required. Furthermore, important information such as harvest time is notified from the server, enabling planned harvesting operations. 【0621】 As a concrete example, consider the case of a large-scale tomato farm in a specific region. The server retrieves the 7-day weather forecast for that region, and AI analyzes the data to formulate an appropriate daily schedule. Based on this, the terminal issues instructions to the automated irrigation system and drones for pesticide spraying, maintaining optimal conditions for tomato growth. The user can monitor these operations in real time via their smartphone and make adjustments as needed. 【0622】 In this way, by compensating for the lack of agricultural expertise and supporting efficient and effective agricultural management, a system is created that reduces the burden on those entering agriculture. 【0623】 The following describes the processing flow. 【0624】 Step 1: 【0625】 The server obtains weather information from external information providers via APIs. The data includes information such as temperature, probability of precipitation, humidity, and wind speed, and this information is stored in a database. 【0626】 Step 2: 【0627】 The server instructs artificial intelligence to analyze the stored weather data. The AI ​​uses this information to create agricultural plans tailored to the type and growth stage of the crops. These plans include timing for watering and pesticide application, as well as necessary fertilization. 【0628】 Step 3: 【0629】 The server sends the generated farming plan to the user's terminal. The user can then view the work schedule and required materials on the terminal's display. 【0630】 Step 4: 【0631】 Users can initiate operation of agricultural equipment via a terminal. The terminal sends instructions to equipment such as agricultural drones and automated irrigation systems according to a set work schedule. This ensures that watering and pesticide application are carried out as planned. 【0632】 Step 5: 【0633】 The terminal collects work status data from agricultural equipment and reports it to the server in real time. Users can check this data and monitor the situation at any time through the terminal. 【0634】 Step 6: 【0635】 After the task is completed, the server analyzes the results and records them in a database to help improve future farming plans. This data will be used for future AI learning. 【0636】 Step 7: 【0637】 The server uses AI to predict the optimal time for harvesting crops and notifies the user's device of the result. The user receives the notification and can begin harvesting at the appropriate time. 【0638】 (Example 1) 【0639】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0640】 In modern agriculture, it is crucial to formulate rapid and accurate work plans in response to changes in weather information. However, conventional methods make it difficult to create precise plans using weather data, and efficient management of agricultural equipment is also not easy. As a result, optimizing work is difficult, and there are limitations to improving productivity. This invention aims to solve these problems and realize automation and efficiency in agriculture. 【0641】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0642】 In this invention, the server includes means for acquiring and analyzing weather information from an external information provider; means for automatically generating an agricultural plan based on the weather information using a generation AI model and formulating work schedules for each crop; and means for remotely controlling agricultural equipment via a computing device and executing agricultural work based on the formulated schedule. This makes it possible to improve the accuracy and efficiency of agricultural work and to realize the automation of agricultural operations. 【0643】 "Weather information" refers to weather-related data obtained from external information providers, including information such as temperature, precipitation, and wind speed. 【0644】 A "generative AI model" is an algorithm that uses artificial intelligence technology to analyze input data and automatically generate plans and predictions based on specific objectives. 【0645】 A "computing device" is an electronic device used to process data and perform calculations, and generally refers to computers and servers. 【0646】 "Agricultural equipment" refers to devices that perform agricultural work automatically or semi-automatically, and includes irrigation systems, pesticide spraying drones, and autonomous agricultural machinery. 【0647】 A "communication device" is a device used for sending and receiving data, and mobile terminals such as smartphones and tablets fall into this category. 【0648】 This invention is a system for automating and streamlining agriculture by utilizing three elements: a server, a terminal, and a user. The server acquires weather data from external information providers using a Web API. The Python requests library is used for this acquisition, and the data is received in JSON format, from which necessary information is extracted using a Python script. 【0649】 The server then uses TensorFlow as the generation AI model to generate an agricultural plan based on the analyzed weather data. The prompts used during generation are input to the AI ​​model in the form of, for example, "Suggest the optimal irrigation schedule for tomatoes this week," and a specific schedule is formulated based on this. 【0650】 The generated farming plan is sent from the server to the terminal via the cloud. Common mobile devices such as smartphones and tablets are used as the terminal. This terminal provides the farming plan to the user through an application built using React Native. Through this application, the user can view the plan sent from the server in real time and control agricultural equipment. 