System

Abstract

A system is provided.SOLUTION: Means for collecting operation information from a plurality of cleaning autonomous mobile devices and generating an optimal cleaning schedule based on the operation information, means for controlling the plurality of cleaning autonomous mobile devices in accordance with the cleaning schedule, means for receiving a request from a user via communication with a client terminal and adjusting the cleaning schedule in real time based on the request, acquiring authentication information of the user using an authentication device installed on a front surface of an article storage device; The system includes a means for performing authentication when delivering the article on the basis of the authentication information, and a means for collecting and managing data related to the delivery of the article.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] Two of the major challenges facing building managers and residents in urban and business districts are improving the efficiency of cleaning operations and ensuring the security of parcel delivery. Conventional systems attempt to address these challenges individually, lacking an integrated solution. Furthermore, optimizing cleaning schedules and confirming parcel delivery require significant human intervention, hindering efficiency. The present invention aims to overcome these challenges and improve the efficiency and security of building management by integrating cleaning and parcel delivery management. [Means for solving the problem]

[0005] The present invention is a system including the following means: means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information; means for controlling the multiple autonomous mobile cleaning devices according to the cleaning schedule; means for receiving requests from users via communication with a client terminal and adjusting the cleaning schedule in real time based on the requests; means for acquiring user authentication information using an authentication device installed in front of an item storage device and performing authentication when handing over items based on the authentication information; and means for collecting and managing data related to the handing over of items. This allows building managers and residents to centrally manage cleaning and deliveries, thereby simultaneously improving the efficiency of cleaning work and ensuring the security of deliveries.

[0006] An "autonomous mobile cleaning device" is a device that uses sensors and AI to recognize its surrounding environment and operates autonomously to clean.

[0007] "Operation information" refers to information such as sensor information collected by the autonomous mobile cleaning device, operation history, and location data.

[0008] A "cleaning schedule" is a plan that defines when and where an autonomous mobile cleaning device will perform cleaning work.

[0009] "Client terminal" refers to a device such as a PC or smartphone used by a user.

[0010] A "request" refers to a request or instruction given by a user to the system through a client terminal.

[0011] "Item storage equipment" refers to equipment or facilities installed for the temporary storage of parcels or other items.

[0012] An "authentication device" is a device for verifying a user's identity, and may include means such as facial recognition technology or fingerprint authentication.

[0013] "Authentication information" refers to information required to verify the identity of a user, and includes, for example, a facial image and fingerprint data.

[0014] "Item delivery" refers to the process of delivering an item stored in an item storage device to a user.

[0015] "Data" refers to various types of information processed within the system, including operational information, authentication information, request content, etc. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention relates to a system including an autonomous mobile cleaning device, an item storage device, and a server and client terminals that control these devices. Specific embodiments of this system will be described below.

[0038] System Overview

[0039] This system consists of an autonomous mobile cleaning device, an item storage device, a server, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device that allows users to receive deliveries and authenticates users using facial recognition technology. The server manages and controls these devices in an integrated manner, adjusting their operation in response to user requests.

[0040] Operation of the autonomous mobile cleaning device

[0041] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on it. If the schedule needs to be adjusted, the server receives a request from the user's client terminal and updates the schedule in real time.

[0042] Operation of the article storage device

[0043] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If the authentication is successful, the item storage device unlocks and the user can collect the parcel. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[0044] Processing user requests

[0045] When a user sends a request for changing the cleaning schedule or receiving a parcel via a client terminal, the server receives the request and performs the necessary processing. For example, if a user requests a change in the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device.

[0046] Specific examples

[0047] For example, if a user wishes to change the cleaning schedule, the following process is performed.

[0048] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[0049] 2. The device sends the request to the server.

[0050] 3. The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database for analysis.

[0051] 4. The server uses AI algorithms to calculate and generate a new optimal schedule.

[0052] 5. The server sends the new cleaning schedule to the terminal and displays it to the user.

[0053] 6. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[0054] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[0055] Similarly, the system also automates and efficiently manages the collection of parcels from the item storage device.

[0056] The above is a specific embodiment of the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security.

[0057] The processing flow will be explained below.

[0058] Changes to cleaning schedules

[0059] Step 1:

[0060] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[0061] Step 2:

[0062] The device (smartphone app) sends the request to the server.

[0063] Step 3:

[0064] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[0065] Step 4:

[0066] The server uses an AI algorithm to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule and sensor data.

[0067] Step 5:

[0068] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[0069] Step 6:

[0070] The user checks the new schedule and presses the approval button.

[0071] Step 7:

[0072] The device (smartphone app) sends the approval information to the server.

[0073] Step 8:

[0074] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[0075] Step 9:

[0076] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[0077] Receiving parcels

[0078] Step 1:

[0079] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[0080] Step 2:

[0081] The terminal (item storage device) transmits the facial authentication data to the server.

[0082] Step 3:

[0083] The server analyzes the facial recognition data and determines that the authentication was successful.

[0084] Step 4:

[0085] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[0086] Step 5:

[0087] The user arrives at the item storage device and holds their face up to the face authentication camera.

[0088] Step 6:

[0089] The terminal (item storage device) transmits the user's facial authentication data to the server.

[0090] Step 7:

[0091] The server analyzes the user's facial recognition data and compares it with database information.

[0092] Step 8:

[0093] The server notifies the terminal (item storage device) that the authentication was successful.

[0094] Step 9:

[0095] The terminal (item storage device) unlocks the door based on the authentication result.

[0096] Step 10:

[0097] The user removes the parcel from the item storage device.

[0098] Step 11:

[0099] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[0100] Example 1

[0101] 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."

[0102] To efficiently and effectively clean buildings and facilities, it is necessary to optimize cleaning schedules and adjust them in real time. Furthermore, when handing over items, strict user authentication is required, and safe and prompt responses are also required. However, with current systems, it is difficult to centrally manage these requirements, making it difficult to achieve both efficiency and safety.

[0103] 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.

[0104] In this invention, the server includes means for collecting environmental data from a plurality of autonomous mobile cleaning devices and generating an optimal cleaning plan based on the environmental data, means for controlling the plurality of autonomous mobile cleaning devices in accordance with the cleaning plan, and means for receiving requests from users via communication with a terminal and adjusting the cleaning plan in real time based on the requests, thereby enabling efficient operation of cleaning activities and safe delivery of items.

[0105] An "autonomous mobile cleaning device" is a mobile device that automatically cleans buildings and facilities, and operates using sensor technology and AI.

[0106] "Environmental data" refers to information about the surrounding situation and conditions collected by sensors installed on the autonomous cleaning device, including the location of obstacles and the degree of dirt on surfaces.

[0107] "Cleaning Plan" means an optimized cleaning schedule and route that is generated based on collected environmental data.

[0108] "Control" means to instruct a specific action or movement and to supervise or operate a device so that it operates in accordance with that instruction.

[0109] "Terminal" refers to various electronic devices used by users, including smartphones, tablets, computers, etc.

[0110] A "request" refers to a request or wish made by a user to the system, and is a request for a specific operation or change.

[0111] An "item storage device" is a device for safely storing parcels and other items, allowing users to receive them after authentication.

[0112] "Authentication device" refers to equipment used to verify and authenticate a user's personal information, including facial recognition cameras and fingerprint authentication sensors.

[0113] "Authentication information" means information used to verify a user's identity, including facial images and fingerprints.

[0114] "Goods" refers to parcels and other items that are subject to delivery.

[0115] "Data" refers to various information processed and managed by the system, including environmental data, certification information, cleaning plans, etc.

[0116] The present invention is a system for efficiently managing both cleaning activities and item delivery, and is composed of an autonomous mobile cleaning device, an item storage device, a server, and a user terminal.

[0117] Operation of the autonomous mobile cleaning device

[0118] The server uses AI algorithms to generate an optimal cleaning plan based on environmental data collected from the autonomous cleaning device. This plan is generated by analyzing information obtained from sensors (e.g., LiDAR sensors and cameras) using Python machine learning libraries (e.g., scikit-learn).

[0119] The generated cleaning plan is sent to the autonomous mobile cleaning device via a communication protocol (e.g., MQTT or HTTP). The autonomous mobile cleaning device automatically cleans the building according to this plan. If the cleaning plan needs to be adjusted, the server can receive requests from the user and update the plan in real time.

[0120] Specific examples

[0121] For example, if a user wishes to change the cleaning schedule, the following process is carried out.

[0122] 1. A user requests a change to the cleaning schedule from a chatbot on a smartphone app.

[0123] 2. The device sends the request to the server.

[0124] 3. The server receives the request and generates a new, optimal plan based on the latest environmental data and the current cleaning plan.

[0125] 4. The server sends the new plan to the terminal and presents it to the user.

[0126] 5. Once the user approves the new plan, the information is sent to the server.

[0127] 6. The server notifies the autonomous mobile cleaning device of the final new plan, and the device operates according to the plan.

[0128] Operation of the article storage device

[0129] The storage device stores parcels and uses facial recognition technology to authenticate users when they come to collect them, using image processing engines such as OpenCV and Google FaceNet.

[0130] The operation of the article storage device is as follows.

[0131] 1. The user approaches the item storage device, faces the camera, and attempts authentication.

