System

Abstract

A system is provided.SOLUTION: A system, comprising: means for acquiring an image; means for analyzing the acquired image to identify a type of waste; means for collecting information regarding processing of the identified waste; means for presenting the information regarding the processing; and means for scheduling collection of the waste based on input from a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The process of disposing of bulky waste is complicated and time-consuming, requiring many steps, which requires time and effort from users. Specific steps include completing the process on local government websites, searching waste collection sites, checking fees, and deciding on collection dates. Furthermore, users may overlook the possibility that items deemed to be bulky waste can actually be disposed of as non-burnable waste, or that items they intended to discard may actually be valuable. The goal of this project is to solve these issues and simplify the process, while also promoting recycling and reuse. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for acquiring images, a means for analyzing the acquired images to identify the type of waste, a means for collecting information regarding the disposal of the identified waste, a means for presenting information regarding the disposal, and a means for scheduling collection of the waste based on input from a user. Furthermore, by further including a means for determining whether the identified waste is non-burnable waste or whether the waste has value, the system can suggest optimal disposal methods and reuse options to the user. This significantly simplifies the procedures for oversized waste, saving the user time and effort, and also promoting recycling and reuse.

[0006] The "means for acquiring images" refers to a device or software that has the function of taking a photo of the waste that the user wants to discard and inputting the image data into the system.

[0007] "Means for analyzing acquired images and identifying the type of waste" refers to a device or software that has the function of using artificial intelligence to analyze images based on input image data and identify the type of waste.

[0008] "Means for collecting information on the disposal of identified waste" refers to equipment or software that has the function of obtaining information on fees and detailed disposal methods for each type of waste from a database or external source.

[0009] "Means for presenting information about processing" refers to a device or software that has the function of notifying the user of the acquired information in a visual, auditory or other form.

[0010] "Means for scheduling waste collection based on user input" means a device or software that allows a user to input a collection date and other details, transmit that information to a waste collection service, and confirm the reservation.

[0011] "Means for determining whether or not a waste is non-combustible waste" refers to a device or software that has criteria for determining whether identified waste can be treated as non-combustible waste and has the function of making a judgment based on those criteria.

[0012] "Means for determining whether or not something has value" refers to a device or software that has the function of evaluating whether identified waste has market value and, based on the results, suggesting reuse or recycling to the user. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

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

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

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

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

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

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

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

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

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0034] This invention is an AI-based system for simplifying the procedure for disposing of bulky waste. The detailed configuration of this system and the program processing are explained below.

[0035] System configuration

[0036] This system mainly consists of the following components:

[0037] 1. Image acquisition method

[0038] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[0039] 2. Image analysis methods

[0040] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[0041] 3. Information gathering methods

[0042] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[0043] 4. Information presentation means

[0044] The terminal has the function of displaying the fees and processing method to the user.

[0045] 5. Collection reservation method

[0046] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[0047] 6. How to determine non-burnable waste

[0048] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[0049] 7. Value Judgment Tools

[0050] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[0051] Program processing

[0052] 1. Image acquisition and transmission

[0053] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[0054] The device sends the captured image to the server.

[0055] 2. Image Analysis

[0056] The server receives the image and analyzes it using AI.

[0057] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[0058] 3. Collection and presentation of information

[0059] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[0060] The server sends the fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[0061] The terminal displays this information to the user.

[0062] 4. Select a collection date and make a reservation

[0063] The user selects the desired collection date (e.g., May 15th) from the options presented.

[0064] The terminal transmits the selected collection date to the server.

[0065] The server receives the collection reservation information and determines the collection schedule.

[0066] 5. Non-burnable garbage classification and guidance

[0067] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[0068] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[0069] 6. Valuable garbage proposals

[0070] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[0071] The server sends information about the estimated price and listing procedures to the terminal.

[0072] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[0073] Specific examples

[0074] 1. Sofa disposal procedures

[0075] A user takes a photo of an old sofa.

[0076] The device sends the photo to the server.

[0077] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[0078] The user selects May 15th as the collection date.

[0079] The terminal sends the collection date to the server and confirms the reservation.

[0080] 2. If the frying pan is non-burnable garbage

[0081] A user takes a photo of an old metal frying pan.

[0082] The device sends the photo to the server.

[0083] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[0084] The device will guide the user on how to dispose of non-burnable waste.

[0085] 3. Proposal for listing a valuable guitar

[0086] A user takes a photo of an old guitar.

[0087] The device sends the photo to the server.

[0088] The server analyzes the photo and determines that it is a valuable guitar. It sends an estimated price of 10,000 yen and instructions on how to list the item.

[0089] The device displays the product description, estimated price, and listing procedure to the user, and the user selects "List."

[0090] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[0091] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse.

[0092] The processing flow will be explained below.

[0093] Program processing steps

[0094] Booking by photo shoot

[0095] Step 1:

[0096] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[0097] Step 2:

[0098] The device sends the photograph to the server.

[0099] Step 3:

[0100] The server passes the received photos to the AI ​​model and begins analysis.

[0101] Step 4:

[0102] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[0103] Step 5:

[0104] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[0105] Step 6:

[0106] The terminal displays the received fee and collection date to the user.

[0107] Step 7:

[0108] The user selects a desired date (for example, May 15th) from the collection dates presented.

[0109] Step 8:

[0110] The terminal transmits the selected collection date and reservation information to the server.

[0111] Step 9:

[0112] The server stores the reservation information and schedules the collection.

[0113] Judgment as non-burnable waste

[0114] Step 1:

[0115] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[0116] Step 2:

[0117] The device sends the photograph to the server.

[0118] Step 3:

[0119] The server passes the received photos to the AI ​​model and begins analysis.

[0120] Step 4:

[0121] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[0122] Step 5:

[0123] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[0124] Step 6:

[0125] The terminal displays information on how to dispose of non-burnable waste to the user.

[0126] Valuable garbage proposals

[0127] Step 1:

[0128] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[0129] Step 2:

[0130] The device sends the photograph to the server.

[0131] Step 3:

[0132] The server passes the received photos to the AI ​​model and begins analysis.

[0133] Step 4:

[0134] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[0135] Step 5:

[0136] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[0137] Step 6:

[0138] The server sends information about the estimated price and listing procedures to the terminal.

[0139] Step 7:

[0140] The terminal displays the received information to the user and guides them through the listing procedure.

[0141] Step 8:

[0142] The user follows the instructions and selects "List."

[0143] Step 9:

[0144] The terminal transmits the request to put up for sale to the server.

[0145] Step 10:

[0146] The server receives the listing information and completes the listing process via the Marketplace API.

[0147] Example 1

[0148] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0149] The conventional procedure for disposing of bulky waste is complicated and time-consuming, and it is difficult to obtain information on appropriate disposal methods and fees. It is also difficult to distinguish between non-burnable and non-burnable waste, and opportunities to reuse or recycle valuable waste are often overlooked. A system that solves these problems and makes the process for disposing of bulky waste efficient and easy is needed.

[0150] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0151] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving collection of the waste based on input from the user, and means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user. This makes it possible to provide information on disposal methods and fees for bulky waste, reserve collection dates, distinguish between non-burnable and combustible waste, and suggest reuse or recycling of valuable waste.

[0152] The "means for acquiring images" refers to a device or software that has the function of taking a photo of the bulky waste that the user wants to dispose of and inputting that image into the system.

[0153] "Means for analyzing acquired images and identifying the type of waste" refers to a device or software that has the function of analyzing image data received by the server using an AI model or the like to identify the type of waste.

[0154] "Means for collecting information on the disposal of identified waste" means a device or software that has the function of allowing the server to retrieve information on fees and disposal methods related to the disposal of waste from a database based on the type of waste identified.

[0155] The "means for presenting information regarding disposal" refers to a device or software that has the function of transmitting information regarding disposal of waste collected by the server to the user's terminal and displaying it on the terminal.

[0156] "Means for reserving waste collection based on user input" refers to a device or software that has the function of sending information such as the desired collection date entered by the user into the terminal to a server, and the server then confirming the collection reservation based on that information.

[0157] The "means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user" refers to a device or software that has the function of a server evaluating the market value of waste and suggesting reuse or recycling of that waste to the user.

[0158] "Means for determining whether waste is non-burnable waste and presenting the relevant information to the user" refers to a device or software that has the function of a server determining whether waste is non-burnable waste based on the results of image analysis, and sending and presenting the results to the user's terminal.

[0159] "Means for using a marketplace API to collect the market value and listing procedures for valuable waste and present them to users" refers to a device or software that has the function of a server using an online marketplace API to collect information on the market value and listing procedures for valuable waste, and sending that information to the user's terminal for presentation.

[0160] The present invention is an AI-based system for simplifying the procedure for disposing of bulky waste. Detailed embodiments of this system are described below.

[0161] System configuration

[0162] This system mainly consists of the following components:

[0163] 1. Image acquisition method

[0164] The device has a function that allows users to take a photo of the bulky waste they want to throw away and input the image into the system. A smartphone or digital camera is the hardware that performs this function.

[0165] 2. Image analysis methods

[0166] The device sends the captured image to a server, which then uses AI to analyze the image and identify the type of waste. Specifically, it uses the generative AI model YOLO (You Only Look Once).

[0167] 3. Information gathering methods

[0168] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[0169] 4. Information presentation means

[0170] The server sends the collected information to the terminal, which then displays the fees and processing method to the user.

[0171] 5. Collection reservation method

[0172] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[0173] 6. How to determine non-burnable waste

[0174] The server has the ability to determine whether the waste is non-combustible based on the analysis results and send that information to the terminal.

[0175] 7. Market value assessment and reuse proposal methods

[0176] The server evaluates whether the waste has market value and uses the marketplace API to make reuse and recycling suggestions to users.

[0177] Program processing

[0178] 1. Image acquisition and transmission

[0179] A user takes a photo of a large piece of trash, such as an old sofa, with a mobile device.

[0180] The device sends the captured image to the server. The image data is sent using an internet connection.

[0181] 2. Image Analysis

[0182] The server inputs the received image into an AI model and starts image analysis, for example, using YOLO.

[0183] The server uses the analysis results to identify the object (e.g., an old sofa) contained in the image, and returns the identification result as a specific name such as sofa.

[0184] 3. Collection and presentation of information

[0185] The server retrieves information about fees and disposal methods related to the identified waste (e.g., sofa) from the database. For example, it retrieves information that the disposal fee for a sofa is 1,200 yen.

[0186] The server checks the dates that can be collected (e.g., May 15th or May 18th) and sends that information to the terminal.

[0187] The terminal will display the fee and collection dates to the user, who can then select a collection date based on the displayed information.

[0188] 4. Select a collection date and make a reservation

[0189] The user selects the desired date (e.g., May 15th) from the available collection dates presented.

[0190] The terminal sends the collection date information selected by the user to the server, which then registers the selected collection date in the database.

[0191] The server confirms the collection reservation information and notifies the user that the reservation has been completed.

[0192] 5. Non-burnable garbage classification and guidance

[0193] The server determines from the analysis results that the waste is non-burnable (e.g., a metal frying pan). The determination is made based on pre-set rules.

[0194] The server notifies the terminal of non-burnable waste information.

[0195] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[0196] 6. Market value assessment and reuse proposals

[0197] If the server determines from the analysis results that the waste has value (e.g., an old guitar), it uses the marketplace API to collect possible product value and listing information.

[0198] The server sends the collected information to the device, including the estimated price (e.g., 10,000 yen) and details of the listing process.

[0199] The device displays the product description, estimated price, and listing procedure to the user. If the user selects "List," the device sends this information to the server. An example of a generated prompt might be, "The estimated value of this guitar is 10,000 yen. Would you like to list it?"

[0200] The server performs the listing procedure on the online auction site and sends a completion notice to the user.

[0201] Specific examples

[0202] For example, a user takes a photo of an old sofa and sends it to a server via their smartphone. The server analyzes the image and recognizes it as a sofa, then retrieves the 1,200 yen handling fee and collection dates (May 15th and May 18th) from a database and sends them to the device. The device displays this information to the user, who selects May 15th. The selected information is sent to the server, which then confirms the collection reservation. In addition, the server can display suggestions for items such as metal frying pans, which can be disposed of as non-burnable waste, and items such as guitars, which can be reused or recycled, for sale.

[0203] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0204] Step 1:

[0205] Image capture and transmission

[0206] The user takes a photo of the bulky item they want to throw away (e.g., an old sofa) with their smartphone. This becomes the input image for the system. Specific actions include opening the camera app and taking a photo.

[0207] The device sends the captured image file to the server. An internet connection is required for transmission, and a protocol such as an HTTP request is used. The input is the captured image file, and the output is the completion of sending the image data to the server.

[0208] Step 2:

[0209] Image analysis

[0210] The server inputs the received image file into the AI ​​model and begins image analysis. Specific operations include using generative AI models such as YOLO (You Only Look Once).

[0211] The server uses an AI model to identify an object (e.g., a sofa) in an image. The input is the received image data, and the output is the name of the identified object (e.g., "sofa"). The server supplies the image data to the AI ​​model and receives the generated label.

[0212] Step 3:

[0213] Collection and presentation of information

[0214] The server collects information related to waste disposal from a database based on the identification result (e.g., "sofa"), and specific operations include querying the database using an SQL query.

[0215] The input is the name of the identification result, and the output is the collected fee and the collectable date information (e.g., "Fee 1,200 yen, collection dates May 15th and May 18th").

[0216] The server sends the collected information to the terminal.

[0217] The terminal displays the collection information (fees and collection date) to the user. Specific operations include displaying the information on the application screen.

[0218] Step 4:

[0219] Selecting and reserving a collection date

[0220] The user selects the desired date (e.g., May 15th) from the available dates presented for collection. This becomes the input for the next process. Specific actions include selecting a date from a calendar interface on the application.

[0221] The terminal sends the user's selection information to the server. The input is the collection date selected by the user, and the output is the completion of information transmission to the server.

[0222] The server registers the collection reservation in the database based on the received selection information, including saving the collection date in the database using an SQL query.

[0223] Step 5:

[0224] Non-burnable waste determination and guidance

[0225] The server determines whether the waste is non-burnable or not based on the results of image analysis. This is done using predefined rules. The input is the result of image analysis, and the output is the determination of whether the waste is non-burnable or not.

[0226] The server sends the result of the judgment to the user's terminal. The input is the judgment result of non-burnable waste, and the output is the completion of information transmission to the terminal.

[0227] The terminal displays a message to the user such as, "Please dispose of metal frying pans as non-burnable garbage on the specified day in the specified place." Specific actions include displaying a message on the application screen.

[0228] Step 6:

[0229] Market value assessment and reuse proposals

[0230] The server evaluates whether the waste has market value based on the results of image analysis. The input is the waste identification result, and the output is the market value assessment result.

[0231] The server uses the marketplace's API to gather possible product values ​​and listing information, including sending API requests and receiving information.

[0232] The server sends the collected information to the terminal. The input is the product value information obtained from the API, and the output is the completion of sending the information to the terminal.

[0233] The terminal displays to the user a description of the product, an estimated price (e.g., 10,000 yen), and listing procedure information. If the user selects "List," the terminal sends this information to the server. Specific operations include displaying listing procedure instructions on the application screen and receiving user input.

[0234] The server processes the listing on the online auction site and sends a completion notice to the user. The input is the user's listing information, and the output is a completion notice of the listing procedure.

[0235] (Application example 1)

[0236] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0237] The present invention aims to solve the problem of the complicated procedure for disposing of bulky waste and the inability of users to properly understand how to dispose of it. It also aims to provide a method for effectively utilizing waste that has value and can be reused or recycled without overlooking that value. Another objective is to simplify the process of reserving collection dates and improve user convenience.

[0238] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0239] In this invention, the server includes a means for presenting a collection method for valuable waste, a means for the user to input a desired collection date, and a means for confirming collection reservation information, which allows the user to easily carry out the procedure for disposing of bulky waste and further enables the user to maximize the value of reusable and recyclable waste.

[0240] The "means for acquiring images" refers to a means by which a user takes a photograph of the bulky waste and inputs the image into the system.

[0241] "Means for analyzing acquired images to identify the type of waste" refers to the means by which the system uses AI to analyze images sent to the server and identify the type of waste.

[0242] The "means for collecting information on the disposal of identified waste" is a means for the server to obtain information on disposal fees and disposal methods for identified waste from the database.

[0243] The "means for presenting information about processing" is a means for displaying information about the acquired fee and processing method to the user.

[0244] The "means for reserving waste collection based on input from the user" refers to a means for the user to input a desired collection date and transmit that information to the server to make a collection reservation.

[0245] "Means for suggesting methods for recovering valuable waste" refers to means for proposing reuse or recycling when waste has market value based on the analysis results.

[0246] The "means for the user to input the desired collection date" is a means for the user to select a collection date through the application and transmit that information to the server.

[0247] The "means for determining collection reservation information" is a means for the server to determine the collection schedule based on the selected collection date and update the reservation information.

[0248] This invention is an AI-based system for simplifying the process of disposing of bulky waste, and is mainly composed of the following components:

[0249] System configuration

[0250] 1. Image acquisition method

[0251] Users can take photos of bulky waste with their smartphones and enter the images into the system.

[0252] 2. Image analysis methods

[0253] The captured images are sent from the smartphone to a cloud server (e.g., AWS EC2) where they are analyzed using an AI image analysis model (e.g., TensorFlow or PyTorch). This analysis identifies the type of waste.

[0254] 3. Information gathering methods

[0255] The server retrieves information on processing fees and processing methods for the identified waste from a cloud database (e.g., Amazon RDS).

[0256] 4. Information presentation means

[0257] Information about processing fees and processing methods is sent from the server to the smartphone and displayed to the user, allowing the user to check the necessary information.

[0258] 5. Collection reservation method

[0259] The user selects the desired collection date from the schedule presented and sends that information to the server via their smartphone. The server then confirms the collection reservation based on the received collection date information.

[0260] 6. How to determine non-burnable waste

[0261] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the user's smartphone and guides them on how to dispose of it properly.

[0262] 7. Value Judgment Tools

[0263] If the server determines that the waste is valuable using the AI ​​image analysis model, it uses a marketplace API (e.g., eBay API) to collect information about the product value and listing, and suggests reuse or recycling to the user.

[0264] Hardware and software used

[0265] Hardware: Smartphone camera, cloud server (AWS EC2), cloud database (Amazon RDS)

[0266] Software: Mobile app (Flutter or React Native), AI image analysis model (TensorFlow or PyTorch), marketplace API (eBay API)

[0267] Specific examples

[0268] 1. Sofa disposal procedures

[0269] A user takes a photo of an old sofa with their smartphone.

[0270] The image is sent to a cloud server, where an AI image analysis model identifies it as a sofa.

[0271] The server retrieves the processing fee and collection date from a cloud database and displays them on the smartphone.

[0272] The user selects the desired collection date, and the server confirms the collection reservation.

[0273] 2. If the frying pan is non-burnable garbage

[0274] A user takes a photo of a metal frying pan with their smartphone.

[0275] The image is sent to a cloud server, and an AI image analysis model determines that the frying pan is non-burnable waste.

[0276] The server obtains the disposal method for non-combustible waste and displays it on the smartphone.

[0277] 3. Proposal for listing a valuable guitar

[0278] A user takes a photo of an old guitar with their smartphone.

[0279] The images are sent to a cloud server, where an AI image analysis model determines whether the guitar is valuable.

[0280] The server uses the marketplace API to obtain estimated prices and listing procedure information, which is then displayed on the smartphone.

[0281] Prompt Sentence Examples

[0282] "Analyze images of bulky waste taken by users with a smartphone app and identify the type of object (e.g. sofa, frying pan). After identification, retrieve the associated processing fee and possible collection date from the database and display them to the user. Also, for valuable objects, obtain an estimated price via the Marketplace API and provide information to guide the listing process."

[0283] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0284] Step 1:

[0285] Users take photos of bulky waste with their smartphones and upload the images to a cloud server via the application.

[0286] Input: Photo of bulky waste

[0287] Output: Image data is sent to the cloud server

[0288] Specific behavior: A user takes a photo with their smartphone camera and uses the application's image upload function to send the image to a cloud server.

[0289] Step 2:

[0290] The server inputs the received image data into an AI image analysis model to identify the type of waste.

[0291] Input: Image data

[0292] Output: Waste type determination (e.g. sofa, frying pan)

[0293] How it works: The images sent to the cloud server are stored and passed to an AI model (e.g., TensorFlow or PyTorch), which then analyzes the images and identifies the type of waste.

[0294] Step 3:

[0295] Based on the identified type of waste, the server collects information on processing fees and processing methods from a cloud database.

[0296] Input: Waste type determination result

[0297] Output: Processing fee and processing method information

[0298] Specific operation: Sends a query to a cloud database (e.g., Amazon RDS) to obtain disposal fees and methods corresponding to the waste type.

