system

Abstract

We provide the system. [Solution] A sensor means for detecting the remaining amount of water, A processing means that processes data from the aforementioned sensor means to determine the remaining amount of water, A communication means that automatically sends an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold, A server that receives an order instruction via the aforementioned communication means, Order processing means that performs order processing in the server A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional water server, since it was necessary to manually check the remaining amount of water and order a water bottle as needed, there was a problem that users were required to perform regular checks to appropriately manage the water supply. Also, even when using a regular delivery service, there was a risk of excess or shortage of water, resulting in increased user effort and management costs.

Means for Solving the Problems

[0005] This invention provides a system that automatically detects the remaining amount of water, processes the data, and automatically places an order when the amount is insufficient. Specifically, the system includes a sensor means for detecting the remaining amount of water, a processing means for determining the remaining amount of water by processing the data from the sensor, a communication means for automatically sending an order instruction when the determined remaining amount of water falls below a predetermined threshold, a server that receives the order instruction, and an order processing means for processing the order on the server. This system reduces the effort required for users to manually check the remaining amount of water and place an order, thereby resolving water shortages and surpluses.

[0006] "Sensor means" refers to a device or apparatus for detecting the remaining amount of water.

[0007] "Processing means" refers to a device or system that receives data from sensor means and has the function of analyzing and determining the remaining amount of water.

[0008] "Communication means" refers to a communication function or device for transmitting order instructions based on the judgment result.

[0009] A "server" is a computer system that receives order instructions from communication devices and processes those orders.

[0010] "Order processing means" refers to a function or system on a server that processes actual orders based on order instructions and arranges for the necessary goods.

[0011] "Remaining water level" refers to the volume of water present in the water dispenser.

[0012] A "threshold" is a threshold value that is triggered when the remaining amount of water falls below a set standard. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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.

Embodiments for Carrying Out the Invention

[0014] 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.

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

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

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

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

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] Embodiments of the present invention will now be described. In the following description, a system that automatically detects the remaining amount of water in a water dispenser and places an order will be described in detail, with the help of specific examples.

[0035] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0036] The terminal's processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level falls below a predetermined threshold (e.g., 30%).

[0037] When the water level falls below a threshold, the terminal's processing mechanism sends an order instruction to the server via a communication mechanism. This communication mechanism utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0038] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0039] As a concrete example, consider the following scenario: A user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. A processing device analyzes this data and confirms that the remaining amount is below a threshold. An order is sent to the server via a communication device, the server processes the order, and a new water bottle is delivered to the user. The user is unaware of this entire process, and their water supply is ensured.

[0040] In this way, the system of the present invention reduces the burden on users and eliminates water shortages or surpluses through monitoring the remaining water level and automatic ordering.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0044] Step 2:

[0045] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[0046] Step 3:

[0047] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[0048] Step 4:

[0049] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[0050] Step 5:

[0051] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[0052] Step 6:

[0053] The terminal uses a communication method to send an order instruction to the server. The order instruction includes the product ID and the order quantity (e.g., 1 bottle of water).

[0054] Step 7:

[0055] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[0056] Step 8:

[0057] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[0058] Step 9:

[0059] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[0060] Step 10:

[0061] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[0062] (Example 1)

[0063] 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."

[0064] In modern society, maintaining a stable water supply for water dispensers is crucial, but manual ordering is cumbersome, especially for home and office use, requiring considerable time and effort. Furthermore, forgetting to order at the appropriate time carries the risk of water shortages. To solve this, a system is needed that monitors water levels in real time and places orders automatically. A mechanism to accurately confirm the results of the order process and notify the user is also essential.

[0065] 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.

[0066] In this invention, the server includes means for transmitting a status code to process an order and return the result to the terminal, and means for analyzing the status code received by the terminal and notifying the user after confirming success. This makes it possible to automatically place an order when the remaining amount of water falls below a predetermined threshold, accurately confirm whether the order process was successful, and notify the user.

[0067] A "sensor" is a device used to measure the remaining amount of water, and is composed of one of the following methods: optical, ultrasonic, or pressure-based.

[0068] "Processing means" refers to a system or device for analyzing data acquired from sensor means and determining the remaining amount of water.

[0069] "Communication means" refers to a device with internet communication capabilities for transmitting order instructions generated by the processing means to a server.

[0070] A "server" is a computer system that receives order instructions transmitted via communication means and processes those orders.

[0071] "Order processing means" refers to the software or hardware function on a server that analyzes order instructions and performs the actual order process.

[0072] A "status code transmission means" is a function that allows the server to generate a status code representing the result of the order processing and return that information to the terminal.

[0073] "Means of notifying the user" refers to a function that analyzes the status code received by the terminal from the server and informs the user that the order processing was successful.

[0074] This invention relates to a system that automatically monitors the remaining amount of water in a water dispenser and automatically reorders water when a certain threshold is reached. This system includes specific devices and methods using particular hardware and software. To aid in understanding this invention, the main components will be described in detail.

[0075] System Configuration

[0076] 1. Sensor means:

[0077] Optical, ultrasonic, or pressure sensors are used. These sensors are positioned to accurately measure the remaining amount of water in the water dispenser.

[0078] For example, an ultrasonic sensor measures the distance to the water surface in a water dispenser and quantifies that data.

[0079] 2. Terminal processing means:

[0080] The system receives and analyzes data acquired from sensor devices. Specifically, it monitors the remaining water level in real time based on remaining water level data and determines whether it has fallen below a predetermined threshold (e.g., 30%).

[0081] The processing system incorporates appropriate programs, enabling automatic data analysis and order processing.

[0082] 3. Means of communication:

[0083] This device transmits order instructions created by the terminal's processing unit to a server. The communication method operates via an internet connection, ensuring consistently stable data transmission.

[0084] 4. Server:

[0085] The server receives order instructions transmitted via communication and processes the order. This process includes analyzing the received data (such as product ID and order quantity) and placing the appropriate order.

[0086] If the order is processed successfully, the server generates a status code 200 (success) and returns it to the terminal.

[0087] 5. Status code transmission means and user notification means:

[0088] The terminal receives a status code returned from the server and parses it to confirm whether the order processing was successful. It then notifies the user of the result. Notification methods include LED illumination, terminal display display, and notifications to a smartphone app.

[0089] Specific example

[0090] As a concrete example, let's consider a water dispenser used at home. The following is a typical scenario:

[0091] 1. At some point, the sensor detects that the remaining water level is 25%.

[0092] 2. The processing device analyzes this data and confirms that the remaining amount is below the threshold.

[0093] 3. An order instruction is sent to the server via a communication means, the server accepts the order, and it is executed by the order processing means.

[0094] 4. The server returns status code 200, and the terminal that receives it notifies the user that the order was successful.

[0095] Example prompts for a generative AI model

[0096] Prompt Example 1: "Please describe in detail the processing steps for the automated water dispenser ordering system, from the type of sensor used to data analysis, and the creation and transmission of order instructions."

[0097] Prompt Example 2: "Please describe in detail how a system that measures the remaining water level in a water dispenser and automatically reorders water works. Include specific actions for each step."

[0098] Thus, the system of the present invention provides automated water supply management, saving users time and effort while ensuring a consistently stable water supply.

[0099] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0100] Step 1:

[0101] Water level measurement

[0102] Specific operation: The device's sensor (optical, ultrasonic, or pressure-based) is activated periodically to measure the remaining water level.

[0103] Input: The physical amount of water remaining in the water dispenser.

[0104] Data processing: The sensor converts the measurement results into digital data.

[0105] Output: Water level data (e.g., "25% remaining").

[0106] Step 2:

[0107] Sending data

[0108] Specific operation: The terminal's sensor measures the data and transmits it to the terminal's processing unit.

[0109] Input: Water level data.

[0110] Data processing: Adjust the data format as needed and convert it to a format suitable for the processing method.

[0111] Output: Receipt of remaining water amount data to the processing device.

[0112] Step 3:

[0113] Data Analysis

[0114] Specific operation: The terminal's processing unit analyzes the received water level data and compares it to a threshold.

[0115] Input: remaining battery data.

[0116] Data calculation: Perform calculations to compare the current water level with a predetermined threshold (e.g., 30%).

[0117] Output: The result of determining whether the value falls below the threshold (e.g., "TRUE" if it falls below, "FALSE" if it does not).

[0118] Step 4:

[0119] Creating and sending order instructions

[0120] Specific operation: If the threshold is not met, the processing unit creates an order instruction and sends it to the server via the communication unit.

[0121] Input: Judgment result ("TRUE") and required information (product ID, order quantity).

[0122] Data processing: Create order instruction data in JSON format, including product ID "WATER123" and order quantity "1 bottle".

[0123] Output: Sending order instruction data to the server.

[0124] Step 5:

[0125] Receiving and processing order instructions

[0126] Specific operation: The server analyzes the order instruction data received from the terminal and processes the order.

[0127] Input: Order instruction data (product ID, order quantity).

[0128] Data processing: Analyze the received data and input instructions into the internal order processing system.

[0129] Output: Order processing result data.

[0130] Step 6:

[0131] Status code response

[0132] Specific operation: The server generates a status code 200 (success) as a result of the order processing and returns it to the terminal.

[0133] Input: Order processing result data.

[0134] Data processing: Create response data including status code 200.

[0135] Output: Sending a status code to the terminal.

[0136] Step 7:

[0137] Result notification

[0138] Specific operation: The terminal receives and parses a status code 200 returned from the server. After confirming success, it notifies the user.

[0139] Input: Status code 200.

[0140] Data calculation: Verify that the status code is 200.

[0141] Output: Executes user notifications, such as LED illumination, display information, and notifications to smartphone apps.

[0142] (Application Example 1)

[0143] 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."

[0144] Managing robot consumables in factories often relies heavily on manual processes, making timely ordering of supplies difficult when supplies are running low. Furthermore, shortages of consumables can disrupt robot operation and reduce overall factory productivity. Therefore, a system that automatically manages and replenishes consumables in a timely manner is needed.

[0145] 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.

[0146] In this invention, the server includes a sensor means for detecting the remaining amount of consumables, a processing means for processing data from the sensor means to determine the remaining amount of consumables, and a communication means for automatically sending an order instruction when the remaining amount of consumables determined by the processing means falls below a predetermined threshold. This makes it possible to automatically monitor the remaining amount of consumables and to quickly place orders when necessary.

[0147] A "sensor means" is a device for measuring the remaining amount of an object to be detected in real time or at regular intervals.

[0148] "Processing means" refers to an electronic circuit or software that analyzes data acquired from sensor means and determines the remaining amount of the object.

[0149] "Communication means" refers to a network interface for sending and receiving data and instructions, and includes the function of sending order instructions to the appropriate server.

[0150] A "server" is a computer system that processes order instructions received via communication methods and executes the necessary procedures.

[0151] "Order processing means" refers to a function implemented within the server that performs actual order processing based on received order data.

[0152] "Consumables" are items that are consumed after a certain period of use or frequency of use, and require replenishment.

[0153] "Real-time monitoring" means immediately understanding and recording the current situation without any time delay.

[0154] "Recording data at regular intervals" means acquiring and accumulating data at predetermined time intervals.

[0155] To implement this invention, a system is constructed that automatically manages the remaining amount of consumables used by factory robots and sends order instructions to a server when necessary. The specific configuration and operation of this system are described below.

[0156] Factory robots are equipped with optical, ultrasonic, or pressure-based sensors to detect the remaining amount of consumables. These sensors periodically measure the remaining amount of consumables and transmit the data to a processing unit.

[0157] The processing means analyzes data received from the sensor means to determine the remaining amount of consumables. An embedded single-board computer such as a Raspberry Pi is used as the processing means. This determination includes real-time monitoring and data recording at regular intervals. For example, it checks whether the remaining amount of consumables falls below a predetermined threshold (e.g., 30%).

[0158] When the remaining amount of consumables falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device includes a network interface using the internet. The order instruction includes necessary information such as the product ID and order quantity.

[0159] The server has an order processing mechanism for processing order instructions received via communication. This order processing mechanism is implemented within the server, analyzes the received data, and executes the necessary processing to place the order. Furthermore, the server confirms that the order processing was successful by returning a status code 200.

[0160] For example, a robot used in a factory can detect oil consumption, and if the remaining amount falls below a threshold, an order instruction is automatically sent to the supply chain management system. As a result, necessary replenishment is carried out in a timely manner, allowing the robots to continue operating and improving the overall productivity of the factory.

[0161] As a concrete example, by inputting the following prompt message into the generation AI model, it is possible to automatically generate the necessary program.

[0162] Example of a prompt:

[0163] Please create a program for a factory robot maintenance system that automatically detects the remaining quantity of consumables and places an automatic order when the quantity falls below a threshold. Specifically, the sensor will consist of either an optical, ultrasonic, or pressure sensor, periodically acquire the remaining quantity data, and send the order instruction via the internet.

[0164] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0165] Step 1:

[0166] A sensor measures the remaining amount of consumables for the factory robot.

[0167] Input: Measurement of remaining amount of consumables by sensor means

[0168] Specific operation: Optical, ultrasonic, or pressure sensors are used to periodically measure the remaining amount of consumables (e.g., oil). An analog or digital signal is generated from the sensor during this process.

[0169] Output: Remaining quantity data of consumables

[0170] Step 2:

[0171] The terminal's processing unit receives and analyzes data from the sensor unit.

[0172] Input: Remaining amount data transmitted from the sensor.

[0173] Specific operation: An embedded single-board computer such as a Raspberry Pi is used to receive data acquired from sensors. The received data is converted into a digital format, and calculations and analyses are performed to determine the remaining amount.

[0174] Output: Remaining quantity of the determined consumable

[0175] Step 3:

[0176] The terminal's processing mechanism compares the remaining amount of consumables to a threshold and generates an order instruction as needed.

[0177] Input: Remaining quantity of the determined consumable, threshold (e.g., 30%)

[0178] Specific operation: A threshold (30%) is set in advance, and this is compared to the current remaining amount of the consumable. If the remaining amount falls below the threshold, a flag is set to indicate that an order is needed.

[0179] Output: Order instructions (if necessary)

[0180] Step 4:

[0181] The terminal's processing unit sends an order instruction to the server via the communication unit.

[0182] Input: Order instructions, network interface

[0183] Specific operation: The order instruction includes necessary information such as product ID and order quantity. This information is compiled and the order instruction is sent to the server via the internet. A POST request using HTTP is used as the communication method.

[0184] Output: Send order instructions to the server

[0185] Step 5:

[0186] The server processes order instructions received via communication means.

[0187] Input: Order instructions (product ID, order quantity, etc.), order processing method within the server

[0188] Specific operation: The server receives an HTTP request and analyzes the contents of the order instruction. Based on the analysis results, the order processing mechanism is executed and the necessary order processing is carried out.

[0189] Output: Order processing result (status code 200 on success)

[0190] Step 6:

[0191] The server returns the order processing result to the terminal.

[0192] Input: Order processing result (status code)

[0193] Specific operation: If the order processing is successful, the server returns a status code 200. The terminal receives this and confirms that the order was completed successfully. If the order fails, an error status code is returned, and processing branches according to the content of the error.

[0194] Output: Order confirmation message (information regarding success or failure)

[0195] 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.

[0196] Embodiments of the present invention will now be described in detail. In this embodiment, in addition to a system that automatically detects and orders water levels, an emotion engine that recognizes user emotions is combined to provide an even more advanced system.

[0197] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0198] The processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level is below a predetermined threshold (e.g., 30%).