【0651】 Examples of agricultural equipment include irrigation systems, drones for spraying pesticides, and autonomous agricultural machinery. These devices operate based on instructions sent from a server and can be remotely controlled by the user from a terminal. In addition, the progress of the work and the operating status of the equipment are fed back in real time and displayed on the application on the terminal. 【0652】 This system enables precise agricultural management even without specialized agricultural knowledge, contributing to improved agricultural productivity and efficiency. 【0653】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0654】 Step 1: 【0655】 The server obtains weather information from external information providers. It issues API requests as input and receives weather data in JSON format as output. Specifically, it uses the Python requests library to make HTTP requests to obtain data such as temperature, precipitation, and wind speed for the target area. The obtained data is saved in preparation for analysis in the next step. 【0656】 Step 2: 【0657】 The server inputs acquired weather information into a generating AI model to create an agricultural plan. Weather data in JSON format is provided as input to a TensorFlow model, and specific work schedules for each crop are obtained as output. In this process, the prompt "Suggest the optimal irrigation schedule for tomatoes this week" is presented to the AI ​​model, and through analysis and calculation, the optimal action plan is formulated. 【0658】 Step 3: 【0659】 The server sends the generated farming plan to the terminal. The created work schedule is uploaded to cloud storage as input, and a push notification is sent to the terminal as output. Here, settings are configured to access the database via the cloud service and reflect the data on the terminal in real time. 【0660】 Step 4: 【0661】 The terminal assists users in operating agricultural equipment based on the received farming plan. It receives plan information sent from the server as input and displays an operation screen via a user interface as output. Specifically, a React Native mobile app provides instructions based on the plan, and the user remotely controls the equipment through this app. For example, it can activate an irrigation system at a specified time. 【0662】 Step 5: 【0663】 The terminal displays feedback on work progress and equipment status obtained from agricultural machinery. It receives status data from the equipment as input and outputs the situation to the user in an easy-to-understand manner. This allows the user to grasp the progress of work in real time and make adjustments to the plan as needed. 【0664】 (Application Example 1) 【0665】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0666】 Agricultural activities in urban areas require efficient and effective management in response to population growth and changes in land use. However, many urban residents lack specialized knowledge about agriculture, making it difficult to operate farms in a sustainable manner. Furthermore, planning must take into account weather uncertainties and limited resources. This complicates farmland management and places a significant burden on residents promoting agriculture in community gardens and shared farmlands. To address these challenges, there is a need to provide a system that allows urban residents to easily engage in agricultural activities and manage them efficiently. 【0667】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0668】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating an environmental schedule, and means for remotely controlling agricultural equipment and executing agricultural work based on the formulated schedule. This makes it possible for urban residents to efficiently manage and sustainably operate agricultural activities in community gardens and shared farmland, even without specialized knowledge. 【0669】 "Weather information" refers to data on atmospheric conditions such as precipitation, temperature, humidity, and wind speed, which are necessary for agricultural planning and environmental management. 【0670】 An "external information provider" is a third-party organization that provides weather information and other necessary data to the system. 【0671】 An "agricultural plan" is a schedule and procedure of work created to optimize the efficiency of crop production. 【0672】 "Artificial intelligence" is a program or system that analyzes large amounts of data, identifies patterns, and makes predictions. 【0673】 An "environmental schedule" is a plan set up to carry out tasks at the appropriate time in urban agriculture and environmental management activities. 【0674】 "Agricultural equipment" refers to all types of machinery and devices used to assist in agricultural work. 【0675】 "Remote control" refers to the means of operating or managing equipment from a physically distant location using communication technology. 【0676】 An "interface" is a means for a user to interact with a system, and includes an operation screen and control functions that enable the input and output of information. 【0677】 An "administrator" is a person or role responsible for operating and monitoring a system or environment, and for adjusting plans as needed. 【0678】 "Real-time" refers to processing and reactions occurring at nearly the same speed as actual time. 【0679】 The system for implementing this invention supports the efficient management of urban agriculture and community gardens. It primarily consists of three elements: a server, a terminal, and a user, and operates as follows: 【0680】 The server first periodically acquires weather information from external information providers. This weather information is analyzed using a generative AI model to generate optimal agricultural plans for each crop. For example, it adjusts water and fertilizer application schedules according to fluctuations in rainfall and temperature. This plan is then transmitted to terminals in the form of an environmental schedule. 