[0132] 2. The item storage device sends the captured facial image to the server.

[0133] 3. The server checks the database and determines whether the authentication is successful.

[0134] 4. If the authentication is successful, the information is sent to the item storage device and the device is unlocked.

[0135] 5. The user can retrieve the parcel.

[0136] Specific examples

[0137] For example, when a user receives a parcel, the following process is carried out.

[0138] 1. The user stands in front of the item storage device and undergoes facial authentication.

[0139] 2. The item storage device recognizes the face and sends the data to the server.

[0140] 3. The server performs authentication, and if successful, sends an unlock command to the item storage device.

[0141] 4. The item storage device is unlocked and the user receives the parcel.

[0142] Example prompts for generative AI models

[0143] "I would like to change the cleaning schedule. What is the current schedule?"

[0144] "I'd like the cleaning completed by this morning. Please reschedule."

[0145] "I would like to receive a parcel, but I would like to use facial recognition."

[0146] The above is a specific embodiment for carrying out the present invention. This system ensures the efficiency of cleaning activities and the safety of item delivery, and can provide a convenient environment for users.

[0147] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0148] Step 1:

[0149] Sensor information collection

[0150] Input: Environmental data from sensors (e.g. LiDAR sensors, cameras)

[0151] Output: Environment data sent to the server

[0152] Specific behavior:

[0153] The autonomous mobile cleaning device uses sensors to acquire real-time environmental data, such as surrounding obstacles and dirt levels, and this data is sent to a server via communication methods such as Wi-Fi or Bluetooth.

[0154] Step 2:

[0155] Generate a cleaning plan

[0156] Input: Environmental data stored on the server

[0157] Output: The generated cleaning plan

[0158] Specific behavior:

[0159] The server uses AI algorithms to generate an optimal cleaning plan based on the received environmental data, using Python machine learning libraries (e.g., scikit-learn) to calculate the optimal route and time schedule for each autonomous cleaning device.

[0160] Step 3:

[0161] Submit a cleaning plan

[0162] Input: Generated cleaning plan

[0163] Output: Cleaning plan sent to the autonomous cleaning device

[0164] Specific behavior:

[0165] The server sends the generated cleaning plan to the autonomous mobile cleaning device using a communication protocol (e.g., MQTT, HTTP). The device follows the received plan and begins cleaning according to the specified route and time schedule.

[0166] Step 4:

[0167] Receiving a user request

[0168] Input: User request (e.g., cleaning schedule change)

[0169] Output: Request sent to the server

[0170] Specific behavior:

[0171] A user uses a client terminal to input a request to change the cleaning schedule. The terminal sends this request to the server, which may include a prompt such as "Please start cleaning at 3 PM."

[0172] Step 5:

[0173] Generate a new cleaning plan

[0174] Input: User request, latest environmental data

[0175] Output: New cleaning plan

[0176] Specific behavior:

[0177] The server receives the user's request and generates a new cleaning plan using AI algorithms based on the latest environmental data, again using Python machine learning libraries (e.g., scikit-learn) to perform the calculations.

[0178] Step 6:

[0179] Submit a new cleaning plan

[0180] Input: A newly generated cleaning plan

[0181] Output: New cleaning plan sent to the autonomous cleaning device and the user terminal

[0182] Specific behavior:

[0183] The server sends the new cleaning plan to the terminal and presents it to the user. If the user approves the new plan, the approval information is sent to the server. The server then sends the final new cleaning plan to the autonomous mobile cleaning device, and the device operates based on the plan.

[0184] Step 7:

[0185] Receiving a facial recognition request

[0186] Input: User's face recognition trigger

[0187] Output: Face image data

[0188] Specific behavior:

[0189] When a user approaches an item storage device and attempts facial authentication, the item storage device uses a camera to capture an image of the user's face and transmits the data to a server.

[0190] Step 8:

[0191] Performing face recognition

[0192] Input: Facial image data

[0193] Output: Authentication result

[0194] Specific behavior:

[0195] The server uses a facial recognition algorithm (e.g., OpenCV or Google FaceNet) to match the image with a registered image in a database. If the authentication is successful, the result is sent to the item storage device.

[0196] Step 9:

[0197] Execution of goods delivery

[0198] Input: Authentication success signal

[0199] Output: Unlocked containment unit

[0200] Specific behavior:

[0201] After the item storage device receives the signal of successful authentication, it releases the electromagnetic lock, allowing the user to remove the item from the unlocked device.

[0202] The above are the specific processing steps of the entire system. This system efficiently carries out cleaning activities and item delivery, providing a convenient and safe environment for users.

[0203] (Application example 1)

[0204] 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."

[0205] Currently, efficient management of cleaning and parts supply within factories is carried out manually or through separate systems, making operations cumbersome. Furthermore, robot schedule changes and optimization cannot be performed in real time, which can lead to reduced production efficiency. Furthermore, authentication and management of parts supply are also dependent on human labor, creating security and efficiency challenges.

[0206] 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.

[0207] In this invention, the server includes means for collecting operation information from a plurality of autonomous mobile cleaning devices and part supply robots and generating optimal cleaning and supply schedules based on the operation information, means for controlling the plurality of autonomous mobile cleaning devices and part supply robots in accordance with the cleaning and supply schedules, and means for receiving requests from users via communication with client terminals and adjusting the cleaning and supply schedules in real time based on the requests. This enables integrated management of cleaning and part supply within a factory, and automation improves efficiency and strengthens security.

[0208] An "autonomous mobile cleaning device" is a mobile machine equipped with sensor technology and AI algorithms that autonomously performs cleaning tasks within a factory.

[0209] A "parts supply robot" is an autonomously operating mechanical device that has the function of automatically supplying parts to designated locations.

[0210] "Operation information" is a collection of data including the current working status and position information of the autonomous mobile cleaning device and the parts supply robot, and environmental information obtained from sensors.

[0211] A "cleaning schedule" is a planned work schedule for an autonomous mobile cleaning device to clean a specific location at a specific time.

[0212] A "supply schedule" is a planned work schedule for a parts supply robot to supply parts to a specific location at a specific time.

[0213] A "client terminal" is a communication device such as a smartphone, tablet, or PC that a user uses to send a request.

[0214] An "authentication device" is a device for acquiring authentication information of a user, and is used to verify the identity of the user using facial recognition technology or the like.

[0215] An "item storage device" is a device for storing and transferring parts and items, and allows users to take out items only after they have been authenticated.

[0216] The "server" is a computer system that manages the autonomous mobile cleaning devices and the parts supply robots in an integrated manner, and processes user requests and creates and adjusts schedules.

[0217] This invention relates to a factory system that comprehensively manages autonomous mobile cleaning devices and parts supply robots. This system efficiently manages cleaning and parts supply within a factory and can respond to user requests in real time.

[0218] System Overview

[0219] This system consists of a server, autonomous mobile cleaning devices, parts supply robots, item storage devices, authentication devices, and client terminals. The server collects operational information from each device and generates optimal cleaning and supply schedules. The server also receives requests from users through communication with the client terminals and adjusts the schedules in real time.

[0220] Hardware and software used

[0221] The autonomous cleaning mobile devices and parts supply robots operate primarily using sensor technology and AI algorithms.

[0222] The server uses a programming language such as Python and a database management system such as SQLite.

[0223] Smartphones, tablets, personal computers, etc. are used as client terminals, and applications or browser-based systems are implemented as user interfaces.

[0224] The authentication device uses facial recognition technology and incorporates a camera and facial recognition algorithms.

[0225] How it works

[0226] 1. The server collects and analyzes operational information sent from the autonomous cleaning devices and the parts supply robots to generate an optimal schedule. The server calculates the schedule based on environmental information from sensors and the current work status, and sets the schedule to ensure efficient cleaning and parts supply.

[0227] 2. Users using client devices can request schedule changes via a smartphone app or tablet. The user's request is sent to the server and processed in real time. For example, if a user requests "Please change the cleaning schedule," the server generates a new schedule based on the current schedule and sensor data and sends instructions to the autonomous mobile cleaning device.

[0228] 3. The item storage device is used by the user to receive parts or items using an authentication device. Once the user is authenticated by facial recognition, the item storage device is unlocked and the parts are handed over. The server processes the authentication information and manages the delivery history.

[0229] Specific examples

[0230] For example, if the user enters the following prompt:

[0231] "Please change the morning cleaning schedule to 1pm."

[0232] "Please provide parts to Section B."

[0233] These requests are sent from the client terminals and processed by the server, which then generates a new schedule and sends instructions to the autonomous mobile cleaning devices and the parts supply robots based on the schedule, thereby improving the overall operational efficiency within the factory.

[0234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0235] Step 1:

[0236] The server collects operation information from the autonomous mobile cleaning device and the part supply robot.

[0237] Input: Operation information from the autonomous mobile cleaning device and the parts supply robot (current work status, location information, sensor information, etc.).

[0238] Data processing: The server analyzes the operational information and stores it in a database. Specifically, it organizes and classifies the information using an SQLite database.

[0239] Output: Operational information stored in a database.

[0240] Step 2:

[0241] The server generates optimal cleaning and supply schedules based on the collected operational information.

[0242] Input: Operation information of the autonomous mobile cleaning device and the parts supply robot stored in the database.