[0199] When the remaining water level falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0200] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0201] Furthermore, this embodiment includes an emotion engine. The emotion engine analyzes the user's voice, facial expressions, or behavior to recognize the user's emotions. For example, if a user is irritated near the water dispenser, the emotion engine can recognize that emotion and, combined with specific behaviors (e.g., a tendency for the water level to decrease faster than expected), adjust the timing and quantity of orders.

[0202] As a concrete example, suppose a user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. The processing unit analyzes this data and confirms that the remaining amount is below a threshold. If the user had just said something like, "The water ran out so quickly," the emotion engine interprets this statement as frustration. As a result, it can send a larger-than-usual order (e.g., two bottles of water) to the server via the communication system.

[0203] The server receives this order instruction and performs the necessary processing. In this way, the ordering process can be adjusted based on the user's preferences, providing a more flexible and user-friendly system.

[0204] The system of the present invention reduces the burden on users by monitoring the remaining amount of water and automatically ordering it, resolving water shortages and surpluses, and also provides further convenience by taking user feelings into consideration.

[0205] The following describes the processing flow.

[0206] Step 1:

[0207] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0208] Step 2:

[0209] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[0210] Step 3:

[0211] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[0212] Step 4:

[0213] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[0214] Step 5:

[0215] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[0216] Step 6:

[0217] The device activates an emotion engine and analyzes the user's voice, facial expressions, or actions. The emotion engine identifies the user's emotions and sends the results to a processing unit.

[0218] Step 7:

[0219] The terminal's processing mechanism determines the content of the order instruction (quantity and timing) based on whether the remaining water level falls below a threshold and on data from the emotion engine.

[0220] Step 8:

[0221] The terminal uses a communication method to send order instructions to the server. The order instructions include the product ID and the normal or adjusted order quantity (e.g., quantity increased or decreased based on sentiment).

[0222] Step 9:

[0223] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[0224] Step 10:

[0225] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[0226] Step 11:

[0227] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[0228] Step 12:

[0229] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[0230] (Example 2)

[0231] 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".

[0232] Traditional water dispenser systems require users to manually order water when the level is low, necessitating frequent checks of the remaining water level. Furthermore, the lack of consideration for user feelings can lead to frustration and dissatisfaction. There is a need to address these issues, reduce operational hassle, and provide a more user-friendly system that takes user feelings into account.

[0233] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a measuring means for detecting the remaining amount of water, a determination means for processing data from the measuring means to determine the remaining amount of water, a transmitting means for automatically sending an order instruction when the remaining amount of water determined by the determination means falls below a predetermined threshold, an information processing device that receives the order instruction via the transmitting means, a control means for performing order processing in the information processing device, an emotion analysis means for analyzing the user's emotions, and an adjustment means for the emotion analysis means to analyze the user's voice, facial expression, or actions to determine the user's emotional state and adjust the order content based on the determination result. This reduces the effort required for the user to manually order water and enables flexible ordering according to the user's emotions.

[0234] "Measuring means" refers to sensors or devices that detect the remaining amount of water.

[0235] "Determination means" refers to a device or program that processes data acquired from measurement means to analyze and determine the remaining amount of water.

[0236] "Transmission means" refers to a device or program used to transmit information and instructions obtained by the determination means to other devices or systems via a communication network.

[0237] An "information processing device" refers to a computer system that receives order instructions sent from a transmission device and processes them accordingly.

[0238] "Control means" refers to devices or programs in an information processing device that execute specific order-related processing based on received order instructions.

[0239] "Emotional analysis tools" refer to devices or programs that analyze a user's voice, facial expressions, and behavior to recognize and determine their emotional state.

[0240] "Adjustment means" refers to a device or program that has the function of adjusting the timing and content of orders based on the user's emotional state determined by the emotion analysis means.

[0241] Modes for carrying out the invention

[0242] This invention provides a system that automatically detects the remaining amount of water and places an automatic order as needed. Furthermore, it has advanced functionality that analyzes the user's emotions and adjusts the timing and quantity of orders based on the results. In this embodiment, sensors, processing means, communication means, information processing device, emotion analysis means, and adjustment means are used in combination. The specific hardware and software used are described below.

[0243] Hardware and software to be used

[0244] 1. Measurement method: Optical, ultrasonic, or pressure-type sensor.

[0245] 2. Determination method: A microcontroller or single-board computer (e.g., Raspberry Pi) for processing sensor data in real time.

[0246] 3. Transmission method: Communication devices such as Wi-Fi modules and Bluetooth modules.

[0247] 4. Information processing equipment: Cloud servers and local servers.

[0248] 5. Control means: Order management system within the server.

[0249] 6. Emotion analysis methods: Speech recognition software, image analysis software, and an AI engine that integrates them (e.g., TENSORFLOW®, PyTorch).

[0250] 7. Adjustment mechanism: Software logic for dynamically changing order details based on data obtained from the emotion analysis mechanism described above.

[0251] Specific examples of the system

[0252] Let's say a user is using a water dispenser at home. This water dispenser is equipped with an optical sensor that periodically measures the remaining water level. When the sensor detects that the water level is 25%, that data is transmitted via Wi-Fi to a terminal's detection device. The detection device analyzes this data and confirms that the water level is below the 30% threshold.

[0253] On the other hand, if a user says aloud, "The water runs out so quickly," that voice is transmitted through the microphone to an emotion analysis system. The emotion analysis system analyzes the voice and determines that the user is irritated. Based on this, the system sends a larger order quantity (e.g., 2 bottles) to the cloud server via the transmission system, instead of the usual order quantity (e.g., 1 bottle). The cloud server receives this order instruction, performs the necessary processing, and completes the order.

[0254] Examples of prompt statements

[0255] "This week, our home water dispenser will run out of water quickly, so please create a program that automatically orders additional water bottles early based on the results of an emotion engine analysis."

[0256] In this way, this system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user feelings into consideration.

[0257] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0258] Program processing flow

[0259] Step 1:

[0260] Water level detection using sensors

[0261] The terminal collects water level data from optical, ultrasonic, or pressure sensors. The measuring device measures the water level and pressure inside the water dispenser and converts these values ​​into digital data.

[0262] Input: Physical water height or pressure

[0263] Output: Digital data (e.g., "Water level 25%")

[0264] As a concrete example, the device's optical sensor measures the water surface altitude at one-minute intervals and determines that data to be "25%".

[0265] Step 2:

[0266] Data transmission to processing means notification

[0267] The terminal collects water level data and transmits it to a processing system via wireless communication. Communication methods such as Wi-Fi and Bluetooth are used.

[0268] Input: Digital data (e.g., "Water level 25%")

[0269] Output: Data sent to the processing unit.

[0270] As a specific example, digital data indicating "25% water remaining" acquired by an optical sensor is transmitted to a processing device via Wi-Fi.

[0271] Step 3:

[0272] Water level analysis and determination

[0273] The processing unit analyzes the received sensor data to determine the remaining water level. Data analysis includes real-time monitoring and data recording. A threshold (e.g., 30%) is set, and it is checked whether the level falls below this threshold.

[0274] Input: Transmitted digital data (e.g., "Remaining water volume: 25%")

[0275] Output: Analysis result (e.g., "The remaining water volume has fallen below the threshold")

[0276] As a specific example, the processing means analyzes the data of "Remaining water volume: 25%" and determines that it is below the threshold of 30%.

[0277] Step 4:

[0278] Transmission of automatic ordering instruction

[0279] Based on the determination result, the processing means transmits an automatic ordering instruction to the server. Necessary information (such as product ID, order quantity, remaining water volume, etc.) is included.

[0280] Input: Analysis result (e.g., "The remaining water volume has fallen below the threshold")

[0281] Output: Automatic ordering instruction (e.g., "Product ID 12345, Quantity 2")

[0282] As a specific example, the processing means determines that "Remaining water volume: 25%" and transmits an ordering instruction of "Product ID 12345, Quantity 2" to the server.

[0283] Step 5:

[0284] Order processing by the server

[0285] The server receives the ordering instruction from the terminal and performs order processing based on it. It checks whether the order is successful and returns a status code 200.

[0286] Input: Automatic ordering instruction (e.g., "Product ID 12345, Quantity 2")

[0287] Output: Status code of order confirmation (e.g., "Status code 200")

[0288] As a concrete example, the server receives an order instruction for "product ID 12345, quantity 2 units," registers the order in the inventory system, and returns "status code 200."

[0289] Step 6:

[0290] Emotional analysis using an emotion engine

[0291] The emotion engine analyzes what the user says near the water dispenser. Using speech recognition software, the user's speech is converted into text, and emotions are extracted from that text.

[0292] Input: User's voice (e.g., "The water runs out so quickly.")

[0293] Output: Emotion analysis result (e.g., determined to be "irritated")

[0294] For example, a user might say, "The water runs out so quickly," and the emotion engine analyzes the audio and determines it to be "frustration."

[0295] Step 7:

[0296] Adjusting the timing and quantity of orders

[0297] Based on the sentiment analysis results, the processing system adjusts the timing and quantity of orders. It increases or decreases the normal order quantity, taking into account the user's emotional state.

[0298] Input: Sentiment analysis result (e.g., "irritation")

[0299] Output: Adjusted order instruction (e.g., "Product ID 12345, Quantity 2")

[0300] As a concrete example, the emotion engine detects the user's "frustration" and changes the order from the usual one unit to two units, then sends the order instruction to the server.

[0301] The above outlines the specific processing flow and the actions taken at each step. This system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user emotions into consideration.

[0302] (Application Example 2)

[0303] 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".

[0304] Traditional water management systems simply measured the remaining water level and automatically placed an order when it fell below a predetermined threshold. This meant they couldn't respond nuancedly to user emotions or usage patterns, sometimes leading to inconvenience. In particular, traditional systems lacked the flexibility to respond when users were dissatisfied with the rate of water consumption or when water was consumed at an unexpectedly rapid pace. Furthermore, there was a need to monitor user emotional expressions, such as frustration near the water dispenser, and reflect these in the ordering process.

[0305] 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.

[0306] In this invention, the server includes a sensor means for detecting the remaining amount of water, a processing means for processing data from the sensor means to determine the remaining amount of water, a communication means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold, a server that receives the order instruction via the communication means, an order processing means for performing order processing on the server, an emotion recognition means for recognizing the user's emotions, and an order adjustment means for adjusting the timing and quantity of the order based on data from the emotion recognition means. This enables flexible water ordering according to the user's emotions and usage.

[0307] "Sensor means" refers to a device for detecting the remaining amount of water, and is composed of either an optical, ultrasonic, or pressure-based sensor.

[0308] The "processing means" is a device or program for processing data from the sensor means to determine the remaining amount of water.

[0309] The "communication means" is a network connection means for automatically transmitting an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold value.

[0310] The "server" is a central processing unit that receives an order instruction via the communication means and performs an order processing.

[0311] The "order processing means" is a function or module for executing an order based on the order instruction received by the server.

[0312] The "emotion recognition means" is a combination of hardware and software for analyzing the user's voice and expression to recognize emotions.

[0313] The "order adjustment means" is a device or program including logic or algorithms for adjusting the timing and quantity of an order based on the data obtained from the emotion recognition means.

[0314] Embodiments of the present invention will be described in detail. In this embodiment, a specific example based on a smartphone application related to an e-commerce site is shown. The system of the present invention has a configuration including the following elements.

[0315] First, in order to detect the remaining amount of water, an optical, ultrasonic, or pressure type sensor means is attached to the water server. The sensor means periodically measures the remaining amount of water in the water server and transmits the data to the processing means of the smartphone. Thereby, the user can grasp the remaining amount of water in real time.

[0316] Data from the sensor is analyzed by a processing unit on a smartphone. The processing unit monitors the data from the sensor in real time and records it at regular intervals. When the remaining water level falls below a predetermined threshold (e.g., 30%), the processing unit automatically activates a communication unit to send an order instruction. The communication unit sends the order instruction to the server via an internet connection.

[0317] The server receives order instructions via the communication device and executes the order using the order processing device. At this time, the server returns status code 200 to confirm that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0318] Furthermore, an emotion recognition mechanism has been added. This emotion recognition mechanism uses the smartphone's camera and microphone to analyze the user's voice and facial expressions to recognize the user's emotions. Emotion recognition analyzes the user's emotions, for example, when the user is irritated near the water dispenser. The analysis results are transmitted to the order adjustment mechanism, which adjusts the timing and quantity of orders. As a result, this system enables flexible ordering based on the user's emotions.

[0319] For example, if the water level in a water dispenser reaches 25% and the user says, "Why is the water running out so quickly!", the emotion recognition system will analyze this as "frustration." As a result, an order for more water bottles than usual (e.g., two bottles) is sent to the server via the communication system. The server receives the order and performs the necessary processing. This provides an ordering service that reflects the user's needs.

[0320] Example of a prompt:

[0321] Write a program that takes a picture of a user's face with their smartphone camera and analyzes their emotions. If the user is irritated, trigger a specific action. Utilize an open-source emotion recognition API. The emotions will be output with labels such as 'neutral' or 'frustrated'.

[0322] This system not only reduces the burden on users and enables appropriate responses when needed, but also allows for flexible ordering that takes user feelings into consideration.

[0323] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0324] Step 1:

[0325] The terminal acquires data from the sensor. This data includes the remaining water level in the water dispenser. Specifically, optical, ultrasonic, or pressure sensors measure the water level and transmit this data to the terminal's processing unit. The input is the sensor measurement data, and the output is the raw data of the remaining water level provided to the processing unit.

[0326] Step 2:

[0327] The terminal's processing unit analyzes data received from the sensor to determine the remaining water level. Specifically, it interprets the raw sensor data using an algorithm and converts it into a percentage display. During this process, real-time monitoring is performed, and data is recorded at regular intervals. The input is the raw sensor data, and the output is the analyzed remaining water level information.

[0328] Step 3:

[0329] When the remaining water level falls below a predetermined threshold, the terminal automatically activates a communication mechanism to send an order instruction. This communication mechanism uses an internet connection to send the order instruction to the server. The input is information from the processing device indicating that the remaining water level has fallen below the threshold, and the output is the order instruction sent to the server.

[0330] Step 4:

[0331] The server receives order instructions via communication and executes the order using the order processing mechanism. Specifically, it starts the order process based on the product ID and order quantity included in the order instruction and performs the necessary database operations. The input is the order instruction received via communication, and the output is the result of the order execution.

[0332] Step 5:

[0333] The system recognizes user emotions using the device's camera and microphone. Specifically, it acquires images of the user's facial expressions and recordings of their voice, and analyzes them using emotion recognition technology. A generative AI model is used to output emotions as labels such as "neutral" or "frustrated." The input is user data acquired from the camera and microphone, and the output is the analyzed emotion label.

[0334] Step 6:

[0335] An order adjustment mechanism operates based on the user's emotion recognition results, adjusting the timing and quantity of orders. For example, if the user is irritated, it will order more water bottles than usual. The input is the emotion recognition result, and the output is the adjusted order instruction.

[0336] 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.

[0337] 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.

[0338] 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.

[0339] [Second Embodiment]

[0340] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0341] 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.

[0342] 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).

[0343] 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.

[0344] 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.

[0345] 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).

[0346] 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.

[0347] 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.

[0348] 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.

[0349] 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.

[0350] 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.

[0351] 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".

[0352] Embodiments of the present invention will now be described. In the following description, a system that automatically detects the remaining amount of water in a water dispenser and places an order will be described in detail, with the help of specific examples.