【0681】 The terminal has the means to remotely control agricultural equipment in real time. Based on the plan received from the server, the terminal can appropriately execute the necessary agricultural tasks. This ensures that agricultural equipment operates according to schedule and performs the prescribed tasks. For example, it is possible to set up an irrigation system to operate automatically according to weather conditions. 【0682】 Users can interact with the system through an interface via their terminal. The system provides users with real-time information on the status of farmland, allowing them to adjust plans as needed. This improves the efficiency and sustainability of agricultural activities in urban areas. 【0683】 For example, if a community garden manager checks the weekend rain forecast and the system determines that it will be sunny on Saturday and Sunday, it can adjust the irrigation schedule and notify the manager via the device. 【0684】 An example of a prompt message is expected to be something like, "Generate an irrigation schedule to optimize tomato growth based on next week's weather." This is how the AI ​​model would be instructed. 【0685】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0686】 Step 1: 【0687】 The server periodically retrieves weather information from external information providers. The input is weather forecast data, and the output is weather information ready for analysis. This updates the weather database with the latest information. Specifically, the server automatically downloads weather information using a defined API. 【0688】 Step 2: 【0689】 The server uses a generative AI model to generate agricultural plans based on acquired weather information. The input is weather information, and the output is the optimal environmental schedule for each crop. In this process, weather data is analyzed, and based on the results, the AI ​​proposes irrigation and fertilization schedules. Specifically, the AI ​​model refers to past weather patterns and crop growth history to formulate an optimized plan. 【0690】 Step 3: 【0691】 The terminal receives the agricultural plan transmitted from the server. The input is the generated agricultural plan, and the output is the latest schedule information held by the terminal. Based on this information, the terminal updates the control program for agricultural equipment located remotely. Specifically, the terminal converts the received plan into operation commands for the equipment and prepares it for execution. 【0692】 Step 4: 【0693】 Users monitor the operating status of agricultural equipment via a terminal and adjust plans as needed. Inputs are equipment operating data and feedback from the system, while outputs are adjusted equipment control instructions. Users can change schedules and issue immediate instructions through the application interface. Specifically, users fine-tune plans using their smartphone's touchscreen. 【0694】 Step 5: 【0695】 The terminal controls agricultural equipment based on user or program instructions, performing tasks according to a predetermined plan. Input is adjusted schedule information, and output is a work completion report. Specifically, the terminal monitors the machine's status in real time and issues commands to perform the necessary agricultural tasks. 【0696】 Step 6: 【0697】 The server collects data after work is completed and records it for future planning improvements. The input is work completion report data, and the output is an updated system database. Specifically, the server compares work results with weather forecasts to improve the accuracy of plans. 【0698】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0699】 This invention provides an automated agricultural planning system that utilizes weather information, and also offers a system that recognizes user emotions to provide further adaptability. By incorporating an emotion engine, this system can adjust work plans and optimize notification content while considering the user's emotional state. The system consists of server, terminal, and user elements. 【0700】 The server uses weather information obtained from external information providers to generate agricultural plans using artificial intelligence. In addition, the server is equipped with an emotion engine that can analyze the user's stress and fatigue levels. The emotion engine determines the user's emotions based on user input and data obtained from terminal sensors, and suggests appropriate responses. Therefore, the pace and content of the planned farm work may be adjusted according to the user's emotions. 【0701】 The device receives the results of the emotion engine's analysis and adjusts the content of notifications to the user and the display on the interface. For example, if it determines that the user is tired, it can send a notification suggesting that the user take a break from work. The device also provides an interface for operating agricultural equipment and plays a role in remotely controlling the equipment according to a plan. 【0702】 Users interact with the system via their devices. An emotion engine suggests crops based on the user's interests and preferences, allowing them to choose crops that align with their emotions and proceed with farming while feeling a sense of fulfillment. This emotion-based suggestion has the effect of increasing motivation in farming. 【0703】 As a concrete example, consider a case where a user has just started growing corn. The server collects local weather forecasts, and the AI ​​creates an optimal growing plan. At that time, the emotion engine analyzes the user's current stress level, and if the user is in a high-stress state, it can suggest a work schedule with more leeway. Furthermore, if the user has shown interest in crops other than corn, it can also suggest alternative options accordingly. 