[0243] Data calculation: Using Python AI algorithms, the system analyzes operational information and generates an efficient schedule, taking into account each robot's operating time, travel time, and work time.

[0244] Output: Optimal cleaning and feeding schedules.

[0245] Step 3:

[0246] The server controls the autonomous mobile cleaning device and the part supply robot according to the generated schedule.

[0247] Input: Optimal cleaning and supply schedules.

[0248] Data processing: The generated schedule is sent as instructions to each robot to execute it. The instructions are sent via the network using protocols such as TCP / IP.

[0249] Output: Instructions for executing the autonomous mobile cleaning device and the parts supply robot.

[0250] Step 4:

[0251] A user uses a client terminal to send a request to a server.

[0252] Input: User request (e.g. "Please change my cleaning schedule").

[0253] Data processing: The request content is sent to the server in JSON format. The request content is entered through the terminal interface.

[0254] Output: The request data sent to the server.

[0255] Step 5:

[0256] The server adjusts the schedule in real time based on requests from users.

[0257] Input: Request data sent by the user, as well as current schedule and sensor data.

[0258] Data calculation: Recalculate and optimize new schedules using AI algorithms. Real-time schedule recalculation using Python.

[0259] Output: The new optimal schedule.

[0260] Step 6:

[0261] The server notifies the user of the new schedule and obtains confirmation.

[0262] Input: The new optimal schedule.

[0263] Data processing: Send the new schedule to the client terminal and display it to the user. Send data via TCP / IP protocol.

[0264] Output: The new schedule displayed on the client terminal.

[0265] Step 7:

[0266] The user confirms the new schedule and sends a notification of approval to the server.

[0267] Input: User confirmation and approval operation.

[0268] Data processing: Pressing the approval button sends the data to the server.

[0269] Output: The authorization data sent to the server.

[0270] Step 8:

[0271] The server notifies each autonomous mobile cleaning device and each part supply robot of the new schedule and causes them to start executing.

[0272] Input: Approval data for the new schedule.

[0273] Data processing: Based on the approved data, the final schedule is sent to each robot and instructions are given to execute it.

[0274] Output: New schedule instructions sent to each robot.

[0275] 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.

[0276] The present invention relates to a system comprising an autonomous mobile cleaning device, an item storage device, an emotion engine, and a server and client terminals that control these. Specific embodiments of this system will be described below.

[0277] System Overview

[0278] This system consists of an autonomous mobile cleaning device, an item storage device, a server, an emotion engine, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device through which users receive deliveries and authenticates users using facial recognition technology. The emotion engine acquires and analyzes user emotion data and adjusts the operation of each device based on that information. The server manages and controls each of these devices in an integrated manner, adjusting their operation in response to user requests.

[0279] Operation of the autonomous mobile cleaning device

[0280] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on this information. The emotion engine can also obtain user emotion data and adjust a new schedule based on that data. If a schedule adjustment is necessary, the server receives a request from the user's client terminal and updates the schedule in real time.

[0281] Operation of the article storage device

[0282] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotion data and can control the device to respond quickly, for example, depending on a specific emotional state. The server processes the authentication information sent from the item storage device and sends the authentication results to the item storage device.

[0283] Processing user requests

[0284] When a user sends a request via a client terminal regarding a change in cleaning schedule or delivery pickup, the server receives the request and performs the necessary processing. For example, if a user requests a change in cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[0285] Specific examples

[0286] For example, if a user requests a change in cleaning schedule to accommodate a busy time, the emotion engine analyzes the user's emotion data and detects that the user's stress level is high. In this case, the following process is performed:

[0287] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[0288] 2. The device sends the request to the server.

[0289] 3. The emotion engine acquires the user's emotional data and analyzes stress levels, etc.

[0290] 4. The server receives the request and retrieves and analyzes the current cleaning schedule, the latest sensor data, and data from the emotion engine from the database.

[0291] 5. The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[0292] 6. The server sends the new cleaning schedule to the terminal and displays the new schedule to the user.

[0293] 7. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[0294] 8. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[0295] Similarly, when a user receives a parcel from an item storage device, the emotion engine functions as follows.

[0296] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[0297] 2. The terminal (item storage device) sends the facial recognition data to the server.

[0298] 3. The server analyzes the facial recognition data and determines that the authentication was successful.

[0299] 4. The server records the fact that the parcel has been stored in the database and sends a notification of the parcel's arrival to the corresponding user.

[0300] 5. The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to that state.

[0301] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[0302] 7. The terminal (item storage device) sends the user's facial authentication data to the server.

[0303] 8. The server analyzes the user's facial recognition data and compares it with database information.

[0304] 9. The server notifies the terminal (item storage device) that the authentication was successful.

[0305] 10. The terminal (item storage device) unlocks the device based on the authentication result.

[0306] 11. The user removes the parcel from the item storage device.

[0307] 12. The server records in the database that the parcel has been picked up and sends a notification to the user that the process is complete.

[0308] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, significantly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[0309] The processing flow will be explained below.

[0310] Changes to cleaning schedules

[0311] Step 1:

[0312] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[0313] Step 2:

[0314] The device (smartphone app) sends the request to the server.

[0315] Step 3:

[0316] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[0317] Step 4:

[0318] The emotion engine acquires the user's emotional data and analyzes the user's stress level and satisfaction.

[0319] Step 5:

[0320] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule, sensor data, and analytical data from the emotion engine.

[0321] Step 6:

[0322] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[0323] Step 7:

[0324] The user checks the new schedule and presses the approval button.

[0325] Step 8:

[0326] The device (smartphone app) sends the approval information to the server.

[0327] Step 9:

[0328] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[0329] Step 10:

[0330] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[0331] Receiving parcels

[0332] Step 1:

[0333] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[0334] Step 2:

[0335] The terminal (item storage device) transmits the facial authentication data to the server.

[0336] Step 3:

[0337] The server analyzes the facial recognition data and determines that the authentication was successful.

[0338] Step 4:

[0339] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[0340] Step 5:

[0341] The emotion engine acquires the user's emotional data and analyzes the user's stress level and expectations.

[0342] Step 6:

[0343] The user arrives at the item storage device and holds their face up to the face authentication camera.

[0344] Step 7:

[0345] The terminal (item storage device) transmits the user's facial authentication data to the server.

[0346] Step 8:

[0347] The server analyzes the user's facial recognition data and compares it with database information.

[0348] Step 9:

[0349] The server notifies the terminal (item storage device) that the authentication was successful.

[0350] Step 10:

[0351] The terminal (item storage device) unlocks the door based on the authentication result.

[0352] Step 11:

[0353] The user removes the parcel from the item storage device.

[0354] Step 12:

[0355] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[0356] Step 13:

[0357] The emotion engine collects the user's emotional data again after receiving the parcel and analyzes the user's satisfaction level.

[0358] The above are the specific processing steps for changing the cleaning schedule and receiving deliveries in a system that combines an emotion engine. This section describes in detail how the server, terminal, and user operate at each step.

[0359] Example 2

[0360] 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."

[0361] In order to efficiently carry out cleaning work and deliver goods, appropriate schedule management and user authentication are necessary, but conventional systems have difficulty responding flexibly to the user's emotional state. Furthermore, the lack of utilization of emotional data has made it difficult to improve the user experience. This has led to concerns that schedule changes and authentication processes cannot be quickly implemented, especially in stressful situations, leading to a decline in user satisfaction.

[0362] 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.

[0363] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to provide a system that can optimize the cleaning schedule and the operation of item storage devices based on user emotion data and respond efficiently and flexibly.

[0364] An "autonomous mobile cleaning device" is a mobile robot that automatically performs cleaning tasks in buildings and other facilities, and operates using sensor technology and AI.

[0365] "Operation information" is information relating to the current position, operation status, cleaning progress, etc. of the autonomous mobile cleaning device.

[0366] A "cleaning schedule" is a plan for an autonomous mobile cleaning device to clean a specific area during a specific time period.

[0367] A "server" is a computing device that exchanges instructions and data with client terminals via communication and comprehensively manages and controls the operation of the autonomous mobile cleaning device and the item storage device.

[0368] A "client terminal" is a device operated by a user, including a smartphone, tablet, or PC, that communicates with a server to make requests and obtain information.

[0369] A "request" is an operation request or instruction that a user sends to the server via a client terminal, such as a request to change a cleaning schedule or receive an item.

[0370] "Emotional data" refers to data that indicates the user's psychological and physiological state, including stress levels and emotional states.

[0371] An "item storage device" is a storage device for users to receive parcels, and is a device that authenticates users using facial recognition technology and the like and safely delivers items.

[0372] "Authentication information" refers to information used by a user to access an item storage unit or other device, and may include facial recognition data.

[0373] An "authentication device" is a device that combines hardware and software to obtain user authentication information and perform authentication.

[0374] A "database" is a data storage location for systematically storing and managing various data handled within a system.

[0375] The present invention relates to an autonomous mobile cleaning system and an item storage system. Detailed embodiments for implementing the system will be described below.

[0376] System configuration

[0377] The system mainly consists of the following components:

[0378] 1. Autonomous Cleaning Vehicle - A robot that automatically performs cleaning tasks within a building and operates using sensor technology and AI.