[0353] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0354] The terminal's processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level falls below a predetermined threshold (e.g., 30%).

[0355] When the water level falls below a threshold, the terminal's processing mechanism sends an order instruction to the server via a communication mechanism. This communication mechanism utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0356] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0357] As a concrete example, consider the following scenario: A user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. A processing device analyzes this data and confirms that the remaining amount is below a threshold. An order is sent to the server via a communication device, the server processes the order, and a new water bottle is delivered to the user. The user is unaware of this entire process, and their water supply is ensured.

[0358] In this way, the system of the present invention reduces the burden on users and eliminates water shortages or surpluses through monitoring the remaining water level and automatic ordering.

[0359] The following describes the processing flow.

[0360] Step 1:

[0361] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0362] Step 2:

[0363] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[0364] Step 3:

[0365] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[0366] Step 4:

[0367] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[0368] Step 5:

[0369] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[0370] Step 6:

[0371] The terminal uses a communication method to send an order instruction to the server. The order instruction includes the product ID and the order quantity (e.g., 1 bottle of water).

[0372] Step 7:

[0373] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[0374] Step 8:

[0375] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[0376] Step 9:

[0377] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[0378] Step 10:

[0379] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[0380] (Example 1)

[0381] 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."

[0382] In modern society, maintaining a stable water supply for water dispensers is crucial, but manual ordering is cumbersome, especially for home and office use, requiring considerable time and effort. Furthermore, forgetting to order at the appropriate time carries the risk of water shortages. To solve this, a system is needed that monitors water levels in real time and places orders automatically. A mechanism to accurately confirm the results of the order process and notify the user is also essential.

[0383] 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.

[0384] In this invention, the server includes means for transmitting a status code to process an order and return the result to the terminal, and means for analyzing the status code received by the terminal and notifying the user after confirming success. This makes it possible to automatically place an order when the remaining amount of water falls below a predetermined threshold, accurately confirm whether the order process was successful, and notify the user.

[0385] A "sensor" is a device used to measure the remaining amount of water, and is composed of one of the following methods: optical, ultrasonic, or pressure-based.

[0386] "Processing means" refers to a system or device for analyzing data acquired from sensor means and determining the remaining amount of water.

[0387] "Communication means" refers to a device with internet communication capabilities for transmitting order instructions generated by the processing means to a server.

[0388] A "server" is a computer system that receives order instructions transmitted via communication means and processes those orders.

[0389] "Order processing means" refers to the software or hardware function on a server that analyzes order instructions and performs the actual order process.

[0390] A "status code transmission means" is a function that allows the server to generate a status code representing the result of the order processing and return that information to the terminal.

[0391] "Means of notifying the user" refers to a function that analyzes the status code received by the terminal from the server and informs the user that the order processing was successful.

[0392] This invention relates to a system that automatically monitors the remaining amount of water in a water dispenser and automatically reorders water when a certain threshold is reached. This system includes specific devices and methods using particular hardware and software. To aid in understanding this invention, the main components will be described in detail.

[0393] System Configuration

[0394] 1. Sensor means:

[0395] Optical, ultrasonic, or pressure sensors are used. These sensors are positioned to accurately measure the remaining amount of water in the water dispenser.

[0396] For example, an ultrasonic sensor measures the distance to the water surface in a water dispenser and quantifies that data.

[0397] 2. Terminal processing means:

[0398] The system receives and analyzes data acquired from sensor devices. Specifically, it monitors the remaining water level in real time based on remaining water level data and determines whether it has fallen below a predetermined threshold (e.g., 30%).

[0399] The processing system incorporates appropriate programs, enabling automatic data analysis and order processing.

[0400] 3. Means of communication:

[0401] This device transmits order instructions created by the terminal's processing unit to a server. The communication method operates via an internet connection, ensuring consistently stable data transmission.

[0402] 4. Server:

[0403] The server receives order instructions transmitted via communication and processes the order. This process includes analyzing the received data (such as product ID and order quantity) and placing the appropriate order.

[0404] If the order is processed successfully, the server generates a status code 200 (success) and returns it to the terminal.

[0405] 5. Status code transmission means and user notification means:

[0406] The terminal receives a status code returned from the server and parses it to confirm whether the order processing was successful. It then notifies the user of the result. Notification methods include LED illumination, terminal display display, and notifications to a smartphone app.

[0407] Specific example

[0408] As a concrete example, let's consider a water dispenser used at home. The following is a typical scenario:

[0409] 1. At some point, the sensor detects that the remaining water level is 25%.

[0410] 2. The processing device analyzes this data and confirms that the remaining amount is below the threshold.

[0411] 3. An order instruction is sent to the server via a communication means, the server accepts the order, and it is executed by the order processing means.

[0412] 4. The server returns status code 200, and the terminal that receives it notifies the user that the order was successful.

[0413] Example prompts for a generative AI model

[0414] Prompt Example 1: "Please describe in detail the processing steps for the automated water dispenser ordering system, from the type of sensor used to data analysis, and the creation and transmission of order instructions."

[0415] Prompt Example 2: "Please describe in detail how a system that measures the remaining water level in a water dispenser and automatically reorders water works. Include specific actions for each step."

[0416] Thus, the system of the present invention provides automated water supply management, saving users time and effort while ensuring a consistently stable water supply.

[0417] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0418] Step 1:

[0419] Water level measurement

[0420] Specific operation: The device's sensor (optical, ultrasonic, or pressure-based) is activated periodically to measure the remaining water level.

[0421] Input: The physical amount of water remaining in the water dispenser.

[0422] Data processing: The sensor converts the measurement results into digital data.

[0423] Output: Water level data (e.g., "25% remaining").

[0424] Step 2:

[0425] Sending data

[0426] Specific operation: The terminal's sensor measures the data and transmits it to the terminal's processing unit.

[0427] Input: Water level data.

[0428] Data processing: Adjust the data format as needed and convert it to a format suitable for the processing method.

[0429] Output: Receipt of remaining water amount data to the processing device.

[0430] Step 3:

[0431] Data Analysis

[0432] Specific operation: The terminal's processing unit analyzes the received water level data and compares it to a threshold.

[0433] Input: remaining battery data.

[0434] Data calculation: Perform calculations to compare the current water level with a predetermined threshold (e.g., 30%).

[0435] Output: The result of determining whether the value falls below the threshold (e.g., "TRUE" if it falls below, "FALSE" if it does not).

[0436] Step 4:

[0437] Creating and sending order instructions

[0438] Specific operation: If the threshold is not met, the processing unit creates an order instruction and sends it to the server via the communication unit.

[0439] Input: Judgment result ("TRUE") and required information (product ID, order quantity).

[0440] Data processing: Create order instruction data in JSON format, including product ID "WATER123" and order quantity "1 bottle".

[0441] Output: Sending order instruction data to the server.

[0442] Step 5:

[0443] Receiving and processing order instructions

[0444] Specific operation: The server analyzes the order instruction data received from the terminal and processes the order.

[0445] Input: Order instruction data (product ID, order quantity).

[0446] Data processing: Analyze the received data and input instructions into the internal order processing system.

[0447] Output: Order processing result data.

[0448] Step 6:

[0449] Status code response

[0450] Specific operation: The server generates a status code 200 (success) as a result of the order processing and returns it to the terminal.

[0451] Input: Order processing result data.

[0452] Data processing: Create response data including status code 200.

[0453] Output: Sending a status code to the terminal.

[0454] Step 7:

[0455] Result notification

[0456] Specific operation: The terminal receives and parses a status code 200 returned from the server. After confirming success, it notifies the user.

[0457] Input: Status code 200.

[0458] Data calculation: Verify that the status code is 200.

[0459] Output: Executes user notifications, such as LED illumination, display information, and notifications to smartphone apps.

[0460] (Application Example 1)

[0461] 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."

[0462] Managing robot consumables in factories often relies heavily on manual processes, making timely ordering of supplies difficult when supplies are running low. Furthermore, shortages of consumables can disrupt robot operation and reduce overall factory productivity. Therefore, a system that automatically manages and replenishes consumables in a timely manner is needed.

[0463] 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.

[0464] In this invention, the server includes a sensor means for detecting the remaining amount of consumables, a processing means for processing data from the sensor means to determine the remaining amount of consumables, and a communication means for automatically sending an order instruction when the remaining amount of consumables determined by the processing means falls below a predetermined threshold. This makes it possible to automatically monitor the remaining amount of consumables and to quickly place orders when necessary.

[0465] A "sensor means" is a device for measuring the remaining amount of an object to be detected in real time or at regular intervals.

[0466] "Processing means" refers to an electronic circuit or software that analyzes data acquired from sensor means and determines the remaining amount of the object.

[0467] "Communication means" refers to a network interface for sending and receiving data and instructions, and includes the function of sending order instructions to the appropriate server.

[0468] A "server" is a computer system that processes order instructions received via communication methods and executes the necessary procedures.

[0469] "Order processing means" refers to a function implemented within the server that performs actual order processing based on received order data.

[0470] "Consumables" are items that are consumed after a certain period of use or frequency of use, and require replenishment.

[0471] "Real-time monitoring" means immediately understanding and recording the current situation without any time delay.

[0472] "Recording data at regular intervals" means acquiring and accumulating data at predetermined time intervals.

[0473] To implement this invention, a system is constructed that automatically manages the remaining amount of consumables used by factory robots and sends order instructions to a server when necessary. The specific configuration and operation of this system are described below.

[0474] Factory robots are equipped with optical, ultrasonic, or pressure-based sensors to detect the remaining amount of consumables. These sensors periodically measure the remaining amount of consumables and transmit the data to a processing unit.

[0475] The processing means analyzes data received from the sensor means to determine the remaining amount of consumables. An embedded single-board computer such as a Raspberry Pi is used as the processing means. This determination includes real-time monitoring and data recording at regular intervals. For example, it checks whether the remaining amount of consumables falls below a predetermined threshold (e.g., 30%).

[0476] When the remaining amount of consumables falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device includes a network interface using the internet. The order instruction includes necessary information such as the product ID and order quantity.

[0477] The server has an order processing mechanism for processing order instructions received via communication. This order processing mechanism is implemented within the server, analyzes the received data, and executes the necessary processing to place the order. Furthermore, the server confirms that the order processing was successful by returning a status code 200.

[0478] For example, a robot used in a factory can detect oil consumption, and if the remaining amount falls below a threshold, an order instruction is automatically sent to the supply chain management system. As a result, necessary replenishment is carried out in a timely manner, allowing the robots to continue operating and improving the overall productivity of the factory.

[0479] As a concrete example, by inputting the following prompt message into the generation AI model, it is possible to automatically generate the necessary program.

[0480] Example of a prompt:

[0481] Please create a program for a factory robot maintenance system that automatically detects the remaining quantity of consumables and places an automatic order when the quantity falls below a threshold. Specifically, the sensor will consist of either an optical, ultrasonic, or pressure sensor, periodically acquire the remaining quantity data, and send the order instruction via the internet.

[0482] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0483] Step 1:

[0484] A sensor measures the remaining amount of consumables for the factory robot.

[0485] Input: Measurement of remaining amount of consumables by sensor means

[0486] Specific operation: Optical, ultrasonic, or pressure sensors are used to periodically measure the remaining amount of consumables (e.g., oil). An analog or digital signal is generated from the sensor during this process.

[0487] Output: Remaining quantity data of consumables

[0488] Step 2:

[0489] The terminal's processing unit receives and analyzes data from the sensor unit.

[0490] Input: Remaining amount data transmitted from the sensor.

[0491] Specific operation: An embedded single-board computer such as a Raspberry Pi is used to receive data acquired from sensors. The received data is converted into a digital format, and calculations and analyses are performed to determine the remaining amount.

[0492] Output: Remaining quantity of the determined consumable

[0493] Step 3:

[0494] The terminal's processing mechanism compares the remaining amount of consumables to a threshold and generates an order instruction as needed.

[0495] Input: Remaining quantity of the determined consumable, threshold (e.g., 30%)

[0496] Specific operation: A threshold (30%) is set in advance, and this is compared to the current remaining amount of the consumable. If the remaining amount falls below the threshold, a flag is set to indicate that an order is needed.

[0497] Output: Order instructions (if necessary)

[0498] Step 4:

[0499] The terminal's processing unit sends an order instruction to the server via the communication unit.

[0500] Input: Order instructions, network interface

[0501] Specific operation: The order instruction includes necessary information such as product ID and order quantity. This information is compiled and the order instruction is sent to the server via the internet. A POST request using HTTP is used as the communication method.

[0502] Output: Send order instructions to the server

[0503] Step 5:

[0504] The server processes order instructions received via communication means.

[0505] Input: Order instructions (product ID, order quantity, etc.), order processing method within the server

[0506] Specific operation: The server receives an HTTP request and analyzes the contents of the order instruction. Based on the analysis results, the order processing mechanism is executed and the necessary order processing is carried out.

[0507] Output: Order processing result (status code 200 on success)

[0508] Step 6:

[0509] The server returns the order processing result to the terminal.

[0510] Input: Order processing result (status code)

[0511] Specific operation: If the order processing is successful, the server returns a status code 200. The terminal receives this and confirms that the order was completed successfully. If the order fails, an error status code is returned, and processing branches according to the content of the error.

[0512] Output: Order confirmation message (information regarding success or failure)

[0513] 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.

[0514] Embodiments of the present invention will now be described in detail. In this embodiment, in addition to a system that automatically detects and orders water levels, an emotion engine that recognizes user emotions is combined to provide an even more advanced system.

[0515] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0516] The processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level is below a predetermined threshold (e.g., 30%).

[0517] When the remaining water level falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0518] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0519] Furthermore, this embodiment includes an emotion engine. The emotion engine analyzes the user's voice, facial expressions, or behavior to recognize the user's emotions. For example, if a user is irritated near the water dispenser, the emotion engine can recognize that emotion and, combined with specific behaviors (e.g., a tendency for the water level to decrease faster than expected), adjust the timing and quantity of orders.

[0520] As a concrete example, suppose a user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. The processing unit analyzes this data and confirms that the remaining amount is below a threshold. If the user had just said something like, "The water ran out so quickly," the emotion engine interprets this statement as frustration. As a result, it can send a larger-than-usual order (e.g., two bottles of water) to the server via the communication system.

[0521] The server receives this order instruction and performs the necessary processing. In this way, the ordering process can be adjusted based on the user's preferences, providing a more flexible and user-friendly system.

[0522] The system of the present invention reduces the burden on users by monitoring the remaining amount of water and automatically ordering it, resolving water shortages and surpluses, and also provides further convenience by taking user feelings into consideration.

[0523] The following describes the processing flow.

[0524] Step 1:

[0525] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0526] Step 2:

[0527] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[0528] Step 3:

[0529] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[0530] Step 4:

[0531] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[0532] Step 5:

[0533] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[0534] Step 6:

[0535] The device activates an emotion engine and analyzes the user's voice, facial expressions, or actions. The emotion engine identifies the user's emotions and sends the results to a processing unit.

[0536] Step 7:

[0537] The terminal's processing mechanism determines the content of the order instruction (quantity and timing) based on whether the remaining water level falls below a threshold and on data from the emotion engine.

[0538] Step 8:

[0539] The terminal uses a communication method to send order instructions to the server. The order instructions include the product ID and the normal or adjusted order quantity (e.g., quantity increased or decreased based on sentiment).

[0540] Step 9:

[0541] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[0542] Step 10:

[0543] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[0544] Step 11:

[0545] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[0546] Step 12:

[0547] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[0548] (Example 2)

[0549] 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".