[0299] Step 4:

[0300] The server sends the collected information to the terminal, which displays the information to the user.

[0301] Input: Processing fee and processing method information

[0302] Output: User-visible processing fee and processing method

[0303] Specific operation: The server sends information such as processing fees and collection dates to the user's smartphone via API, and the smartphone app displays the information to the user.

[0304] Step 5:

[0305] The user selects the desired collection date from the available collection dates displayed and transmits the information to the server via the terminal.

[0306] Input: User's desired collection date

[0307] Output: Collection date information sent to the server

[0308] How it works: The user selects a collection date using the smartphone app interface, and that information is sent to the server via an API.

[0309] Step 6:

[0310] The server confirms the collection reservation based on the received collection date information and updates the schedule.

[0311] Input: User's desired collection date

[0312] Output: Confirmed collection reservation information

[0313] Specific operation: The server saves the received collection date information in the database and updates and confirms the collection schedule.

[0314] Step 7:

[0315] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the terminal and guides the user on the appropriate disposal method.

[0316] Input: Waste is non-burnable waste

[0317] Output: How to dispose of non-burnable waste

[0318] Specific operation: If the server determines that the item is non-combustible waste using the AI ​​model, it sends information about how to dispose of it to the user's smartphone, and the application displays that information.

[0319] Step 8:

[0320] If the server determines that the waste has value using the AI ​​image analysis model, it uses the marketplace API to collect information about the product's value and listing, and suggests reuse or recycling to the user.

[0321] Input: Determination that the waste is valuable

[0322] Output: Information on product value and listing procedures

[0323] How it works: The server queries a marketplace API (e.g., eBay API) to obtain information about the product's value and listing process, and sends it to the user's smartphone. The application displays this information to the user and suggests reuse and recycling options.

[0324] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0325] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes the user's emotions. The detailed configuration of this system and the program processing are described below.

[0326] System configuration

[0327] This system mainly consists of the following components:

[0328] 1. Image acquisition method

[0329] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[0330] 2. Image analysis methods

[0331] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[0332] 3. Information gathering methods

[0333] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[0334] 4. Information presentation means

[0335] The terminal has the function of displaying the fees and processing method to the user.

[0336] 5. Collection reservation method

[0337] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[0338] 6. How to determine non-burnable waste

[0339] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[0340] 7. Value Judgment Tools

[0341] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[0342] 8. Emotion Engine

[0343] It has the ability to recognize the user's emotions and provide information and simplify procedures based on that.

[0344] Program processing

[0345] 1. Image acquisition and transmission

[0346] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[0347] The device sends the captured image to the server.

[0348] 2. Image Analysis

[0349] The server receives the image and analyzes it using AI.

[0350] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[0351] 3. Collection and presentation of information

[0352] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[0353] The server returns the handling fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[0354] The terminal displays this information to the user.

[0355] 4. Select a collection date and make a reservation

[0356] The user selects the desired collection date (e.g., May 15th) from the options presented.

[0357] The terminal transmits the selected collection date to the server.

[0358] The server receives the collection reservation information and determines the collection schedule.

[0359] 5. Non-burnable garbage classification and guidance

[0360] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[0361] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[0362] 6. Valuable garbage proposals

[0363] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[0364] The server sends information about the estimated price and listing procedures to the terminal.

[0365] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[0366] 7. The Emotional Engine

[0367] The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state.

[0368] When the emotion engine determines that the user is feeling stressed, an encouraging message is displayed to the user through the information presentation means.

[0369] If more emotion engines are needed, they instruct the server or terminal how to simplify the steps of the procedure.

[0370] Specific examples

[0371] 1. Sofa disposal procedures

[0372] A user takes a photo of an old sofa.

[0373] The device sends the photo to the server.

[0374] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[0375] The user selects May 15th as the collection date.

[0376] The terminal sends the collection date to the server and confirms the reservation.

[0377] 2. If the frying pan is non-burnable garbage

[0378] A user takes a photo of a metal frying pan.

[0379] The device sends the photo to the server.

[0380] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[0381] The device will guide the user on how to dispose of non-burnable waste.

[0382] 3. When a guitar is valuable

[0383] A user takes a photo of an old guitar.

[0384] The device sends the photo to the server.

[0385] The server analyzes the photo and determines that the guitar is valuable. It sends an estimated price of 10,000 yen and instructions on how to list the item to the user's device.

[0386] The device displays the product description, estimated price, and listing procedure to the user, and they select "List."

[0387] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[0388] 4. User Emotion Recognition

[0389] If the user is feeling stressed, the emotion engine will analyze and recognize the state.

[0390] The emotion engine instructs the device to display an appropriate encouraging message.

[0391] The emotion engine instructs the server or terminal to automate or simplify parts of the procedure, allowing the user to proceed smoothly.

[0392] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse. In addition, the emotion engine provides a comfortable operating experience for users.

[0393] The processing flow will be explained below.

[0394] Program processing steps

[0395] Booking by photo shoot

[0396] Step 1:

[0397] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[0398] Step 2:

[0399] The device sends the photograph to the server.

[0400] Step 3:

[0401] The server passes the received photos to the AI ​​model and begins analysis.

[0402] Step 4:

[0403] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[0404] Step 5:

[0405] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[0406] Step 6:

[0407] The terminal displays the received fee and collection date to the user.

[0408] Step 7:

[0409] The user selects a desired date (for example, May 15th) from the collection dates presented.

[0410] Step 8:

[0411] The terminal transmits the selected collection date and reservation information to the server.

[0412] Step 9:

[0413] The server stores the reservation information and schedules the collection.

[0414] Judgment as non-burnable waste

[0415] Step 1:

[0416] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[0417] Step 2:

[0418] The device sends the photograph to the server.

[0419] Step 3:

[0420] The server passes the received photos to the AI ​​model and begins analysis.

[0421] Step 4:

[0422] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[0423] Step 5:

[0424] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[0425] Step 6:

[0426] The terminal displays information on how to dispose of non-burnable waste to the user.

[0427] Valuable garbage proposals

[0428] Step 1:

[0429] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[0430] Step 2:

[0431] The device sends the photograph to the server.

[0432] Step 3:

[0433] The server passes the received photos to the AI ​​model and begins analysis.

[0434] Step 4:

[0435] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[0436] Step 5:

[0437] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[0438] Step 6:

[0439] The server sends information about the estimated price and listing procedures to the terminal.

[0440] Step 7:

[0441] The terminal displays the received information to the user and guides them through the listing procedure.

[0442] Step 8:

[0443] The user follows the instructions and selects "List."

[0444] Step 9:

[0445] The terminal transmits the request to put up for sale to the server.

[0446] Step 10:

[0447] The server receives the listing information and completes the listing process via the Marketplace API.

[0448] User support with emotion engine

[0449] Step 1:

[0450] When a user uses the system, the emotion engine captures the user's facial expressions and voice through the camera and microphone.

[0451] Step 2:

[0452] The facial expression and voice data acquired by the device is sent to the server.

[0453] Step 3:

[0454] The server passes the received facial expression and voice data to the emotion engine and begins analysis.

[0455] Step 4:

[0456] The server determines whether the user is feeling stressed or dissatisfied based on the analysis of the emotion engine.

[0457] Step 5:

[0458] The server determines the appropriate message and dialogue procedure based on the emotional state and sends that information to the terminal.

[0459] Step 6:

[0460] The device displays an appropriate message to the user (e.g., "We're here to help you. Let us know if you have any questions.").

[0461] Step 7:

[0462] As the user proceeds, the emotion engine continues to monitor the user's emotional state and instructs the server to simplify the process if necessary.

[0463] Step 8:

[0464] The server handles the simplification of procedures, for example by providing auto-filling and additional support to reduce the burden on the user.

[0465] Example 2

[0466] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0467] The process of disposing of bulky waste is complicated and often stressful for users. Furthermore, if the waste has market value, opportunities for reuse or recycling may be missed. Furthermore, there is a lack of means to recognize the user's emotions and provide appropriate support, which hinders the user's operational experience.

[0468] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0469] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving waste collection based on input from the user, and means for recognizing the user's emotions and providing information based on the emotions. This makes it possible to carry out the procedure for disposing of oversized waste easily and smoothly, preventing missed opportunities for reuse and recycling and providing a comfortable operating experience for the user.

[0470] "Means for acquiring images" refers to devices or software that allow a user to take an image of the waste they wish to dispose of and input that image into the system.

[0471] "Means for analyzing acquired images and identifying the type of waste" refers to devices or software that analyze received images and identify the type of waste depicted in the images using AI models, etc.

[0472] "Means for collecting information on the disposal of identified waste" refers to devices or software that retrieve information such as disposal methods and fees from a database based on the type of identified waste.

[0473] "Means for presenting information about processing" refers to devices or software that display collected information such as processing methods and fees to users.

[0474] "Means for reserving waste collection based on user input" refers to devices or software that reserve waste collection based on information entered by the user, such as the desired collection date.

[0475] "Means for recognizing a user's emotions and providing information based on those emotions" refers to devices or software that analyze a user's facial expressions, voice, etc. to identify emotions and provide information according to those emotions.

[0476] "Means for determining whether waste is non-combustible waste" refers to devices or software that determine whether identified waste is non-combustible waste.

[0477] "Means for determining whether waste has market value and proposing reuse or recycling if it is determined to have market value" refers to devices or software that determine whether identified waste has market value and, if it is determined to have value, proposes reuse or recycling.

[0478] MODE FOR CARRYING OUT THE INVENTION

[0479] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes user emotions. The system mainly includes the following hardware and software components:

[0480] Hardware and software used

[0481] Device: Smartphone or digital camera

[0482] Server: Cloud server with database and AI model

[0483] software:

[0484] Image processing: OpenCV

[0485] Image Analysis and Classification: TensorFlow

[0486] Emotion recognition: Emotion API

[0487] System Operation Overview

[0488] 1. Image acquisition method

[0489] The user takes a photo of the bulky waste they want to throw away using a smartphone or digital camera.

[0490] The images taken by the device are sent to the server via a system-specific app.

[0491] 2. Image analysis methods

[0492] Based on the images received by the server, preprocessing is performed using OpenCV.

[0493] The server uses TensorFlow to analyze the images and identify the type of waste.

[0494] 3. Information gathering methods

[0495] The server collects fees and disposal methods from a database based on the identified waste type.

[0496] 4. Information presentation means

[0497] The terminal presents the fee received from the server and the collection date to the user.

[0498] 5. Collection reservation method

[0499] The user selects the desired collection date and transmits that information from the terminal to the server.

[0500] The server schedules the collection appointment.

[0501] 6. How to determine non-burnable waste

[0502] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[0503] The device will guide the user on how to dispose of non-burnable waste.

[0504] 7. Value Judgment Tools

[0505] The server determines whether the waste has market value and makes suggestions for reuse or recycling as needed.

[0506] The server connects to the marketplace's API to collect estimated prices and listing procedures.

[0507] The terminal presents this information to the user and guides them through the listing procedure.

[0508] 8. Emotion Engine

[0509] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[0510] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[0511] If necessary, instructions will be provided to simplify the steps of the procedure.

[0512] Specific examples

[0513] 1. Sofa disposal procedures

[0514] A user takes a photo of an old sofa.

[0515] The device sends the photo to the server.

[0516] The server analyzes the image and identifies it as a sofa.

[0517] The fee is 1,200 yen and collection dates are May 15th and May 18th.

[0518] The user selects May 15th as the collection date, and the terminal sends the information to the server.

[0519] The server confirms the collection reservation.

[0520] 2. If the frying pan is non-burnable garbage

[0521] A user takes a photo of a metal frying pan.

[0522] The device sends the photo to the server.

[0523] The server analyzes the image and identifies the frying pan as non-combustible waste.

[0524] The device will guide the user on how to dispose of non-burnable waste.

[0525] 3. When a guitar is valuable

[0526] A user takes a photo of an old guitar.

[0527] The device sends the photo to the server.

[0528] The server analyzes the image and determines that it is a valuable guitar.

[0529] An estimated price of 10,000 yen and instructions on how to proceed with listing will be sent to your device.

[0530] The device displays the product description, estimated price, and listing procedure to the user, and asks whether they want to list the item.

[0531] If the user chooses to put up an item for auction, the terminal transmits the information to the server, which then processes the item for auction at the online auction.

[0532] Prompt Sentence Examples

[0533] "I want to simplify the process of throwing away an old sofa. Create a program where I can take a photo, submit it, and the system will suggest fees and a reservation date."

[0534] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0535] Step 1:

[0536] The user takes a photo of the bulky trash they want to throw away using their mobile device.

[0537] Input: Photo of bulky waste

[0538] Output: Image data saved on the device

[0539] Specific operation: The user takes a photo of the sofa using the smartphone's camera app. After taking the photo, the photo is saved in the device's gallery.

[0540] Step 2:

[0541] The images taken by the device are sent to the server via a system-specific app.

[0542] Input: Image data stored on the device

[0543] Output: Image data sent to the server

[0544] Specific operation: The user launches the system's dedicated app and selects the photo of the sofa they have taken. After selection, the system's dedicated app sends the image data to the server.

[0545] Step 3:

[0546] Based on the images received by the server, preprocessing is performed using OpenCV.

[0547] Input: Image data received by the server

[0548] Output: Preprocessed image data

[0549] Specific operation: The server uses OpenCV to perform preprocessing such as image noise removal and resizing.

[0550] Step 4:

[0551] The server uses TensorFlow to analyze the images and identify the type of waste.

[0552] Input: Preprocessed image data

[0553] Output: Identified waste types

[0554] How it works: Preprocessed image data is fed into a TensorFlow AI model to identify the type of waste (e.g., sofa).

[0555] Step 5:

[0556] The server collects fees and disposal methods from a database based on the identified waste type.

[0557] Input: Identified waste type

[0558] Output: Information about fees and disposal methods

[0559] Specific operation: The server retrieves the fee (e.g., 1,200 yen) and collection date (e.g., May 15th, May 18th) from the database based on the type of waste (e.g., sofa).

[0560] Step 6:

[0561] The terminal presents the fee received from the server and the collection date to the user.

[0562] Input: Fee and disposal method information

[0563] Output: Information presented to the user

[0564] Specific operation: The terminal will display a pop-up message to the user indicating the fee (e.g., 1,200 yen) and the collection dates (e.g., May 15th, May 18th).

[0565] Step 7:

[0566] The user selects the desired collection date, and the terminal transmits this information to the server.

[0567] Input: User selected collection date

[0568] Output: Data sent to the server on the collection date

[0569] Specific operation: The user taps to select a collection date (e.g., May 15th) on the device, and the device sends the selected collection date to the server.

[0570] Step 8:

[0571] The server schedules the collection appointment.

[0572] Input: User selected collection date

[0573] Output: Notification of confirmed collection reservation

[0574] Specific operation: The server checks the collection date and confirms the schedule. After confirmation, a notification "Collection reservation confirmed" is displayed on the device.

[0575] Step 9:

[0576] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[0577] Input: AI analysis results

[0578] Output: Information about details of non-burnable waste

[0579] Specific operation: The server determines that the item is non-combustible waste (e.g., a metal frying pan) and sends disposal instructions (e.g., to dispose of in a designated place on a designated day) to the terminal.

[0580] Step 10:

[0581] The device will guide the user on how to dispose of non-burnable waste.

[0582] Input: Information about details of non-burnable waste

[0583] Output: Information presented to the user

[0584] Specific operation: The device displays the message, "Please dispose of metal frying pans as non-burnable waste in the designated place on the designated day."

[0585] Step 11:

[0586] The server determines whether the waste has market value and makes suggestions for reuse or recycling.

[0587] Input: AI analysis results and marketplace information

[0588] Output: Reuse and recycling suggestions

[0589] Specific operation: For waste items that the server determines to be valuable (e.g., old guitars), it obtains the estimated price (e.g., 10,000 yen) and listing instructions and sends them to the terminal.

[0590] Step 12:

[0591] The terminal provides users with information about valuable waste and guides them through the listing process.

[0592] Input: Reuse and recycling suggestions

[0593] Output: Information presented to the user

[0594] Specific operation: The device displays "The estimated price of this guitar is 10,000 yen. Would you like to list it?" and if the user selects "List it," it guides the user through the listing process.

[0595] Step 13:

[0596] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[0597] Input: User's facial expressions and voice data

[0598] Output: User's emotional state

[0599] Specific operation: The emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and identify their emotional state (e.g., stress).

[0600] Step 14:

[0601] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[0602] Input: User's emotional state

[0603] Output: An encouraging message

[0604] Specific operation: If it is determined that the user is feeling stressed, the device will display a message saying, "Don't worry. The procedure will be easy."

[0605] (Application example 2)

[0606] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0607] Conventional industrial waste treatment systems do not distinguish between different types of waste, provide appropriate treatment methods, or evaluate the market value of valuable waste, resulting in insufficient treatment efficiency and effective resource utilization. Furthermore, there is a lack of operational support that takes into account the emotional state of workers, which increases the stress and burden of operation.

[0608] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the treatment of the identified waste, means for presenting information on the treatment, means for booking waste collection based on input from the user, means for evaluating the value of the waste and suggesting reuse or recycling, means for issuing operational instructions for carrying out a waste treatment method within the factory, and means for recognizing the operator's emotions and issuing corresponding alerts and instructions. This enables efficient and accurate waste treatment and reduces worker stress.

[0609] The "means for acquiring images" refers to a device for taking images of waste and recording them as digital data.

[0610] The "means for analyzing the acquired image and identifying the type of waste" is a combination of software and hardware for processing image data and automatically determining the type of waste.

[0611] The "means for collecting information on the disposal of identified waste" is a system for obtaining information on appropriate disposal methods and fees from a database based on the identification results.

[0612] A "means for presenting information about a process" is a device that displays or communicates the collected information to the user visually or audibly.

[0613] The "means for scheduling waste collection based on user input" refers to a system that receives user instructions and schedules collection activities based on that information.

[0614] "Means for assessing the value of waste and proposing reuse and recycling" is a system that determines the market value of identified waste and suggests the possibility of reuse or recycling.

[0615] The "means for issuing operational instructions for carrying out waste treatment methods within the factory" is a system that transmits instructions to equipment and workers within the factory for carrying out appropriate treatment operations for identified waste.

[0616] "Means for recognizing the operator's emotions and issuing corresponding alerts and instructions" refers to a system that detects the emotional state of the worker from their facial expressions and voice, and provides appropriate alerts and work instructions.

[0617] This invention relates to a robot system that efficiently processes industrial waste generated in factories. This system has multiple functions for identifying waste, suggesting processing methods, assessing its value, providing appropriate operating instructions, and recognizing the emotions of the operator.

[0618] Hardware and software used

[0619] Hardware:

[0620] Industrial robots (e.g. general-purpose robot arms)

[0621] Image capture camera (e.g. high resolution camera)

[0622] Microphones for emotion recognition (e.g., high-sensitivity microphones)

[0623] software:

[0624] AI models for image analysis (e.g., TensorFlow, OpenCV)

[0625] Sentiment analysis engines (e.g., emotion recognition software)

[0626] Database (e.g. SQL database)

[0627] Robot control software (e.g. robot operating system)

[0628] Program Description

[0629] 1. Image acquisition and analysis:

[0630] The server captures images of the waste using high-resolution cameras mounted on robotic arms inside the factory.

[0631] The captured images are then analyzed using a TensorFlow-based AI model to automatically identify the type of waste.

[0632] 2. Information Collection and Presentation:

[0633] The server collects information about processing fees and methods from an SQL database based on the type of waste identified.

[0634] The collected information is presented to the operator via a display and voice notification device installed on the robot.

[0635] 3. Value Assessment and Proposition:

[0636] If the identified waste has market value, the server evaluates its value and suggests the possibility of reuse or recycling.

[0637] If necessary, collect and suggest pricing information via external marketplace APIs.

[0638] 4. Instructions for carrying out the processing method:

[0639] The robotic arm moves or processes the identified waste to the appropriate location based on instructions from the server.

[0640] For example, metal pieces go to a metal recycling container and plastic pieces go to a plastic recycling container.

[0641] 5. Emotion recognition and response:

[0642] The server uses a sensitive microphone to collect the operator's voice and uses emotion recognition software to analyze their emotions.

[0643] If the user is feeling stressed, appropriate encouraging messages and information will be provided, along with operational support.

[0644] Examples of concrete examples and prompts

[0645] Examples:

[0646] Example 1: Processing metal pieces

[0647] The system identifies metal pieces from the captured images and instructs them to be moved to a metal recycling container.

[0648] If a worker is feeling stressed, display the message "Good job! Let's try a little harder."

[0649] Example prompt sentence:

[0650] Example prompts to input to the AI ​​model:

[0651] "Analyze this image to identify the type of waste in the image. Distinguish whether the waste is metal, plastic, or paper, and use that information to suggest an appropriate disposal method."