[0379] 2. Item storage device - A device that allows users to receive parcels, and uses facial recognition technology for authentication.

[0380] 3. Server - Integrated management and control of autonomous mobile cleaning devices, item storage devices, and user client terminals.

[0381] 4. Emotion Engine - Captures and analyzes user emotional data and adjusts system behavior based on that information.

[0382] 5. Client terminal - A device operated by a user, including a smartphone, tablet, or PC.

[0383] Operation of the autonomous mobile cleaning device

[0384] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The cleaning schedule is sent from the server to the autonomous mobile cleaning devices, and the devices perform cleaning in accordance with the schedule. The emotion engine also acquires user emotion data and can adjust a new schedule based on that data. When a user requests a change to the cleaning schedule from a client terminal, the server adjusts the schedule in real time and notifies the autonomous mobile cleaning devices.

[0385] Operation of the article storage device

[0386] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotional data and responds quickly to specific emotional states. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[0387] Processing user requests

[0388] When a user sends a request via a client terminal to change the cleaning schedule or receive a package, the server receives the request and performs the necessary processing. For example, if a user requests a change to the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[0389] Specific examples

[0390] For example, if a user wants to change the cleaning schedule during a busy time, the following process occurs:

[0391] 1. The user requests a "change in cleaning schedule" from the AI ​​chatbot via a client device (e.g., a smartphone app).

[0392] Example prompt: "I'd like to change the cleaning schedule. It's difficult to clean at this time, so could you please do it later?"

[0393] 2. The client terminal sends the request to the server.

[0394] 3. The emotion engine collects the user's emotional data and analyzes their stress level.

[0395] 4. The server receives the request and generates a new schedule based on the current cleaning schedule and the latest sensor information.

[0396] 5. The server sends the new cleaning schedule to the client terminal and displays it to the user.

[0397] 6. Once the user approves the new schedule, the information is sent to the server.

[0398] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning according to the schedule.

[0399] Similarly, when a user receives a parcel from an item storage device, the following process occurs:

[0400] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[0401] 2. The item storage device sends the facial recognition data to the server.

[0402] 3. The server analyzes the facial recognition data and determines whether authentication was successful.

[0403] 4. The server notifies the user that the parcel has been stored.

[0404] Example prompt: "Please let me know that I have a parcel. I'm busy at work, so I'll come and get it later."

[0405] 5. The emotion engine analyzes the user's emotional data and adjusts its behavior.

[0406] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[0407] 7. The item storage device sends the facial recognition data to the server.

[0408] 8. The server confirms successful authentication and sends an unlock command to the item storage device.

[0409] 9. The item storage device unlocks and the user receives the delivery.

[0410] 10. The server records the completion of receipt in the database and notifies the user.

[0411] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[0412] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0413] Processing steps of the autonomous mobile cleaning device

[0414] Step 1:

[0415] The user requests a "change in cleaning schedule" from the AI ​​chatbot on the client device.

[0416] Specific action: Open the smartphone app and send a message to the chatbot saying, "Please change the cleaning schedule to one hour from now."

[0417] Input: User request

[0418] Output: The data sent to the terminal by the request statement.

[0419] Step 2:

[0420] The terminal sends the user's request to the server.

[0421] Specific operation: The client terminal creates an HTTP request and sends it to the server.

[0422] Input: User request

[0423] Output: The request data sent to the server

[0424] Step 3:

[0425] The emotion engine acquires the user's emotional data and analyzes their stress level.

[0426] What it does: The emotion engine uses the user's past behavioral history and current state (e.g., heart rate, facial recognition data) to assess stress levels.

[0427] Input: User's physiological data and behavioral history

[0428] Output: Stress level evaluation result

[0429] Step 4:

[0430] The server receives the request, retrieves the current cleaning schedule and the latest sensor information, and analyzes it.

[0431] Specific operation: The server obtains the current schedule and sensor information of the autonomous cleaning mobile device from the database.

[0432] Input: User request data, current cleaning schedule, sensor information

[0433] Output: Complete set of data required for schedule recalculation

[0434] Step 5:

[0435] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[0436] Specific operation: The schedule is recalculated and generated using a machine learning model based on the data collected by the server.

[0437] Input: Current schedule, sensor information, user emotion data

[0438] Output: New cleaning schedule

[0439] Step 6:

[0440] The server sends the new cleaning schedule to the terminal and displays it to the user.

[0441] Specific operation: The server returns new schedule data in an HTTP response, and the terminal displays this in a GUI.

[0442] Input: New cleaning schedule

[0443] Output: GUI display data on the terminal

[0444] Step 7:

[0445] When the user checks the new schedule and presses the approval button, the information is sent to the server.

[0446] Specific operation: The user taps the confirmation button on their smartphone, and the approval data is sent to the server.

[0447] Input: User approval operation data

[0448] Output: Authorization data sent to the server

[0449] Step 8:

[0450] The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning.

[0451] Specific operation: The server transmits a new schedule to the autonomous mobile cleaning device, and the device starts operating based on the schedule.

[0452] Input: New cleaning schedule

[0453] Output: Autonomous cleaning device begins operation

[0454] Processing steps of the article storage device

[0455] Step 1:

[0456] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[0457] Specific actions: The delivery person stands in front of the facial recognition camera and faces forward.

[0458] Input: Delivery person's facial data

[0459] Output: Storage reception data for storage device

[0460] Step 2:

[0461] The item storage device (terminal) transmits the facial authentication data to the server.

[0462] Specific operation: Facial recognition data is packaged into packets and sent to the server.

[0463] Input: Delivery person's facial recognition data

[0464] Output: Facial recognition data sent to the server

[0465] Step 3:

[0466] The server analyzes the facial recognition data and determines that the authentication was successful.

[0467] Specific operation: The server uses an AI algorithm to compare the facial recognition data with database information and determine the authentication result.

[0468] Input: Facial recognition data, database information

[0469] Output: Authentication result

[0470] Step 4:

[0471] The server records in a database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[0472] Specific operation: The server updates the database and sends a push notification to the user device.

[0473] Input: Delivery storage completion data, corresponding user information

[0474] Output: Push notification data

[0475] Step 5:

[0476] The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to the user's emotion state.

[0477] Specific behavior: The emotion engine detects the user's emotional state and sets behavior parameters.

[0478] Input: User emotion data

[0479] Output: Operating parameters

[0480] Step 6:

[0481] The user arrives at the item storage device and holds their face up to the face authentication camera.

[0482] Specific actions: Stand in front of the item storage device and hold your face towards the camera.

[0483] Input: User's face data

[0484] Output: Authentication request data

[0485] Step 7:

[0486] The item storage device (terminal) transmits the user's facial authentication data to the server.

[0487] Specific operation: Sends authentication data to the server.

[0488] Input: Facial recognition data

[0489] Output: Authentication data sent to the server

[0490] Step 8:

[0491] The server analyzes the facial recognition data and compares it with database information.

[0492] Specific operation: The server uses an AI algorithm to match the facial recognition data and generate a recognition result.

[0493] Input: Authentication data, database information

[0494] Output: Authentication result

[0495] Step 9:

[0496] The server notifies the item storage device (terminal) that the authentication was successful.

[0497] Specific operation: Send an authentication success message to the item storage device.

[0498] Input: Authentication result

[0499] Output: Unlock instruction data for the item storage device

[0500] Step 10:

[0501] The item storage device (terminal) unlocks the device based on the authentication result.

[0502] Specific operation: Activates the unlocking mechanism and releases the locked state.

[0503] Input: Unlock instruction data

[0504] Output: Unlocked

[0505] Step 11:

[0506] The user removes the parcel from the item storage device.

[0507] Specific operation: After unlocking, open the storage device and remove the parcel.

[0508] Input: Unlocked containment device

[0509] Output: Retrieved parcel

[0510] Step 12:

[0511] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[0512] Specific operation: A receipt completion message is sent to the user's device via push notification.

[0513] Input: Data extracted

[0514] Output: Push notification data

[0515] (Application example 2)

[0516] 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."

[0517] Modern brick-and-mortar stores require improved efficiency and security in cleaning and item pickup. However, these tasks still require a large amount of labor, and providing services that take into account the emotional state of users is difficult. Especially during stressful times, more flexible and prompt responses are needed to improve user satisfaction.

[0518] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0519] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to adjust the operation of the entire system based on user emotion data and provide flexible and efficient cleaning work and item collection.

[0520] An "autonomous mobile cleaning device" is a machine that uses sensor technology and artificial intelligence to autonomously move around inside buildings and brick-and-mortar stores and clean.

[0521] The "cleaning schedule" is a timetable or schedule information that plans which areas an autonomous mobile cleaning device will clean at which times.

[0522] A "client terminal" is a communication device used by a user, such as a smartphone, tablet, or PC, that communicates with a server to send requests and receive information.

[0523] An "item storage device" is a device that stores parcels and purchased items and allows users to receive items using authentication technology such as facial recognition.

[0524] An "authentication device" is a device for obtaining user authentication information, and includes, for example, a camera or sensor for identifying a user using facial recognition technology.

[0525] An "emotion engine" is software or a system that acquires and analyzes the user's emotional data and adjusts the operation of each device based on the results.