[0550] Traditional water dispenser systems require users to manually order water when the level is low, necessitating frequent checks of the remaining water level. Furthermore, the lack of consideration for user feelings can lead to frustration and dissatisfaction. There is a need to address these issues, reduce operational hassle, and provide a more user-friendly system that takes user feelings into account.

[0551] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a measuring means for detecting the remaining amount of water, a determination means for processing data from the measuring means to determine the remaining amount of water, a transmitting means for automatically sending an order instruction when the remaining amount of water determined by the determination means falls below a predetermined threshold, an information processing device that receives the order instruction via the transmitting means, a control means for performing order processing in the information processing device, an emotion analysis means for analyzing the user's emotions, and an adjustment means for the emotion analysis means to analyze the user's voice, facial expression, or actions to determine the user's emotional state and adjust the order content based on the determination result. This reduces the effort required for the user to manually order water and enables flexible ordering according to the user's emotions.

[0552] "Measuring means" refers to sensors or devices that detect the remaining amount of water.

[0553] "Determination means" refers to a device or program that processes data acquired from measurement means to analyze and determine the remaining amount of water.

[0554] "Transmission means" refers to a device or program used to transmit information and instructions obtained by the determination means to other devices or systems via a communication network.

[0555] An "information processing device" refers to a computer system that receives order instructions sent from a transmission device and processes them accordingly.

[0556] "Control means" refers to devices or programs in an information processing device that execute specific order-related processing based on received order instructions.

[0557] "Emotional analysis tools" refer to devices or programs that analyze a user's voice, facial expressions, and behavior to recognize and determine their emotional state.

[0558] "Adjustment means" refers to a device or program that has the function of adjusting the timing and content of orders based on the user's emotional state determined by the emotion analysis means.

[0559] Modes for carrying out the invention

[0560] This invention provides a system that automatically detects the remaining amount of water and places an automatic order as needed. Furthermore, it has advanced functionality that analyzes the user's emotions and adjusts the timing and quantity of orders based on the results. In this embodiment, sensors, processing means, communication means, information processing device, emotion analysis means, and adjustment means are used in combination. The specific hardware and software used are described below.

[0561] Hardware and software to be used

[0562] 1. Measurement method: Optical, ultrasonic, or pressure-type sensor.

[0563] 2. Determination method: A microcontroller or single-board computer (e.g., Raspberry Pi) for processing sensor data in real time.

[0564] 3. Transmission method: Communication devices such as Wi-Fi modules and Bluetooth modules.

[0565] 4. Information processing equipment: Cloud servers and local servers.

[0566] 5. Control means: Order management system within the server.

[0567] 6. Emotion analysis methods: speech recognition software, image analysis software, and an AI engine that integrates them (e.g., TensorFlow, PyTorch).

[0568] 7. Adjustment mechanism: Software logic for dynamically changing order details based on data obtained from the emotion analysis mechanism described above.

[0569] Specific examples of the system

[0570] Let's say a user is using a water dispenser at home. This water dispenser is equipped with an optical sensor that periodically measures the remaining water level. When the sensor detects that the water level is 25%, that data is transmitted via Wi-Fi to a terminal's detection device. The detection device analyzes this data and confirms that the water level is below the 30% threshold.

[0571] On the other hand, if a user says aloud, "The water runs out so quickly," that voice is transmitted through the microphone to an emotion analysis system. The emotion analysis system analyzes the voice and determines that the user is irritated. Based on this, the system sends a larger order quantity (e.g., 2 bottles) to the cloud server via the transmission system, instead of the usual order quantity (e.g., 1 bottle). The cloud server receives this order instruction, performs the necessary processing, and completes the order.

[0572] Examples of prompt statements

[0573] "This week, our home water dispenser will run out of water quickly, so please create a program that automatically orders additional water bottles early based on the results of an emotion engine analysis."

[0574] In this way, this system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user feelings into consideration.

[0575] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0576] Program processing flow

[0577] Step 1:

[0578] Water level detection using sensors

[0579] The terminal collects water level data from optical, ultrasonic, or pressure sensors. The measuring device measures the water level and pressure inside the water dispenser and converts these values ​​into digital data.

[0580] Input: Physical water height or pressure

[0581] Output: Digital data (e.g., "Water level 25%")

[0582] As a concrete example, the device's optical sensor measures the water surface altitude at one-minute intervals and determines that data to be "25%".

[0583] Step 2:

[0584] Data transmission to processing means notification

[0585] The terminal collects water level data and transmits it to a processing system via wireless communication. Communication methods such as Wi-Fi and Bluetooth are used.

[0586] Input: Digital data (e.g., "Water level 25%")

[0587] Output: Data sent to the processing unit.

[0588] As a specific example, digital data indicating "25% water remaining" acquired by an optical sensor is transmitted to a processing device via Wi-Fi.

[0589] Step 3:

[0590] Water level analysis and determination

[0591] The processing unit analyzes the received sensor data to determine the remaining water level. Data analysis includes real-time monitoring and data recording. A threshold (e.g., 30%) is set, and it is checked whether the level falls below this threshold.

[0592] Input: Sent digital data (e.g., "Water level 25%")

[0593] Output: Analysis results (e.g., "The remaining water level has fallen below the threshold")

[0594] As a concrete example, the processing device analyzes data showing "25% water remaining" and determines that this is below the 30% threshold.

[0595] Step 4:

[0596] Sending automated order instructions

[0597] Based on the judgment result, the processing device sends an automatic order instruction to the server. This instruction includes necessary information (product ID, order quantity, remaining water level, etc.).

[0598] Input: Analysis result (e.g., "The remaining water level has fallen below the threshold")

[0599] Output: Automatic order instruction (Example: "Product ID 12345, Quantity 2")

[0600] As a specific example, the processing device determines that "the remaining water level is 25%" and sends an order instruction to the server for "product ID 12345, quantity 2 bottles".

[0601] Step 5:

[0602] Order processing by server

[0603] The server receives order instructions from the terminal and processes the order based on them. It then checks whether the order was successful and returns a status code of 200.

[0604] Input: Automatic order instruction (Example: "Product ID 12345, Quantity 2")

[0605] Output: Order confirmation status code (e.g., "Status code 200")

[0606] As a concrete example, the server receives an order instruction for "product ID 12345, quantity 2 units," registers the order in the inventory system, and returns "status code 200."

[0607] Step 6:

[0608] Emotional analysis using an emotion engine

[0609] The emotion engine analyzes what the user says near the water dispenser. Using speech recognition software, the user's speech is converted into text, and emotions are extracted from that text.

[0610] Input: User's voice (e.g., "The water runs out so quickly.")

[0611] Output: Emotion analysis result (e.g., determined to be "irritated")

[0612] For example, a user might say, "The water runs out so quickly," and the emotion engine analyzes the audio and determines it to be "frustration."

[0613] Step 7:

[0614] Adjusting the timing and quantity of orders

[0615] Based on the sentiment analysis results, the processing system adjusts the timing and quantity of orders. It increases or decreases the normal order quantity, taking into account the user's emotional state.

[0616] Input: Sentiment analysis result (e.g., "irritation")

[0617] Output: Adjusted order instruction (e.g., "Product ID 12345, Quantity 2")

[0618] As a concrete example, the emotion engine detects the user's "frustration" and changes the order from the usual one unit to two units, then sends the order instruction to the server.

[0619] The above outlines the specific processing flow and the actions taken at each step. This system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user emotions into consideration.

[0620] (Application Example 2)

[0621] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0622] Traditional water management systems simply measured the remaining water level and automatically placed an order when it fell below a predetermined threshold. This meant they couldn't respond nuancedly to user emotions or usage patterns, sometimes leading to inconvenience. In particular, traditional systems lacked the flexibility to respond when users were dissatisfied with the rate of water consumption or when water was consumed at an unexpectedly rapid pace. Furthermore, there was a need to monitor user emotional expressions, such as frustration near the water dispenser, and reflect these in the ordering process.

[0623] 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.

[0624] In this invention, the server includes a sensor means for detecting the remaining amount of water, a processing means for processing data from the sensor means to determine the remaining amount of water, a communication means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold, a server that receives the order instruction via the communication means, an order processing means for performing order processing on the server, an emotion recognition means for recognizing the user's emotions, and an order adjustment means for adjusting the timing and quantity of the order based on data from the emotion recognition means. This enables flexible water ordering according to the user's emotions and usage.

[0625] "Sensor means" refers to a device for detecting the remaining amount of water, and is composed of either an optical, ultrasonic, or pressure-based sensor.

[0626] "Processing means" refers to a device or program for processing data from the sensor means to determine the remaining amount of water.

[0627] "Communication means" refers to network connection means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold.

[0628] A "server" is a central processing unit that receives order instructions via the aforementioned communication means and processes the orders.

[0629] "Order processing means" refers to a function or module that executes an order based on an order instruction received by the server.

[0630] An "emotion recognition system" is a combination of hardware and software that analyzes a user's voice and facial expressions to recognize their emotions.

[0631] "Order adjustment means" refers to a device or program that includes logic or algorithms for adjusting the timing and quantity of orders based on data obtained from the emotion recognition means.

[0632] Embodiments of the present invention will now be described in detail. This embodiment provides a specific example based on a smartphone application related to an e-commerce site. The system of the present invention has the following configuration:

[0633] First, to detect the remaining water level, an optical, ultrasonic, or pressure-type sensor is installed in the water dispenser. The sensor periodically measures the amount of water remaining in the dispenser and transmits this data to a processing device in a smartphone. This allows the user to know the remaining water level in real time.

[0634] Data from the sensor is analyzed by a processing unit on a smartphone. The processing unit monitors the data from the sensor in real time and records it at regular intervals. When the remaining water level falls below a predetermined threshold (e.g., 30%), the processing unit automatically activates a communication unit to send an order instruction. The communication unit sends the order instruction to the server via an internet connection.

[0635] The server receives order instructions via the communication device and executes the order using the order processing device. At this time, the server returns status code 200 to confirm that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0636] Furthermore, an emotion recognition mechanism has been added. This emotion recognition mechanism uses the smartphone's camera and microphone to analyze the user's voice and facial expressions to recognize the user's emotions. Emotion recognition analyzes the user's emotions, for example, when the user is irritated near the water dispenser. The analysis results are transmitted to the order adjustment mechanism, which adjusts the timing and quantity of orders. As a result, this system enables flexible ordering based on the user's emotions.

[0637] For example, if the water level in a water dispenser reaches 25% and the user says, "Why is the water running out so quickly!", the emotion recognition system will analyze this as "frustration." As a result, an order for more water bottles than usual (e.g., two bottles) is sent to the server via the communication system. The server receives the order and performs the necessary processing. This provides an ordering service that reflects the user's needs.

[0638] Example of a prompt:

[0639] Write a program that takes a picture of a user's face with their smartphone camera and analyzes their emotions. If the user is irritated, trigger a specific action. Utilize an open-source emotion recognition API. The emotions will be output with labels such as 'neutral' or 'frustrated'.

[0640] This system not only reduces the burden on users and enables appropriate responses when needed, but also allows for flexible ordering that takes user feelings into consideration.

[0641] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0642] Step 1:

[0643] The terminal acquires data from the sensor. This data includes the remaining water level in the water dispenser. Specifically, optical, ultrasonic, or pressure sensors measure the water level and transmit this data to the terminal's processing unit. The input is the sensor measurement data, and the output is the raw data of the remaining water level provided to the processing unit.

[0644] Step 2:

[0645] The terminal's processing unit analyzes data received from the sensor to determine the remaining water level. Specifically, it interprets the raw sensor data using an algorithm and converts it into a percentage display. During this process, real-time monitoring is performed, and data is recorded at regular intervals. The input is the raw sensor data, and the output is the analyzed remaining water level information.

[0646] Step 3:

[0647] When the remaining water level falls below a predetermined threshold, the terminal automatically activates a communication mechanism to send an order instruction. This communication mechanism uses an internet connection to send the order instruction to the server. The input is information from the processing device indicating that the remaining water level has fallen below the threshold, and the output is the order instruction sent to the server.

[0648] Step 4:

[0649] The server receives order instructions via communication and executes the order using the order processing mechanism. Specifically, it starts the order process based on the product ID and order quantity included in the order instruction and performs the necessary database operations. The input is the order instruction received via communication, and the output is the result of the order execution.

[0650] Step 5:

[0651] The system recognizes user emotions using the device's camera and microphone. Specifically, it acquires images of the user's facial expressions and recordings of their voice, and analyzes them using emotion recognition technology. A generative AI model is used to output emotions as labels such as "neutral" or "frustrated." The input is user data acquired from the camera and microphone, and the output is the analyzed emotion label.

[0652] Step 6:

[0653] An order adjustment mechanism operates based on the user's emotion recognition results, adjusting the timing and quantity of orders. For example, if the user is irritated, it will order more water bottles than usual. The input is the emotion recognition result, and the output is the adjusted order instruction.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] [Third Embodiment]

[0658] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0659] 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.

[0660] 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).

[0661] 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.

[0662] 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.

[0663] 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).

[0664] 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.

[0665] 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.

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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".

[0670] Embodiments of the present invention will now be described. In the following description, a system that automatically detects the remaining amount of water in a water dispenser and places an order will be described in detail, with the help of specific examples.

[0671] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0672] The terminal's processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level falls below a predetermined threshold (e.g., 30%).

[0673] When the water level falls below a threshold, the terminal's processing mechanism sends an order instruction to the server via a communication mechanism. This communication mechanism utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0674] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0675] As a concrete example, consider the following scenario: A user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. A processing device analyzes this data and confirms that the remaining amount is below a threshold. An order is sent to the server via a communication device, the server processes the order, and a new water bottle is delivered to the user. The user is unaware of this entire process, and their water supply is ensured.

[0676] In this way, the system of the present invention reduces the burden on users and eliminates water shortages or surpluses through monitoring the remaining water level and automatic ordering.

[0677] The following describes the processing flow.

[0678] Step 1:

[0679] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0680] Step 2:

[0681] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[0682] Step 3:

[0683] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[0684] Step 4:

[0685] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[0686] Step 5:

[0687] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[0688] Step 6:

[0689] The terminal uses a communication method to send an order instruction to the server. The order instruction includes the product ID and the order quantity (e.g., 1 bottle of water).

[0690] Step 7:

[0691] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[0692] Step 8:

[0693] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[0694] Step 9:

[0695] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[0696] Step 10:

[0697] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[0698] (Example 1)

[0699] 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."

[0700] In modern society, maintaining a stable water supply for water dispensers is crucial, but manual ordering is cumbersome, especially for home and office use, requiring considerable time and effort. Furthermore, forgetting to order at the appropriate time carries the risk of water shortages. To solve this, a system is needed that monitors water levels in real time and places orders automatically. A mechanism to accurately confirm the results of the order process and notify the user is also essential.

[0701] 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.

[0702] In this invention, the server includes means for transmitting a status code to process an order and return the result to the terminal, and means for analyzing the status code received by the terminal and notifying the user after confirming success. This makes it possible to automatically place an order when the remaining amount of water falls below a predetermined threshold, accurately confirm whether the order process was successful, and notify the user.

[0703] A "sensor" is a device used to measure the remaining amount of water, and is composed of one of the following methods: optical, ultrasonic, or pressure-based.

[0704] "Processing means" refers to a system or device for analyzing data acquired from sensor means and determining the remaining amount of water.

[0705] "Communication means" refers to a device with internet communication capabilities for transmitting order instructions generated by the processing means to a server.