[0652] Example prompts for the emotion engine:

[0653] "Recognize the worker's emotions from this voice data and generate appropriate encouraging messages if they are feeling stressed."

[0654] In this way, the invention is expected to realize efficient and accurate waste disposal within factories while also reducing worker stress.

[0655] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0656] Step 1:

[0657] The server captures images of the waste using high-resolution cameras mounted on robotic arms inside the factory.

[0658] Input: Physical state of waste

[0659] Output: High-resolution waste image data

[0660] Step 2:

[0661] The server receives the captured image data, analyzes it using an AI model for image analysis, and automatically identifies the type of waste.

[0662] Input: High-resolution waste image data

[0663] Output: Identified waste type (e.g. metal pieces, plastic pieces)

[0664] Step 3:

[0665] The server collects information on processing fees and processing methods from an SQL database based on the identified waste type.

[0666] Input: Identified waste type

[0667] Output: Information on waste disposal fees and disposal methods

[0668] Step 4:

[0669] The server sends the collected information to the robot control terminal in the factory and presents it to the operator via a display or audio notification device.

[0670] Input: Waste disposal fee and disposal method information

[0671] Output: Proposed processing fee and processing method information

[0672] Step 5:

[0673] The server evaluates the market value of the identified waste and determines whether it can be reused or recycled, and if necessary, uses marketplace APIs to collect pricing information.

[0674] Input: Identified waste type

[0675] Output: Market value assessment and suggestions for reuse and recycling

[0676] Step 6:

[0677] The server issues operational instructions to the robotic arm to move or process the identified waste to an appropriate location.

[0678] Input: Identified waste type and disposal method information

[0679] Output: Proper disposal of waste

[0680] Step 7:

[0681] The server uses a highly sensitive microphone to collect the operator's voice and uses emotion recognition software to analyze the operator's emotions.

[0682] Input: Operator's voice data

[0683] Output: Emotional state of the operator (e.g., stress, joy)

[0684] Step 8:

[0685] If the server determines that the operator is feeling stressed, it provides encouraging messages and appropriate information to assist the operator in their work.

[0686] Input: Emotional state of the operator

[0687] Output: Encouraging messages and work support information

[0688] In this way, through the above processing steps, efficient and accurate waste disposal is achieved within the factory.

[0689] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0690] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0691] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0692] [Second embodiment]

[0693] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0694] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0695] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0696] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0697] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0698] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0699] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0700] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0701] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0702] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0703] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0704] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0705] This invention is an AI-based system for simplifying the procedure for disposing of bulky waste. The detailed configuration of this system and the program processing are explained below.

[0706] System configuration

[0707] This system mainly consists of the following components:

[0708] 1. Image acquisition method

[0709] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[0710] 2. Image analysis methods

[0711] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[0712] 3. Information gathering methods

[0713] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[0714] 4. Information presentation means

[0715] The terminal has the function of displaying the fees and processing method to the user.

[0716] 5. Collection reservation method

[0717] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[0718] 6. How to determine non-burnable waste

[0719] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[0720] 7. Value Judgment Tools

[0721] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[0722] Program processing

[0723] 1. Image acquisition and transmission

[0724] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[0725] The device sends the captured image to the server.

[0726] 2. Image Analysis

[0727] The server receives the image and analyzes it using AI.

[0728] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[0729] 3. Collection and presentation of information

[0730] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[0731] The server sends the fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[0732] The terminal displays this information to the user.

[0733] 4. Select a collection date and make a reservation

[0734] The user selects the desired collection date (e.g., May 15th) from the options presented.

[0735] The terminal transmits the selected collection date to the server.

[0736] The server receives the collection reservation information and determines the collection schedule.

[0737] 5. Non-burnable garbage classification and guidance

[0738] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[0739] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[0740] 6. Valuable garbage proposals

[0741] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[0742] The server sends information about the estimated price and listing procedures to the terminal.

[0743] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[0744] Specific examples

[0745] 1. Sofa disposal procedures

[0746] A user takes a photo of an old sofa.

[0747] The device sends the photo to the server.

[0748] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[0749] The user selects May 15th as the collection date.

[0750] The terminal sends the collection date to the server and confirms the reservation.

[0751] 2. If the frying pan is non-burnable garbage

[0752] A user takes a photo of an old metal frying pan.

[0753] The device sends the photo to the server.

[0754] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[0755] The device will guide the user on how to dispose of non-burnable waste.

[0756] 3. Proposal for listing a valuable guitar

[0757] A user takes a photo of an old guitar.

[0758] The device sends the photo to the server.

[0759] The server analyzes the photo and determines that it is a valuable guitar. It sends an estimated price of 10,000 yen and instructions on how to list the item.

[0760] The device displays the product description, estimated price, and listing procedure to the user, and the user selects "List."

[0761] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[0762] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse.

[0763] The processing flow will be explained below.

[0764] Program processing steps

[0765] Booking by photo shoot

[0766] Step 1:

[0767] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[0768] Step 2:

[0769] The device sends the photograph to the server.

[0770] Step 3:

[0771] The server passes the received photos to the AI ​​model and begins analysis.

[0772] Step 4:

[0773] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[0774] Step 5:

[0775] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[0776] Step 6:

[0777] The terminal displays the received fee and collection date to the user.

[0778] Step 7:

[0779] The user selects a desired date (for example, May 15th) from the collection dates presented.

[0780] Step 8:

[0781] The terminal transmits the selected collection date and reservation information to the server.

[0782] Step 9:

[0783] The server stores the reservation information and schedules the collection.

[0784] Judgment as non-burnable waste

[0785] Step 1:

[0786] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[0787] Step 2:

[0788] The device sends the photograph to the server.

[0789] Step 3:

[0790] The server passes the received photos to the AI ​​model and begins analysis.

[0791] Step 4:

[0792] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[0793] Step 5:

[0794] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[0795] Step 6:

[0796] The terminal displays information on how to dispose of non-burnable waste to the user.

[0797] Valuable garbage proposals

[0798] Step 1:

[0799] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[0800] Step 2:

[0801] The device sends the photograph to the server.

[0802] Step 3:

[0803] The server passes the received photos to the AI ​​model and begins analysis.

[0804] Step 4:

[0805] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[0806] Step 5:

[0807] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[0808] Step 6:

[0809] The server sends information about the estimated price and listing procedures to the terminal.

[0810] Step 7:

[0811] The terminal displays the received information to the user and guides them through the listing procedure.

[0812] Step 8:

[0813] The user follows the instructions and selects "List."

[0814] Step 9:

[0815] The terminal transmits the request to put up for sale to the server.

[0816] Step 10:

[0817] The server receives the listing information and completes the listing process via the Marketplace API.

[0818] Example 1

[0819] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0820] The conventional procedure for disposing of bulky waste is complicated and time-consuming, and it is difficult to obtain information on appropriate disposal methods and fees. It is also difficult to distinguish between non-burnable and non-burnable waste, and opportunities to reuse or recycle valuable waste are often overlooked. A system that solves these problems and makes the process for disposing of bulky waste efficient and easy is needed.

[0821] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0822] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving collection of the waste based on input from the user, and means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user. This makes it possible to provide information on disposal methods and fees for bulky waste, reserve collection dates, distinguish between non-burnable and combustible waste, and suggest reuse or recycling of valuable waste.

[0823] The "means for acquiring images" refers to a device or software that has the function of taking a photo of the bulky waste that the user wants to dispose of and inputting that image into the system.

[0824] "Means for analyzing acquired images and identifying the type of waste" refers to a device or software that has the function of analyzing image data received by the server using an AI model or the like to identify the type of waste.

[0825] "Means for collecting information on the disposal of identified waste" means a device or software that has the function of allowing the server to retrieve information on fees and disposal methods related to the disposal of waste from a database based on the type of waste identified.

[0826] The "means for presenting information regarding disposal" refers to a device or software that has the function of transmitting information regarding disposal of waste collected by the server to the user's terminal and displaying it on the terminal.

[0827] "Means for reserving waste collection based on user input" refers to a device or software that has the function of sending information such as the desired collection date entered by the user into the terminal to a server, and the server then confirming the collection reservation based on that information.

[0828] The "means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user" refers to a device or software that has the function of a server evaluating the market value of waste and suggesting reuse or recycling of that waste to the user.

[0829] "Means for determining whether waste is non-burnable waste and presenting the relevant information to the user" refers to a device or software that has the function of a server determining whether waste is non-burnable waste based on the results of image analysis, and sending and presenting the results to the user's terminal.

[0830] "Means for using a marketplace API to collect the market value and listing procedures for valuable waste and present them to users" refers to a device or software that has the function of a server using an online marketplace API to collect information on the market value and listing procedures for valuable waste, and sending that information to the user's terminal for presentation.

[0831] The present invention is an AI-based system for simplifying the procedure for disposing of bulky waste. Detailed embodiments of this system are described below.

[0832] System configuration

[0833] This system mainly consists of the following components:

[0834] 1. Image acquisition method

[0835] The device has a function that allows users to take a photo of the bulky waste they want to throw away and input the image into the system. A smartphone or digital camera is the hardware that performs this function.

[0836] 2. Image analysis methods

[0837] The device sends the captured image to a server, which then uses AI to analyze the image and identify the type of waste. Specifically, it uses the generative AI model YOLO (You Only Look Once).

[0838] 3. Information gathering methods

[0839] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[0840] 4. Information presentation means

[0841] The server sends the collected information to the terminal, which then displays the fees and processing method to the user.

[0842] 5. Collection reservation method

[0843] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[0844] 6. How to determine non-burnable waste

[0845] The server has the ability to determine whether the waste is non-combustible based on the analysis results and send that information to the terminal.

[0846] 7. Market value assessment and reuse proposal methods

[0847] The server evaluates whether the waste has market value and uses the marketplace API to make reuse and recycling suggestions to users.

[0848] Program processing

[0849] 1. Image acquisition and transmission

[0850] A user takes a photo of a large piece of trash, such as an old sofa, with a mobile device.

[0851] The device sends the captured image to the server. The image data is sent using an internet connection.

[0852] 2. Image Analysis

[0853] The server inputs the received image into an AI model and starts image analysis, for example, using YOLO.

[0854] The server uses the analysis results to identify the object (e.g., an old sofa) contained in the image, and returns the identification result as a specific name such as sofa.

[0855] 3. Collection and presentation of information

[0856] The server retrieves information about fees and disposal methods related to the identified waste (e.g., sofa) from the database. For example, it retrieves information that the disposal fee for a sofa is 1,200 yen.

[0857] The server checks the dates that can be collected (e.g., May 15th or May 18th) and sends that information to the terminal.

[0858] The terminal will display the fee and collection dates to the user, who can then select a collection date based on the displayed information.

[0859] 4. Select a collection date and make a reservation

[0860] The user selects the desired date (e.g., May 15th) from the available collection dates presented.

[0861] The terminal sends the collection date information selected by the user to the server, which then registers the selected collection date in the database.

[0862] The server confirms the collection reservation information and notifies the user that the reservation has been completed.

[0863] 5. Non-burnable garbage classification and guidance

[0864] The server determines from the analysis results that the waste is non-burnable (e.g., a metal frying pan). The determination is made based on pre-set rules.

[0865] The server notifies the terminal of non-burnable waste information.

[0866] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[0867] 6. Market value assessment and reuse proposals

[0868] If the server determines from the analysis results that the waste has value (e.g., an old guitar), it uses the marketplace API to collect possible product value and listing information.

[0869] The server sends the collected information to the device, including the estimated price (e.g., 10,000 yen) and details of the listing process.

[0870] The device displays the product description, estimated price, and listing procedure to the user. If the user selects "List," the device sends this information to the server. An example of a generated prompt might be, "The estimated value of this guitar is 10,000 yen. Would you like to list it?"

[0871] The server performs the listing procedure on the online auction site and sends a completion notice to the user.

[0872] Specific examples

[0873] For example, a user takes a photo of an old sofa and sends it to a server via their smartphone. The server analyzes the image and recognizes it as a sofa, then retrieves the 1,200 yen handling fee and collection dates (May 15th and May 18th) from a database and sends them to the device. The device displays this information to the user, who selects May 15th. The selected information is sent to the server, which then confirms the collection reservation. In addition, the server can display suggestions for items such as metal frying pans, which can be disposed of as non-burnable waste, and items such as guitars, which can be reused or recycled, for sale.

[0874] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0875] Step 1:

[0876] Image capture and transmission

[0877] The user takes a photo of the bulky item they want to throw away (e.g., an old sofa) with their smartphone. This becomes the input image for the system. Specific actions include opening the camera app and taking a photo.

[0878] The device sends the captured image file to the server. An internet connection is required for transmission, and a protocol such as an HTTP request is used. The input is the captured image file, and the output is the completion of sending the image data to the server.

[0879] Step 2:

[0880] Image analysis

[0881] The server inputs the received image file into the AI ​​model and begins image analysis. Specific operations include using generative AI models such as YOLO (You Only Look Once).

[0882] The server uses an AI model to identify an object (e.g., a sofa) in an image. The input is the received image data, and the output is the name of the identified object (e.g., "sofa"). The server supplies the image data to the AI ​​model and receives the generated label.

[0883] Step 3:

[0884] Collection and presentation of information

[0885] The server collects information related to waste disposal from a database based on the identification result (e.g., "sofa"), and specific operations include querying the database using an SQL query.

[0886] The input is the name of the identification result, and the output is the collected fee and the collectable date information (e.g., "Fee 1,200 yen, collection dates May 15th and May 18th").

[0887] The server sends the collected information to the terminal.

[0888] The terminal displays the collection information (fees and collection date) to the user. Specific operations include displaying the information on the application screen.

[0889] Step 4:

[0890] Selecting and reserving a collection date

[0891] The user selects the desired date (e.g., May 15th) from the available dates presented for collection. This becomes the input for the next process. Specific actions include selecting a date from a calendar interface on the application.

[0892] The terminal sends the user's selection information to the server. The input is the collection date selected by the user, and the output is the completion of information transmission to the server.

[0893] The server registers the collection reservation in the database based on the received selection information, including saving the collection date in the database using an SQL query.

[0894] Step 5:

[0895] Non-burnable waste determination and guidance

[0896] The server determines whether the waste is non-burnable or not based on the results of image analysis. This is done using predefined rules. The input is the result of image analysis, and the output is the determination of whether the waste is non-burnable or not.

[0897] The server sends the result of the judgment to the user's terminal. The input is the judgment result of non-burnable waste, and the output is the completion of information transmission to the terminal.

[0898] The terminal displays a message to the user such as, "Please dispose of metal frying pans as non-burnable garbage on the specified day in the specified place." Specific actions include displaying a message on the application screen.

[0899] Step 6:

[0900] Market value assessment and reuse proposals

[0901] The server evaluates whether the waste has market value based on the results of image analysis. The input is the waste identification result, and the output is the market value assessment result.

[0902] The server uses the marketplace's API to gather possible product values ​​and listing information, including sending API requests and receiving information.

[0903] The server sends the collected information to the terminal. The input is the product value information obtained from the API, and the output is the completion of sending the information to the terminal.

[0904] The terminal displays to the user a description of the product, an estimated price (e.g., 10,000 yen), and listing procedure information. If the user selects "List," the terminal sends this information to the server. Specific operations include displaying listing procedure instructions on the application screen and receiving user input.

[0905] The server processes the listing on the online auction site and sends a completion notice to the user. The input is the user's listing information, and the output is a completion notice of the listing procedure.

[0906] (Application example 1)

[0907] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0908] The present invention aims to solve the problem of the complicated procedure for disposing of bulky waste and the inability of users to properly understand how to dispose of it. It also aims to provide a method for effectively utilizing waste that has value and can be reused or recycled without overlooking that value. Another objective is to simplify the process of reserving collection dates and improve user convenience.

[0909] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0910] In this invention, the server includes a means for presenting a collection method for valuable waste, a means for the user to input a desired collection date, and a means for confirming collection reservation information, which allows the user to easily carry out the procedure for disposing of bulky waste and further enables the user to maximize the value of reusable and recyclable waste.

[0911] The "means for acquiring images" refers to a means by which a user takes a photograph of the bulky waste and inputs the image into the system.

[0912] "Means for analyzing acquired images to identify the type of waste" refers to the means by which the system uses AI to analyze images sent to the server and identify the type of waste.

[0913] The "means for collecting information on the disposal of identified waste" is a means for the server to obtain information on disposal fees and disposal methods for identified waste from the database.

[0914] The "means for presenting information about processing" is a means for displaying information about the acquired fee and processing method to the user.

[0915] The "means for reserving waste collection based on input from the user" refers to a means for the user to input a desired collection date and transmit that information to the server to make a collection reservation.

[0916] "Means for suggesting methods for recovering valuable waste" refers to means for proposing reuse or recycling when waste has market value based on the analysis results.

[0917] The "means for the user to input the desired collection date" is a means for the user to select a collection date through the application and transmit that information to the server.

[0918] The "means for determining collection reservation information" is a means for the server to determine the collection schedule based on the selected collection date and update the reservation information.

[0919] This invention is an AI-based system for simplifying the process of disposing of bulky waste, and is mainly composed of the following components:

[0920] System configuration

[0921] 1. Image acquisition method

[0922] Users can take photos of bulky waste with their smartphones and enter the images into the system.

[0923] 2. Image analysis methods

[0924] The captured images are sent from the smartphone to a cloud server (e.g., AWS EC2) where they are analyzed using an AI image analysis model (e.g., TensorFlow or PyTorch). This analysis identifies the type of waste.

[0925] 3. Information gathering methods

[0926] The server retrieves information on processing fees and processing methods for the identified waste from a cloud database (e.g., Amazon RDS).

[0927] 4. Information presentation means

[0928] Information about processing fees and processing methods is sent from the server to the smartphone and displayed to the user, allowing the user to check the necessary information.

[0929] 5. Collection reservation method

[0930] The user selects the desired collection date from the schedule presented and sends that information to the server via their smartphone. The server then confirms the collection reservation based on the received collection date information.

[0931] 6. How to determine non-burnable waste

[0932] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the user's smartphone and guides them on how to dispose of it properly.

[0933] 7. Value Judgment Tools

[0934] If the server determines that the waste is valuable using the AI ​​image analysis model, it uses a marketplace API (e.g., eBay API) to collect information about the product value and listing, and suggests reuse or recycling to the user.

[0935] Hardware and software used

[0936] Hardware: Smartphone camera, cloud server (AWS EC2), cloud database (Amazon RDS)

[0937] Software: Mobile app (Flutter or React Native), AI image analysis model (TensorFlow or PyTorch), marketplace API (eBay API)

[0938] Specific examples

[0939] 1. Sofa disposal procedures

[0940] A user takes a photo of an old sofa with their smartphone.

[0941] The image is sent to a cloud server, where an AI image analysis model identifies it as a sofa.

[0942] The server retrieves the processing fee and collection date from a cloud database and displays them on the smartphone.

[0943] The user selects the desired collection date, and the server confirms the collection reservation.

[0944] 2. If the frying pan is non-burnable garbage

[0945] A user takes a photo of a metal frying pan with their smartphone.

[0946] The image is sent to a cloud server, and an AI image analysis model determines that the frying pan is non-burnable waste.

[0947] The server obtains the disposal method for non-combustible waste and displays it on the smartphone.

[0948] 3. Proposal for listing a valuable guitar

[0949] A user takes a photo of an old guitar with their smartphone.

[0950] The images are sent to a cloud server, where an AI image analysis model determines whether the guitar is valuable.

[0951] The server uses the marketplace API to obtain estimated prices and listing procedure information, which is then displayed on the smartphone.

[0952] Prompt Sentence Examples

[0953] "Analyze images of bulky waste taken by users with a smartphone app and identify the type of object (e.g. sofa, frying pan). After identification, retrieve the associated processing fee and possible collection date from the database and display them to the user. Also, for valuable objects, obtain an estimated price via the Marketplace API and provide information to guide the listing process."

[0954] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0955] Step 1:

[0956] Users take photos of bulky waste with their smartphones and upload the images to a cloud server via the application.

[0957] Input: Photo of bulky waste

[0958] Output: Image data is sent to the cloud server

[0959] Specific behavior: A user takes a photo with their smartphone camera and uses the application's image upload function to send the image to a cloud server.

[0960] Step 2:

[0961] The server inputs the received image data into an AI image analysis model to identify the type of waste.

[0962] Input: Image data

[0963] Output: Waste type determination (e.g. sofa, frying pan)

[0964] How it works: The images sent to the cloud server are stored and passed to an AI model (e.g., TensorFlow or PyTorch), which then analyzes the images and identifies the type of waste.

[0965] Step 3:

[0966] Based on the identified type of waste, the server collects information on processing fees and processing methods from a cloud database.