[0526] "User emotion data" is data that indicates the user's emotional state (for example, joy, anger, sadness, stress, etc.) based on information acquired from the user's facial expressions, voice, behavior, etc.

[0527] A "server" is a computer system that manages and controls data sent from multiple devices and terminals in an integrated manner and performs the necessary processing.

[0528] System configuration

[0529] The present invention is an integrated system consisting of the following elements:

[0530] 1. Autonomous mobile cleaning device: A device that combines sensor technology and artificial intelligence to move autonomously and clean buildings or physical stores.

[0531] 2. Item storage device: A device that stores parcels and purchased items and allows users to receive them using authentication technology such as facial recognition.

[0532] 3. Server: A computer system that centrally manages and controls data from each device and terminal and performs the necessary processing.

[0533] 4. Emotion engine: Software or a system that acquires and analyzes user emotional data and adjusts the behavior of each device based on the results.

[0534] 5. Client terminal: A communication device used by a user, such as a smartphone, tablet, or PC, that communicates with the server and sends and receives requests.

[0535] System Operation

[0536] The overall system operates as follows.

[0537] First, the autonomous mobile cleaning device uses sensor technology and artificial intelligence to detect its surrounding environment and autonomously move around buildings and physical stores to clean. Operational information is sent to a server, which generates an optimal cleaning schedule. Users can request changes to the cleaning schedule via their client device, and the server adjusts the schedule in real time if requested. Furthermore, an emotion engine analyzes the user's emotional data and optimizes the cleaning schedule and item handover behavior based on the user's specific emotional state.

[0538] Next, during the process of receiving a parcel or purchased item from the item storage device, the user's authentication information is acquired by an authentication device (such as a facial recognition camera). If authentication is successful, the item storage device is unlocked and the user can receive the item. At this time, the emotion engine analyzes the user's emotional state and adjusts its behavior to respond quickly if the user's stress level is high.

[0539] Hardware and software used

[0540] The specific hardware and software used to implement the present invention are described below.

[0541] Hardware: Facial recognition cameras (e.g., high-resolution cameras), autonomous mobile cleaning devices (e.g., high-performance robots), and storage devices (e.g., smart lockers)

[0542] Software: Emotion data analysis API (e.g., advanced electronic data analysis platform), facial recognition software (e.g., image processing library), data management server (e.g., distributed computing platform)

[0543] Examples and prompts

[0544] For example, if a user wishes to change their cleaning schedule, the following process takes place: When the user requests a "change in cleaning schedule" from the client terminal to the AI ​​chatbot, the request is sent to the server. The emotion engine analyzes the user's emotional data and determines their stress level. The server generates a new, optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine, and displays it to the user. If the user approves the new schedule, the server notifies the autonomous mobile cleaning device of the new schedule.

[0545] Prompt Sentence Examples

[0546] "Design a system that dynamically changes the schedule of a cleaning robot based on user emotional data. Also, create a program for a system that implements facial recognition functionality for an item storage device and processes handovers according to the customer's emotional state."

[0547] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0548] Step 1:

[0549] The user requests a "change in cleaning schedule" from the client device to the AI ​​chatbot.

[0550] Input: User input request

[0551] Output: Request content

[0552] Specific operation: The user opens the smartphone app and enters the desired change to the cleaning schedule into the chatbot via text.

[0553] Step 2:

[0554] The terminal transmits the request content to the server.

[0555] Input: Request content

[0556] Output: Request data sent to the server

[0557] Specific operation: The client terminal converts the request content into JSON format and sends it as an HTTP request to the server's API endpoint.

[0558] Step 3:

[0559] The server receives the request and the emotion engine retrieves the user's emotion data and analyzes their emotional state, including stress level.

[0560] Input: Request data, user emotion data

[0561] Output: Emotional state

[0562] Specific operation: The server calls the emotion data analysis API to obtain the user's emotion data, and analyzes the data to determine the stress level and emotional state.

[0563] Step 4:

[0564] The server generates a new optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine.

[0565] Inputs: Current cleaning schedule, latest sensor data, emotion engine data

[0566] Output: New cleaning schedule

[0567] Specific operation: The server retrieves the current cleaning schedule and sensor data from the database, combines it with data from the emotion engine, and uses an optimization algorithm to calculate a new cleaning schedule.

[0568] Step 5:

[0569] The server sends the new cleaning schedule to the client terminal and displays the new schedule to the user.

[0570] Input: New cleaning schedule

[0571] Output: The new schedule as displayed to the user

[0572] Specific operation: The server converts the new cleaning schedule into JSON format and sends it to the client device as an HTTP response. The client device displays the new schedule.

[0573] Step 6:

[0574] When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[0575] Input: User approval

[0576] Output: Authorization information sent to the server

[0577] Specific operation: When the user presses the confirmation button on the client terminal, approval information is sent to the server's API endpoint as an HTTP request.

[0578] Step 7:

[0579] The server notifies the autonomous mobile cleaning device of the new schedule.

[0580] Input: Approved new schedule

[0581] Output: Instructions to the autonomous cleaning device

[0582] Specific operation: The server sends the approved new schedule to the control system of the autonomous mobile cleaning device, causing it to execute the instructions.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] [Second embodiment]

[0587] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0588] 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.

[0589] 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).

[0590] 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.

[0591] 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.

[0592] 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).

[0593] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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."

[0599] The present invention relates to a system including an autonomous mobile cleaning device, an item storage device, and a server and client terminals that control these devices. Specific embodiments of this system will be described below.

[0600] System Overview

[0601] This system consists of an autonomous mobile cleaning device, an item storage device, a server, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device that allows users to receive deliveries and authenticates users using facial recognition technology. The server manages and controls these devices in an integrated manner, adjusting their operation in response to user requests.

[0602] Operation of the autonomous mobile cleaning device

[0603] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on it. If the schedule needs to be adjusted, the server receives a request from the user's client terminal and updates the schedule in real time.

[0604] Operation of the article storage device

[0605] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If the authentication is successful, the item storage device unlocks and the user can collect the parcel. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[0606] Processing user requests

[0607] When a user sends a request for changing the cleaning schedule or receiving a parcel via a client terminal, the server receives the request and performs the necessary processing. For example, if a user requests a change in the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device.

[0608] Specific examples

[0609] For example, if a user wishes to change the cleaning schedule, the following process is performed.

[0610] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[0611] 2. The device sends the request to the server.

[0612] 3. The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database for analysis.

[0613] 4. The server uses AI algorithms to calculate and generate a new optimal schedule.

[0614] 5. The server sends the new cleaning schedule to the terminal and displays it to the user.

[0615] 6. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[0616] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[0617] Similarly, the system also automates and efficiently manages the collection of parcels from the item storage device.

[0618] The above is a specific embodiment of the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security.

[0619] The processing flow will be explained below.

[0620] Changes to cleaning schedules

[0621] Step 1:

[0622] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[0623] Step 2:

[0624] The device (smartphone app) sends the request to the server.

[0625] Step 3:

[0626] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[0627] Step 4:

[0628] The server uses an AI algorithm to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule and sensor data.

[0629] Step 5:

[0630] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[0631] Step 6:

[0632] The user checks the new schedule and presses the approval button.

[0633] Step 7:

[0634] The device (smartphone app) sends the approval information to the server.

[0635] Step 8:

[0636] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[0637] Step 9:

[0638] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[0639] Receiving parcels

[0640] Step 1:

[0641] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[0642] Step 2:

[0643] The terminal (item storage device) transmits the facial authentication data to the server.

[0644] Step 3:

[0645] The server analyzes the facial recognition data and determines that the authentication was successful.

[0646] Step 4:

[0647] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[0648] Step 5:

[0649] The user arrives at the item storage device and holds their face up to the face authentication camera.

[0650] Step 6:

[0651] The terminal (item storage device) transmits the user's facial authentication data to the server.

[0652] Step 7:

[0653] The server analyzes the user's facial recognition data and compares it with database information.

[0654] Step 8:

[0655] The server notifies the terminal (item storage device) that the authentication was successful.

[0656] Step 9:

[0657] The terminal (item storage device) unlocks the door based on the authentication result.

[0658] Step 10:

[0659] The user removes the parcel from the item storage device.

[0660] Step 11:

[0661] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[0662] Example 1

[0663] 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."

[0664] To efficiently and effectively clean buildings and facilities, it is necessary to optimize cleaning schedules and adjust them in real time. Furthermore, when handing over items, strict user authentication is required, and safe and prompt responses are also required. However, with current systems, it is difficult to centrally manage these requirements, making it difficult to achieve both efficiency and safety.

[0665] 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.

[0666] In this invention, the server includes means for collecting environmental data from a plurality of autonomous mobile cleaning devices and generating an optimal cleaning plan based on the environmental data, means for controlling the plurality of autonomous mobile cleaning devices in accordance with the cleaning plan, and means for receiving requests from users via communication with a terminal and adjusting the cleaning plan in real time based on the requests, thereby enabling efficient operation of cleaning activities and safe delivery of items.

[0667] An "autonomous mobile cleaning device" is a mobile device that automatically cleans buildings and facilities, and operates using sensor technology and AI.