[0706] A "server" is a computer system that receives order instructions transmitted via communication means and processes those orders.

[0707] "Order processing means" refers to the software or hardware function on a server that analyzes order instructions and performs the actual order process.

[0708] A "status code transmission means" is a function that allows the server to generate a status code representing the result of the order processing and return that information to the terminal.

[0709] "Means of notifying the user" refers to a function that analyzes the status code received by the terminal from the server and informs the user that the order processing was successful.

[0710] This invention relates to a system that automatically monitors the remaining amount of water in a water dispenser and automatically reorders water when a certain threshold is reached. This system includes specific devices and methods using particular hardware and software. To aid in understanding this invention, the main components will be described in detail.

[0711] System Configuration

[0712] 1. Sensor means:

[0713] Optical, ultrasonic, or pressure sensors are used. These sensors are positioned to accurately measure the remaining amount of water in the water dispenser.

[0714] For example, an ultrasonic sensor measures the distance to the water surface in a water dispenser and quantifies that data.

[0715] 2. Terminal processing means:

[0716] The system receives and analyzes data acquired from sensor devices. Specifically, it monitors the remaining water level in real time based on remaining water level data and determines whether it has fallen below a predetermined threshold (e.g., 30%).

[0717] The processing system incorporates appropriate programs, enabling automatic data analysis and order processing.

[0718] 3. Means of communication:

[0719] This device transmits order instructions created by the terminal's processing unit to a server. The communication method operates via an internet connection, ensuring consistently stable data transmission.

[0720] 4. Server:

[0721] The server receives order instructions transmitted via communication and processes the order. This process includes analyzing the received data (such as product ID and order quantity) and placing the appropriate order.

[0722] If the order is processed successfully, the server generates a status code 200 (success) and returns it to the terminal.

[0723] 5. Status code transmission means and user notification means:

[0724] The terminal receives a status code returned from the server and parses it to confirm whether the order processing was successful. It then notifies the user of the result. Notification methods include LED illumination, terminal display display, and notifications to a smartphone app.

[0725] Specific example

[0726] As a concrete example, let's consider a water dispenser used at home. The following is a typical scenario:

[0727] 1. At some point, the sensor detects that the remaining water level is 25%.

[0728] 2. The processing device analyzes this data and confirms that the remaining amount is below the threshold.

[0729] 3. An order instruction is sent to the server via a communication means, the server accepts the order, and it is executed by the order processing means.

[0730] 4. The server returns status code 200, and the terminal that receives it notifies the user that the order was successful.

[0731] Example prompts for a generative AI model

[0732] Prompt Example 1: "Please describe in detail the processing steps for the automated water dispenser ordering system, from the type of sensor used to data analysis, and the creation and transmission of order instructions."

[0733] Prompt Example 2: "Please describe in detail how a system that measures the remaining water level in a water dispenser and automatically reorders water works. Include specific actions for each step."

[0734] Thus, the system of the present invention provides automated water supply management, saving users time and effort while ensuring a consistently stable water supply.

[0735] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0736] Step 1:

[0737] Water level measurement

[0738] Specific operation: The device's sensor (optical, ultrasonic, or pressure-based) is activated periodically to measure the remaining water level.

[0739] Input: The physical amount of water remaining in the water dispenser.

[0740] Data processing: The sensor converts the measurement results into digital data.

[0741] Output: Water level data (e.g., "25% remaining").

[0742] Step 2:

[0743] Sending data

[0744] Specific operation: The terminal's sensor measures the data and transmits it to the terminal's processing unit.

[0745] Input: Water level data.

[0746] Data processing: Adjust the data format as needed and convert it to a format suitable for the processing method.

[0747] Output: Receipt of remaining water amount data to the processing device.

[0748] Step 3:

[0749] Data Analysis

[0750] Specific operation: The terminal's processing unit analyzes the received water level data and compares it to a threshold.

[0751] Input: remaining battery data.

[0752] Data calculation: Perform calculations to compare the current water level with a predetermined threshold (e.g., 30%).

[0753] Output: The result of determining whether the value falls below the threshold (e.g., "TRUE" if it falls below, "FALSE" if it does not).

[0754] Step 4:

[0755] Creating and sending order instructions

[0756] Specific operation: If the threshold is not met, the processing unit creates an order instruction and sends it to the server via the communication unit.

[0757] Input: Judgment result ("TRUE") and required information (product ID, order quantity).

[0758] Data processing: Create order instruction data in JSON format, including product ID "WATER123" and order quantity "1 bottle".

[0759] Output: Sending order instruction data to the server.

[0760] Step 5:

[0761] Receiving and processing order instructions

[0762] Specific operation: The server analyzes the order instruction data received from the terminal and processes the order.

[0763] Input: Order instruction data (product ID, order quantity).

[0764] Data processing: Analyze the received data and input instructions into the internal order processing system.

[0765] Output: Order processing result data.

[0766] Step 6:

[0767] Status code response

[0768] Specific operation: The server generates a status code 200 (success) as a result of the order processing and returns it to the terminal.

[0769] Input: Order processing result data.

[0770] Data processing: Create response data including status code 200.

[0771] Output: Sending a status code to the terminal.

[0772] Step 7:

[0773] Result notification

[0774] Specific operation: The terminal receives and parses a status code 200 returned from the server. After confirming success, it notifies the user.

[0775] Input: Status code 200.

[0776] Data calculation: Verify that the status code is 200.

[0777] Output: Executes user notifications, such as LED illumination, display information, and notifications to smartphone apps.

[0778] (Application Example 1)

[0779] 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."

[0780] Managing robot consumables in factories often relies heavily on manual processes, making timely ordering of supplies difficult when supplies are running low. Furthermore, shortages of consumables can disrupt robot operation and reduce overall factory productivity. Therefore, a system that automatically manages and replenishes consumables in a timely manner is needed.

[0781] 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.

[0782] In this invention, the server includes a sensor means for detecting the remaining amount of consumables, a processing means for processing data from the sensor means to determine the remaining amount of consumables, and a communication means for automatically sending an order instruction when the remaining amount of consumables determined by the processing means falls below a predetermined threshold. This makes it possible to automatically monitor the remaining amount of consumables and to quickly place orders when necessary.

[0783] A "sensor means" is a device for measuring the remaining amount of an object to be detected in real time or at regular intervals.

[0784] "Processing means" refers to an electronic circuit or software that analyzes data acquired from sensor means and determines the remaining amount of the object.

[0785] "Communication means" refers to a network interface for sending and receiving data and instructions, and includes the function of sending order instructions to the appropriate server.

[0786] A "server" is a computer system that processes order instructions received via communication methods and executes the necessary procedures.

[0787] "Order processing means" refers to a function implemented within the server that performs actual order processing based on received order data.

[0788] "Consumables" are items that are consumed after a certain period of use or frequency of use, and require replenishment.

[0789] "Real-time monitoring" means immediately understanding and recording the current situation without any time delay.

[0790] "Recording data at regular intervals" means acquiring and accumulating data at predetermined time intervals.

[0791] To implement this invention, a system is constructed that automatically manages the remaining amount of consumables used by factory robots and sends order instructions to a server when necessary. The specific configuration and operation of this system are described below.

[0792] Factory robots are equipped with optical, ultrasonic, or pressure-based sensors to detect the remaining amount of consumables. These sensors periodically measure the remaining amount of consumables and transmit the data to a processing unit.

[0793] The processing means analyzes data received from the sensor means to determine the remaining amount of consumables. An embedded single-board computer such as a Raspberry Pi is used as the processing means. This determination includes real-time monitoring and data recording at regular intervals. For example, it checks whether the remaining amount of consumables falls below a predetermined threshold (e.g., 30%).

[0794] When the remaining amount of consumables falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device includes a network interface using the internet. The order instruction includes necessary information such as the product ID and order quantity.

[0795] The server has an order processing mechanism for processing order instructions received via communication. This order processing mechanism is implemented within the server, analyzes the received data, and executes the necessary processing to place the order. Furthermore, the server confirms that the order processing was successful by returning a status code 200.

[0796] For example, a robot used in a factory can detect oil consumption, and if the remaining amount falls below a threshold, an order instruction is automatically sent to the supply chain management system. As a result, necessary replenishment is carried out in a timely manner, allowing the robots to continue operating and improving the overall productivity of the factory.

[0797] As a concrete example, by inputting the following prompt message into the generation AI model, it is possible to automatically generate the necessary program.

[0798] Example of a prompt:

[0799] Please create a program for a factory robot maintenance system that automatically detects the remaining quantity of consumables and places an automatic order when the quantity falls below a threshold. Specifically, the sensor will consist of either an optical, ultrasonic, or pressure sensor, periodically acquire the remaining quantity data, and send the order instruction via the internet.

[0800] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0801] Step 1:

[0802] A sensor measures the remaining amount of consumables for the factory robot.

[0803] Input: Measurement of remaining amount of consumables by sensor means

[0804] Specific operation: Optical, ultrasonic, or pressure sensors are used to periodically measure the remaining amount of consumables (e.g., oil). An analog or digital signal is generated from the sensor during this process.

[0805] Output: Remaining quantity data of consumables

[0806] Step 2:

[0807] The terminal's processing unit receives and analyzes data from the sensor unit.

[0808] Input: Remaining amount data transmitted from the sensor.

[0809] Specific operation: An embedded single-board computer such as a Raspberry Pi is used to receive data acquired from sensors. The received data is converted into a digital format, and calculations and analyses are performed to determine the remaining amount.

[0810] Output: Remaining quantity of the determined consumable

[0811] Step 3:

[0812] The terminal's processing mechanism compares the remaining amount of consumables to a threshold and generates an order instruction as needed.

[0813] Input: Remaining quantity of the determined consumable, threshold (e.g., 30%)

[0814] Specific operation: A threshold (30%) is set in advance, and this is compared to the current remaining amount of the consumable. If the remaining amount falls below the threshold, a flag is set to indicate that an order is needed.

[0815] Output: Order instructions (if necessary)

[0816] Step 4:

[0817] The terminal's processing unit sends an order instruction to the server via the communication unit.

[0818] Input: Order instructions, network interface

[0819] Specific operation: The order instruction includes necessary information such as product ID and order quantity. This information is compiled and the order instruction is sent to the server via the internet. A POST request using HTTP is used as the communication method.

[0820] Output: Send order instructions to the server

[0821] Step 5:

[0822] The server processes order instructions received via communication means.

[0823] Input: Order instructions (product ID, order quantity, etc.), order processing method within the server

[0824] Specific operation: The server receives an HTTP request and analyzes the contents of the order instruction. Based on the analysis results, the order processing mechanism is executed and the necessary order processing is carried out.

[0825] Output: Order processing result (status code 200 on success)

[0826] Step 6:

[0827] The server returns the order processing result to the terminal.

[0828] Input: Order processing result (status code)

[0829] Specific operation: If the order processing is successful, the server returns a status code 200. The terminal receives this and confirms that the order was completed successfully. If the order fails, an error status code is returned, and processing branches according to the content of the error.

[0830] Output: Order confirmation message (information regarding success or failure)

[0831] 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.

[0832] Embodiments of the present invention will now be described in detail. In this embodiment, in addition to a system that automatically detects and orders water levels, an emotion engine that recognizes user emotions is combined to provide an even more advanced system.

[0833] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0834] The processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level is below a predetermined threshold (e.g., 30%).

[0835] When the remaining water level falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0836] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0837] Furthermore, this embodiment includes an emotion engine. The emotion engine analyzes the user's voice, facial expressions, or behavior to recognize the user's emotions. For example, if a user is irritated near the water dispenser, the emotion engine can recognize that emotion and, combined with specific behaviors (e.g., a tendency for the water level to decrease faster than expected), adjust the timing and quantity of orders.

[0838] As a concrete example, suppose a user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. The processing unit analyzes this data and confirms that the remaining amount is below a threshold. If the user had just said something like, "The water ran out so quickly," the emotion engine interprets this statement as frustration. As a result, it can send a larger-than-usual order (e.g., two bottles of water) to the server via the communication system.

[0839] The server receives this order instruction and performs the necessary processing. In this way, the ordering process can be adjusted based on the user's preferences, providing a more flexible and user-friendly system.

[0840] The system of the present invention reduces the burden on users by monitoring the remaining amount of water and automatically ordering it, resolving water shortages and surpluses, and also provides further convenience by taking user feelings into consideration.

[0841] The following describes the processing flow.

[0842] Step 1:

[0843] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0844] Step 2:

[0845] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[0846] Step 3:

[0847] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[0848] Step 4:

[0849] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[0850] Step 5:

[0851] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[0852] Step 6:

[0853] The device activates an emotion engine and analyzes the user's voice, facial expressions, or actions. The emotion engine identifies the user's emotions and sends the results to a processing unit.

[0854] Step 7:

[0855] The terminal's processing mechanism determines the content of the order instruction (quantity and timing) based on whether the remaining water level falls below a threshold and on data from the emotion engine.

[0856] Step 8:

[0857] The terminal uses a communication method to send order instructions to the server. The order instructions include the product ID and the normal or adjusted order quantity (e.g., quantity increased or decreased based on sentiment).

[0858] Step 9:

[0859] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[0860] Step 10:

[0861] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[0862] Step 11:

[0863] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[0864] Step 12:

[0865] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[0866] (Example 2)

[0867] 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."

[0868] Traditional water dispenser systems require users to manually order water when the level is low, necessitating frequent checks of the remaining water level. Furthermore, the lack of consideration for user feelings can lead to frustration and dissatisfaction. There is a need to address these issues, reduce operational hassle, and provide a more user-friendly system that takes user feelings into account.

[0869] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a measuring means for detecting the remaining amount of water, a determination means for processing data from the measuring means to determine the remaining amount of water, a transmitting means for automatically sending an order instruction when the remaining amount of water determined by the determination means falls below a predetermined threshold, an information processing device that receives the order instruction via the transmitting means, a control means for performing order processing in the information processing device, an emotion analysis means for analyzing the user's emotions, and an adjustment means for the emotion analysis means to analyze the user's voice, facial expression, or actions to determine the user's emotional state and adjust the order content based on the determination result. This reduces the effort required for the user to manually order water and enables flexible ordering according to the user's emotions.

[0870] "Measuring means" refers to sensors or devices that detect the remaining amount of water.

[0871] "Determination means" refers to a device or program that processes data acquired from measurement means to analyze and determine the remaining amount of water.

[0872] "Transmission means" refers to a device or program used to transmit information and instructions obtained by the determination means to other devices or systems via a communication network.

[0873] An "information processing device" refers to a computer system that receives order instructions sent from a transmission device and processes them accordingly.

[0874] "Control means" refers to devices or programs in an information processing device that execute specific order-related processing based on received order instructions.

[0875] "Emotional analysis tools" refer to devices or programs that analyze a user's voice, facial expressions, and behavior to recognize and determine their emotional state.

[0876] "Adjustment means" refers to a device or program that has the function of adjusting the timing and content of orders based on the user's emotional state determined by the emotion analysis means.

[0877] Modes for carrying out the invention

[0878] This invention provides a system that automatically detects the remaining amount of water and places an automatic order as needed. Furthermore, it has advanced functionality that analyzes the user's emotions and adjusts the timing and quantity of orders based on the results. In this embodiment, sensors, processing means, communication means, information processing device, emotion analysis means, and adjustment means are used in combination. The specific hardware and software used are described below.

[0879] Hardware and software to be used

[0880] 1. Measurement method: Optical, ultrasonic, or pressure-type sensor.