[0967] Input: Waste type determination result

[0968] Output: Processing fee and processing method information

[0969] Specific operation: Sends a query to a cloud database (e.g., Amazon RDS) to obtain disposal fees and methods corresponding to the waste type.

[0970] Step 4:

[0971] The server sends the collected information to the terminal, which displays the information to the user.

[0972] Input: Processing fee and processing method information

[0973] Output: User-visible processing fee and processing method

[0974] Specific operation: The server sends information such as processing fees and collection dates to the user's smartphone via API, and the smartphone app displays the information to the user.

[0975] Step 5:

[0976] The user selects the desired collection date from the available collection dates displayed and transmits the information to the server via the terminal.

[0977] Input: User's desired collection date

[0978] Output: Collection date information sent to the server

[0979] How it works: The user selects a collection date using the smartphone app interface, and that information is sent to the server via an API.

[0980] Step 6:

[0981] The server confirms the collection reservation based on the received collection date information and updates the schedule.

[0982] Input: User's desired collection date

[0983] Output: Confirmed collection reservation information

[0984] Specific operation: The server saves the received collection date information in the database and updates and confirms the collection schedule.

[0985] Step 7:

[0986] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the terminal and guides the user on the appropriate disposal method.

[0987] Input: Waste is non-burnable waste

[0988] Output: How to dispose of non-burnable waste

[0989] Specific operation: If the server determines that the item is non-combustible waste using the AI ​​model, it sends information about how to dispose of it to the user's smartphone, and the application displays that information.

[0990] Step 8:

[0991] If the server determines that the waste has value using the AI ​​image analysis model, it uses the marketplace API to collect information about the product's value and listing, and suggests reuse or recycling to the user.

[0992] Input: Determination that the waste is valuable

[0993] Output: Information on product value and listing procedures

[0994] How it works: The server queries a marketplace API (e.g., eBay API) to obtain information about the product's value and listing process, and sends it to the user's smartphone. The application displays this information to the user and suggests reuse and recycling options.

[0995] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0996] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes the user's emotions. The detailed configuration of this system and the program processing are described below.

[0997] System configuration

[0998] This system mainly consists of the following components:

[0999] 1. Image acquisition method

[1000] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[1001] 2. Image analysis methods

[1002] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[1003] 3. Information gathering methods

[1004] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[1005] 4. Information presentation means

[1006] The terminal has the function of displaying the fees and processing method to the user.

[1007] 5. Collection reservation method

[1008] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[1009] 6. How to determine non-burnable waste

[1010] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[1011] 7. Value Judgment Tools

[1012] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[1013] 8. Emotion Engine

[1014] It has the ability to recognize the user's emotions and provide information and simplify procedures based on that.

[1015] Program processing

[1016] 1. Image acquisition and transmission

[1017] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[1018] The device sends the captured image to the server.

[1019] 2. Image Analysis

[1020] The server receives the image and analyzes it using AI.

[1021] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[1022] 3. Collection and presentation of information

[1023] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[1024] The server returns the handling fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[1025] The terminal displays this information to the user.

[1026] 4. Select a collection date and make a reservation

[1027] The user selects the desired collection date (e.g., May 15th) from the options presented.

[1028] The terminal transmits the selected collection date to the server.

[1029] The server receives the collection reservation information and determines the collection schedule.

[1030] 5. Non-burnable garbage classification and guidance

[1031] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[1032] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[1033] 6. Valuable garbage proposals

[1034] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[1035] The server sends information about the estimated price and listing procedures to the terminal.

[1036] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[1037] 7. The Emotional Engine

[1038] The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state.

[1039] When the emotion engine determines that the user is feeling stressed, an encouraging message is displayed to the user through the information presentation means.

[1040] If more emotion engines are needed, they instruct the server or terminal how to simplify the steps of the procedure.

[1041] Specific examples

[1042] 1. Sofa disposal procedures

[1043] A user takes a photo of an old sofa.

[1044] The device sends the photo to the server.

[1045] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[1046] The user selects May 15th as the collection date.

[1047] The terminal sends the collection date to the server and confirms the reservation.

[1048] 2. If the frying pan is non-burnable garbage

[1049] A user takes a photo of a metal frying pan.

[1050] The device sends the photo to the server.

[1051] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[1052] The device will guide the user on how to dispose of non-burnable waste.

[1053] 3. When a guitar is valuable

[1054] A user takes a photo of an old guitar.

[1055] The device sends the photo to the server.

[1056] The server analyzes the photo and determines that the guitar is valuable. It sends an estimated price of 10,000 yen and instructions on how to list the item to the user's device.

[1057] The device displays the product description, estimated price, and listing procedure to the user, and they select "List."

[1058] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[1059] 4. User Emotion Recognition

[1060] If the user is feeling stressed, the emotion engine will analyze and recognize the state.

[1061] The emotion engine instructs the device to display an appropriate encouraging message.

[1062] The emotion engine instructs the server or terminal to automate or simplify parts of the procedure, allowing the user to proceed smoothly.

[1063] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse. In addition, the emotion engine provides a comfortable operating experience for users.

[1064] The processing flow will be explained below.

[1065] Program processing steps

[1066] Booking by photo shoot

[1067] Step 1:

[1068] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[1069] Step 2:

[1070] The device sends the photograph to the server.

[1071] Step 3:

[1072] The server passes the received photos to the AI ​​model and begins analysis.

[1073] Step 4:

[1074] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[1075] Step 5:

[1076] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[1077] Step 6:

[1078] The terminal displays the received fee and collection date to the user.

[1079] Step 7:

[1080] The user selects a desired date (for example, May 15th) from the collection dates presented.

[1081] Step 8:

[1082] The terminal transmits the selected collection date and reservation information to the server.

[1083] Step 9:

[1084] The server stores the reservation information and schedules the collection.

[1085] Judgment as non-burnable waste

[1086] Step 1:

[1087] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[1088] Step 2:

[1089] The device sends the photograph to the server.

[1090] Step 3:

[1091] The server passes the received photos to the AI ​​model and begins analysis.

[1092] Step 4:

[1093] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[1094] Step 5:

[1095] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[1096] Step 6:

[1097] The terminal displays information on how to dispose of non-burnable waste to the user.

[1098] Valuable garbage proposals

[1099] Step 1:

[1100] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[1101] Step 2:

[1102] The device sends the photograph to the server.

[1103] Step 3:

[1104] The server passes the received photos to the AI ​​model and begins analysis.

[1105] Step 4:

[1106] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[1107] Step 5:

[1108] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[1109] Step 6:

[1110] The server sends information about the estimated price and listing procedures to the terminal.

[1111] Step 7:

[1112] The terminal displays the received information to the user and guides them through the listing procedure.

[1113] Step 8:

[1114] The user follows the instructions and selects "List."

[1115] Step 9:

[1116] The terminal transmits the request to put up for sale to the server.

[1117] Step 10:

[1118] The server receives the listing information and completes the listing process via the Marketplace API.

[1119] User support with emotion engine

[1120] Step 1:

[1121] When a user uses the system, the emotion engine captures the user's facial expressions and voice through the camera and microphone.

[1122] Step 2:

[1123] The facial expression and voice data acquired by the device is sent to the server.

[1124] Step 3:

[1125] The server passes the received facial expression and voice data to the emotion engine and begins analysis.

[1126] Step 4:

[1127] The server determines whether the user is feeling stressed or dissatisfied based on the analysis of the emotion engine.

[1128] Step 5:

[1129] The server determines the appropriate message and dialogue procedure based on the emotional state and sends that information to the terminal.

[1130] Step 6:

[1131] The device displays an appropriate message to the user (e.g., "We're here to help you. Let us know if you have any questions.").

[1132] Step 7:

[1133] As the user proceeds, the emotion engine continues to monitor the user's emotional state and instructs the server to simplify the process if necessary.

[1134] Step 8:

[1135] The server handles the simplification of procedures, for example by providing auto-filling and additional support to reduce the burden on the user.

[1136] Example 2

[1137] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1138] The process of disposing of bulky waste is complicated and often stressful for users. Furthermore, if the waste has market value, opportunities for reuse or recycling may be missed. Furthermore, there is a lack of means to recognize the user's emotions and provide appropriate support, which hinders the user's operational experience.

[1139] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1140] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving waste collection based on input from the user, and means for recognizing the user's emotions and providing information based on the emotions. This makes it possible to carry out the procedure for disposing of oversized waste easily and smoothly, preventing missed opportunities for reuse and recycling and providing a comfortable operating experience for the user.

[1141] "Means for acquiring images" refers to devices or software that allow a user to take an image of the waste they wish to dispose of and input that image into the system.

[1142] "Means for analyzing acquired images and identifying the type of waste" refers to devices or software that analyze received images and identify the type of waste depicted in the images using AI models, etc.

[1143] "Means for collecting information on the disposal of identified waste" refers to devices or software that retrieve information such as disposal methods and fees from a database based on the type of identified waste.

[1144] "Means for presenting information about processing" refers to devices or software that display collected information such as processing methods and fees to users.

[1145] "Means for reserving waste collection based on user input" refers to devices or software that reserve waste collection based on information entered by the user, such as the desired collection date.

[1146] "Means for recognizing a user's emotions and providing information based on those emotions" refers to devices or software that analyze a user's facial expressions, voice, etc. to identify emotions and provide information according to those emotions.

[1147] "Means for determining whether waste is non-combustible waste" refers to devices or software that determine whether identified waste is non-combustible waste.

[1148] "Means for determining whether waste has market value and proposing reuse or recycling if it is determined to have market value" refers to devices or software that determine whether identified waste has market value and, if it is determined to have value, proposes reuse or recycling.

[1149] MODE FOR CARRYING OUT THE INVENTION

[1150] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes user emotions. The system mainly includes the following hardware and software components:

[1151] Hardware and software used

[1152] Device: Smartphone or digital camera

[1153] Server: Cloud server with database and AI model

[1154] software:

[1155] Image processing: OpenCV

[1156] Image Analysis and Classification: TensorFlow

[1157] Emotion recognition: Emotion API

[1158] System Operation Overview

[1159] 1. Image acquisition method

[1160] The user takes a photo of the bulky waste they want to throw away using a smartphone or digital camera.

[1161] The images taken by the device are sent to the server via a system-specific app.

[1162] 2. Image analysis methods

[1163] Based on the images received by the server, preprocessing is performed using OpenCV.

[1164] The server uses TensorFlow to analyze the images and identify the type of waste.

[1165] 3. Information gathering methods

[1166] The server collects fees and disposal methods from a database based on the identified waste type.

[1167] 4. Information presentation means

[1168] The terminal presents the fee received from the server and the collection date to the user.

[1169] 5. Collection reservation method

[1170] The user selects the desired collection date and transmits that information from the terminal to the server.

[1171] The server schedules the collection appointment.

[1172] 6. How to determine non-burnable waste

[1173] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[1174] The device will guide the user on how to dispose of non-burnable waste.

[1175] 7. Value Judgment Tools

[1176] The server determines whether the waste has market value and makes suggestions for reuse or recycling as needed.

[1177] The server connects to the marketplace's API to collect estimated prices and listing procedures.

[1178] The terminal presents this information to the user and guides them through the listing procedure.

[1179] 8. Emotion Engine

[1180] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[1181] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[1182] If necessary, instructions will be provided to simplify the steps of the procedure.

[1183] Specific examples

[1184] 1. Sofa disposal procedures

[1185] A user takes a photo of an old sofa.

[1186] The device sends the photo to the server.

[1187] The server analyzes the image and identifies it as a sofa.

[1188] The fee is 1,200 yen and collection dates are May 15th and May 18th.

[1189] The user selects May 15th as the collection date, and the terminal sends the information to the server.

[1190] The server confirms the collection reservation.

[1191] 2. If the frying pan is non-burnable garbage

[1192] A user takes a photo of a metal frying pan.

[1193] The device sends the photo to the server.

[1194] The server analyzes the image and identifies the frying pan as non-combustible waste.

[1195] The device will guide the user on how to dispose of non-burnable waste.

[1196] 3. When a guitar is valuable

[1197] A user takes a photo of an old guitar.

[1198] The device sends the photo to the server.

[1199] The server analyzes the image and determines that it is a valuable guitar.

[1200] An estimated price of 10,000 yen and instructions on how to proceed with listing will be sent to your device.

[1201] The device displays the product description, estimated price, and listing procedure to the user, and asks whether they want to list the item.

[1202] If the user chooses to put up an item for auction, the terminal transmits the information to the server, which then processes the item for auction at the online auction.

[1203] Prompt Sentence Examples

[1204] "I want to simplify the process of throwing away an old sofa. Create a program where I can take a photo, submit it, and the system will suggest fees and a reservation date."

[1205] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1206] Step 1:

[1207] The user takes a photo of the bulky trash they want to throw away using their mobile device.

[1208] Input: Photo of bulky waste

[1209] Output: Image data saved on the device

[1210] Specific operation: The user takes a photo of the sofa using the smartphone's camera app. After taking the photo, the photo is saved in the device's gallery.

[1211] Step 2:

[1212] The images taken by the device are sent to the server via a system-specific app.

[1213] Input: Image data stored on the device

[1214] Output: Image data sent to the server

[1215] Specific operation: The user launches the system's dedicated app and selects the photo of the sofa they have taken. After selection, the system's dedicated app sends the image data to the server.

[1216] Step 3:

[1217] Based on the images received by the server, preprocessing is performed using OpenCV.

[1218] Input: Image data received by the server

[1219] Output: Preprocessed image data

[1220] Specific operation: The server uses OpenCV to perform preprocessing such as image noise removal and resizing.

[1221] Step 4:

[1222] The server uses TensorFlow to analyze the images and identify the type of waste.

[1223] Input: Preprocessed image data

[1224] Output: Identified waste types

[1225] How it works: Preprocessed image data is fed into a TensorFlow AI model to identify the type of waste (e.g., sofa).

[1226] Step 5:

[1227] The server collects fees and disposal methods from a database based on the identified waste type.

[1228] Input: Identified waste type

[1229] Output: Information about fees and disposal methods

[1230] Specific operation: The server retrieves the fee (e.g., 1,200 yen) and collection date (e.g., May 15th, May 18th) from the database based on the type of waste (e.g., sofa).

[1231] Step 6:

[1232] The terminal presents the fee received from the server and the collection date to the user.

[1233] Input: Fee and disposal method information

[1234] Output: Information presented to the user

[1235] Specific operation: The terminal will display a pop-up message to the user indicating the fee (e.g., 1,200 yen) and the collection dates (e.g., May 15th, May 18th).

[1236] Step 7:

[1237] The user selects the desired collection date, and the terminal transmits this information to the server.

[1238] Input: User selected collection date

[1239] Output: Data sent to the server on the collection date

[1240] Specific operation: The user taps to select a collection date (e.g., May 15th) on the device, and the device sends the selected collection date to the server.

[1241] Step 8:

[1242] The server schedules the collection appointment.

[1243] Input: User selected collection date

[1244] Output: Notification of confirmed collection reservation

[1245] Specific operation: The server checks the collection date and confirms the schedule. After confirmation, a notification "Collection reservation confirmed" is displayed on the device.

[1246] Step 9:

[1247] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[1248] Input: AI analysis results

[1249] Output: Information about details of non-burnable waste

[1250] Specific operation: The server determines that the item is non-combustible waste (e.g., a metal frying pan) and sends disposal instructions (e.g., to dispose of in a designated place on a designated day) to the terminal.

[1251] Step 10:

[1252] The device will guide the user on how to dispose of non-burnable waste.

[1253] Input: Information about details of non-burnable waste

[1254] Output: Information presented to the user

[1255] Specific operation: The device displays the message, "Please dispose of metal frying pans as non-burnable waste in the designated place on the designated day."

[1256] Step 11:

[1257] The server determines whether the waste has market value and makes suggestions for reuse or recycling.

[1258] Input: AI analysis results and marketplace information

[1259] Output: Reuse and recycling suggestions

[1260] Specific operation: For waste items that the server determines to be valuable (e.g., old guitars), it obtains the estimated price (e.g., 10,000 yen) and listing instructions and sends them to the terminal.

[1261] Step 12:

[1262] The terminal provides users with information about valuable waste and guides them through the listing process.

[1263] Input: Reuse and recycling suggestions

[1264] Output: Information presented to the user

[1265] Specific operation: The device displays "The estimated price of this guitar is 10,000 yen. Would you like to list it?" and if the user selects "List it," it guides the user through the listing process.

[1266] Step 13:

[1267] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[1268] Input: User's facial expressions and voice data

[1269] Output: User's emotional state

[1270] Specific operation: The emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and identify their emotional state (e.g., stress).

[1271] Step 14:

[1272] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[1273] Input: User's emotional state

[1274] Output: An encouraging message

[1275] Specific operation: If it is determined that the user is feeling stressed, the device will display a message saying, "Don't worry. The procedure will be easy."

[1276] (Application example 2)

[1277] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1278] Conventional industrial waste treatment systems do not distinguish between different types of waste, provide appropriate treatment methods, or evaluate the market value of valuable waste, resulting in insufficient treatment efficiency and effective resource utilization. Furthermore, there is a lack of operational support that takes into account the emotional state of workers, which increases the stress and burden of operation.

[1279] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the treatment of the identified waste, means for presenting information on the treatment, means for booking waste collection based on input from the user, means for evaluating the value of the waste and suggesting reuse or recycling, means for issuing operational instructions for carrying out a waste treatment method within the factory, and means for recognizing the operator's emotions and issuing corresponding alerts and instructions. This enables efficient and accurate waste treatment and reduces worker stress.

[1280] The "means for acquiring images" refers to a device for taking images of waste and recording them as digital data.

[1281] The "means for analyzing the acquired image and identifying the type of waste" is a combination of software and hardware for processing image data and automatically determining the type of waste.

[1282] The "means for collecting information on the disposal of identified waste" is a system for obtaining information on appropriate disposal methods and fees from a database based on the identification results.

[1283] A "means for presenting information about a process" is a device that displays or communicates the collected information to the user visually or audibly.

[1284] The "means for scheduling waste collection based on user input" refers to a system that receives user instructions and schedules collection activities based on that information.

[1285] "Means for assessing the value of waste and proposing reuse and recycling" is a system that determines the market value of identified waste and suggests the possibility of reuse or recycling.

[1286] The "means for issuing operational instructions for carrying out waste treatment methods within the factory" is a system that transmits instructions to equipment and workers within the factory for carrying out appropriate treatment operations for identified waste.

[1287] "Means for recognizing the operator's emotions and issuing corresponding alerts and instructions" refers to a system that detects the emotional state of the worker from their facial expressions and voice, and provides appropriate alerts and work instructions.

[1288] This invention relates to a robot system that efficiently processes industrial waste generated in factories. This system has multiple functions for identifying waste, suggesting processing methods, assessing its value, providing appropriate operating instructions, and recognizing the emotions of the operator.

[1289] Hardware and software used

[1290] Hardware:

[1291] Industrial robots (e.g. general-purpose robot arms)

[1292] Image capture camera (e.g. high resolution camera)

[1293] Microphones for emotion recognition (e.g., high-sensitivity microphones)

[1294] software:

[1295] AI models for image analysis (e.g., TensorFlow, OpenCV)

[1296] Sentiment analysis engines (e.g., emotion recognition software)

[1297] Database (e.g. SQL database)

[1298] Robot control software (e.g. robot operating system)

[1299] Program Description

[1300] 1. Image acquisition and analysis:

[1301] The server captures images of the waste using high-resolution cameras mounted on robotic arms inside the factory.

[1302] The captured images are then analyzed using a TensorFlow-based AI model to automatically identify the type of waste.

[1303] 2. Information Collection and Presentation:

[1304] The server collects information about processing fees and methods from an SQL database based on the type of waste identified.

[1305] The collected information is presented to the operator via a display and voice notification device installed on the robot.

[1306] 3. Value Assessment and Proposition:

[1307] If the identified waste has market value, the server evaluates its value and suggests the possibility of reuse or recycling.

[1308] If necessary, collect and suggest pricing information via external marketplace APIs.

[1309] 4. Instructions for carrying out the processing method:

[1310] The robotic arm moves or processes the identified waste to the appropriate location based on instructions from the server.

[1311] For example, metal pieces go to a metal recycling container and plastic pieces go to a plastic recycling container.

[1312] 5. Emotion recognition and response:

[1313] The server uses a sensitive microphone to collect the operator's voice and uses emotion recognition software to analyze their emotions.

[1314] If the user is feeling stressed, appropriate encouraging messages and information will be provided, along with operational support.

[1315] Examples of concrete examples and prompts

[1316] Examples:

[1317] Example 1: Processing metal pieces

[1318] The system identifies metal pieces from the captured images and instructs them to be moved to a metal recycling container.

[1319] If a worker is feeling stressed, display the message "Good job! Let's try a little harder."