【0704】 In this way, this system combines emotional understanding with agricultural efficiency to provide a more humane agricultural experience, aiming to reduce the burden on newcomers to agriculture while improving the quality of work. 【0705】 The following describes the processing flow. 【0706】 Step 1: 【0707】 The server obtains weather information for each region through APIs from external information providers. This includes temperature, humidity, wind speed, and probability of precipitation, and the obtained data is stored in an internal database. 【0708】 Step 2: 【0709】 The server sends stored weather information to artificial intelligence to generate an optimal farming plan for each crop. This plan includes water and pesticide application schedules based on soil conditions and growth stage. 【0710】 Step 3: 【0711】 The emotion engine installed on the server receives user emotion data from the terminal and analyzes stress and fatigue levels. Using this analysis, the agricultural work schedule is adjusted as needed. 【0712】 Step 4: 【0713】 The terminal notifies the user of the adjusted farming plan and sentiment analysis results received from the server. This may include progress reports tailored to the user's condition and recommendations for rest. 【0714】 Step 5: 【0715】 Users can remotely control agricultural equipment using the terminal interface and initiate work based on a created schedule. Equipment operation includes automated water and pesticide spraying, as well as machine operation at specified times. 【0716】 Step 6: 【0717】 The terminal transmits feedback from agricultural equipment and work completion data to the server in real time. This allows users to check work progress and re-evaluate the schedule as needed. 【0718】 Step 7: 【0719】 The server predicts the harvest time based on an analysis of crop growth and current conditions. As the harvest time approaches, a notification is sent to the user's device, and the optimal harvesting method is suggested. 【0720】 Step 8: 【0721】 The emotion engine analyzes emotional data obtained through work and uses it to improve long-term farming plans. It also generates suggestions for the user's next crops and tasks based on this data. 【0722】 (Example 2) 【0723】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0724】 In recent years, changes in weather conditions have a significant impact on work schedules in agriculture, necessitating efficient planning. However, conventional systems fail to adequately alleviate users' mental burden because they do not consider the emotional state of the users. Furthermore, there is room for improvement in the remote operation of agricultural equipment and the utilization of data after work. To address these challenges, there is a need to provide flexible and efficient agricultural planning that reflects the individual circumstances of each user. 【0725】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0726】 In this invention, the server includes means for acquiring weather information from an external information provider, means for analyzing the weather information using artificial intelligence that automatically generates agricultural plans and formulating a work schedule, and means for analyzing the user's emotional state and adjusting the work schedule based on the analysis. This makes it possible to formulate and execute flexible agricultural plans that respond to weather conditions and the user's emotional state. 【0727】 "Weather information" refers to data on environmental conditions such as local temperature, humidity, rainfall, and sunshine duration, obtained from external information providers. 【0728】 An "agricultural plan" is a series of plans for crop cultivation and work schedules that are automatically created by artificial intelligence based on weather information. 【0729】 "Artificial intelligence" is a technology used in computer systems to mimic human intellectual work, analyze data, and make optimal decisions. 【0730】 "Emotional state" is an indicator that shows the mental and emotional condition of the user, and is an assessment that includes stress levels and fatigue levels. 【0731】 "Agricultural machinery" refers to machines and devices used to carry out agricultural work, and this includes equipment such as tractors and irrigation systems. 【0732】 "Remote control" is a technology that allows you to operate machinery and devices from a distance using electrical or electronic means without physically touching the equipment. 【0733】 "Adjustment" is the process of modifying or optimizing pre-planned schedules and tasks, taking into account the emotional state of the users. 【0734】 A "notification" is information sent from the system to the user, and includes scheduled actions and urgent suggestions. 【0735】 "Analysis" is the process of extracting useful information from complex data and expressing it in an easily understandable format. 【0736】 Modes for carrying out the invention 【0737】 This invention is a system that automates agricultural planning using weather information and further proposes effective plans by incorporating the user's emotional state. The hardware used includes a server for managing information, user devices as terminals, and agricultural equipment requested by the user. The software integrates a generative AI model and an emotion analysis engine, enabling advanced data processing. 【0738】 The server obtains real-time weather information from external information providers via API and uses this information to develop appropriate agricultural plans using a generated AI model. Furthermore, the server is equipped with an emotion analysis engine that can analyze user emotion data based on information obtained from the terminal. Based on this analysis, the server flexibly adjusts the work schedule and plan content. 