[0881] 2. Determination method: A microcontroller or single-board computer (e.g., Raspberry Pi) for processing sensor data in real time.

[0882] 3. Transmission method: Communication devices such as Wi-Fi modules and Bluetooth modules.

[0883] 4. Information processing equipment: Cloud servers and local servers.

[0884] 5. Control means: Order management system within the server.

[0885] 6. Emotion analysis methods: speech recognition software, image analysis software, and an AI engine that integrates them (e.g., TensorFlow, PyTorch).

[0886] 7. Adjustment mechanism: Software logic for dynamically changing order details based on data obtained from the emotion analysis mechanism described above.

[0887] Specific examples of the system

[0888] Let's say a user is using a water dispenser at home. This water dispenser is equipped with an optical sensor that periodically measures the remaining water level. When the sensor detects that the water level is 25%, that data is transmitted via Wi-Fi to a terminal's detection device. The detection device analyzes this data and confirms that the water level is below the 30% threshold.

[0889] On the other hand, if a user says aloud, "The water runs out so quickly," that voice is transmitted through the microphone to an emotion analysis system. The emotion analysis system analyzes the voice and determines that the user is irritated. Based on this, the system sends a larger order quantity (e.g., 2 bottles) to the cloud server via the transmission system, instead of the usual order quantity (e.g., 1 bottle). The cloud server receives this order instruction, performs the necessary processing, and completes the order.

[0890] Examples of prompt statements

[0891] "This week, our home water dispenser will run out of water quickly, so please create a program that automatically orders additional water bottles early based on the results of an emotion engine analysis."

[0892] In this way, this system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user feelings into consideration.

[0893] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0894] Program processing flow

[0895] Step 1:

[0896] Water level detection using sensors

[0897] The terminal collects water level data from optical, ultrasonic, or pressure sensors. The measuring device measures the water level and pressure inside the water dispenser and converts these values ​​into digital data.

[0898] Input: Physical water height or pressure

[0899] Output: Digital data (e.g., "Water level 25%")

[0900] As a concrete example, the device's optical sensor measures the water surface altitude at one-minute intervals and determines that data to be "25%".

[0901] Step 2:

[0902] Data transmission to processing means notification

[0903] The terminal collects water level data and transmits it to a processing system via wireless communication. Communication methods such as Wi-Fi and Bluetooth are used.

[0904] Input: Digital data (e.g., "Water level 25%")

[0905] Output: Data sent to the processing unit.

[0906] As a specific example, digital data indicating "25% water remaining" acquired by an optical sensor is transmitted to a processing device via Wi-Fi.

[0907] Step 3:

[0908] Water level analysis and determination

[0909] The processing unit analyzes the received sensor data to determine the remaining water level. Data analysis includes real-time monitoring and data recording. A threshold (e.g., 30%) is set, and it is checked whether the level falls below this threshold.

[0910] Input: Sent digital data (e.g., "Water level 25%")

[0911] Output: Analysis results (e.g., "The remaining water level has fallen below the threshold")

[0912] As a concrete example, the processing device analyzes data showing "25% water remaining" and determines that this is below the 30% threshold.

[0913] Step 4:

[0914] Sending automated order instructions

[0915] Based on the judgment result, the processing device sends an automatic order instruction to the server. This instruction includes necessary information (product ID, order quantity, remaining water level, etc.).

[0916] Input: Analysis result (e.g., "The remaining water level has fallen below the threshold")

[0917] Output: Automatic order instruction (Example: "Product ID 12345, Quantity 2")

[0918] As a specific example, the processing device determines that "the remaining water level is 25%" and sends an order instruction to the server for "product ID 12345, quantity 2 bottles".

[0919] Step 5:

[0920] Order processing by server

[0921] The server receives order instructions from the terminal and processes the order based on them. It then checks whether the order was successful and returns a status code of 200.

[0922] Input: Automatic order instruction (Example: "Product ID 12345, Quantity 2")

[0923] Output: Order confirmation status code (e.g., "Status code 200")

[0924] As a concrete example, the server receives an order instruction for "product ID 12345, quantity 2 units," registers the order in the inventory system, and returns "status code 200."

[0925] Step 6:

[0926] Emotional analysis using an emotion engine

[0927] The emotion engine analyzes what the user says near the water dispenser. Using speech recognition software, the user's speech is converted into text, and emotions are extracted from that text.

[0928] Input: User's voice (e.g., "The water runs out so quickly.")

[0929] Output: Emotion analysis result (e.g., determined to be "irritated")

[0930] For example, a user might say, "The water runs out so quickly," and the emotion engine analyzes the audio and determines it to be "frustration."

[0931] Step 7:

[0932] Adjusting the timing and quantity of orders

[0933] Based on the sentiment analysis results, the processing system adjusts the timing and quantity of orders. It increases or decreases the normal order quantity, taking into account the user's emotional state.

[0934] Input: Sentiment analysis result (e.g., "irritation")

[0935] Output: Adjusted order instruction (e.g., "Product ID 12345, Quantity 2")

[0936] As a concrete example, the emotion engine detects the user's "frustration" and changes the order from the usual one unit to two units, then sends the order instruction to the server.

[0937] The above outlines the specific processing flow and the actions taken at each step. This system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user emotions into consideration.

[0938] (Application Example 2)

[0939] 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."

[0940] Traditional water management systems simply measured the remaining water level and automatically placed an order when it fell below a predetermined threshold. This meant they couldn't respond nuancedly to user emotions or usage patterns, sometimes leading to inconvenience. In particular, traditional systems lacked the flexibility to respond when users were dissatisfied with the rate of water consumption or when water was consumed at an unexpectedly rapid pace. Furthermore, there was a need to monitor user emotional expressions, such as frustration near the water dispenser, and reflect these in the ordering process.

[0941] 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.

[0942] In this invention, the server includes a sensor means for detecting the remaining amount of water, a processing means for processing data from the sensor means to determine the remaining amount of water, a communication means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold, a server that receives the order instruction via the communication means, an order processing means for performing order processing on the server, an emotion recognition means for recognizing the user's emotions, and an order adjustment means for adjusting the timing and quantity of the order based on data from the emotion recognition means. This enables flexible water ordering according to the user's emotions and usage.

[0943] "Sensor means" refers to a device for detecting the remaining amount of water, and is composed of either an optical, ultrasonic, or pressure-based sensor.

[0944] "Processing means" refers to a device or program for processing data from the sensor means to determine the remaining amount of water.

[0945] "Communication means" refers to network connection means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold.

[0946] A "server" is a central processing unit that receives order instructions via the aforementioned communication means and processes the orders.

[0947] "Order processing means" refers to a function or module that executes an order based on an order instruction received by the server.

[0948] An "emotion recognition system" is a combination of hardware and software that analyzes a user's voice and facial expressions to recognize their emotions.

[0949] "Order adjustment means" refers to a device or program that includes logic or algorithms for adjusting the timing and quantity of orders based on data obtained from the emotion recognition means.

[0950] Embodiments of the present invention will now be described in detail. This embodiment provides a specific example based on a smartphone application related to an e-commerce site. The system of the present invention has the following configuration:

[0951] First, to detect the remaining water level, an optical, ultrasonic, or pressure-type sensor is installed in the water dispenser. The sensor periodically measures the amount of water remaining in the dispenser and transmits this data to a processing device in a smartphone. This allows the user to know the remaining water level in real time.

[0952] Data from the sensor is analyzed by a processing unit on a smartphone. The processing unit monitors the data from the sensor in real time and records it at regular intervals. When the remaining water level falls below a predetermined threshold (e.g., 30%), the processing unit automatically activates a communication unit to send an order instruction. The communication unit sends the order instruction to the server via an internet connection.

[0953] The server receives order instructions via the communication device and executes the order using the order processing device. At this time, the server returns status code 200 to confirm that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0954] Furthermore, an emotion recognition mechanism has been added. This emotion recognition mechanism uses the smartphone's camera and microphone to analyze the user's voice and facial expressions to recognize the user's emotions. Emotion recognition analyzes the user's emotions, for example, when the user is irritated near the water dispenser. The analysis results are transmitted to the order adjustment mechanism, which adjusts the timing and quantity of orders. As a result, this system enables flexible ordering based on the user's emotions.

[0955] For example, if the water level in a water dispenser reaches 25% and the user says, "Why is the water running out so quickly!", the emotion recognition system will analyze this as "frustration." As a result, an order for more water bottles than usual (e.g., two bottles) is sent to the server via the communication system. The server receives the order and performs the necessary processing. This provides an ordering service that reflects the user's needs.

[0956] Example of a prompt:

[0957] Write a program that takes a picture of a user's face with their smartphone camera and analyzes their emotions. If the user is irritated, trigger a specific action. Utilize an open-source emotion recognition API. The emotions will be output with labels such as 'neutral' or 'frustrated'.

[0958] This system not only reduces the burden on users and enables appropriate responses when needed, but also allows for flexible ordering that takes user feelings into consideration.

[0959] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0960] Step 1:

[0961] The terminal acquires data from the sensor. This data includes the remaining water level in the water dispenser. Specifically, optical, ultrasonic, or pressure sensors measure the water level and transmit this data to the terminal's processing unit. The input is the sensor measurement data, and the output is the raw data of the remaining water level provided to the processing unit.

[0962] Step 2:

[0963] The terminal's processing unit analyzes data received from the sensor to determine the remaining water level. Specifically, it interprets the raw sensor data using an algorithm and converts it into a percentage display. During this process, real-time monitoring is performed, and data is recorded at regular intervals. The input is the raw sensor data, and the output is the analyzed remaining water level information.

[0964] Step 3:

[0965] When the remaining water level falls below a predetermined threshold, the terminal automatically activates a communication mechanism to send an order instruction. This communication mechanism uses an internet connection to send the order instruction to the server. The input is information from the processing device indicating that the remaining water level has fallen below the threshold, and the output is the order instruction sent to the server.

[0966] Step 4:

[0967] The server receives order instructions via communication and executes the order using the order processing mechanism. Specifically, it starts the order process based on the product ID and order quantity included in the order instruction and performs the necessary database operations. The input is the order instruction received via communication, and the output is the result of the order execution.

[0968] Step 5:

[0969] The system recognizes user emotions using the device's camera and microphone. Specifically, it acquires images of the user's facial expressions and recordings of their voice, and analyzes them using emotion recognition technology. A generative AI model is used to output emotions as labels such as "neutral" or "frustrated." The input is user data acquired from the camera and microphone, and the output is the analyzed emotion label.

[0970] Step 6:

[0971] An order adjustment mechanism operates based on the user's emotion recognition results, adjusting the timing and quantity of orders. For example, if the user is irritated, it will order more water bottles than usual. The input is the emotion recognition result, and the output is the adjusted order instruction.

[0972] 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.

[0973] 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.

[0974] 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.

[0975] [Fourth Embodiment]

[0976] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0977] 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.

[0978] 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).

[0979] 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.

[0980] 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.

[0981] 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).

[0982] 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.

[0983] 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.

[0984] 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.

[0985] 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.

[0986] 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.

[0987] 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.

[0988] 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".

[0989] Embodiments of the present invention will now be described. In the following description, a system that automatically detects the remaining amount of water in a water dispenser and places an order will be described in detail, with the help of specific examples.

[0990] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[0991] The terminal's processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level falls below a predetermined threshold (e.g., 30%).

[0992] When the water level falls below a threshold, the terminal's processing mechanism sends an order instruction to the server via a communication mechanism. This communication mechanism utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[0993] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[0994] As a concrete example, consider the following scenario: A user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. A processing device analyzes this data and confirms that the remaining amount is below a threshold. An order is sent to the server via a communication device, the server processes the order, and a new water bottle is delivered to the user. The user is unaware of this entire process, and their water supply is ensured.

[0995] In this way, the system of the present invention reduces the burden on users and eliminates water shortages or surpluses through monitoring the remaining water level and automatic ordering.

[0996] The following describes the processing flow.

[0997] Step 1:

[0998] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[0999] Step 2:

[1000] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[1001] Step 3:

[1002] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[1003] Step 4:

[1004] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[1005] Step 5:

[1006] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[1007] Step 6:

[1008] The terminal uses a communication method to send an order instruction to the server. The order instruction includes the product ID and the order quantity (e.g., 1 bottle of water).

[1009] Step 7:

[1010] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[1011] Step 8:

[1012] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[1013] Step 9:

[1014] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[1015] Step 10:

[1016] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[1017] (Example 1)

[1018] 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".

[1019] In modern society, maintaining a stable water supply for water dispensers is crucial, but manual ordering is cumbersome, especially for home and office use, requiring considerable time and effort. Furthermore, forgetting to order at the appropriate time carries the risk of water shortages. To solve this, a system is needed that monitors water levels in real time and places orders automatically. A mechanism to accurately confirm the results of the order process and notify the user is also essential.

[1020] 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.

[1021] In this invention, the server includes means for transmitting a status code to process an order and return the result to the terminal, and means for analyzing the status code received by the terminal and notifying the user after confirming success. This makes it possible to automatically place an order when the remaining amount of water falls below a predetermined threshold, accurately confirm whether the order process was successful, and notify the user.

[1022] A "sensor" is a device used to measure the remaining amount of water, and is composed of one of the following methods: optical, ultrasonic, or pressure-based.

[1023] "Processing means" refers to a system or device for analyzing data acquired from sensor means and determining the remaining amount of water.

[1024] "Communication means" refers to a device with internet communication capabilities for transmitting order instructions generated by the processing means to a server.

[1025] A "server" is a computer system that receives order instructions transmitted via communication means and processes those orders.

[1026] "Order processing means" refers to the software or hardware function on a server that analyzes order instructions and performs the actual order process.

[1027] A "status code transmission means" is a function that allows the server to generate a status code representing the result of the order processing and return that information to the terminal.

[1028] "Means of notifying the user" refers to a function that analyzes the status code received by the terminal from the server and informs the user that the order processing was successful.

[1029] This invention relates to a system that automatically monitors the remaining amount of water in a water dispenser and automatically reorders water when a certain threshold is reached. This system includes specific devices and methods using particular hardware and software. To aid in understanding this invention, the main components will be described in detail.

[1030] System Configuration

[1031] 1. Sensor means:

[1032] Optical, ultrasonic, or pressure sensors are used. These sensors are positioned to accurately measure the remaining amount of water in the water dispenser.

[1033] For example, an ultrasonic sensor measures the distance to the water surface in a water dispenser and quantifies that data.

[1034] 2. Terminal processing means:

[1035] The system receives and analyzes data acquired from sensor devices. Specifically, it monitors the remaining water level in real time based on remaining water level data and determines whether it has fallen below a predetermined threshold (e.g., 30%).

[1036] The processing system incorporates appropriate programs, enabling automatic data analysis and order processing.

[1037] 3. Means of communication:

[1038] This device transmits order instructions created by the terminal's processing unit to a server. The communication method operates via an internet connection, ensuring consistently stable data transmission.

[1039] 4. Server:

[1040] The server receives order instructions transmitted via communication and processes the order. This process includes analyzing the received data (such as product ID and order quantity) and placing the appropriate order.

[1041] If the order is processed successfully, the server generates a status code 200 (success) and returns it to the terminal.

[1042] 5. Status code transmission means and user notification means:

[1043] The terminal receives a status code returned from the server and parses it to confirm whether the order processing was successful. It then notifies the user of the result. Notification methods include LED illumination, terminal display display, and notifications to a smartphone app.