[0668] "Environmental data" refers to information about the surrounding situation and conditions collected by sensors installed on the autonomous cleaning device, including the location of obstacles and the degree of dirt on surfaces.

[0669] "Cleaning Plan" means an optimized cleaning schedule and route that is generated based on collected environmental data.

[0670] "Control" means to instruct a specific action or movement and to supervise or operate a device so that it operates in accordance with that instruction.

[0671] "Terminal" refers to various electronic devices used by users, including smartphones, tablets, computers, etc.

[0672] A "request" refers to a request or wish made by a user to the system, and is a request for a specific operation or change.

[0673] An "item storage device" is a device for safely storing parcels and other items, allowing users to receive them after authentication.

[0674] "Authentication device" refers to equipment used to verify and authenticate a user's personal information, including facial recognition cameras and fingerprint authentication sensors.

[0675] "Authentication information" means information used to verify a user's identity, including facial images and fingerprints.

[0676] "Goods" refers to parcels and other items that are subject to delivery.

[0677] "Data" refers to various information processed and managed by the system, including environmental data, certification information, cleaning plans, etc.

[0678] The present invention is a system for efficiently managing both cleaning activities and item delivery, and is composed of an autonomous mobile cleaning device, an item storage device, a server, and a user terminal.

[0679] Operation of the autonomous mobile cleaning device

[0680] The server uses AI algorithms to generate an optimal cleaning plan based on environmental data collected from the autonomous cleaning device. This plan is generated by analyzing information obtained from sensors (e.g., LiDAR sensors and cameras) using Python machine learning libraries (e.g., scikit-learn).

[0681] The generated cleaning plan is sent to the autonomous mobile cleaning device via a communication protocol (e.g., MQTT or HTTP). The autonomous mobile cleaning device automatically cleans the building according to this plan. If the cleaning plan needs to be adjusted, the server can receive requests from the user and update the plan in real time.

[0682] Specific examples

[0683] For example, if a user wishes to change the cleaning schedule, the following process is carried out.

[0684] 1. A user requests a change to the cleaning schedule from a chatbot on a smartphone app.

[0685] 2. The device sends the request to the server.

[0686] 3. The server receives the request and generates a new, optimal plan based on the latest environmental data and the current cleaning plan.

[0687] 4. The server sends the new plan to the terminal and presents it to the user.

[0688] 5. Once the user approves the new plan, the information is sent to the server.

[0689] 6. The server notifies the autonomous mobile cleaning device of the final new plan, and the device operates according to the plan.

[0690] Operation of the article storage device

[0691] The storage device stores parcels and uses facial recognition technology to authenticate users when they come to collect them, using image processing engines such as OpenCV and Google FaceNet.

[0692] The operation of the article storage device is as follows.

[0693] 1. The user approaches the item storage device, faces the camera, and attempts authentication.

[0694] 2. The item storage device sends the captured facial image to the server.

[0695] 3. The server checks the database and determines whether the authentication is successful.

[0696] 4. If the authentication is successful, the information is sent to the item storage device and the device is unlocked.

[0697] 5. The user can retrieve the parcel.

[0698] Specific examples

[0699] For example, when a user receives a parcel, the following process is carried out.

[0700] 1. The user stands in front of the item storage device and undergoes facial authentication.

[0701] 2. The item storage device recognizes the face and sends the data to the server.

[0702] 3. The server performs authentication, and if successful, sends an unlock command to the item storage device.

[0703] 4. The item storage device is unlocked and the user receives the parcel.

[0704] Example prompts for generative AI models

[0705] "I would like to change the cleaning schedule. What is the current schedule?"

[0706] "I'd like the cleaning completed by this morning. Please reschedule."

[0707] "I would like to receive a parcel, but I would like to use facial recognition."

[0708] The above is a specific embodiment for carrying out the present invention. This system ensures the efficiency of cleaning activities and the safety of item delivery, and can provide a convenient environment for users.

[0709] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0710] Step 1:

[0711] Sensor information collection

[0712] Input: Environmental data from sensors (e.g. LiDAR sensors, cameras)

[0713] Output: Environment data sent to the server

[0714] Specific behavior:

[0715] The autonomous mobile cleaning device uses sensors to acquire real-time environmental data, such as surrounding obstacles and dirt levels, and this data is sent to a server via communication methods such as Wi-Fi or Bluetooth.

[0716] Step 2:

[0717] Generate a cleaning plan

[0718] Input: Environmental data stored on the server

[0719] Output: The generated cleaning plan

[0720] Specific behavior:

[0721] The server uses AI algorithms to generate an optimal cleaning plan based on the received environmental data, using Python machine learning libraries (e.g., scikit-learn) to calculate the optimal route and time schedule for each autonomous cleaning device.

[0722] Step 3:

[0723] Submit a cleaning plan

[0724] Input: Generated cleaning plan

[0725] Output: Cleaning plan sent to the autonomous cleaning device

[0726] Specific behavior:

[0727] The server sends the generated cleaning plan to the autonomous mobile cleaning device using a communication protocol (e.g., MQTT, HTTP). The device follows the received plan and begins cleaning according to the specified route and time schedule.

[0728] Step 4:

[0729] Receiving a user request

[0730] Input: User request (e.g., cleaning schedule change)

[0731] Output: Request sent to the server

[0732] Specific behavior:

[0733] A user uses a client terminal to input a request to change the cleaning schedule. The terminal sends this request to the server, which may include a prompt such as "Please start cleaning at 3 PM."

[0734] Step 5:

[0735] Generate a new cleaning plan

[0736] Input: User request, latest environmental data

[0737] Output: New cleaning plan

[0738] Specific behavior:

[0739] The server receives the user's request and generates a new cleaning plan using AI algorithms based on the latest environmental data, again using Python machine learning libraries (e.g., scikit-learn) to perform the calculations.

[0740] Step 6:

[0741] Submit a new cleaning plan

[0742] Input: A newly generated cleaning plan

[0743] Output: New cleaning plan sent to the autonomous cleaning device and the user terminal

[0744] Specific behavior:

[0745] The server sends the new cleaning plan to the terminal and presents it to the user. If the user approves the new plan, the approval information is sent to the server. The server then sends the final new cleaning plan to the autonomous mobile cleaning device, and the device operates based on the plan.

[0746] Step 7:

[0747] Receiving a facial recognition request

[0748] Input: User's face recognition trigger

[0749] Output: Face image data

[0750] Specific behavior:

[0751] When a user approaches an item storage device and attempts facial authentication, the item storage device uses a camera to capture an image of the user's face and transmits the data to a server.

[0752] Step 8:

[0753] Performing face recognition

[0754] Input: Facial image data

[0755] Output: Authentication result

[0756] Specific behavior:

[0757] The server uses a facial recognition algorithm (e.g., OpenCV or Google FaceNet) to match the image with a registered image in a database. If the authentication is successful, the result is sent to the item storage device.

[0758] Step 9:

[0759] Execution of goods delivery

[0760] Input: Authentication success signal

[0761] Output: Unlocked containment unit

[0762] Specific behavior:

[0763] After the item storage device receives the signal of successful authentication, it releases the electromagnetic lock, allowing the user to remove the item from the unlocked device.

[0764] The above are the specific processing steps of the entire system. This system efficiently carries out cleaning activities and item delivery, providing a convenient and safe environment for users.

[0765] (Application example 1)

[0766] 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."

[0767] Currently, efficient management of cleaning and parts supply within factories is carried out manually or through separate systems, making operations cumbersome. Furthermore, robot schedule changes and optimization cannot be performed in real time, which can lead to reduced production efficiency. Furthermore, authentication and management of parts supply are also dependent on human labor, creating security and efficiency challenges.

[0768] 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.

[0769] In this invention, the server includes means for collecting operation information from a plurality of autonomous mobile cleaning devices and part supply robots and generating optimal cleaning and supply schedules based on the operation information, means for controlling the plurality of autonomous mobile cleaning devices and part supply robots in accordance with the cleaning and supply schedules, and means for receiving requests from users via communication with client terminals and adjusting the cleaning and supply schedules in real time based on the requests. This enables integrated management of cleaning and part supply within a factory, and automation improves efficiency and strengthens security.

[0770] An "autonomous mobile cleaning device" is a mobile machine equipped with sensor technology and AI algorithms that autonomously performs cleaning tasks within a factory.

[0771] A "parts supply robot" is an autonomously operating mechanical device that has the function of automatically supplying parts to designated locations.

[0772] "Operation information" is a collection of data including the current working status and position information of the autonomous mobile cleaning device and the parts supply robot, and environmental information obtained from sensors.

[0773] A "cleaning schedule" is a planned work schedule for an autonomous mobile cleaning device to clean a specific location at a specific time.

[0774] A "supply schedule" is a planned work schedule for a parts supply robot to supply parts to a specific location at a specific time.

[0775] A "client terminal" is a communication device such as a smartphone, tablet, or PC that a user uses to send a request.

[0776] An "authentication device" is a device for acquiring authentication information of a user, and is used to verify the identity of the user using facial recognition technology or the like.

[0777] An "item storage device" is a device for storing and transferring parts and items, and allows users to take out items only after they have been authenticated.

[0778] The "server" is a computer system that manages the autonomous mobile cleaning devices and the parts supply robots in an integrated manner, and processes user requests and creates and adjusts schedules.