【0739】 The terminal functions as an interface between the user and the system, displaying information received from the server and sending notifications. Specifically, if the user is under high stress, it will send an alert such as "You should take a break." The terminal is also equipped with an interface for the user to remotely control agricultural equipment, enabling planned equipment operation. 【0740】 Users can interact with this system through their devices and receive crop selection suggestions based on sentiment analysis. This allows users to choose crops they are interested in and perform farming tasks with a sense of satisfaction. For example, when a user plans to cultivate corn, the server collects local weather data and uses AI to create a cultivation plan. In doing so, it suggests a schedule with buffer time if necessary, based on sentiment analysis. 【0741】 An example of a prompt message that could be input to the generating AI model is: "Based on the current weather information and the user's stress level, please suggest the optimal corn cultivation plan. Also, if the user is interested in sunflowers, please include a cultivation plan for those as well." 【0742】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0743】 Step 1: 【0744】 The server obtains weather information through APIs from external information providers. It sends region-based requests to the API as input and receives data on temperature, humidity, rainfall, and sunshine duration for the specified region as output. This data is then organized and stored for input into a generating AI model. 【0745】 Step 2: 【0746】 The server uses a generative AI model to analyze acquired weather information data and generate a farming plan. The input includes weather information and a prompt message such as "Generate optimal cultivation plan." The AI ​​model analyzes this information and generates a farming plan as output, which may include, for example, appropriate planting dates and irrigation schedules for corn. 【0747】 Step 3: 【0748】 The device acquires information about the user's emotional state, such as heart rate and input data. Inputs include wearable devices and direct input. The output is the integration of this information to obtain numerical data representing the user's stress level and fatigue level. 【0749】 Step 4: 【0750】 The server adjusts existing farming plans based on emotional state data acquired from the terminal. The inputs are the generated farming plan and the user's emotional state data. This data is processed by an emotional analysis engine, which then outputs an adjusted work schedule adapted to the user's emotions. 【0751】 Step 5: 【0752】 The terminal displays the adjusted work schedule sent from the server on its screen and notifies the user. Input includes the adjusted schedule and a template message to send to the user. Output generates specific notifications, such as "We recommend taking a break today," and presents them visually to the user. 【0753】 Step 6: 【0754】 Users can review proposed plans and crops via their terminal and approve, reject, or modify them. Input includes the displayed information and the user's decisions. Output is the data returned to the server as the selected work plan or modification request. 【0755】 Step 7: 【0756】 The server stores user selections and feedback in a database, which is then used for future analyses and plan generation. Inputs consist of user selections and work progress data. Based on this, the output is accumulated as data that contributes to improving the accuracy of agricultural planning and sentiment analysis. 【0757】 (Application Example 2) 【0758】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0759】 Agricultural activities in modern urban environments require efficient operations while considering the physical and mental state of workers. However, conventional systems struggle to take workers' emotions into account, resulting in inappropriate work plans and a decline in work efficiency and sustainability. Furthermore, a system capable of real-time situation monitoring and immediate response is needed. Therefore, a system is required that can adaptively adjust agricultural plans while considering workers' emotions. 【0760】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0761】 In this invention, the server includes means for acquiring weather information from an external organization and processing input data for recognizing emotional states; means for analyzing weather information and emotional data using artificial intelligence and an emotion engine to automatically generate agricultural plans and formulate work schedules; and means for remotely operating agricultural equipment to perform agricultural work based on the formulated schedule, as well as adjusting notifications and suggestions according to the user's emotional state. This makes it possible to formulate and execute agricultural plans that take into account the emotional state of the workers, thereby achieving both improved work efficiency and worker comfort. 【0762】 "Weather information" refers to data on the natural environment that affects agricultural planning, such as weather, temperature, precipitation, and wind speed. 【0763】 An "external organization" refers to an organization or system that provides weather information or other data. 【0764】 "Emotional state" refers to information that indicates the user's mental and psychological state, including stress and fatigue. 【0765】 "Input data" refers to data obtained from the user, including their emotional state, as well as environmental information. 【0766】 "Artificial intelligence" is a computer technology that uses machine learning and data analysis techniques to automatically generate agricultural plans. 