[1044] Specific example

[1045] As a concrete example, let's consider a water dispenser used at home. The following is a typical scenario:

[1046] 1. At some point, the sensor detects that the remaining water level is 25%.

[1047] 2. The processing device analyzes this data and confirms that the remaining amount is below the threshold.

[1048] 3. An order instruction is sent to the server via a communication means, the server accepts the order, and it is executed by the order processing means.

[1049] 4. The server returns status code 200, and the terminal that receives it notifies the user that the order was successful.

[1050] Example prompts for a generative AI model

[1051] Prompt Example 1: "Please describe in detail the processing steps for the automated water dispenser ordering system, from the type of sensor used to data analysis, and the creation and transmission of order instructions."

[1052] Prompt Example 2: "Please describe in detail how a system that measures the remaining water level in a water dispenser and automatically reorders water works. Include specific actions for each step."

[1053] Thus, the system of the present invention provides automated water supply management, saving users time and effort while ensuring a consistently stable water supply.

[1054] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1055] Step 1:

[1056] Water level measurement

[1057] Specific operation: The device's sensor (optical, ultrasonic, or pressure-based) is activated periodically to measure the remaining water level.

[1058] Input: The physical amount of water remaining in the water dispenser.

[1059] Data processing: The sensor converts the measurement results into digital data.

[1060] Output: Water level data (e.g., "25% remaining").

[1061] Step 2:

[1062] Sending data

[1063] Specific operation: The terminal's sensor measures the data and transmits it to the terminal's processing unit.

[1064] Input: Water level data.

[1065] Data processing: Adjust the data format as needed and convert it to a format suitable for the processing method.

[1066] Output: Receipt of remaining water amount data to the processing device.

[1067] Step 3:

[1068] Data Analysis

[1069] Specific operation: The terminal's processing unit analyzes the received water level data and compares it to a threshold.

[1070] Input: remaining battery data.

[1071] Data calculation: Perform calculations to compare the current water level with a predetermined threshold (e.g., 30%).

[1072] Output: The result of determining whether the value falls below the threshold (e.g., "TRUE" if it falls below, "FALSE" if it does not).

[1073] Step 4:

[1074] Creating and sending order instructions

[1075] Specific operation: If the threshold is not met, the processing unit creates an order instruction and sends it to the server via the communication unit.

[1076] Input: Judgment result ("TRUE") and required information (product ID, order quantity).

[1077] Data processing: Create order instruction data in JSON format, including product ID "WATER123" and order quantity "1 bottle".

[1078] Output: Sending order instruction data to the server.

[1079] Step 5:

[1080] Receiving and processing order instructions

[1081] Specific operation: The server analyzes the order instruction data received from the terminal and processes the order.

[1082] Input: Order instruction data (product ID, order quantity).

[1083] Data processing: Analyze the received data and input instructions into the internal order processing system.

[1084] Output: Order processing result data.

[1085] Step 6:

[1086] Status code response

[1087] Specific operation: The server generates a status code 200 (success) as a result of the order processing and returns it to the terminal.

[1088] Input: Order processing result data.

[1089] Data processing: Create response data including status code 200.

[1090] Output: Sending a status code to the terminal.

[1091] Step 7:

[1092] Result notification

[1093] Specific operation: The terminal receives and parses a status code 200 returned from the server. After confirming success, it notifies the user.

[1094] Input: Status code 200.

[1095] Data calculation: Verify that the status code is 200.

[1096] Output: Executes user notifications, such as LED illumination, display information, and notifications to smartphone apps.

[1097] (Application Example 1)

[1098] 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".

[1099] Managing robot consumables in factories often relies heavily on manual processes, making timely ordering of supplies difficult when supplies are running low. Furthermore, shortages of consumables can disrupt robot operation and reduce overall factory productivity. Therefore, a system that automatically manages and replenishes consumables in a timely manner is needed.

[1100] 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.

[1101] In this invention, the server includes a sensor means for detecting the remaining amount of consumables, a processing means for processing data from the sensor means to determine the remaining amount of consumables, and a communication means for automatically sending an order instruction when the remaining amount of consumables determined by the processing means falls below a predetermined threshold. This makes it possible to automatically monitor the remaining amount of consumables and to quickly place orders when necessary.

[1102] A "sensor means" is a device for measuring the remaining amount of an object to be detected in real time or at regular intervals.

[1103] "Processing means" refers to an electronic circuit or software that analyzes data acquired from sensor means and determines the remaining amount of the object.

[1104] "Communication means" refers to a network interface for sending and receiving data and instructions, and includes the function of sending order instructions to the appropriate server.

[1105] A "server" is a computer system that processes order instructions received via communication methods and executes the necessary procedures.

[1106] "Order processing means" refers to a function implemented within the server that performs actual order processing based on received order data.

[1107] "Consumables" are items that are consumed after a certain period of use or frequency of use, and require replenishment.

[1108] "Real-time monitoring" means immediately understanding and recording the current situation without any time delay.

[1109] "Recording data at regular intervals" means acquiring and accumulating data at predetermined time intervals.

[1110] To implement this invention, a system is constructed that automatically manages the remaining amount of consumables used by factory robots and sends order instructions to a server when necessary. The specific configuration and operation of this system are described below.

[1111] Factory robots are equipped with optical, ultrasonic, or pressure-based sensors to detect the remaining amount of consumables. These sensors periodically measure the remaining amount of consumables and transmit the data to a processing unit.

[1112] The processing means analyzes data received from the sensor means to determine the remaining amount of consumables. An embedded single-board computer such as a Raspberry Pi is used as the processing means. This determination includes real-time monitoring and data recording at regular intervals. For example, it checks whether the remaining amount of consumables falls below a predetermined threshold (e.g., 30%).

[1113] When the remaining amount of consumables falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device includes a network interface using the internet. The order instruction includes necessary information such as the product ID and order quantity.

[1114] The server has an order processing mechanism for processing order instructions received via communication. This order processing mechanism is implemented within the server, analyzes the received data, and executes the necessary processing to place the order. Furthermore, the server confirms that the order processing was successful by returning a status code 200.

[1115] For example, a robot used in a factory can detect oil consumption, and if the remaining amount falls below a threshold, an order instruction is automatically sent to the supply chain management system. As a result, necessary replenishment is carried out in a timely manner, allowing the robots to continue operating and improving the overall productivity of the factory.

[1116] As a concrete example, by inputting the following prompt message into the generation AI model, it is possible to automatically generate the necessary program.

[1117] Example of a prompt:

[1118] Please create a program for a factory robot maintenance system that automatically detects the remaining quantity of consumables and places an automatic order when the quantity falls below a threshold. Specifically, the sensor will consist of either an optical, ultrasonic, or pressure sensor, periodically acquire the remaining quantity data, and send the order instruction via the internet.

[1119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1120] Step 1:

[1121] A sensor measures the remaining amount of consumables for the factory robot.

[1122] Input: Measurement of remaining amount of consumables by sensor means

[1123] Specific operation: Optical, ultrasonic, or pressure sensors are used to periodically measure the remaining amount of consumables (e.g., oil). An analog or digital signal is generated from the sensor during this process.

[1124] Output: Remaining quantity data of consumables

[1125] Step 2:

[1126] The terminal's processing unit receives and analyzes data from the sensor unit.

[1127] Input: Remaining amount data transmitted from the sensor.

[1128] Specific operation: An embedded single-board computer such as a Raspberry Pi is used to receive data acquired from sensors. The received data is converted into a digital format, and calculations and analyses are performed to determine the remaining amount.

[1129] Output: Remaining quantity of the determined consumable

[1130] Step 3:

[1131] The terminal's processing mechanism compares the remaining amount of consumables to a threshold and generates an order instruction as needed.

[1132] Input: Remaining quantity of the determined consumable, threshold (e.g., 30%)

[1133] Specific operation: A threshold (30%) is set in advance, and this is compared to the current remaining amount of the consumable. If the remaining amount falls below the threshold, a flag is set to indicate that an order is needed.

[1134] Output: Order instructions (if necessary)

[1135] Step 4:

[1136] The terminal's processing unit sends an order instruction to the server via the communication unit.

[1137] Input: Order instructions, network interface

[1138] Specific operation: The order instruction includes necessary information such as product ID and order quantity. This information is compiled and the order instruction is sent to the server via the internet. A POST request using HTTP is used as the communication method.

[1139] Output: Send order instructions to the server

[1140] Step 5:

[1141] The server processes order instructions received via communication means.

[1142] Input: Order instructions (product ID, order quantity, etc.), order processing method within the server

[1143] Specific operation: The server receives an HTTP request and analyzes the contents of the order instruction. Based on the analysis results, the order processing mechanism is executed and the necessary order processing is carried out.

[1144] Output: Order processing result (status code 200 on success)

[1145] Step 6:

[1146] The server returns the order processing result to the terminal.

[1147] Input: Order processing result (status code)

[1148] Specific operation: If the order processing is successful, the server returns a status code 200. The terminal receives this and confirms that the order was completed successfully. If the order fails, an error status code is returned, and processing branches according to the content of the error.

[1149] Output: Order confirmation message (information regarding success or failure)

[1150] 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.

[1151] Embodiments of the present invention will now be described in detail. In this embodiment, in addition to a system that automatically detects and orders water levels, an emotion engine that recognizes user emotions is combined to provide an even more advanced system.

[1152] The terminal is equipped with a sensor that detects the remaining amount of water. This sensor is either optical, ultrasonic, or pressure-based. The sensor periodically measures the amount of water remaining in the water dispenser and transmits the data to a processing unit.

[1153] The processing unit analyzes data received from the sensor unit to determine the remaining water level. This determination includes real-time monitoring of the water level and recording of data at regular intervals. During this process, it checks whether the remaining water level is below a predetermined threshold (e.g., 30%).

[1154] When the remaining water level falls below a threshold, the processing unit sends an order instruction to the server via a communication device. This communication device utilizes the internet, and the order instruction includes necessary information such as the product ID and order quantity.

[1155] The server processes order instructions received via the communication method. It analyzes the received data and executes the order processing mechanism to place the necessary orders. The server returns status code 200, confirming that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[1156] Furthermore, this embodiment includes an emotion engine. The emotion engine analyzes the user's voice, facial expressions, or behavior to recognize the user's emotions. For example, if a user is irritated near the water dispenser, the emotion engine can recognize that emotion and, combined with specific behaviors (e.g., a tendency for the water level to decrease faster than expected), adjust the timing and quantity of orders.

[1157] As a concrete example, suppose a user is using a water dispenser at home. At some point, a sensor detects that the water level is 25%. The processing unit analyzes this data and confirms that the remaining amount is below a threshold. If the user had just said something like, "The water ran out so quickly," the emotion engine interprets this statement as frustration. As a result, it can send a larger-than-usual order (e.g., two bottles of water) to the server via the communication system.

[1158] The server receives this order instruction and performs the necessary processing. In this way, the ordering process can be adjusted based on the user's preferences, providing a more flexible and user-friendly system.

[1159] The system of the present invention reduces the burden on users by monitoring the remaining amount of water and automatically ordering it, resolving water shortages and surpluses, and also provides further convenience by taking user feelings into consideration.

[1160] The following describes the processing flow.

[1161] Step 1:

[1162] The terminal initializes the sensor device. It checks whether the sensor device is functioning correctly and prepares to detect the remaining water level.

[1163] Step 2:

[1164] The terminal acquires water level data from a sensor at regular intervals. This interval is set, for example, to every hour.

[1165] Step 3:

[1166] The terminal transmits the acquired water level data to the processing unit. The processing unit analyzes the data and determines the current water level.

[1167] Step 4:

[1168] The terminal displays the remaining water level determined by the processing device and provides information to the user. For example, it displays a message such as, "The current water level is 45%."

[1169] Step 5:

[1170] The terminal's processing mechanism checks whether the remaining water level is below a predetermined threshold (e.g., 30%). If the result of this check is below the threshold, the system proceeds to the next step.

[1171] Step 6:

[1172] The device activates an emotion engine and analyzes the user's voice, facial expressions, or actions. The emotion engine identifies the user's emotions and sends the results to a processing unit.

[1173] Step 7:

[1174] The terminal's processing mechanism determines the content of the order instruction (quantity and timing) based on whether the remaining water level falls below a threshold and on data from the emotion engine.

[1175] Step 8:

[1176] The terminal uses a communication method to send order instructions to the server. The order instructions include the product ID and the normal or adjusted order quantity (e.g., quantity increased or decreased based on sentiment).

[1177] Step 9:

[1178] The server receives order instructions via communication means. It analyzes the received data and executes the order processing means.

[1179] Step 10:

[1180] The server formally processes the order using the order processing mechanism. If the order is successful, the server returns status code 200. If it fails, it returns the appropriate error status code.

[1181] Step 11:

[1182] The terminal checks for a response from the server. If a status code of 200 is returned, it displays the message "Order successful." If an error occurs, it displays an error message according to the nature of the error.

[1183] Step 12:

[1184] The terminal waits until the next check time. This interval is, for example, one hour, and after waiting, the process from step 2 is repeated.

[1185] (Example 2)

[1186] 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".

[1187] Traditional water dispenser systems require users to manually order water when the level is low, necessitating frequent checks of the remaining water level. Furthermore, the lack of consideration for user feelings can lead to frustration and dissatisfaction. There is a need to address these issues, reduce operational hassle, and provide a more user-friendly system that takes user feelings into account.

[1188] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a measuring means for detecting the remaining amount of water, a determination means for processing data from the measuring means to determine the remaining amount of water, a transmitting means for automatically sending an order instruction when the remaining amount of water determined by the determination means falls below a predetermined threshold, an information processing device that receives the order instruction via the transmitting means, a control means for performing order processing in the information processing device, an emotion analysis means for analyzing the user's emotions, and an adjustment means for the emotion analysis means to analyze the user's voice, facial expression, or actions to determine the user's emotional state and adjust the order content based on the determination result. This reduces the effort required for the user to manually order water and enables flexible ordering according to the user's emotions.

[1189] "Measuring means" refers to sensors or devices that detect the remaining amount of water.

[1190] "Determination means" refers to a device or program that processes data acquired from measurement means to analyze and determine the remaining amount of water.

[1191] "Transmission means" refers to a device or program used to transmit information and instructions obtained by the determination means to other devices or systems via a communication network.

[1192] An "information processing device" refers to a computer system that receives order instructions sent from a transmission device and processes them accordingly.

[1193] "Control means" refers to devices or programs in an information processing device that execute specific order-related processing based on received order instructions.

[1194] "Emotional analysis tools" refer to devices or programs that analyze a user's voice, facial expressions, and behavior to recognize and determine their emotional state.

[1195] "Adjustment means" refers to a device or program that has the function of adjusting the timing and content of orders based on the user's emotional state determined by the emotion analysis means.

[1196] Modes for carrying out the invention

[1197] This invention provides a system that automatically detects the remaining amount of water and places an automatic order as needed. Furthermore, it has advanced functionality that analyzes the user's emotions and adjusts the timing and quantity of orders based on the results. In this embodiment, sensors, processing means, communication means, information processing device, emotion analysis means, and adjustment means are used in combination. The specific hardware and software used are described below.

[1198] Hardware and software to be used

[1199] 1. Measurement method: Optical, ultrasonic, or pressure-type sensor.

[1200] 2. Determination method: A microcontroller or single-board computer (e.g., Raspberry Pi) for processing sensor data in real time.

[1201] 3. Transmission method: Communication devices such as Wi-Fi modules and Bluetooth modules.

[1202] 4. Information processing equipment: Cloud servers and local servers.