[0779] This invention relates to a factory system that comprehensively manages autonomous mobile cleaning devices and parts supply robots. This system efficiently manages cleaning and parts supply within a factory and can respond to user requests in real time.

[0780] System Overview

[0781] This system consists of a server, autonomous mobile cleaning devices, parts supply robots, item storage devices, authentication devices, and client terminals. The server collects operational information from each device and generates optimal cleaning and supply schedules. The server also receives requests from users through communication with the client terminals and adjusts the schedules in real time.

[0782] Hardware and software used

[0783] The autonomous cleaning mobile devices and parts supply robots operate primarily using sensor technology and AI algorithms.

[0784] The server uses a programming language such as Python and a database management system such as SQLite.

[0785] Smartphones, tablets, personal computers, etc. are used as client terminals, and applications or browser-based systems are implemented as user interfaces.

[0786] The authentication device uses facial recognition technology and incorporates a camera and facial recognition algorithms.

[0787] How it works

[0788] 1. The server collects and analyzes operational information sent from the autonomous cleaning devices and the parts supply robots to generate an optimal schedule. The server calculates the schedule based on environmental information from sensors and the current work status, and sets the schedule to ensure efficient cleaning and parts supply.

[0789] 2. Users using client devices can request schedule changes via a smartphone app or tablet. The user's request is sent to the server and processed in real time. For example, if a user requests "Please change the cleaning schedule," the server generates a new schedule based on the current schedule and sensor data and sends instructions to the autonomous mobile cleaning device.

[0790] 3. The item storage device is used by the user to receive parts or items using an authentication device. Once the user is authenticated by facial recognition, the item storage device is unlocked and the parts are handed over. The server processes the authentication information and manages the delivery history.

[0791] Specific examples

[0792] For example, if the user enters the following prompt:

[0793] "Please change the morning cleaning schedule to 1pm."

[0794] "Please provide parts to Section B."

[0795] These requests are sent from the client terminals and processed by the server, which then generates a new schedule and sends instructions to the autonomous mobile cleaning devices and the parts supply robots based on the schedule, thereby improving the overall operational efficiency within the factory.

[0796] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0797] Step 1:

[0798] The server collects operation information from the autonomous mobile cleaning device and the part supply robot.

[0799] Input: Operation information from the autonomous mobile cleaning device and the parts supply robot (current work status, location information, sensor information, etc.).

[0800] Data processing: The server analyzes the operational information and stores it in a database. Specifically, it organizes and classifies the information using an SQLite database.

[0801] Output: Operational information stored in a database.

[0802] Step 2:

[0803] The server generates optimal cleaning and supply schedules based on the collected operational information.

[0804] Input: Operation information of the autonomous mobile cleaning device and the parts supply robot stored in the database.

[0805] Data calculation: Using Python AI algorithms, the system analyzes operational information and generates an efficient schedule, taking into account each robot's operating time, travel time, and work time.

[0806] Output: Optimal cleaning and feeding schedules.

[0807] Step 3:

[0808] The server controls the autonomous mobile cleaning device and the part supply robot according to the generated schedule.

[0809] Input: Optimal cleaning and supply schedules.

[0810] Data processing: The generated schedule is sent as instructions to each robot to execute it. The instructions are sent via the network using protocols such as TCP / IP.

[0811] Output: Instructions for executing the autonomous mobile cleaning device and the parts supply robot.

[0812] Step 4:

[0813] A user uses a client terminal to send a request to a server.

[0814] Input: User request (e.g. "Please change my cleaning schedule").

[0815] Data processing: The request content is sent to the server in JSON format. The request content is entered through the terminal interface.

[0816] Output: The request data sent to the server.

[0817] Step 5:

[0818] The server adjusts the schedule in real time based on requests from users.

[0819] Input: Request data sent by the user, as well as current schedule and sensor data.

[0820] Data calculation: Recalculate and optimize new schedules using AI algorithms. Real-time schedule recalculation using Python.

[0821] Output: The new optimal schedule.

[0822] Step 6:

[0823] The server notifies the user of the new schedule and obtains confirmation.

[0824] Input: The new optimal schedule.

[0825] Data processing: Send the new schedule to the client terminal and display it to the user. Send data via TCP / IP protocol.

[0826] Output: The new schedule displayed on the client terminal.

[0827] Step 7:

[0828] The user confirms the new schedule and sends a notification of approval to the server.

[0829] Input: User confirmation and approval operation.

[0830] Data processing: Pressing the approval button sends the data to the server.

[0831] Output: The authorization data sent to the server.

[0832] Step 8:

[0833] The server notifies each autonomous mobile cleaning device and each part supply robot of the new schedule and causes them to start executing.

[0834] Input: Approval data for the new schedule.

[0835] Data processing: Based on the approved data, the final schedule is sent to each robot and instructions are given to execute it.

[0836] Output: New schedule instructions sent to each robot.

[0837] 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.

[0838] The present invention relates to a system comprising an autonomous mobile cleaning device, an item storage device, an emotion engine, and a server and client terminals that control these. Specific embodiments of this system will be described below.

[0839] System Overview

[0840] This system consists of an autonomous mobile cleaning device, an item storage device, a server, an emotion engine, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device through which users receive deliveries and authenticates users using facial recognition technology. The emotion engine acquires and analyzes user emotion data and adjusts the operation of each device based on that information. The server manages and controls each of these devices in an integrated manner, adjusting their operation in response to user requests.

[0841] Operation of the autonomous mobile cleaning device

[0842] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on this information. The emotion engine can also obtain user emotion data and adjust a new schedule based on that data. If a schedule adjustment is necessary, the server receives a request from the user's client terminal and updates the schedule in real time.

[0843] Operation of the article storage device

[0844] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotion data and can control the device to respond quickly, for example, depending on a specific emotional state. The server processes the authentication information sent from the item storage device and sends the authentication results to the item storage device.

[0845] Processing user requests

[0846] When a user sends a request via a client terminal regarding a change in cleaning schedule or delivery pickup, the server receives the request and performs the necessary processing. For example, if a user requests a change in cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[0847] Specific examples

[0848] For example, if a user requests a change in cleaning schedule to accommodate a busy time, the emotion engine analyzes the user's emotion data and detects that the user's stress level is high. In this case, the following process is performed:

[0849] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[0850] 2. The device sends the request to the server.

[0851] 3. The emotion engine acquires the user's emotional data and analyzes stress levels, etc.

[0852] 4. The server receives the request and retrieves and analyzes the current cleaning schedule, the latest sensor data, and data from the emotion engine from the database.

[0853] 5. The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[0854] 6. The server sends the new cleaning schedule to the terminal and displays the new schedule to the user.

[0855] 7. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[0856] 8. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[0857] Similarly, when a user receives a parcel from an item storage device, the emotion engine functions as follows.

[0858] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[0859] 2. The terminal (item storage device) sends the facial recognition data to the server.

[0860] 3. The server analyzes the facial recognition data and determines that the authentication was successful.

[0861] 4. The server records the fact that the parcel has been stored in the database and sends a notification of the parcel's arrival to the corresponding user.

[0862] 5. The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to that state.

[0863] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[0864] 7. The terminal (item storage device) sends the user's facial authentication data to the server.

[0865] 8. The server analyzes the user's facial recognition data and compares it with database information.

[0866] 9. The server notifies the terminal (item storage device) that the authentication was successful.

[0867] 10. The terminal (item storage device) unlocks the device based on the authentication result.

[0868] 11. The user removes the parcel from the item storage device.

[0869] 12. The server records in the database that the parcel has been picked up and sends a notification to the user that the process is complete.

[0870] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, significantly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[0871] The processing flow will be explained below.

[0872] Changes to cleaning schedules

[0873] Step 1:

[0874] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[0875] Step 2:

[0876] The device (smartphone app) sends the request to the server.

[0877] Step 3:

[0878] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[0879] Step 4:

[0880] The emotion engine acquires the user's emotional data and analyzes the user's stress level and satisfaction.

[0881] Step 5:

[0882] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule, sensor data, and analytical data from the emotion engine.

[0883] Step 6:

[0884] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[0885] Step 7:

[0886] The user checks the new schedule and presses the approval button.

[0887] Step 8:

[0888] The device (smartphone app) sends the approval information to the server.

[0889] Step 9:

[0890] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[0891] Step 10:

[0892] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[0893] Receiving parcels

[0894] Step 1:

[0895] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[0896] Step 2:

[0897] The terminal (item storage device) transmits the facial authentication data to the server.

[0898] Step 3:

[0899] The server analyzes the facial recognition data and determines that the authentication was successful.

[0900] Step 4:

[0901] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[0902] Step 5:

[0903] The emotion engine acquires the user's emotional data and analyzes the user's stress level and expectations.

[0904] Step 6:

[0905] The user arrives at the item storage device and holds their face up to the face authentication camera.

[0906] Step 7:

[0907] The terminal (item storage device) transmits the user's facial authentication data to the server.

[0908] Step 8:

[0909] The server analyzes the user's facial recognition data and compares it with database information.

[0910] Step 9:

[0911] The server notifies the terminal (item storage device) that the authentication was successful.

[0912] Step 10:

[0913] The terminal (item storage device) unlocks the door based on the authentication result.