【0767】 An "emotion engine" is a technology that analyzes a user's emotional state and provides appropriate work plans and notifications based on that analysis. 【0768】 "Agricultural equipment" refers to devices and machines used to support or automate agricultural work. 【0769】 "Remote control" refers to the means of controlling equipment or systems from a distance. 【0770】 A "schedule" refers to a plan or schedule that is carried out based on time and order. 【0771】 A "notification" is a message or alert used to inform a user of information. 【0772】 A "suggestion" is something that presents the optimal action or choice based on the user's state and environment. 【0773】 The system in this invention is built using a smartphone and a server. The server obtains weather information from an external organization via the internet. Next, the server uses an emotion engine to analyze the user's emotional state based on sensor data obtained from the smartphone's camera and microphone. This analysis can utilize open-source libraries such as OpenCV and the Google Cloud Speech-to-Text API for speech analysis. 【0774】 The server uses artificial intelligence technology to automatically generate farming plans that take into account weather information and the user's emotional state. Based on the generated plan, a work schedule is created, and this information is sent to the terminal. The terminal receives this information and notifies the user in a timely manner. These notifications may include suggestions for taking a break if the user is fatigued, or suggestions for carrying out the planned farming tasks. 【0775】 The terminal also has an interface for remotely operating agricultural equipment and performing tasks according to a plan. Furthermore, data obtained after agricultural activities are returned to the server and used for future planning. 【0776】 For example, when a user starts growing a new crop, the server can obtain local weather forecast data, perform sentiment analysis, and then propose a less stressful and more efficient work plan. 【0777】 Example of a prompt: 【0778】 "If a user is relaxing and tending to lavender with birdsong in the background, but feeling a little tired, please suggest the optimal work plan." 【0779】 In this way, the server integrates and analyzes weather information and sentiment data to provide users with the optimal agricultural experience. 【0780】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0781】 Step 1: 【0782】 The server obtains weather information from external organizations via the internet. It sends requests based on region and time period as input, and receives data such as weather, temperature, and precipitation as output. This makes it possible to understand local climate conditions. 【0783】 Step 2: 【0784】 The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. It collects real-time audio and video data as input and generates data indicating the user's emotional state as output. This provides a basis for analyzing the user's stress and fatigue levels. 【0785】 Step 3: 【0786】 The server uses artificial intelligence to generate agricultural plans based on acquired weather information and sentiment data. It integrates the data obtained in steps 1 and 2 as input and performs data calculations. As output, it provides an optimal work schedule. This creates a plan that takes weather conditions and user sentiment into account. 【0787】 Step 4: 【0788】 The terminal receives the work schedule sent from the server and notifies the user. It receives the generated schedule as input and sends visual and auditory notifications to the user as output. These notifications are optimized for the user's emotional state and include suggestions to improve work efficiency. 【0789】 Step 5: 【0790】 The user operates a terminal to remotely control agricultural equipment. The system controls the equipment based on work schedules and terminal operation instructions as input, and performs agricultural tasks as output. This allows for efficient farming even from remote locations. 【0791】 Step 6: 【0792】 After completing a task, the terminal sends the data of the executed task to the server. It collects task execution result data as input and sends that data to the server as output. This allows for the accumulation of data that can be used to inform future agricultural planning. 【0793】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0794】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0795】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0796】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0797】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0798】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0799】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0800】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0801】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0802】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0803】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0804】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0805】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0806】 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. 【0807】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0808】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0809】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0810】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0811】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0812】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0813】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0814】 The following is further disclosed regarding the embodiments described above. 【0815】 (Claim 1) 【0816】 Obtaining weather information from external information providers is a means to an end. 