[1203] 5. Control means: Order management system within the server.

[1204] 6. Emotion analysis methods: speech recognition software, image analysis software, and an AI engine that integrates them (e.g., TensorFlow, PyTorch).

[1205] 7. Adjustment mechanism: Software logic for dynamically changing order details based on data obtained from the emotion analysis mechanism described above.

[1206] Specific examples of the system

[1207] Let's say a user is using a water dispenser at home. This water dispenser is equipped with an optical sensor that periodically measures the remaining water level. When the sensor detects that the water level is 25%, that data is transmitted via Wi-Fi to a terminal's detection device. The detection device analyzes this data and confirms that the water level is below the 30% threshold.

[1208] On the other hand, if a user says aloud, "The water runs out so quickly," that voice is transmitted through the microphone to an emotion analysis system. The emotion analysis system analyzes the voice and determines that the user is irritated. Based on this, the system sends a larger order quantity (e.g., 2 bottles) to the cloud server via the transmission system, instead of the usual order quantity (e.g., 1 bottle). The cloud server receives this order instruction, performs the necessary processing, and completes the order.

[1209] Examples of prompt statements

[1210] "This week, our home water dispenser will run out of water quickly, so please create a program that automatically orders additional water bottles early based on the results of an emotion engine analysis."

[1211] In this way, this system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user feelings into consideration.

[1212] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1213] Program processing flow

[1214] Step 1:

[1215] Water level detection using sensors

[1216] The terminal collects water level data from optical, ultrasonic, or pressure sensors. The measuring device measures the water level and pressure inside the water dispenser and converts these values ​​into digital data.

[1217] Input: Physical water height or pressure

[1218] Output: Digital data (e.g., "Water level 25%")

[1219] As a concrete example, the device's optical sensor measures the water surface altitude at one-minute intervals and determines that data to be "25%".

[1220] Step 2:

[1221] Data transmission to processing means notification

[1222] The terminal collects water level data and transmits it to a processing system via wireless communication. Communication methods such as Wi-Fi and Bluetooth are used.

[1223] Input: Digital data (e.g., "Water level 25%")

[1224] Output: Data sent to the processing unit.

[1225] As a specific example, digital data indicating "25% water remaining" acquired by an optical sensor is transmitted to a processing device via Wi-Fi.

[1226] Step 3:

[1227] Water level analysis and determination

[1228] The processing unit analyzes the received sensor data to determine the remaining water level. Data analysis includes real-time monitoring and data recording. A threshold (e.g., 30%) is set, and it is checked whether the level falls below this threshold.

[1229] Input: Sent digital data (e.g., "Water level 25%")

[1230] Output: Analysis results (e.g., "The remaining water level has fallen below the threshold")

[1231] As a concrete example, the processing device analyzes data showing "25% water remaining" and determines that this is below the 30% threshold.

[1232] Step 4:

[1233] Sending automated order instructions

[1234] Based on the judgment result, the processing device sends an automatic order instruction to the server. This instruction includes necessary information (product ID, order quantity, remaining water level, etc.).

[1235] Input: Analysis result (e.g., "The remaining water level has fallen below the threshold")

[1236] Output: Automatic order instruction (Example: "Product ID 12345, Quantity 2")

[1237] As a specific example, the processing device determines that "the remaining water level is 25%" and sends an order instruction to the server for "product ID 12345, quantity 2 bottles".

[1238] Step 5:

[1239] Order processing by server

[1240] The server receives order instructions from the terminal and processes the order based on them. It then checks whether the order was successful and returns a status code of 200.

[1241] Input: Automatic order instruction (Example: "Product ID 12345, Quantity 2")

[1242] Output: Order confirmation status code (e.g., "Status code 200")

[1243] As a concrete example, the server receives an order instruction for "product ID 12345, quantity 2 units," registers the order in the inventory system, and returns "status code 200."

[1244] Step 6:

[1245] Emotional analysis using an emotion engine

[1246] The emotion engine analyzes what the user says near the water dispenser. Using speech recognition software, the user's speech is converted into text, and emotions are extracted from that text.

[1247] Input: User's voice (e.g., "The water runs out so quickly.")

[1248] Output: Emotion analysis result (e.g., determined to be "irritated")

[1249] For example, a user might say, "The water runs out so quickly," and the emotion engine analyzes the audio and determines it to be "frustration."

[1250] Step 7:

[1251] Adjusting the timing and quantity of orders

[1252] Based on the sentiment analysis results, the processing system adjusts the timing and quantity of orders. It increases or decreases the normal order quantity, taking into account the user's emotional state.

[1253] Input: Sentiment analysis result (e.g., "irritation")

[1254] Output: Adjusted order instruction (e.g., "Product ID 12345, Quantity 2")

[1255] As a concrete example, the emotion engine detects the user's "frustration" and changes the order from the usual one unit to two units, then sends the order instruction to the server.

[1256] The above outlines the specific processing flow and the actions taken at each step. This system significantly reduces the effort required from users and provides a user-friendly ordering system that takes user emotions into consideration.

[1257] (Application Example 2)

[1258] 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".

[1259] Traditional water management systems simply measured the remaining water level and automatically placed an order when it fell below a predetermined threshold. This meant they couldn't respond nuancedly to user emotions or usage patterns, sometimes leading to inconvenience. In particular, traditional systems lacked the flexibility to respond when users were dissatisfied with the rate of water consumption or when water was consumed at an unexpectedly rapid pace. Furthermore, there was a need to monitor user emotional expressions, such as frustration near the water dispenser, and reflect these in the ordering process.

[1260] 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.

[1261] In this invention, the server includes a sensor means for detecting the remaining amount of water, a processing means for processing data from the sensor means to determine the remaining amount of water, a communication means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold, a server that receives the order instruction via the communication means, an order processing means for performing order processing on the server, an emotion recognition means for recognizing the user's emotions, and an order adjustment means for adjusting the timing and quantity of the order based on data from the emotion recognition means. This enables flexible water ordering according to the user's emotions and usage.

[1262] "Sensor means" refers to a device for detecting the remaining amount of water, and is composed of either an optical, ultrasonic, or pressure-based sensor.

[1263] "Processing means" refers to a device or program for processing data from the sensor means to determine the remaining amount of water.

[1264] "Communication means" refers to network connection means for automatically sending an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold.

[1265] A "server" is a central processing unit that receives order instructions via the aforementioned communication means and processes the orders.

[1266] "Order processing means" refers to a function or module that executes an order based on an order instruction received by the server.

[1267] An "emotion recognition system" is a combination of hardware and software that analyzes a user's voice and facial expressions to recognize their emotions.

[1268] "Order adjustment means" refers to a device or program that includes logic or algorithms for adjusting the timing and quantity of orders based on data obtained from the emotion recognition means.

[1269] Embodiments of the present invention will now be described in detail. This embodiment provides a specific example based on a smartphone application related to an e-commerce site. The system of the present invention has the following configuration:

[1270] First, to detect the remaining water level, an optical, ultrasonic, or pressure-type sensor is installed in the water dispenser. The sensor periodically measures the amount of water remaining in the dispenser and transmits this data to a processing device in a smartphone. This allows the user to know the remaining water level in real time.

[1271] Data from the sensor is analyzed by a processing unit on a smartphone. The processing unit monitors the data from the sensor in real time and records it at regular intervals. When the remaining water level falls below a predetermined threshold (e.g., 30%), the processing unit automatically activates a communication unit to send an order instruction. The communication unit sends the order instruction to the server via an internet connection.

[1272] The server receives order instructions via the communication device and executes the order using the order processing device. At this time, the server returns status code 200 to confirm that the order processing was successful. This eliminates the need for users to manually place orders and ensures that new water bottles are automatically ordered at the appropriate time every time.

[1273] Furthermore, an emotion recognition mechanism has been added. This emotion recognition mechanism uses the smartphone's camera and microphone to analyze the user's voice and facial expressions to recognize the user's emotions. Emotion recognition analyzes the user's emotions, for example, when the user is irritated near the water dispenser. The analysis results are transmitted to the order adjustment mechanism, which adjusts the timing and quantity of orders. As a result, this system enables flexible ordering based on the user's emotions.

[1274] For example, if the water level in a water dispenser reaches 25% and the user says, "Why is the water running out so quickly!", the emotion recognition system will analyze this as "frustration." As a result, an order for more water bottles than usual (e.g., two bottles) is sent to the server via the communication system. The server receives the order and performs the necessary processing. This provides an ordering service that reflects the user's needs.

[1275] Example of a prompt:

[1276] Write a program that takes a picture of a user's face with their smartphone camera and analyzes their emotions. If the user is irritated, trigger a specific action. Utilize an open-source emotion recognition API. The emotions will be output with labels such as 'neutral' or 'frustrated'.

[1277] This system not only reduces the burden on users and enables appropriate responses when needed, but also allows for flexible ordering that takes user feelings into consideration.

[1278] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1279] Step 1:

[1280] The terminal acquires data from the sensor. This data includes the remaining water level in the water dispenser. Specifically, optical, ultrasonic, or pressure sensors measure the water level and transmit this data to the terminal's processing unit. The input is the sensor measurement data, and the output is the raw data of the remaining water level provided to the processing unit.

[1281] Step 2:

[1282] The terminal's processing unit analyzes data received from the sensor to determine the remaining water level. Specifically, it interprets the raw sensor data using an algorithm and converts it into a percentage display. During this process, real-time monitoring is performed, and data is recorded at regular intervals. The input is the raw sensor data, and the output is the analyzed remaining water level information.

[1283] Step 3:

[1284] When the remaining water level falls below a predetermined threshold, the terminal automatically activates a communication mechanism to send an order instruction. This communication mechanism uses an internet connection to send the order instruction to the server. The input is information from the processing device indicating that the remaining water level has fallen below the threshold, and the output is the order instruction sent to the server.

[1285] Step 4:

[1286] The server receives order instructions via communication and executes the order using the order processing mechanism. Specifically, it starts the order process based on the product ID and order quantity included in the order instruction and performs the necessary database operations. The input is the order instruction received via communication, and the output is the result of the order execution.

[1287] Step 5:

[1288] The system recognizes user emotions using the device's camera and microphone. Specifically, it acquires images of the user's facial expressions and recordings of their voice, and analyzes them using emotion recognition technology. A generative AI model is used to output emotions as labels such as "neutral" or "frustrated." The input is user data acquired from the camera and microphone, and the output is the analyzed emotion label.

[1289] Step 6:

[1290] An order adjustment mechanism operates based on the user's emotion recognition results, adjusting the timing and quantity of orders. For example, if the user is irritated, it will order more water bottles than usual. The input is the emotion recognition result, and the output is the adjusted order instruction.

[1291] 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.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] 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.

[1296] 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.

[1297] 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.

[1298] 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.

[1299] 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."

[1300] 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.

[1301] 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.

[1302] 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] 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.

[1308] 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.

[1309] 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.

[1310] 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.

[1311] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1312] The following is further disclosed regarding the embodiments described above.

[1313] (Claim 1)

[1314] A sensor means for detecting the remaining amount of water,

[1315] A processing means that processes data from the aforementioned sensor means to determine the remaining amount of water,

[1316] A communication means that automatically sends an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold,

[1317] A server that receives an order instruction via the aforementioned communication means,

[1318] Order processing means that performs order processing on the server.

[1319] A system that includes this.

[1320] (Claim 2)

[1321] The system according to claim 1, wherein the sensor means is optical, ultrasonic, or pressure-type.

[1322] (Claim 3)

[1323] The system according to claim 1, wherein the processing means includes means for monitoring the remaining amount of water in real time and recording data at regular intervals.

[1324]

[1325] "Example 1"

[1326] (Claim 1)

[1327] A sensor means for detecting the remaining amount of water,

[1328] A processing means that processes data from the aforementioned sensor means to determine the remaining amount of water,

[1329] A communication means that automatically sends an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold,

[1330] A server that receives an order instruction via the aforementioned communication means,

[1331] The server performs order processing and sends a status code to the terminal,

[1332] A means for analyzing the status code received by the terminal and notifying the user after confirming success.

[1333] A system that includes this.

[1334] (Claim 2)

[1335] The system according to claim 1, wherein the sensor means is optical, ultrasonic, or pressure-type.

[1336] (Claim 3)

[1337] The system according to claim 1, wherein the processing means includes means for monitoring the remaining amount of water in real time and recording data at regular intervals.

[1338] "Application Example 1"

[1339] (Claim 1)

[1340] A sensor means for detecting the remaining amount of consumables,

[1341] A processing means that processes data from the aforementioned sensor means to determine the remaining amount of consumables,

[1342] A communication means that automatically sends an order instruction when the remaining amount of consumables determined by the processing means falls below a predetermined threshold,

[1343] A server that receives an order instruction via the aforementioned communication means,

[1344] Order processing means that performs order processing on the server.

[1345] A system that includes this.

[1346] (Claim 2)

[1347] The system according to claim 1, wherein the sensor means is optical, ultrasonic, or pressure-type.

[1348] (Claim 3)

[1349] The system according to claim 1, wherein the processing means includes means for monitoring the remaining amount of consumables in real time and recording data at regular intervals.

[1350] "Example 2 of combining an emotion engine"

[1351] (Claim 1)

[1352] A measuring means for detecting the remaining amount of water,

[1353] A determination means that processes data from the aforementioned measuring means to determine the remaining amount of water,

[1354] A transmission means that automatically sends an order instruction when the remaining amount of water determined by the determination means falls below a predetermined threshold,

[1355] An information processing device that receives an order instruction via the aforementioned transmission means,

[1356] The information processing device includes a control means for processing orders,

[1357] A means of analyzing user emotions,

[1358] The emotion analysis means analyzes the user's voice, facial expressions, or actions to determine the user's emotional state, and the adjustment means adjusts the order details based on the determination result.

[1359] A system that includes this.

[1360] (Claim 2)

[1361] The system according to claim 1, wherein the measuring means is optical, ultrasonic, or pressure-based.

[1362] (Claim 3)

[1363] The system according to claim 1, wherein the determination means includes means for monitoring the remaining amount of water in real time and recording data at regular intervals.

[1364] "Application example 2 when combining with an emotional engine"

[1365] (Claim 1)

[1366] A sensor means for detecting the remaining amount of water,

[1367] A processing means that processes data from the aforementioned sensor means to determine the remaining amount of water,

[1368] A communication means that automatically sends an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold,

[1369] A server that receives an order instruction via the aforementioned communication means,

[1370] The server includes an order processing means for processing orders,

[1371] A means of recognizing the user's emotions,

[1372] Order adjustment means that adjusts the timing and quantity of orders based on data from the emotion recognition means.

[1373] A system that includes this.

[1374] (Claim 2)

[1375] The system according to claim 1, wherein the sensor means is optical, ultrasonic, or pressure-type.

[1376] (Claim 3)

[1377] The system according to claim 1, wherein the processing means includes means for monitoring the remaining amount of water in real time and recording data at regular intervals. [Explanation of symbols]

[1378] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A sensor means for detecting the remaining amount of water, A processing means that processes data from the aforementioned sensor means to determine the remaining amount of water, A communication means that automatically sends an order instruction when the remaining amount of water determined by the processing means falls below a predetermined threshold, A server that receives an order instruction via the aforementioned communication means, Order processing means that performs order processing in the server A system that includes this.

2. The system according to claim 1, wherein the sensor means is optical, ultrasonic, or pressure-type.

3. The system according to claim 1, wherein the processing means includes means for monitoring the remaining amount of water in real time and recording data at regular intervals.

Images