[1320] Example prompt sentence:

[1321] Example prompts to input to the AI ​​model:

[1322] "Analyze this image to identify the type of waste in the image. Distinguish whether the waste is metal, plastic, or paper, and use that information to suggest an appropriate disposal method."

[1323] Example prompts for the emotion engine:

[1324] "Recognize the worker's emotions from this voice data and generate appropriate encouraging messages if they are feeling stressed."

[1325] In this way, the invention is expected to realize efficient and accurate waste disposal within factories while also reducing worker stress.

[1326] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1327] Step 1:

[1328] The server captures images of the waste using high-resolution cameras mounted on robotic arms inside the factory.

[1329] Input: Physical state of waste

[1330] Output: High-resolution waste image data

[1331] Step 2:

[1332] The server receives the captured image data, analyzes it using an AI model for image analysis, and automatically identifies the type of waste.

[1333] Input: High-resolution waste image data

[1334] Output: Identified waste type (e.g. metal pieces, plastic pieces)

[1335] Step 3:

[1336] The server collects information on processing fees and processing methods from an SQL database based on the identified waste type.

[1337] Input: Identified waste type

[1338] Output: Information on waste disposal fees and disposal methods

[1339] Step 4:

[1340] The server sends the collected information to the robot control terminal in the factory and presents it to the operator via a display or audio notification device.

[1341] Input: Waste disposal fee and disposal method information

[1342] Output: Proposed processing fee and processing method information

[1343] Step 5:

[1344] The server evaluates the market value of the identified waste and determines whether it can be reused or recycled, and if necessary, uses marketplace APIs to collect pricing information.

[1345] Input: Identified waste type

[1346] Output: Market value assessment and suggestions for reuse and recycling

[1347] Step 6:

[1348] The server issues operational instructions to the robotic arm to move or process the identified waste to an appropriate location.

[1349] Input: Identified waste type and disposal method information

[1350] Output: Proper disposal of waste

[1351] Step 7:

[1352] The server uses a highly sensitive microphone to collect the operator's voice and uses emotion recognition software to analyze the operator's emotions.

[1353] Input: Operator's voice data

[1354] Output: Emotional state of the operator (e.g., stress, joy)

[1355] Step 8:

[1356] If the server determines that the operator is feeling stressed, it provides encouraging messages and appropriate information to assist the operator in their work.

[1357] Input: Emotional state of the operator

[1358] Output: Encouraging messages and work support information

[1359] In this way, through the above processing steps, efficient and accurate waste disposal is achieved within the factory.

[1360] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1361] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1362] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1363] [Third embodiment]

[1364] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1365] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1366] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1367] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1368] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1369] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1370] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1371] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1372] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1373] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1374] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1375] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1376] This invention is an AI-based system for simplifying the procedure for disposing of bulky waste. The detailed configuration of this system and the program processing are explained below.

[1377] System configuration

[1378] This system mainly consists of the following components:

[1379] 1. Image acquisition method

[1380] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[1381] 2. Image analysis methods

[1382] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[1383] 3. Information gathering methods

[1384] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[1385] 4. Information presentation means

[1386] The terminal has the function of displaying the fees and processing method to the user.

[1387] 5. Collection reservation method

[1388] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[1389] 6. How to determine non-burnable waste

[1390] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[1391] 7. Value Judgment Tools

[1392] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[1393] Program processing

[1394] 1. Image acquisition and transmission

[1395] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[1396] The device sends the captured image to the server.

[1397] 2. Image Analysis

[1398] The server receives the image and analyzes it using AI.

[1399] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[1400] 3. Collection and presentation of information

[1401] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[1402] The server sends the fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[1403] The terminal displays this information to the user.

[1404] 4. Select a collection date and make a reservation

[1405] The user selects the desired collection date (e.g., May 15th) from the options presented.

[1406] The terminal transmits the selected collection date to the server.

[1407] The server receives the collection reservation information and determines the collection schedule.

[1408] 5. Non-burnable garbage classification and guidance

[1409] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[1410] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[1411] 6. Valuable garbage proposals

[1412] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[1413] The server sends information about the estimated price and listing procedures to the terminal.

[1414] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[1415] Specific examples

[1416] 1. Sofa disposal procedures

[1417] A user takes a photo of an old sofa.

[1418] The device sends the photo to the server.

[1419] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[1420] The user selects May 15th as the collection date.

[1421] The terminal sends the collection date to the server and confirms the reservation.

[1422] 2. If the frying pan is non-burnable garbage

[1423] A user takes a photo of an old metal frying pan.

[1424] The device sends the photo to the server.

[1425] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[1426] The device will guide the user on how to dispose of non-burnable waste.

[1427] 3. Proposal for listing a valuable guitar

[1428] A user takes a photo of an old guitar.

[1429] The device sends the photo to the server.

[1430] The server analyzes the photo and determines that it is a valuable guitar. It sends an estimated price of 10,000 yen and instructions on how to list the item.

[1431] The device displays the product description, estimated price, and listing procedure to the user, and the user selects "List."

[1432] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[1433] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse.

[1434] The processing flow will be explained below.

[1435] Program processing steps

[1436] Booking by photo shoot

[1437] Step 1:

[1438] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[1439] Step 2:

[1440] The device sends the photograph to the server.

[1441] Step 3:

[1442] The server passes the received photos to the AI ​​model and begins analysis.

[1443] Step 4:

[1444] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[1445] Step 5:

[1446] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[1447] Step 6:

[1448] The terminal displays the received fee and collection date to the user.

[1449] Step 7:

[1450] The user selects a desired date (for example, May 15th) from the collection dates presented.

[1451] Step 8:

[1452] The terminal transmits the selected collection date and reservation information to the server.

[1453] Step 9:

[1454] The server stores the reservation information and schedules the collection.

[1455] Judgment as non-burnable waste

[1456] Step 1:

[1457] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[1458] Step 2:

[1459] The device sends the photograph to the server.

[1460] Step 3:

[1461] The server passes the received photos to the AI ​​model and begins analysis.

[1462] Step 4:

[1463] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[1464] Step 5:

[1465] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[1466] Step 6:

[1467] The terminal displays information on how to dispose of non-burnable waste to the user.

[1468] Valuable garbage proposals

[1469] Step 1:

[1470] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[1471] Step 2:

[1472] The device sends the photograph to the server.

[1473] Step 3:

[1474] The server passes the received photos to the AI ​​model and begins analysis.

[1475] Step 4:

[1476] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[1477] Step 5:

[1478] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[1479] Step 6:

[1480] The server sends information about the estimated price and listing procedures to the terminal.

[1481] Step 7:

[1482] The terminal displays the received information to the user and guides them through the listing procedure.

[1483] Step 8:

[1484] The user follows the instructions and selects "List."

[1485] Step 9:

[1486] The terminal transmits the request to put up for sale to the server.

[1487] Step 10:

[1488] The server receives the listing information and completes the listing process via the Marketplace API.

[1489] Example 1

[1490] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1491] The conventional procedure for disposing of bulky waste is complicated and time-consuming, and it is difficult to obtain information on appropriate disposal methods and fees. It is also difficult to distinguish between non-burnable and non-burnable waste, and opportunities to reuse or recycle valuable waste are often overlooked. A system that solves these problems and makes the process for disposing of bulky waste efficient and easy is needed.

[1492] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1493] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving collection of the waste based on input from the user, and means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user. This makes it possible to provide information on disposal methods and fees for bulky waste, reserve collection dates, distinguish between non-burnable and combustible waste, and suggest reuse or recycling of valuable waste.

[1494] The "means for acquiring images" refers to a device or software that has the function of taking a photo of the bulky waste that the user wants to dispose of and inputting that image into the system.

[1495] "Means for analyzing acquired images and identifying the type of waste" refers to a device or software that has the function of analyzing image data received by the server using an AI model or the like to identify the type of waste.

[1496] "Means for collecting information on the disposal of identified waste" means a device or software that has the function of allowing the server to retrieve information on fees and disposal methods related to the disposal of waste from a database based on the type of waste identified.

[1497] The "means for presenting information regarding disposal" refers to a device or software that has the function of transmitting information regarding disposal of waste collected by the server to the user's terminal and displaying it on the terminal.

[1498] "Means for reserving waste collection based on user input" refers to a device or software that has the function of sending information such as the desired collection date entered by the user into the terminal to a server, and the server then confirming the collection reservation based on that information.

[1499] The "means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user" refers to a device or software that has the function of a server evaluating the market value of waste and suggesting reuse or recycling of that waste to the user.

[1500] "Means for determining whether waste is non-burnable waste and presenting the relevant information to the user" refers to a device or software that has the function of a server determining whether waste is non-burnable waste based on the results of image analysis, and sending and presenting the results to the user's terminal.

[1501] "Means for using a marketplace API to collect the market value and listing procedures for valuable waste and present them to users" refers to a device or software that has the function of a server using an online marketplace API to collect information on the market value and listing procedures for valuable waste, and sending that information to the user's terminal for presentation.

[1502] The present invention is an AI-based system for simplifying the procedure for disposing of bulky waste. Detailed embodiments of this system are described below.

[1503] System configuration

[1504] This system mainly consists of the following components:

[1505] 1. Image acquisition method

[1506] The device has a function that allows users to take a photo of the bulky waste they want to throw away and input the image into the system. A smartphone or digital camera is the hardware that performs this function.

[1507] 2. Image analysis methods

[1508] The device sends the captured image to a server, which then uses AI to analyze the image and identify the type of waste. Specifically, it uses the generative AI model YOLO (You Only Look Once).

[1509] 3. Information gathering methods

[1510] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[1511] 4. Information presentation means

[1512] The server sends the collected information to the terminal, which then displays the fees and processing method to the user.

[1513] 5. Collection reservation method

[1514] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[1515] 6. How to determine non-burnable waste

[1516] The server has the ability to determine whether the waste is non-combustible based on the analysis results and send that information to the terminal.

[1517] 7. Market value assessment and reuse proposal methods

[1518] The server evaluates whether the waste has market value and uses the marketplace API to make reuse and recycling suggestions to users.

[1519] Program processing

[1520] 1. Image acquisition and transmission

[1521] A user takes a photo of a large piece of trash, such as an old sofa, with a mobile device.

[1522] The device sends the captured image to the server. The image data is sent using an internet connection.

[1523] 2. Image Analysis

[1524] The server inputs the received image into an AI model and starts image analysis, for example, using YOLO.

[1525] The server uses the analysis results to identify the object (e.g., an old sofa) contained in the image, and returns the identification result as a specific name such as sofa.

[1526] 3. Collection and presentation of information

[1527] The server retrieves information about fees and disposal methods related to the identified waste (e.g., sofa) from the database. For example, it retrieves information that the disposal fee for a sofa is 1,200 yen.

[1528] The server checks the dates that can be collected (e.g., May 15th or May 18th) and sends that information to the terminal.

[1529] The terminal will display the fee and collection dates to the user, who can then select a collection date based on the displayed information.

[1530] 4. Select a collection date and make a reservation

[1531] The user selects the desired date (e.g., May 15th) from the available collection dates presented.

[1532] The terminal sends the collection date information selected by the user to the server, which then registers the selected collection date in the database.

[1533] The server confirms the collection reservation information and notifies the user that the reservation has been completed.

[1534] 5. Non-burnable garbage classification and guidance

[1535] The server determines from the analysis results that the waste is non-burnable (e.g., a metal frying pan). The determination is made based on pre-set rules.

[1536] The server notifies the terminal of non-burnable waste information.

[1537] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[1538] 6. Market value assessment and reuse proposals

[1539] If the server determines from the analysis results that the waste has value (e.g., an old guitar), it uses the marketplace API to collect possible product value and listing information.

[1540] The server sends the collected information to the device, including the estimated price (e.g., 10,000 yen) and details of the listing process.

[1541] The device displays the product description, estimated price, and listing procedure to the user. If the user selects "List," the device sends this information to the server. An example of a generated prompt might be, "The estimated value of this guitar is 10,000 yen. Would you like to list it?"

[1542] The server performs the listing procedure on the online auction site and sends a completion notice to the user.

[1543] Specific examples

[1544] For example, a user takes a photo of an old sofa and sends it to a server via their smartphone. The server analyzes the image and recognizes it as a sofa, then retrieves the 1,200 yen handling fee and collection dates (May 15th and May 18th) from a database and sends them to the device. The device displays this information to the user, who selects May 15th. The selected information is sent to the server, which then confirms the collection reservation. In addition, the server can display suggestions for items such as metal frying pans, which can be disposed of as non-burnable waste, and items such as guitars, which can be reused or recycled, for sale.

[1545] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1546] Step 1:

[1547] Image capture and transmission

[1548] The user takes a photo of the bulky item they want to throw away (e.g., an old sofa) with their smartphone. This becomes the input image for the system. Specific actions include opening the camera app and taking a photo.

[1549] The device sends the captured image file to the server. An internet connection is required for transmission, and a protocol such as an HTTP request is used. The input is the captured image file, and the output is the completion of sending the image data to the server.

[1550] Step 2:

[1551] Image analysis

[1552] The server inputs the received image file into the AI ​​model and begins image analysis. Specific operations include using generative AI models such as YOLO (You Only Look Once).

[1553] The server uses an AI model to identify an object (e.g., a sofa) in an image. The input is the received image data, and the output is the name of the identified object (e.g., "sofa"). The server supplies the image data to the AI ​​model and receives the generated label.

[1554] Step 3:

[1555] Collection and presentation of information

[1556] The server collects information related to waste disposal from a database based on the identification result (e.g., "sofa"), and specific operations include querying the database using an SQL query.

[1557] The input is the name of the identification result, and the output is the collected fee and the collectable date information (e.g., "Fee 1,200 yen, collection dates May 15th and May 18th").

[1558] The server sends the collected information to the terminal.

[1559] The terminal displays the collection information (fees and collection date) to the user. Specific operations include displaying the information on the application screen.

[1560] Step 4:

[1561] Selecting and reserving a collection date

[1562] The user selects the desired date (e.g., May 15th) from the available dates presented for collection. This becomes the input for the next process. Specific actions include selecting a date from a calendar interface on the application.

[1563] The terminal sends the user's selection information to the server. The input is the collection date selected by the user, and the output is the completion of information transmission to the server.

[1564] The server registers the collection reservation in the database based on the received selection information, including saving the collection date in the database using an SQL query.

[1565] Step 5:

[1566] Non-burnable waste determination and guidance

[1567] The server determines whether the waste is non-burnable or not based on the results of image analysis. This is done using predefined rules. The input is the result of image analysis, and the output is the determination of whether the waste is non-burnable or not.

[1568] The server sends the result of the judgment to the user's terminal. The input is the judgment result of non-burnable waste, and the output is the completion of information transmission to the terminal.

[1569] The terminal displays a message to the user such as, "Please dispose of metal frying pans as non-burnable garbage on the specified day in the specified place." Specific actions include displaying a message on the application screen.

[1570] Step 6:

[1571] Market value assessment and reuse proposals

[1572] The server evaluates whether the waste has market value based on the results of image analysis. The input is the waste identification result, and the output is the market value assessment result.

[1573] The server uses the marketplace's API to gather possible product values ​​and listing information, including sending API requests and receiving information.

[1574] The server sends the collected information to the terminal. The input is the product value information obtained from the API, and the output is the completion of sending the information to the terminal.

[1575] The terminal displays to the user a description of the product, an estimated price (e.g., 10,000 yen), and listing procedure information. If the user selects "List," the terminal sends this information to the server. Specific operations include displaying listing procedure instructions on the application screen and receiving user input.

[1576] The server processes the listing on the online auction site and sends a completion notice to the user. The input is the user's listing information, and the output is a completion notice of the listing procedure.

[1577] (Application example 1)

[1578] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1579] The present invention aims to solve the problem of the complicated procedure for disposing of bulky waste and the inability of users to properly understand how to dispose of it. It also aims to provide a method for effectively utilizing waste that has value and can be reused or recycled without overlooking that value. Another objective is to simplify the process of reserving collection dates and improve user convenience.

[1580] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1581] In this invention, the server includes a means for presenting a collection method for valuable waste, a means for the user to input a desired collection date, and a means for confirming collection reservation information, which allows the user to easily carry out the procedure for disposing of bulky waste and further enables the user to maximize the value of reusable and recyclable waste.

[1582] The "means for acquiring images" refers to a means by which a user takes a photograph of the bulky waste and inputs the image into the system.

[1583] "Means for analyzing acquired images to identify the type of waste" refers to the means by which the system uses AI to analyze images sent to the server and identify the type of waste.

[1584] The "means for collecting information on the disposal of identified waste" is a means for the server to obtain information on disposal fees and disposal methods for identified waste from the database.

[1585] The "means for presenting information about processing" is a means for displaying information about the acquired fee and processing method to the user.

[1586] The "means for reserving waste collection based on input from the user" refers to a means for the user to input a desired collection date and transmit that information to the server to make a collection reservation.

[1587] "Means for suggesting methods for recovering valuable waste" refers to means for proposing reuse or recycling when waste has market value based on the analysis results.

[1588] The "means for the user to input the desired collection date" is a means for the user to select a collection date through the application and transmit that information to the server.

[1589] The "means for determining collection reservation information" is a means for the server to determine the collection schedule based on the selected collection date and update the reservation information.

[1590] This invention is an AI-based system for simplifying the process of disposing of bulky waste, and is mainly composed of the following components:

[1591] System configuration

[1592] 1. Image acquisition method

[1593] Users can take photos of bulky waste with their smartphones and enter the images into the system.

[1594] 2. Image analysis methods

[1595] The captured images are sent from the smartphone to a cloud server (e.g., AWS EC2) where they are analyzed using an AI image analysis model (e.g., TensorFlow or PyTorch). This analysis identifies the type of waste.

[1596] 3. Information gathering methods

[1597] The server retrieves information on processing fees and processing methods for the identified waste from a cloud database (e.g., Amazon RDS).

[1598] 4. Information presentation means

[1599] Information about processing fees and processing methods is sent from the server to the smartphone and displayed to the user, allowing the user to check the necessary information.

[1600] 5. Collection reservation method

[1601] The user selects the desired collection date from the schedule presented and sends that information to the server via their smartphone. The server then confirms the collection reservation based on the received collection date information.

[1602] 6. How to determine non-burnable waste

[1603] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the user's smartphone and guides them on how to dispose of it properly.

[1604] 7. Value Judgment Tools

[1605] If the server determines that the waste is valuable using the AI ​​image analysis model, it uses a marketplace API (e.g., eBay API) to collect information about the product value and listing, and suggests reuse or recycling to the user.

[1606] Hardware and software used

[1607] Hardware: Smartphone camera, cloud server (AWS EC2), cloud database (Amazon RDS)

[1608] Software: Mobile app (Flutter or React Native), AI image analysis model (TensorFlow or PyTorch), marketplace API (eBay API)

[1609] Specific examples

[1610] 1. Sofa disposal procedures

[1611] A user takes a photo of an old sofa with their smartphone.

[1612] The image is sent to a cloud server, where an AI image analysis model identifies it as a sofa.

[1613] The server retrieves the processing fee and collection date from a cloud database and displays them on the smartphone.

[1614] The user selects the desired collection date, and the server confirms the collection reservation.

[1615] 2. If the frying pan is non-burnable garbage

[1616] A user takes a photo of a metal frying pan with their smartphone.

[1617] The image is sent to a cloud server, and an AI image analysis model determines that the frying pan is non-burnable waste.

[1618] The server obtains the disposal method for non-combustible waste and displays it on the smartphone.

[1619] 3. Proposal for listing a valuable guitar

[1620] A user takes a photo of an old guitar with their smartphone.

[1621] The images are sent to a cloud server, where an AI image analysis model determines whether the guitar is valuable.

[1622] The server uses the marketplace API to obtain estimated prices and listing procedure information, which is then displayed on the smartphone.

[1623] Prompt Sentence Examples

[1624] "Analyze images of bulky waste taken by users with a smartphone app and identify the type of object (e.g. sofa, frying pan). After identification, retrieve the associated processing fee and possible collection date from the database and display them to the user. Also, for valuable objects, obtain an estimated price via the Marketplace API and provide information to guide the listing process."

[1625] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1626] Step 1:

[1627] Users take photos of bulky waste with their smartphones and upload the images to a cloud server via the application.

[1628] Input: Photo of bulky waste

[1629] Output: Image data is sent to the cloud server

[1630] Specific behavior: A user takes a photo with their smartphone camera and uses the application's image upload function to send the image to a cloud server.

[1631] Step 2:

[1632] The server inputs the received image data into an AI image analysis model to identify the type of waste.

[1633] Input: Image data

[1634] Output: Waste type determination (e.g. sofa, frying pan)

[1635] How it works: The images sent to the cloud server are stored and passed to an AI model (e.g., TensorFlow or PyTorch), which then analyzes the images and identifies the type of waste.

[1636] Step 3:

[1637] Based on the identified type of waste, the server collects information on processing fees and processing methods from a cloud database.