【0817】 A means for analyzing weather information using artificial intelligence that automatically generates agricultural plans and formulating work schedules, 【0818】 A means of remotely controlling agricultural equipment to perform agricultural work according to a set schedule, 【0819】 A means of collecting data after work and recording it to use in improving future agricultural plans, 【0820】 A system that includes this. 【0821】 (Claim 2) 【0822】 The system according to claim 1, which predicts the harvest time and sends a notification to the user. 【0823】 (Claim 3) 【0824】 The system according to claim 1, which enables users to check the status of agricultural equipment in real time via a communication terminal. 【0825】 "Example 1" 【0826】 (Claim 1) 【0827】 A means of obtaining and analyzing weather information from external information providers, 【0828】 A means for automatically generating agricultural plans based on weather information using a generation AI model and formulating work schedules for each crop, 【0829】 A means of remotely controlling agricultural equipment via a computing device and performing agricultural work based on a formulated schedule, 【0830】 A means of collecting the progress of agricultural work and the operating status of equipment, and notifying users in real time, 【0831】 A means of recording the collected data and analyzing it to use it for improving future agricultural plans, 【0832】 A system that includes this. 【0833】 (Claim 2) 【0834】 The system according to claim 1, which predicts the harvest time using a generative AI model and notifies the user of that information. 【0835】 (Claim 3) 【0836】 The system according to claim 1, which allows users to check the status of agricultural equipment in real time via a communication device and change work instructions as needed. 【0837】 "Application Example 1" 【0838】 (Claim 1) 【0839】 Obtaining weather information from external information providers is a means to an end. 【0840】 A means for analyzing weather information using artificial intelligence that automatically generates agricultural plans and formulating an environmental schedule, 【0841】 A means of remotely controlling agricultural equipment to perform agricultural work according to a formulated schedule, 【0842】 A means of collecting information after work and recording it to use in improving future agricultural plans, 【0843】 A means that, via an interface, enables the manager of an environmental conservation area to monitor the situation in real time and adjust the environmental plan as needed, 【0844】 A system that includes this. 【0845】 (Claim 2) 【0846】 The system according to claim 1, which predicts the harvest time and sends a notification to the administrator via an information terminal. 【0847】 (Claim 3) 【0848】 The system according to claim 1, which enables an administrator to check the status of agricultural equipment in real time via a communication device. 【0849】 "Example 2 of combining an emotion engine" 【0850】 (Claim 1) 【0851】 Obtaining weather information from external information providers is a means to an end. 【0852】 A means for analyzing weather information using artificial intelligence that automatically generates agricultural plans and formulating work schedules, 【0853】 A means for analyzing the emotional state of the user, and a means for adjusting the work schedule based on said analysis, 【0854】 A means of remotely controlling agricultural equipment to perform agricultural work based on a coordinated schedule, 【0855】 A means of collecting data after work and recording it to use in improving future agricultural plans, 【0856】 A system that includes this. 【0857】 (Claim 2) 【0858】 The system according to claim 1, which predicts the harvest time and sends notifications according to the user's emotional state. 【0859】 (Claim 3) 【0860】 The system according to claim 1, which enables a user to check the status of agricultural equipment and their own emotional state in real time via a communication terminal. 【0861】 "Application example 2 when combining with an emotional engine" 【0862】 (Claim 1) 【0863】 A means for obtaining weather information from an external organization and processing input data for recognizing emotional states, 【0864】 A means of formulating work schedules by analyzing weather and sentiment data using artificial intelligence and an emotion engine that automatically generates agricultural plans, 【0865】 A means for remotely controlling agricultural equipment to perform agricultural work according to a set schedule, and for adjusting notifications and suggestions according to the user's emotional state, 【0866】 A means of collecting and recording post-work data and emotional responses to use in improving future agricultural plans, 【0867】 A system that includes this. 【0868】 (Claim 2) 【0869】 The system according to claim 1, which predicts the growth stage and harvest timing of crops and sends notifications at an appropriate time that matches the user's emotional state. 【0870】 (Claim 3) 【0871】 The system according to claim 1, which enables users to check the status and emotional feedback of agricultural equipment in real time via an information terminal. [Explanation of Symbols] 【0872】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] Means of obtaining weather information from external information providers, A means for analyzing weather information using artificial intelligence that automatically generates agricultural plans and formulating work schedules, A means of remotely controlling agricultural equipment to perform agricultural work according to a set schedule, A means of collecting data after work and recording it to use in improving future agricultural plans, A system that includes this. [Claim 2] The system according to claim 1, which predicts the harvest time and sends a notification to the user. [Claim 3] The system according to claim 1, which enables users to check the status of agricultural equipment in real time via a communication terminal.

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