[1638] Input: Waste type determination result

[1639] Output: Processing fee and processing method information

[1640] Specific operation: Sends a query to a cloud database (e.g., Amazon RDS) to obtain disposal fees and methods corresponding to the waste type.

[1641] Step 4:

[1642] The server sends the collected information to the terminal, which displays the information to the user.

[1643] Input: Processing fee and processing method information

[1644] Output: User-visible processing fee and processing method

[1645] Specific operation: The server sends information such as processing fees and collection dates to the user's smartphone via API, and the smartphone app displays the information to the user.

[1646] Step 5:

[1647] The user selects the desired collection date from the available collection dates displayed and transmits the information to the server via the terminal.

[1648] Input: User's desired collection date

[1649] Output: Collection date information sent to the server

[1650] How it works: The user selects a collection date using the smartphone app interface, and that information is sent to the server via an API.

[1651] Step 6:

[1652] The server confirms the collection reservation based on the received collection date information and updates the schedule.

[1653] Input: User's desired collection date

[1654] Output: Confirmed collection reservation information

[1655] Specific operation: The server saves the received collection date information in the database and updates and confirms the collection schedule.

[1656] Step 7:

[1657] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the terminal and guides the user on the appropriate disposal method.

[1658] Input: Waste is non-burnable waste

[1659] Output: How to dispose of non-burnable waste

[1660] Specific operation: If the server determines that the item is non-combustible waste using the AI ​​model, it sends information about how to dispose of it to the user's smartphone, and the application displays that information.

[1661] Step 8:

[1662] If the server determines that the waste has value using the AI ​​image analysis model, it uses the marketplace API to collect information about the product's value and listing, and suggests reuse or recycling to the user.

[1663] Input: Determination that the waste is valuable

[1664] Output: Information on product value and listing procedures

[1665] How it works: The server queries a marketplace API (e.g., eBay API) to obtain information about the product's value and listing process, and sends it to the user's smartphone. The application displays this information to the user and suggests reuse and recycling options.

[1666] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1667] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes the user's emotions. The detailed configuration of this system and the program processing are described below.

[1668] System configuration

[1669] This system mainly consists of the following components:

[1670] 1. Image acquisition method

[1671] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[1672] 2. Image analysis methods

[1673] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[1674] 3. Information gathering methods

[1675] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[1676] 4. Information presentation means

[1677] The terminal has the function of displaying the fees and processing method to the user.

[1678] 5. Collection reservation method

[1679] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[1680] 6. How to determine non-burnable waste

[1681] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[1682] 7. Value Judgment Tools

[1683] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[1684] 8. Emotion Engine

[1685] It has the ability to recognize the user's emotions and provide information and simplify procedures based on that.

[1686] Program processing

[1687] 1. Image acquisition and transmission

[1688] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[1689] The device sends the captured image to the server.

[1690] 2. Image Analysis

[1691] The server receives the image and analyzes it using AI.

[1692] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[1693] 3. Collection and presentation of information

[1694] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[1695] The server returns the handling fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[1696] The terminal displays this information to the user.

[1697] 4. Select a collection date and make a reservation

[1698] The user selects the desired collection date (e.g., May 15th) from the options presented.

[1699] The terminal transmits the selected collection date to the server.

[1700] The server receives the collection reservation information and determines the collection schedule.

[1701] 5. Non-burnable garbage classification and guidance

[1702] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[1703] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[1704] 6. Valuable garbage proposals

[1705] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[1706] The server sends information about the estimated price and listing procedures to the terminal.

[1707] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[1708] 7. The Emotional Engine

[1709] The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state.

[1710] When the emotion engine determines that the user is feeling stressed, an encouraging message is displayed to the user through the information presentation means.

[1711] If more emotion engines are needed, they instruct the server or terminal how to simplify the steps of the procedure.

[1712] Specific examples

[1713] 1. Sofa disposal procedures

[1714] A user takes a photo of an old sofa.

[1715] The device sends the photo to the server.

[1716] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[1717] The user selects May 15th as the collection date.

[1718] The terminal sends the collection date to the server and confirms the reservation.

[1719] 2. If the frying pan is non-burnable garbage

[1720] A user takes a photo of a metal frying pan.

[1721] The device sends the photo to the server.

[1722] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[1723] The device will guide the user on how to dispose of non-burnable waste.

[1724] 3. When a guitar is valuable

[1725] A user takes a photo of an old guitar.

[1726] The device sends the photo to the server.

[1727] The server analyzes the photo and determines that the guitar is valuable. It sends an estimated price of 10,000 yen and instructions on how to list the item to the user's device.

[1728] The device displays the product description, estimated price, and listing procedure to the user, and they select "List."

[1729] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[1730] 4. User Emotion Recognition

[1731] If the user is feeling stressed, the emotion engine will analyze and recognize the state.

[1732] The emotion engine instructs the device to display an appropriate encouraging message.

[1733] The emotion engine instructs the server or terminal to automate or simplify parts of the procedure, allowing the user to proceed smoothly.

[1734] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse. In addition, the emotion engine provides a comfortable operating experience for users.

[1735] The processing flow will be explained below.

[1736] Program processing steps

[1737] Booking by photo shoot

[1738] Step 1:

[1739] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[1740] Step 2:

[1741] The device sends the photograph to the server.

[1742] Step 3:

[1743] The server passes the received photos to the AI ​​model and begins analysis.

[1744] Step 4:

[1745] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[1746] Step 5:

[1747] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[1748] Step 6:

[1749] The terminal displays the received fee and collection date to the user.

[1750] Step 7:

[1751] The user selects a desired date (for example, May 15th) from the collection dates presented.

[1752] Step 8:

[1753] The terminal transmits the selected collection date and reservation information to the server.

[1754] Step 9:

[1755] The server stores the reservation information and schedules the collection.

[1756] Judgment as non-burnable waste

[1757] Step 1:

[1758] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[1759] Step 2:

[1760] The device sends the photograph to the server.

[1761] Step 3:

[1762] The server passes the received photos to the AI ​​model and begins analysis.

[1763] Step 4:

[1764] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[1765] Step 5:

[1766] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[1767] Step 6:

[1768] The terminal displays information on how to dispose of non-burnable waste to the user.

[1769] Valuable garbage proposals

[1770] Step 1:

[1771] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[1772] Step 2:

[1773] The device sends the photograph to the server.

[1774] Step 3:

[1775] The server passes the received photos to the AI ​​model and begins analysis.

[1776] Step 4:

[1777] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[1778] Step 5:

[1779] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[1780] Step 6:

[1781] The server sends information about the estimated price and listing procedures to the terminal.

[1782] Step 7:

[1783] The terminal displays the received information to the user and guides them through the listing procedure.

[1784] Step 8:

[1785] The user follows the instructions and selects "List."

[1786] Step 9:

[1787] The terminal transmits the request to put up for sale to the server.

[1788] Step 10:

[1789] The server receives the listing information and completes the listing process via the Marketplace API.

[1790] User support with emotion engine

[1791] Step 1:

[1792] When a user uses the system, the emotion engine captures the user's facial expressions and voice through the camera and microphone.

[1793] Step 2:

[1794] The facial expression and voice data acquired by the device is sent to the server.

[1795] Step 3:

[1796] The server passes the received facial expression and voice data to the emotion engine and begins analysis.

[1797] Step 4:

[1798] The server determines whether the user is feeling stressed or dissatisfied based on the analysis of the emotion engine.

[1799] Step 5:

[1800] The server determines the appropriate message and dialogue procedure based on the emotional state and sends that information to the terminal.

[1801] Step 6:

[1802] The device displays an appropriate message to the user (e.g., "We're here to help you. Let us know if you have any questions.").

[1803] Step 7:

[1804] As the user proceeds, the emotion engine continues to monitor the user's emotional state and instructs the server to simplify the process if necessary.

[1805] Step 8:

[1806] The server handles the simplification of procedures, for example by providing auto-filling and additional support to reduce the burden on the user.

[1807] Example 2

[1808] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1809] The process of disposing of bulky waste is complicated and often stressful for users. Furthermore, if the waste has market value, opportunities for reuse or recycling may be missed. Furthermore, there is a lack of means to recognize the user's emotions and provide appropriate support, which hinders the user's operational experience.

[1810] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1811] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving waste collection based on input from the user, and means for recognizing the user's emotions and providing information based on the emotions. This makes it possible to carry out the procedure for disposing of oversized waste easily and smoothly, preventing missed opportunities for reuse and recycling and providing a comfortable operating experience for the user.

[1812] "Means for acquiring images" refers to devices or software that allow a user to take an image of the waste they wish to dispose of and input that image into the system.

[1813] "Means for analyzing acquired images and identifying the type of waste" refers to devices or software that analyze received images and identify the type of waste depicted in the images using AI models, etc.

[1814] "Means for collecting information on the disposal of identified waste" refers to devices or software that retrieve information such as disposal methods and fees from a database based on the type of identified waste.

[1815] "Means for presenting information about processing" refers to devices or software that display collected information such as processing methods and fees to users.

[1816] "Means for reserving waste collection based on user input" refers to devices or software that reserve waste collection based on information entered by the user, such as the desired collection date.

[1817] "Means for recognizing a user's emotions and providing information based on those emotions" refers to devices or software that analyze a user's facial expressions, voice, etc. to identify emotions and provide information according to those emotions.

[1818] "Means for determining whether waste is non-combustible waste" refers to devices or software that determine whether identified waste is non-combustible waste.

[1819] "Means for determining whether waste has market value and proposing reuse or recycling if it is determined to have market value" refers to devices or software that determine whether identified waste has market value and, if it is determined to have value, proposes reuse or recycling.

[1820] MODE FOR CARRYING OUT THE INVENTION

[1821] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes user emotions. The system mainly includes the following hardware and software components:

[1822] Hardware and software used

[1823] Device: Smartphone or digital camera

[1824] Server: Cloud server with database and AI model

[1825] software:

[1826] Image processing: OpenCV

[1827] Image Analysis and Classification: TensorFlow

[1828] Emotion recognition: Emotion API

[1829] System Operation Overview

[1830] 1. Image acquisition method

[1831] The user takes a photo of the bulky waste they want to throw away using a smartphone or digital camera.

[1832] The images taken by the device are sent to the server via a system-specific app.

[1833] 2. Image analysis methods

[1834] Based on the images received by the server, preprocessing is performed using OpenCV.

[1835] The server uses TensorFlow to analyze the images and identify the type of waste.

[1836] 3. Information gathering methods

[1837] The server collects fees and disposal methods from a database based on the identified waste type.

[1838] 4. Information presentation means

[1839] The terminal presents the fee received from the server and the collection date to the user.

[1840] 5. Collection reservation method

[1841] The user selects the desired collection date and transmits that information from the terminal to the server.

[1842] The server schedules the collection appointment.

[1843] 6. How to determine non-burnable waste

[1844] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[1845] The device will guide the user on how to dispose of non-burnable waste.

[1846] 7. Value Judgment Tools

[1847] The server determines whether the waste has market value and makes suggestions for reuse or recycling as needed.

[1848] The server connects to the marketplace's API to collect estimated prices and listing procedures.

[1849] The terminal presents this information to the user and guides them through the listing procedure.

[1850] 8. Emotion Engine

[1851] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[1852] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[1853] If necessary, instructions will be provided to simplify the steps of the procedure.

[1854] Specific examples

[1855] 1. Sofa disposal procedures

[1856] A user takes a photo of an old sofa.

[1857] The device sends the photo to the server.

[1858] The server analyzes the image and identifies it as a sofa.

[1859] The fee is 1,200 yen and collection dates are May 15th and May 18th.

[1860] The user selects May 15th as the collection date, and the terminal sends the information to the server.

[1861] The server confirms the collection reservation.

[1862] 2. If the frying pan is non-burnable garbage

[1863] A user takes a photo of a metal frying pan.

[1864] The device sends the photo to the server.

[1865] The server analyzes the image and identifies the frying pan as non-combustible waste.

[1866] The device will guide the user on how to dispose of non-burnable waste.

[1867] 3. When a guitar is valuable

[1868] A user takes a photo of an old guitar.

[1869] The device sends the photo to the server.

[1870] The server analyzes the image and determines that it is a valuable guitar.

[1871] An estimated price of 10,000 yen and instructions on how to proceed with listing will be sent to your device.

[1872] The device displays the product description, estimated price, and listing procedure to the user, and asks whether they want to list the item.

[1873] If the user chooses to put up an item for auction, the terminal transmits the information to the server, which then processes the item for auction at the online auction.

[1874] Prompt Sentence Examples

[1875] "I want to simplify the process of throwing away an old sofa. Create a program where I can take a photo, submit it, and the system will suggest fees and a reservation date."

[1876] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1877] Step 1:

[1878] The user takes a photo of the bulky trash they want to throw away using their mobile device.

[1879] Input: Photo of bulky waste

[1880] Output: Image data saved on the device

[1881] Specific operation: The user takes a photo of the sofa using the smartphone's camera app. After taking the photo, the photo is saved in the device's gallery.

[1882] Step 2:

[1883] The images taken by the device are sent to the server via a system-specific app.

[1884] Input: Image data stored on the device

[1885] Output: Image data sent to the server

[1886] Specific operation: The user launches the system's dedicated app and selects the photo of the sofa they have taken. After selection, the system's dedicated app sends the image data to the server.

[1887] Step 3:

[1888] Based on the images received by the server, preprocessing is performed using OpenCV.

[1889] Input: Image data received by the server

[1890] Output: Preprocessed image data

[1891] Specific operation: The server uses OpenCV to perform preprocessing such as image noise removal and resizing.

[1892] Step 4:

[1893] The server uses TensorFlow to analyze the images and identify the type of waste.

[1894] Input: Preprocessed image data

[1895] Output: Identified waste types

[1896] How it works: Preprocessed image data is fed into a TensorFlow AI model to identify the type of waste (e.g., sofa).

[1897] Step 5:

[1898] The server collects fees and disposal methods from a database based on the identified waste type.

[1899] Input: Identified waste type

[1900] Output: Information about fees and disposal methods

[1901] Specific operation: The server retrieves the fee (e.g., 1,200 yen) and collection date (e.g., May 15th, May 18th) from the database based on the type of waste (e.g., sofa).

[1902] Step 6:

[1903] The terminal presents the fee received from the server and the collection date to the user.

[1904] Input: Fee and disposal method information

[1905] Output: Information presented to the user

[1906] Specific operation: The terminal will display a pop-up message to the user indicating the fee (e.g., 1,200 yen) and the collection dates (e.g., May 15th, May 18th).

[1907] Step 7:

[1908] The user selects the desired collection date, and the terminal transmits this information to the server.

[1909] Input: User selected collection date

[1910] Output: Data sent to the server on the collection date

[1911] Specific operation: The user taps to select a collection date (e.g., May 15th) on the device, and the device sends the selected collection date to the server.

[1912] Step 8:

[1913] The server schedules the collection appointment.

[1914] Input: User selected collection date

[1915] Output: Notification of confirmed collection reservation

[1916] Specific operation: The server checks the collection date and confirms the schedule. After confirmation, a notification "Collection reservation confirmed" is displayed on the device.

[1917] Step 9:

[1918] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[1919] Input: AI analysis results

[1920] Output: Information about details of non-burnable waste

[1921] Specific operation: The server determines that the item is non-combustible waste (e.g., a metal frying pan) and sends disposal instructions (e.g., to dispose of in a designated place on a designated day) to the terminal.

[1922] Step 10:

[1923] The device will guide the user on how to dispose of non-burnable waste.

[1924] Input: Information about details of non-burnable waste

[1925] Output: Information presented to the user

[1926] Specific operation: The device displays the message, "Please dispose of metal frying pans as non-burnable waste in the designated place on the designated day."

[1927] Step 11:

[1928] The server determines whether the waste has market value and makes suggestions for reuse or recycling.

[1929] Input: AI analysis results and marketplace information

[1930] Output: Reuse and recycling suggestions

[1931] Specific operation: For waste items that the server determines to be valuable (e.g., old guitars), it obtains the estimated price (e.g., 10,000 yen) and listing instructions and sends them to the terminal.

[1932] Step 12:

[1933] The terminal provides users with information about valuable waste and guides them through the listing process.

[1934] Input: Reuse and recycling suggestions

[1935] Output: Information presented to the user

[1936] Specific operation: The device displays "The estimated price of this guitar is 10,000 yen. Would you like to list it?" and if the user selects "List it," it guides the user through the listing process.

[1937] Step 13:

[1938] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[1939] Input: User's facial expressions and voice data

[1940] Output: User's emotional state

[1941] Specific operation: The emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and identify their emotional state (e.g., stress).

[1942] Step 14:

[1943] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[1944] Input: User's emotional state

[1945] Output: An encouraging message

[1946] Specific operation: If it is determined that the user is feeling stressed, the device will display a message saying, "Don't worry. The procedure will be easy."

[1947] (Application example 2)

[1948] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1949] Conventional industrial waste treatment systems do not distinguish between different types of waste, provide appropriate treatment methods, or evaluate the market value of valuable waste, resulting in insufficient treatment efficiency and effective resource utilization. Furthermore, there is a lack of operational support that takes into account the emotional state of workers, which increases the stress and burden of operation.

[1950] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the treatment of the identified waste, means for presenting information on the treatment, means for booking waste collection based on input from the user, means for evaluating the value of the waste and suggesting reuse or recycling, means for issuing operational instructions for carrying out a waste treatment method within the factory, and means for recognizing the operator's emotions and issuing corresponding alerts and instructions. This enables efficient and accurate waste treatment and reduces worker stress.

[1951] The "means for acquiring images" refers to a device for taking images of waste and recording them as digital data.

[1952] The "means for analyzing the acquired image and identifying the type of waste" is a combination of software and hardware for processing image data and automatically determining the type of waste.

[1953] The "means for collecting information on the disposal of identified waste" is a system for obtaining information on appropriate disposal methods and fees from a database based on the identification results.

[1954] A "means for presenting information about a process" is a device that displays or communicates the collected information to the user visually or audibly.

[1955] The "means for scheduling waste collection based on user input" refers to a system that receives user instructions and schedules collection activities based on that information.

[1956] "Means for assessing the value of waste and proposing reuse and recycling" is a system that determines the market value of identified waste and suggests the possibility of reuse or recycling.

[1957] The "means for issuing operational instructions for carrying out waste treatment methods within the factory" is a system that transmits instructions to equipment and workers within the factory for carrying out appropriate treatment operations for identified waste.

[1958] "Means for recognizing the operator's emotions and issuing corresponding alerts and instructions" refers to a system that detects the emotional state of the worker from their facial expressions and voice, and provides appropriate alerts and work instructions.

[1959] This invention relates to a robot system that efficiently processes industrial waste generated in factories. This system has multiple functions for identifying waste, suggesting processing methods, assessing its value, providing appropriate operating instructions, and recognizing the emotions of the operator.

[1960] Hardware and software used

[1961] Hardware:

[1962] Industrial robots (e.g. general-purpose robot arms)

[1963] Image capture camera (e.g. high resolution camera)

[1964] Microphones for emotion recognition (e.g., high-sensitivity microphones)

[1965] software:

[1966] AI models for image analysis (e.g., TensorFlow, OpenCV)

[1967] Sentiment analysis engines (e.g., emotion recognition software)

[1968] Database (e.g. SQL database)

[1969] Robot control software (e.g. robot operating system)

[1970] Program Description

[1971] 1. Image acquisition and analysis:

[1972] The server captures images of the waste using high-resolution cameras mounted on robotic arms inside the factory.

[1973] The captured images are then analyzed using a TensorFlow-based AI model to automatically identify the type of waste.

[1974] 2. Information Collection and Presentation:

[1975] The server collects information about processing fees and methods from an SQL database based on the type of waste identified.

[1976] The collected information is presented to the operator via a display and voice notification device installed on the robot.

[1977] 3. Value Assessment and Proposition:

[1978] If the identified waste has market value, the server evaluates its value and suggests the possibility of reuse or recycling.

[1979] If necessary, collect and suggest pricing information via external marketplace APIs.

[1980] 4. Instructions for carrying out the processing method:

[1981] The robotic arm moves or processes the identified waste to the appropriate location based on instructions from the server.

[1982] For example, metal pieces go to a metal recycling container and plastic pieces go to a plastic recycling container.

[1983] 5. Emotion recognition and response:

[1984] The server uses a sensitive microphone to collect the operator's voice and uses emotion recognition software to analyze their emotions.

[1985] If the user is feeling stressed, appropriate encouraging messages and information will be provided, along with operational support.

[1986] Examples of concrete examples and prompts

[1987] Examples:

[1988] Example 1: Processing metal pieces

[1989] The system identifies metal pieces from the captured images and instructs them to be moved to a metal recycling container.

[1990] If a worker is feeling stressed, display the message "Good job! Let's try a little harder."

[1991] Example prompt sentence:

[1992] Example prompts to input to the AI ​​model:

[1993] "Analyze this image to identify the type of waste in the image. Distinguish whether the waste is metal, plastic, or paper, and use that information to suggest an appropriate disposal method."

[1994] Example prompts for the emotion engine:

[1995] "Recognize the worker's emotions from this voice data and generate appropriate encouraging messages if they are feeling stressed."

[1996] In this way, the invention is expected to realize efficient and accurate waste disposal within factories while also reducing worker stress.

[1997] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1998] Step 1:

[1999] The server captures images of the waste using high-resolution cameras mounted on robotic arms inside the factory.

[2000] Input: Physical state of waste

[2001] Output: High-resolution waste image data

[2002] Step 2:

[2003] The server receives the captured image data, analyzes it using an AI model for image analysis, and automatically identifies the type of waste.

[2004] Input: High-resolution waste image data

[2005] Output: Identified waste type (e.g. metal pieces, plastic pieces)

[2006] Step 3:

[2007] The server collects information on processing fees and processing methods from an SQL database based on the identified waste type.

[2008] Input: Identified waste type

[2009] Output: Information on waste disposal fees and disposal methods

[2010] Step 4:

[2011] The server sends the collected information to the robot control terminal in the factory and presents it to the operator via a display or audio notification device.

[2012] Input: Waste disposal fee and disposal method information

[2013] Output: Proposed processing fee and processing method information

[2014] Step 5:

[2015] The server evaluates the market value of the identified waste and determines whether it can be reused or recycled, and if necessary, uses marketplace APIs to collect pricing information.

[2016] Input: Identified waste type

[2017] Output: Market value assessment and suggestions for reuse and recycling

[2018] Step 6:

[2019] The server issues operational instructions to the robotic arm to move or process the identified waste to an appropriate location.

[2020] Input: Identified waste type and disposal method information

[2021] Output: Proper disposal of waste

[2022] Step 7:

[2023] The server uses a highly sensitive microphone to collect the operator's voice and uses emotion recognition software to analyze the operator's emotions.

[2024] Input: Operator's voice data

[2025] Output: Emotional state of the operator (e.g., stress, joy)

[2026] Step 8:

[2027] If the server determines that the operator is feeling stressed, it provides encouraging messages and appropriate information to assist the operator in their work.

[2028] Input: Emotional state of the operator

[2029] Output: Encouraging messages and work support information

[2030] In this way, through the above processing steps, efficient and accurate waste disposal is achieved within the factory.

[2031] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2032] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2033] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2034] [Fourth embodiment]

[2035] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2036] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2037] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2038] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2039] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2040] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2041] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2042] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2043] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2044] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2045] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2046] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2047] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2048] This invention is an AI-based system for simplifying the procedure for disposing of bulky waste. The detailed configuration of this system and the program processing are explained below.

[2049] System configuration

[2050] This system mainly consists of the following components:

[2051] 1. Image acquisition method

[2052] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[2053] 2. Image analysis methods

[2054] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[2055] 3. Information gathering methods

[2056] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[2057] 4. Information presentation means

[2058] The terminal has the function of displaying the fees and processing method to the user.

[2059] 5. Collection reservation method

[2060] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[2061] 6. How to determine non-burnable waste

[2062] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[2063] 7. Value Judgment Tools

[2064] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[2065] Program processing

[2066] 1. Image acquisition and transmission

[2067] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[2068] The device sends the captured image to the server.

[2069] 2. Image Analysis

[2070] The server receives the image and analyzes it using AI.

[2071] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[2072] 3. Collection and presentation of information

[2073] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[2074] The server sends the fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[2075] The terminal displays this information to the user.

[2076] 4. Select a collection date and make a reservation

[2077] The user selects the desired collection date (e.g., May 15th) from the options presented.

[2078] The terminal transmits the selected collection date to the server.

[2079] The server receives the collection reservation information and determines the collection schedule.

[2080] 5. Non-burnable garbage classification and guidance

[2081] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[2082] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[2083] 6. Valuable garbage proposals

[2084] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[2085] The server sends information about the estimated price and listing procedures to the terminal.

[2086] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[2087] Specific examples

[2088] 1. Sofa disposal procedures

[2089] A user takes a photo of an old sofa.

[2090] The device sends the photo to the server.

[2091] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[2092] The user selects May 15th as the collection date.

[2093] The terminal sends the collection date to the server and confirms the reservation.

[2094] 2. If the frying pan is non-burnable garbage

[2095] A user takes a photo of an old metal frying pan.

[2096] The device sends the photo to the server.

[2097] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[2098] The device will guide the user on how to dispose of non-burnable waste.

[2099] 3. Proposal for listing a valuable guitar

[2100] A user takes a photo of an old guitar.

[2101] The device sends the photo to the server.

[2102] The server analyzes the photo and determines that it is a valuable guitar. It sends an estimated price of 10,000 yen and instructions on how to list the item.

[2103] The device displays the product description, estimated price, and listing procedure to the user, and the user selects "List."

[2104] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[2105] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse.

[2106] The processing flow will be explained below.

[2107] Program processing steps

[2108] Booking by photo shoot

[2109] Step 1:

[2110] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[2111] Step 2:

[2112] The device sends the photograph to the server.

[2113] Step 3:

[2114] The server passes the received photos to the AI ​​model and begins analysis.

[2115] Step 4:

[2116] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[2117] Step 5:

[2118] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[2119] Step 6:

[2120] The terminal displays the received fee and collection date to the user.

[2121] Step 7:

[2122] The user selects a desired date (for example, May 15th) from the collection dates presented.

[2123] Step 8:

[2124] The terminal transmits the selected collection date and reservation information to the server.

[2125] Step 9:

[2126] The server stores the reservation information and schedules the collection.

[2127] Judgment as non-burnable waste

[2128] Step 1:

[2129] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[2130] Step 2:

[2131] The device sends the photograph to the server.

[2132] Step 3:

[2133] The server passes the received photos to the AI ​​model and begins analysis.

[2134] Step 4:

[2135] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[2136] Step 5:

[2137] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[2138] Step 6:

[2139] The terminal displays information on how to dispose of non-burnable waste to the user.

[2140] Valuable garbage proposals

[2141] Step 1:

[2142] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[2143] Step 2:

[2144] The device sends the photograph to the server.

[2145] Step 3:

[2146] The server passes the received photos to the AI ​​model and begins analysis.

[2147] Step 4:

[2148] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[2149] Step 5:

[2150] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[2151] Step 6:

[2152] The server sends information about the estimated price and listing procedures to the terminal.

[2153] Step 7:

[2154] The terminal displays the received information to the user and guides them through the listing procedure.

[2155] Step 8:

[2156] The user follows the instructions and selects "List."

[2157] Step 9:

[2158] The terminal transmits the request to put up for sale to the server.

[2159] Step 10:

[2160] The server receives the listing information and completes the listing process via the Marketplace API.

[2161] Example 1

[2162] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2163] The conventional procedure for disposing of bulky waste is complicated and time-consuming, and it is difficult to obtain information on appropriate disposal methods and fees. It is also difficult to distinguish between non-burnable and non-burnable waste, and opportunities to reuse or recycle valuable waste are often overlooked. A system that solves these problems and makes the process for disposing of bulky waste efficient and easy is needed.

[2164] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2165] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving collection of the waste based on input from the user, and means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user. This makes it possible to provide information on disposal methods and fees for bulky waste, reserve collection dates, distinguish between non-burnable and combustible waste, and suggest reuse or recycling of valuable waste.

[2166] The "means for acquiring images" refers to a device or software that has the function of taking a photo of the bulky waste that the user wants to dispose of and inputting that image into the system.

[2167] "Means for analyzing acquired images and identifying the type of waste" refers to a device or software that has the function of analyzing image data received by the server using an AI model or the like to identify the type of waste.

[2168] "Means for collecting information on the disposal of identified waste" means a device or software that has the function of allowing the server to retrieve information on fees and disposal methods related to the disposal of waste from a database based on the type of waste identified.

[2169] The "means for presenting information regarding disposal" refers to a device or software that has the function of transmitting information regarding disposal of waste collected by the server to the user's terminal and displaying it on the terminal.

[2170] "Means for reserving waste collection based on user input" refers to a device or software that has the function of sending information such as the desired collection date entered by the user into the terminal to a server, and the server then confirming the collection reservation based on that information.

[2171] The "means for evaluating whether the identified waste has market value and suggesting reuse or recycling to the user" refers to a device or software that has the function of a server evaluating the market value of waste and suggesting reuse or recycling of that waste to the user.

[2172] "Means for determining whether waste is non-burnable waste and presenting the relevant information to the user" refers to a device or software that has the function of a server determining whether waste is non-burnable waste based on the results of image analysis, and sending and presenting the results to the user's terminal.

[2173] "Means for using a marketplace API to collect the market value and listing procedures for valuable waste and present them to users" refers to a device or software that has the function of a server using an online marketplace API to collect information on the market value and listing procedures for valuable waste, and sending that information to the user's terminal for presentation.

[2174] The present invention is an AI-based system for simplifying the procedure for disposing of bulky waste. Detailed embodiments of this system are described below.

[2175] System configuration

[2176] This system mainly consists of the following components:

[2177] 1. Image acquisition method

[2178] The device has a function that allows users to take a photo of the bulky waste they want to throw away and input the image into the system. A smartphone or digital camera is the hardware that performs this function.

[2179] 2. Image analysis methods

[2180] The device sends the captured image to a server, which then uses AI to analyze the image and identify the type of waste. Specifically, it uses the generative AI model YOLO (You Only Look Once).

[2181] 3. Information gathering methods

[2182] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[2183] 4. Information presentation means

[2184] The server sends the collected information to the terminal, which then displays the fees and processing method to the user.

[2185] 5. Collection reservation method

[2186] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[2187] 6. How to determine non-burnable waste

[2188] The server has the ability to determine whether the waste is non-combustible based on the analysis results and send that information to the terminal.

[2189] 7. Market value assessment and reuse proposal methods

[2190] The server evaluates whether the waste has market value and uses the marketplace API to make reuse and recycling suggestions to users.

[2191] Program processing

[2192] 1. Image acquisition and transmission

[2193] A user takes a photo of a large piece of trash, such as an old sofa, with a mobile device.

[2194] The device sends the captured image to the server. The image data is sent using an internet connection.

[2195] 2. Image Analysis

[2196] The server inputs the received image into an AI model and starts image analysis, for example, using YOLO.

[2197] The server uses the analysis results to identify the object (e.g., an old sofa) contained in the image, and returns the identification result as a specific name such as sofa.

[2198] 3. Collection and presentation of information

[2199] The server retrieves information about fees and disposal methods related to the identified waste (e.g., sofa) from the database. For example, it retrieves information that the disposal fee for a sofa is 1,200 yen.

[2200] The server checks the dates that can be collected (e.g., May 15th or May 18th) and sends that information to the terminal.

[2201] The terminal will display the fee and collection dates to the user, who can then select a collection date based on the displayed information.

[2202] 4. Select a collection date and make a reservation

[2203] The user selects the desired date (e.g., May 15th) from the available collection dates presented.

[2204] The terminal sends the collection date information selected by the user to the server, which then registers the selected collection date in the database.

[2205] The server confirms the collection reservation information and notifies the user that the reservation has been completed.

[2206] 5. Non-burnable garbage classification and guidance

[2207] The server determines from the analysis results that the waste is non-burnable (e.g., a metal frying pan). The determination is made based on pre-set rules.

[2208] The server notifies the terminal of non-burnable waste information.

[2209] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[2210] 6. Market value assessment and reuse proposals

[2211] If the server determines from the analysis results that the waste has value (e.g., an old guitar), it uses the marketplace API to collect possible product value and listing information.

[2212] The server sends the collected information to the device, including the estimated price (e.g., 10,000 yen) and details of the listing process.

[2213] The device displays the product description, estimated price, and listing procedure to the user. If the user selects "List," the device sends this information to the server. An example of a generated prompt might be, "The estimated value of this guitar is 10,000 yen. Would you like to list it?"

[2214] The server performs the listing procedure on the online auction site and sends a completion notice to the user.

[2215] Specific examples

[2216] For example, a user takes a photo of an old sofa and sends it to a server via their smartphone. The server analyzes the image and recognizes it as a sofa, then retrieves the 1,200 yen handling fee and collection dates (May 15th and May 18th) from a database and sends them to the device. The device displays this information to the user, who selects May 15th. The selected information is sent to the server, which then confirms the collection reservation. In addition, the server can display suggestions for items such as metal frying pans, which can be disposed of as non-burnable waste, and items such as guitars, which can be reused or recycled, for sale.

[2217] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2218] Step 1:

[2219] Image capture and transmission

[2220] The user takes a photo of the bulky item they want to throw away (e.g., an old sofa) with their smartphone. This becomes the input image for the system. Specific actions include opening the camera app and taking a photo.

[2221] The device sends the captured image file to the server. An internet connection is required for transmission, and a protocol such as an HTTP request is used. The input is the captured image file, and the output is the completion of sending the image data to the server.

[2222] Step 2:

[2223] Image analysis

[2224] The server inputs the received image file into the AI ​​model and begins image analysis. Specific operations include using generative AI models such as YOLO (You Only Look Once).

[2225] The server uses an AI model to identify an object (e.g., a sofa) in an image. The input is the received image data, and the output is the name of the identified object (e.g., "sofa"). The server supplies the image data to the AI ​​model and receives the generated label.

[2226] Step 3:

[2227] Collection and presentation of information

[2228] The server collects information related to waste disposal from a database based on the identification result (e.g., "sofa"), and specific operations include querying the database using an SQL query.

[2229] The input is the name of the identification result, and the output is the collected fee and the collectable date information (e.g., "Fee 1,200 yen, collection dates May 15th and May 18th").

[2230] The server sends the collected information to the terminal.

[2231] The terminal displays the collection information (fees and collection date) to the user. Specific operations include displaying the information on the application screen.

[2232] Step 4:

[2233] Selecting and reserving a collection date

[2234] The user selects the desired date (e.g., May 15th) from the available dates presented for collection. This becomes the input for the next process. Specific actions include selecting a date from a calendar interface on the application.

[2235] The terminal sends the user's selection information to the server. The input is the collection date selected by the user, and the output is the completion of information transmission to the server.

[2236] The server registers the collection reservation in the database based on the received selection information, including saving the collection date in the database using an SQL query.

[2237] Step 5:

[2238] Non-burnable waste determination and guidance

[2239] The server determines whether the waste is non-burnable or not based on the results of image analysis. This is done using predefined rules. The input is the result of image analysis, and the output is the determination of whether the waste is non-burnable or not.

[2240] The server sends the result of the judgment to the user's terminal. The input is the judgment result of non-burnable waste, and the output is the completion of information transmission to the terminal.

[2241] The terminal displays a message to the user such as, "Please dispose of metal frying pans as non-burnable garbage on the specified day in the specified place." Specific actions include displaying a message on the application screen.

[2242] Step 6:

[2243] Market value assessment and reuse proposals

[2244] The server evaluates whether the waste has market value based on the results of image analysis. The input is the waste identification result, and the output is the market value assessment result.

[2245] The server uses the marketplace's API to gather possible product values ​​and listing information, including sending API requests and receiving information.

[2246] The server sends the collected information to the terminal. The input is the product value information obtained from the API, and the output is the completion of sending the information to the terminal.

[2247] The terminal displays to the user a description of the product, an estimated price (e.g., 10,000 yen), and listing procedure information. If the user selects "List," the terminal sends this information to the server. Specific operations include displaying listing procedure instructions on the application screen and receiving user input.

[2248] The server processes the listing on the online auction site and sends a completion notice to the user. The input is the user's listing information, and the output is a completion notice of the listing procedure.

[2249] (Application example 1)

[2250] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2251] The present invention aims to solve the problem of the complicated procedure for disposing of bulky waste and the inability of users to properly understand how to dispose of it. It also aims to provide a method for effectively utilizing waste that has value and can be reused or recycled without overlooking that value. Another objective is to simplify the process of reserving collection dates and improve user convenience.

[2252] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2253] In this invention, the server includes a means for presenting a collection method for valuable waste, a means for the user to input a desired collection date, and a means for confirming collection reservation information, which allows the user to easily carry out the procedure for disposing of bulky waste and further enables the user to maximize the value of reusable and recyclable waste.

[2254] The "means for acquiring images" refers to a means by which a user takes a photograph of the bulky waste and inputs the image into the system.

[2255] "Means for analyzing acquired images to identify the type of waste" refers to the means by which the system uses AI to analyze images sent to the server and identify the type of waste.

[2256] The "means for collecting information on the disposal of identified waste" is a means for the server to obtain information on disposal fees and disposal methods for identified waste from the database.

[2257] The "means for presenting information about processing" is a means for displaying information about the acquired fee and processing method to the user.

[2258] The "means for reserving waste collection based on input from the user" refers to a means for the user to input a desired collection date and transmit that information to the server to make a collection reservation.

[2259] "Means for suggesting methods for recovering valuable waste" refers to means for proposing reuse or recycling when waste has market value based on the analysis results.

[2260] The "means for the user to input the desired collection date" is a means for the user to select a collection date through the application and transmit that information to the server.

[2261] The "means for determining collection reservation information" is a means for the server to determine the collection schedule based on the selected collection date and update the reservation information.

[2262] This invention is an AI-based system for simplifying the process of disposing of bulky waste, and is mainly composed of the following components:

[2263] System configuration

[2264] 1. Image acquisition method

[2265] Users can take photos of bulky waste with their smartphones and enter the images into the system.

[2266] 2. Image analysis methods

[2267] The captured images are sent from the smartphone to a cloud server (e.g., AWS EC2) where they are analyzed using an AI image analysis model (e.g., TensorFlow or PyTorch). This analysis identifies the type of waste.

[2268] 3. Information gathering methods

[2269] The server retrieves information on processing fees and processing methods for the identified waste from a cloud database (e.g., Amazon RDS).

[2270] 4. Information presentation means

[2271] Information about processing fees and processing methods is sent from the server to the smartphone and displayed to the user, allowing the user to check the necessary information.

[2272] 5. Collection reservation method

[2273] The user selects the desired collection date from the schedule presented and sends that information to the server via their smartphone. The server then confirms the collection reservation based on the received collection date information.

[2274] 6. How to determine non-burnable waste

[2275] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the user's smartphone and guides them on how to dispose of it properly.

[2276] 7. Value Judgment Tools

[2277] If the server determines that the waste is valuable using the AI ​​image analysis model, it uses a marketplace API (e.g., eBay API) to collect information about the product value and listing, and suggests reuse or recycling to the user.

[2278] Hardware and software used

[2279] Hardware: Smartphone camera, cloud server (AWS EC2), cloud database (Amazon RDS)

[2280] Software: Mobile app (Flutter or React Native), AI image analysis model (TensorFlow or PyTorch), marketplace API (eBay API)

[2281] Specific examples

[2282] 1. Sofa disposal procedures

[2283] A user takes a photo of an old sofa with their smartphone.

[2284] The image is sent to a cloud server, where an AI image analysis model identifies it as a sofa.

[2285] The server retrieves the processing fee and collection date from a cloud database and displays them on the smartphone.

[2286] The user selects the desired collection date, and the server confirms the collection reservation.

[2287] 2. If the frying pan is non-burnable garbage

[2288] A user takes a photo of a metal frying pan with their smartphone.

[2289] The image is sent to a cloud server, and an AI image analysis model determines that the frying pan is non-burnable waste.

[2290] The server obtains the disposal method for non-combustible waste and displays it on the smartphone.

[2291] 3. Proposal for listing a valuable guitar

[2292] A user takes a photo of an old guitar with their smartphone.

[2293] The images are sent to a cloud server, where an AI image analysis model determines whether the guitar is valuable.

[2294] The server uses the marketplace API to obtain estimated prices and listing procedure information, which is then displayed on the smartphone.

[2295] Prompt Sentence Examples

[2296] "Analyze images of bulky waste taken by users with a smartphone app and identify the type of object (e.g. sofa, frying pan). After identification, retrieve the associated processing fee and possible collection date from the database and display them to the user. Also, for valuable objects, obtain an estimated price via the Marketplace API and provide information to guide the listing process."

[2297] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2298] Step 1:

[2299] Users take photos of bulky waste with their smartphones and upload the images to a cloud server via the application.

[2300] Input: Photo of bulky waste

[2301] Output: Image data is sent to the cloud server

[2302] Specific behavior: A user takes a photo with their smartphone camera and uses the application's image upload function to send the image to a cloud server.

[2303] Step 2:

[2304] The server inputs the received image data into an AI image analysis model to identify the type of waste.

[2305] Input: Image data

[2306] Output: Waste type determination (e.g. sofa, frying pan)

[2307] How it works: The images sent to the cloud server are stored and passed to an AI model (e.g., TensorFlow or PyTorch), which then analyzes the images and identifies the type of waste.

[2308] Step 3:

[2309] Based on the identified type of waste, the server collects information on processing fees and processing methods from a cloud database.

[2310] Input: Waste type determination result

[2311] Output: Processing fee and processing method information

[2312] Specific operation: Sends a query to a cloud database (e.g., Amazon RDS) to obtain disposal fees and methods corresponding to the waste type.

[2313] Step 4:

[2314] The server sends the collected information to the terminal, which displays the information to the user.

[2315] Input: Processing fee and processing method information

[2316] Output: User-visible processing fee and processing method

[2317] Specific operation: The server sends information such as processing fees and collection dates to the user's smartphone via API, and the smartphone app displays the information to the user.

[2318] Step 5:

[2319] The user selects the desired collection date from the available collection dates displayed and transmits the information to the server via the terminal.

[2320] Input: User's desired collection date

[2321] Output: Collection date information sent to the server

[2322] How it works: The user selects a collection date using the smartphone app interface, and that information is sent to the server via an API.

[2323] Step 6:

[2324] The server confirms the collection reservation based on the received collection date information and updates the schedule.

[2325] Input: User's desired collection date

[2326] Output: Confirmed collection reservation information

[2327] Specific operation: The server saves the received collection date information in the database and updates and confirms the collection schedule.

[2328] Step 7:

[2329] If the server determines using the AI ​​image analysis model that the waste is non-combustible, it sends that information to the terminal and guides the user on the appropriate disposal method.

[2330] Input: Waste is non-burnable waste

[2331] Output: How to dispose of non-burnable waste

[2332] Specific operation: If the server determines that the item is non-combustible waste using the AI ​​model, it sends information about how to dispose of it to the user's smartphone, and the application displays that information.

[2333] Step 8:

[2334] If the server determines that the waste has value using the AI ​​image analysis model, it uses the marketplace API to collect information about the product's value and listing, and suggests reuse or recycling to the user.

[2335] Input: Determination that the waste is valuable

[2336] Output: Information on product value and listing procedures

[2337] How it works: The server queries a marketplace API (e.g., eBay API) to obtain information about the product's value and listing process, and sends it to the user's smartphone. The application displays this information to the user and suggests reuse and recycling options.

[2338] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2339] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes the user's emotions. The detailed configuration of this system and the program processing are described below.

[2340] System configuration

[2341] This system mainly consists of the following components:

[2342] 1. Image acquisition method

[2343] The device has the function of allowing users to take a photo of the bulky waste they want to throw away and input that image into the system.

[2344] 2. Image analysis methods

[2345] The device sends the images it takes to a server, which then uses AI to analyze the images and identify the type of waste.

[2346] 3. Information gathering methods

[2347] The server has a function to obtain information on fees and processing methods for the identified waste from the database.

[2348] 4. Information presentation means

[2349] The terminal has the function of displaying the fees and processing method to the user.

[2350] 5. Collection reservation method

[2351] The user inputs the desired collection date, the terminal sends the information to the server, and the server then reserves the collection.

[2352] 6. How to determine non-burnable waste

[2353] The server has the function of determining whether the identified waste is non-combustible waste and sending the relevant information to the terminal.

[2354] 7. Value Judgment Tools

[2355] The server evaluates whether the identified waste has market value and has the function of suggesting reuse or recycling to the user.

[2356] 8. Emotion Engine

[2357] It has the ability to recognize the user's emotions and provide information and simplify procedures based on that.

[2358] Program processing

[2359] 1. Image acquisition and transmission

[2360] The user takes a photo of the bulky waste they want to throw away using a mobile device or digital camera.

[2361] The device sends the captured image to the server.

[2362] 2. Image Analysis

[2363] The server receives the image and analyzes it using AI.

[2364] The server uses AI models to identify the type of waste, such as an old sofa or a metal frying pan.

[2365] 3. Collection and presentation of information

[2366] The server collects information on fees and disposal methods from a database based on the identified type of waste.

[2367] The server returns the handling fee (for example, 1,200 yen) and the available collection dates (for example, May 15th and May 18th) to the terminal.

[2368] The terminal displays this information to the user.

[2369] 4. Select a collection date and make a reservation

[2370] The user selects the desired collection date (e.g., May 15th) from the options presented.

[2371] The terminal transmits the selected collection date to the server.

[2372] The server receives the collection reservation information and determines the collection schedule.

[2373] 5. Non-burnable garbage classification and guidance

[2374] If the server determines that the waste is non-combustible waste based on the results of its AI analysis, it will send that information to the terminal.

[2375] The terminal displays instructions to the user such as "Please dispose of metal frying pans as non-burnable waste on the specified day in the specified place."

[2376] 6. Valuable garbage proposals

[2377] If the server determines from the analysis results that the waste is valuable, it uses the API of a marketplace (e.g., an online auction) to collect information about the product value and listing.

[2378] The server sends information about the estimated price and listing procedures to the terminal.

[2379] The terminal displays to the user a description of the product, an estimated price, and the listing procedure, and guides the user through the listing procedure if desired.

[2380] 7. The Emotional Engine

[2381] The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state.

[2382] When the emotion engine determines that the user is feeling stressed, an encouraging message is displayed to the user through the information presentation means.

[2383] If more emotion engines are needed, they instruct the server or terminal how to simplify the steps of the procedure.

[2384] Specific examples

[2385] 1. Sofa disposal procedures

[2386] A user takes a photo of an old sofa.

[2387] The device sends the photo to the server.

[2388] The server analyzes the photo and determines it is a sofa. A handling fee of 1,200 yen is charged, and collection dates are May 15th and May 18th.

[2389] The user selects May 15th as the collection date.

[2390] The terminal sends the collection date to the server and confirms the reservation.

[2391] 2. If the frying pan is non-burnable garbage

[2392] A user takes a photo of a metal frying pan.

[2393] The device sends the photo to the server.

[2394] The server analyzes the photo and determines that the frying pan is non-combustible waste.

[2395] The device will guide the user on how to dispose of non-burnable waste.

[2396] 3. When a guitar is valuable

[2397] A user takes a photo of an old guitar.

[2398] The device sends the photo to the server.

[2399] The server analyzes the photo and determines that the guitar is valuable. It sends an estimated price of 10,000 yen and instructions on how to list the item to the user's device.

[2400] The device displays the product description, estimated price, and listing procedure to the user, and they select "List."

[2401] The terminal transmits the listing information to the server, and the server carries out the listing procedure for the online auction.

[2402] 4. User Emotion Recognition

[2403] If the user is feeling stressed, the emotion engine will analyze and recognize the state.

[2404] The emotion engine instructs the device to display an appropriate encouraging message.

[2405] The emotion engine instructs the server or terminal to automate or simplify parts of the procedure, allowing the user to proceed smoothly.

[2406] In this way, users can easily dispose of bulky waste and avoid missing out on opportunities for recycling and reuse. In addition, the emotion engine provides a comfortable operating experience for users.

[2407] The processing flow will be explained below.

[2408] Program processing steps

[2409] Booking by photo shoot

[2410] Step 1:

[2411] The user takes a photo of the bulky item they want to throw away (such as an old sofa).

[2412] Step 2:

[2413] The device sends the photograph to the server.

[2414] Step 3:

[2415] The server passes the received photos to the AI ​​model and begins analysis.

[2416] Step 4:

[2417] The server will use AI analysis to identify the type, size, and weight of the garbage and calculate the corresponding fee.

[2418] Step 5:

[2419] The server returns the calculated fee (for example, 1,200 yen) and available collection dates (for example, May 15th and May 18th) to the terminal.

[2420] Step 6:

[2421] The terminal displays the received fee and collection date to the user.

[2422] Step 7:

[2423] The user selects a desired date (for example, May 15th) from the collection dates presented.

[2424] Step 8:

[2425] The terminal transmits the selected collection date and reservation information to the server.

[2426] Step 9:

[2427] The server stores the reservation information and schedules the collection.

[2428] Judgment as non-burnable waste

[2429] Step 1:

[2430] The user takes a photo of the trash they want to throw away (e.g., a metal frying pan).

[2431] Step 2:

[2432] The device sends the photograph to the server.

[2433] Step 3:

[2434] The server passes the received photos to the AI ​​model and begins analysis.

[2435] Step 4:

[2436] The server identifies the type of garbage based on AI analysis and determines whether it can be classified as non-combustible garbage.

[2437] Step 5:

[2438] If the server determines that the item is non-burnable waste, it sends that information and details on how to dispose of it to the terminal.

[2439] Step 6:

[2440] The terminal displays information on how to dispose of non-burnable waste to the user.

[2441] Valuable garbage proposals

[2442] Step 1:

[2443] The user takes a photo of an item they are thinking of throwing away (for example, an old guitar).

[2444] Step 2:

[2445] The device sends the photograph to the server.

[2446] Step 3:

[2447] The server passes the received photos to the AI ​​model and begins analysis.

[2448] Step 4:

[2449] The server uses AI analysis to identify the type of garbage and evaluate whether the item has market value.

[2450] Step 5:

[2451] Based on the evaluation results, the server calls the marketplace API to collect information on the estimated price of the product and the listing procedure.

[2452] Step 6:

[2453] The server sends information about the estimated price and listing procedures to the terminal.

[2454] Step 7:

[2455] The terminal displays the received information to the user and guides them through the listing procedure.

[2456] Step 8:

[2457] The user follows the instructions and selects "List."

[2458] Step 9:

[2459] The terminal transmits the request to put up for sale to the server.

[2460] Step 10:

[2461] The server receives the listing information and completes the listing process via the Marketplace API.

[2462] User support with emotion engine

[2463] Step 1:

[2464] When a user uses the system, the emotion engine captures the user's facial expressions and voice through the camera and microphone.

[2465] Step 2:

[2466] The facial expression and voice data acquired by the device is sent to the server.

[2467] Step 3:

[2468] The server passes the received facial expression and voice data to the emotion engine and begins analysis.

[2469] Step 4:

[2470] The server determines whether the user is feeling stressed or dissatisfied based on the analysis of the emotion engine.

[2471] Step 5:

[2472] The server determines the appropriate message and dialogue procedure based on the emotional state and sends that information to the terminal.

[2473] Step 6:

[2474] The device displays an appropriate message to the user (e.g., "We're here to help you. Let us know if you have any questions.").

[2475] Step 7:

[2476] As the user proceeds, the emotion engine continues to monitor the user's emotional state and instructs the server to simplify the process if necessary.

[2477] Step 8:

[2478] The server handles the simplification of procedures, for example by providing auto-filling and additional support to reduce the burden on the user.

[2479] Example 2

[2480] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2481] The process of disposing of bulky waste is complicated and often stressful for users. Furthermore, if the waste has market value, opportunities for reuse or recycling may be missed. Furthermore, there is a lack of means to recognize the user's emotions and provide appropriate support, which hinders the user's operational experience.

[2482] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2483] In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the disposal of the identified waste, means for presenting information on the disposal, means for reserving waste collection based on input from the user, and means for recognizing the user's emotions and providing information based on the emotions. This makes it possible to carry out the procedure for disposing of oversized waste easily and smoothly, preventing missed opportunities for reuse and recycling and providing a comfortable operating experience for the user.

[2484] "Means for acquiring images" refers to devices or software that allow a user to take an image of the waste they wish to dispose of and input that image into the system.

[2485] "Means for analyzing acquired images and identifying the type of waste" refers to devices or software that analyze received images and identify the type of waste depicted in the images using AI models, etc.

[2486] "Means for collecting information on the disposal of identified waste" refers to devices or software that retrieve information such as disposal methods and fees from a database based on the type of identified waste.

[2487] "Means for presenting information about processing" refers to devices or software that display collected information such as processing methods and fees to users.

[2488] "Means for reserving waste collection based on user input" refers to devices or software that reserve waste collection based on information entered by the user, such as the desired collection date.

[2489] "Means for recognizing a user's emotions and providing information based on those emotions" refers to devices or software that analyze a user's facial expressions, voice, etc. to identify emotions and provide information according to those emotions.

[2490] "Means for determining whether waste is non-combustible waste" refers to devices or software that determine whether identified waste is non-combustible waste.

[2491] "Means for determining whether waste has market value and proposing reuse or recycling if it is determined to have market value" refers to devices or software that determine whether identified waste has market value and, if it is determined to have value, proposes reuse or recycling.

[2492] MODE FOR CARRYING OUT THE INVENTION

[2493] This invention combines an AI-based system for simplifying the process of disposing of bulky waste with an emotion engine that recognizes user emotions. The system mainly includes the following hardware and software components:

[2494] Hardware and software used

[2495] Device: Smartphone or digital camera

[2496] Server: Cloud server with database and AI model

[2497] software:

[2498] Image processing: OpenCV

[2499] Image Analysis and Classification: TensorFlow

[2500] Emotion recognition: Emotion API

[2501] System Operation Overview

[2502] 1. Image acquisition method

[2503] The user takes a photo of the bulky waste they want to throw away using a smartphone or digital camera.

[2504] The images taken by the device are sent to the server via a system-specific app.

[2505] 2. Image analysis methods

[2506] Based on the images received by the server, preprocessing is performed using OpenCV.

[2507] The server uses TensorFlow to analyze the images and identify the type of waste.

[2508] 3. Information gathering methods

[2509] The server collects fees and disposal methods from a database based on the identified waste type.

[2510] 4. Information presentation means

[2511] The terminal presents the fee received from the server and the collection date to the user.

[2512] 5. Collection reservation method

[2513] The user selects the desired collection date and transmits that information from the terminal to the server.

[2514] The server schedules the collection appointment.

[2515] 6. How to determine non-burnable waste

[2516] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[2517] The device will guide the user on how to dispose of non-burnable waste.

[2518] 7. Value Judgment Tools

[2519] The server determines whether the waste has market value and makes suggestions for reuse or recycling as needed.

[2520] The server connects to the marketplace's API to collect estimated prices and listing procedures.

[2521] The terminal presents this information to the user and guides them through the listing procedure.

[2522] 8. Emotion Engine

[2523] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[2524] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[2525] If necessary, instructions will be provided to simplify the steps of the procedure.

[2526] Specific examples

[2527] 1. Sofa disposal procedures

[2528] A user takes a photo of an old sofa.

[2529] The device sends the photo to the server.

[2530] The server analyzes the image and identifies it as a sofa.

[2531] The fee is 1,200 yen and collection dates are May 15th and May 18th.

[2532] The user selects May 15th as the collection date, and the terminal sends the information to the server.

[2533] The server confirms the collection reservation.

[2534] 2. If the frying pan is non-burnable garbage

[2535] A user takes a photo of a metal frying pan.

[2536] The device sends the photo to the server.

[2537] The server analyzes the image and identifies the frying pan as non-combustible waste.

[2538] The device will guide the user on how to dispose of non-burnable waste.

[2539] 3. When a guitar is valuable

[2540] A user takes a photo of an old guitar.

[2541] The device sends the photo to the server.

[2542] The server analyzes the image and determines that it is a valuable guitar.

[2543] An estimated price of 10,000 yen and instructions on how to proceed with listing will be sent to your device.

[2544] The device displays the product description, estimated price, and listing procedure to the user, and asks whether they want to list the item.

[2545] If the user chooses to put up an item for auction, the terminal transmits the information to the server, which then processes the item for auction at the online auction.

[2546] Prompt Sentence Examples

[2547] "I want to simplify the process of throwing away an old sofa. Create a program where I can take a photo, submit it, and the system will suggest fees and a reservation date."

[2548] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2549] Step 1:

[2550] The user takes a photo of the bulky trash they want to throw away using their mobile device.

[2551] Input: Photo of bulky waste

[2552] Output: Image data saved on the device

[2553] Specific operation: The user takes a photo of the sofa using the smartphone's camera app. After taking the photo, the photo is saved in the device's gallery.

[2554] Step 2:

[2555] The images taken by the device are sent to the server via a system-specific app.

[2556] Input: Image data stored on the device

[2557] Output: Image data sent to the server

[2558] Specific operation: The user launches the system's dedicated app and selects the photo of the sofa they have taken. After selection, the system's dedicated app sends the image data to the server.

[2559] Step 3:

[2560] Based on the images received by the server, preprocessing is performed using OpenCV.

[2561] Input: Image data received by the server

[2562] Output: Preprocessed image data

[2563] Specific operation: The server uses OpenCV to perform preprocessing such as image noise removal and resizing.

[2564] Step 4:

[2565] The server uses TensorFlow to analyze the images and identify the type of waste.

[2566] Input: Preprocessed image data

[2567] Output: Identified waste types

[2568] How it works: Preprocessed image data is fed into a TensorFlow AI model to identify the type of waste (e.g., sofa).

[2569] Step 5:

[2570] The server collects fees and disposal methods from a database based on the identified waste type.

[2571] Input: Identified waste type

[2572] Output: Information about fees and disposal methods

[2573] Specific operation: The server retrieves the fee (e.g., 1,200 yen) and collection date (e.g., May 15th, May 18th) from the database based on the type of waste (e.g., sofa).

[2574] Step 6:

[2575] The terminal presents the fee received from the server and the collection date to the user.

[2576] Input: Fee and disposal method information

[2577] Output: Information presented to the user

[2578] Specific operation: The terminal will display a pop-up message to the user indicating the fee (e.g., 1,200 yen) and the collection dates (e.g., May 15th, May 18th).

[2579] Step 7:

[2580] The user selects the desired collection date, and the terminal transmits this information to the server.

[2581] Input: User selected collection date

[2582] Output: Data sent to the server on the collection date

[2583] Specific operation: The user taps to select a collection date (e.g., May 15th) on the device, and the device sends the selected collection date to the server.

[2584] Step 8:

[2585] The server schedules the collection appointment.

[2586] Input: User selected collection date

[2587] Output: Notification of confirmed collection reservation

[2588] Specific operation: The server checks the collection date and confirms the schedule. After confirmation, a notification "Collection reservation confirmed" is displayed on the device.

[2589] Step 9:

[2590] If the server determines through AI analysis that the waste is non-combustible, it sends that information to the device.

[2591] Input: AI analysis results

[2592] Output: Information about details of non-burnable waste

[2593] Specific operation: The server determines that the item is non-combustible waste (e.g., a metal frying pan) and sends disposal instructions (e.g., to dispose of in a designated place on a designated day) to the terminal.

[2594] Step 10:

[2595] The device will guide the user on how to dispose of non-burnable waste.

[2596] Input: Information about details of non-burnable waste

[2597] Output: Information presented to the user

[2598] Specific operation: The device displays the message, "Please dispose of metal frying pans as non-burnable waste in the designated place on the designated day."

[2599] Step 11:

[2600] The server determines whether the waste has market value and makes suggestions for reuse or recycling.

[2601] Input: AI analysis results and marketplace information

[2602] Output: Reuse and recycling suggestions

[2603] Specific operation: For waste items that the server determines to be valuable (e.g., old guitars), it obtains the estimated price (e.g., 10,000 yen) and listing instructions and sends them to the terminal.

[2604] Step 12:

[2605] The terminal provides users with information about valuable waste and guides them through the listing process.

[2606] Input: Reuse and recycling suggestions

[2607] Output: Information presented to the user

[2608] Specific operation: The device displays "The estimated price of this guitar is 10,000 yen. Would you like to list it?" and if the user selects "List it," it guides the user through the listing process.

[2609] Step 13:

[2610] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state.

[2611] Input: User's facial expressions and voice data

[2612] Output: User's emotional state

[2613] Specific operation: The emotion engine uses the device's camera and microphone to analyze the user's facial expressions and voice and identify their emotional state (e.g., stress).

[2614] Step 14:

[2615] If the emotion engine determines that the user is feeling stressed, it instructs the server to display an encouraging message on the terminal.

[2616] Input: User's emotional state

[2617] Output: An encouraging message

[2618] Specific operation: If it is determined that the user is feeling stressed, the device will display a message saying, "Don't worry. The procedure will be easy."

[2619] (Application example 2)

[2620] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2621] Conventional industrial waste treatment systems do not distinguish between different types of waste, provide appropriate treatment methods, or evaluate the market value of valuable waste, resulting in insufficient treatment efficiency and effective resource utilization. Furthermore, there is a lack of operational support that takes into account the emotional state of workers, which increases the stress and burden of operation.

[2622] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring images, means for analyzing the acquired images to identify the type of waste, means for collecting information on the treatment of the identified waste, means for presenting in...

Claims

1. a means for acquiring an image; means for analyzing the acquired images to identify the type of waste; means of collecting information on the disposal of identified wastes; means for presenting information about the processing; means for scheduling waste collection based on input from a user; A system including:

2. The system of claim 1 further comprising means for determining whether the waste is non-combustible waste.

3. 10. The system of claim 1, further comprising means for determining whether the waste material is valuable.

Images