[0914] Step 11:

[0915] The user removes the parcel from the item storage device.

[0916] Step 12:

[0917] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[0918] Step 13:

[0919] The emotion engine collects the user's emotional data again after receiving the parcel and analyzes the user's satisfaction level.

[0920] The above are the specific processing steps for changing the cleaning schedule and receiving deliveries in a system that combines an emotion engine. This section describes in detail how the server, terminal, and user operate at each step.

[0921] Example 2

[0922] 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."

[0923] In order to efficiently carry out cleaning work and deliver goods, appropriate schedule management and user authentication are necessary, but conventional systems have difficulty responding flexibly to the user's emotional state. Furthermore, the lack of utilization of emotional data has made it difficult to improve the user experience. This has led to concerns that schedule changes and authentication processes cannot be quickly implemented, especially in stressful situations, leading to a decline in user satisfaction.

[0924] 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.

[0925] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to provide a system that can optimize the cleaning schedule and the operation of item storage devices based on user emotion data and respond efficiently and flexibly.

[0926] An "autonomous mobile cleaning device" is a mobile robot that automatically performs cleaning tasks in buildings and other facilities, and operates using sensor technology and AI.

[0927] "Operation information" is information relating to the current position, operation status, cleaning progress, etc. of the autonomous mobile cleaning device.

[0928] A "cleaning schedule" is a plan for an autonomous mobile cleaning device to clean a specific area during a specific time period.

[0929] A "server" is a computing device that exchanges instructions and data with client terminals via communication and comprehensively manages and controls the operation of the autonomous mobile cleaning device and the item storage device.

[0930] A "client terminal" is a device operated by a user, including a smartphone, tablet, or PC, that communicates with a server to make requests and obtain information.

[0931] A "request" is an operation request or instruction that a user sends to the server via a client terminal, such as a request to change a cleaning schedule or receive an item.

[0932] "Emotional data" refers to data that indicates the user's psychological and physiological state, including stress levels and emotional states.

[0933] An "item storage device" is a storage device for users to receive parcels, and is a device that authenticates users using facial recognition technology and the like and safely delivers items.

[0934] "Authentication information" refers to information used by a user to access an item storage unit or other device, and may include facial recognition data.

[0935] An "authentication device" is a device that combines hardware and software to obtain user authentication information and perform authentication.

[0936] A "database" is a data storage location for systematically storing and managing various data handled within a system.

[0937] The present invention relates to an autonomous mobile cleaning system and an item storage system. Detailed embodiments for implementing the system will be described below.

[0938] System configuration

[0939] The system mainly consists of the following components:

[0940] 1. Autonomous Cleaning Vehicle - A robot that automatically performs cleaning tasks within a building and operates using sensor technology and AI.

[0941] 2. Item storage device - A device that allows users to receive parcels, and uses facial recognition technology for authentication.

[0942] 3. Server - Integrated management and control of autonomous mobile cleaning devices, item storage devices, and user client terminals.

[0943] 4. Emotion Engine - Captures and analyzes user emotional data and adjusts system behavior based on that information.

[0944] 5. Client terminal - A device operated by a user, including a smartphone, tablet, or PC.

[0945] Operation of the autonomous mobile cleaning device

[0946] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The cleaning schedule is sent from the server to the autonomous mobile cleaning devices, and the devices perform cleaning in accordance with the schedule. The emotion engine also acquires user emotion data and can adjust a new schedule based on that data. When a user requests a change to the cleaning schedule from a client terminal, the server adjusts the schedule in real time and notifies the autonomous mobile cleaning devices.

[0947] Operation of the article storage device

[0948] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotional data and responds quickly to specific emotional states. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[0949] Processing user requests

[0950] When a user sends a request via a client terminal to change the cleaning schedule or receive a package, the server receives the request and performs the necessary processing. For example, if a user requests a change to the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[0951] Specific examples

[0952] For example, if a user wants to change the cleaning schedule during a busy time, the following process occurs:

[0953] 1. The user requests a "change in cleaning schedule" from the AI ​​chatbot via a client device (e.g., a smartphone app).

[0954] Example prompt: "I'd like to change the cleaning schedule. It's difficult to clean at this time, so could you please do it later?"

[0955] 2. The client terminal sends the request to the server.

[0956] 3. The emotion engine collects the user's emotional data and analyzes their stress level.

[0957] 4. The server receives the request and generates a new schedule based on the current cleaning schedule and the latest sensor information.

[0958] 5. The server sends the new cleaning schedule to the client terminal and displays it to the user.

[0959] 6. Once the user approves the new schedule, the information is sent to the server.

[0960] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning according to the schedule.

[0961] Similarly, when a user receives a parcel from an item storage device, the following process occurs:

[0962] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[0963] 2. The item storage device sends the facial recognition data to the server.

[0964] 3. The server analyzes the facial recognition data and determines whether authentication was successful.

[0965] 4. The server notifies the user that the parcel has been stored.

[0966] Example prompt: "Please let me know that I have a parcel. I'm busy at work, so I'll come and get it later."

[0967] 5. The emotion engine analyzes the user's emotional data and adjusts its behavior.

[0968] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[0969] 7. The item storage device sends the facial recognition data to the server.

[0970] 8. The server confirms successful authentication and sends an unlock command to the item storage device.

[0971] 9. The item storage device unlocks and the user receives the delivery.

[0972] 10. The server records the completion of receipt in the database and notifies the user.

[0973] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[0974] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0975] Processing steps of the autonomous mobile cleaning device

[0976] Step 1:

[0977] The user requests a "change in cleaning schedule" from the AI ​​chatbot on the client device.

[0978] Specific action: Open the smartphone app and send a message to the chatbot saying, "Please change the cleaning schedule to one hour from now."

[0979] Input: User request

[0980] Output: The data sent to the terminal by the request statement.

[0981] Step 2:

[0982] The terminal sends the user's request to the server.

[0983] Specific operation: The client terminal creates an HTTP request and sends it to the server.

[0984] Input: User request

[0985] Output: The request data sent to the server

[0986] Step 3:

[0987] The emotion engine acquires the user's emotional data and analyzes their stress level.

[0988] What it does: The emotion engine uses the user's past behavioral history and current state (e.g., heart rate, facial recognition data) to assess stress levels.

[0989] Input: User's physiological data and behavioral history

[0990] Output: Stress level evaluation result

[0991] Step 4:

[0992] The server receives the request, retrieves the current cleaning schedule and the latest sensor information, and analyzes it.

[0993] Specific operation: The server obtains the current schedule and sensor information of the autonomous cleaning mobile device from the database.

[0994] Input: User request data, current cleaning schedule, sensor information

[0995] Output: Complete set of data required for schedule recalculation

[0996] Step 5:

[0997] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[0998] Specific operation: The schedule is recalculated and generated using a machine learning model based on the data collected by the server.

[0999] Input: Current schedule, sensor information, user emotion data

[1000] Output: New cleaning schedule

[1001] Step 6:

[1002] The server sends the new cleaning schedule to the terminal and displays it to the user.

[1003] Specific operation: The server returns new schedule data in an HTTP response, and the terminal displays this in a GUI.

[1004] Input: New cleaning schedule

[1005] Output: GUI display data on the terminal

[1006] Step 7:

[1007] When the user checks the new schedule and presses the approval button, the information is sent to the server.

[1008] Specific operation: The user taps the confirmation button on their smartphone, and the approval data is sent to the server.

[1009] Input: User approval operation data

[1010] Output: Authorization data sent to the server

[1011] Step 8:

[1012] The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning.

[1013] Specific operation: The server transmits a new schedule to the autonomous mobile cleaning device, and the device starts operating based on the schedule.

[1014] Input: New cleaning schedule

[1015] Output: Autonomous cleaning device begins operation

[1016] Processing steps of the article storage device

[1017] Step 1:

[1018] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[1019] Specific actions: The delivery person stands in front of the facial recognition camera and faces forward.

[1020] Input: Delivery person's facial data

[1021] Output: Storage reception data for storage device

[1022] Step 2:

[1023] The item storage device (terminal) transmits the facial authentication data to the server.

[1024] Specific operation: Facial recognition data is packaged into packets and sent to the server.

[1025] Input: Delivery person's facial recognition data

[1026] Output: Facial recognition data sent to the server

[1027] Step 3:

[1028] The server analyzes the facial recognition data and determines that the authentication was successful.

[1029] Specific operation: The server uses an AI algorithm to compare the facial recognition data with database information and determine the authentication result.

[1030] Input: Facial recognition data, database information

[1031] Output: Authentication result

[1032] Step 4:

[1033] The server records in a database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[1034] Specific operation: The server updates the database and sends a push notification to the user device.

[1035] Input: Delivery storage completion data, corresponding user information

[1036] Output: Push notification data

[1037] Step 5:

[1038] The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to the user's emotion state.

[1039] Specific behavior: The emotion engine detects the user's emotional state and sets behavior parameters.

[1040] Input: User emotion data

[1041] Output: Operating parameters

[1042] Step 6:

[1043] The user arrives at the item storage device and holds their face up to the face authentication camera.

[1044] Specific actions: Stand in front of the item storage device and hold your face towards the camera.

[1045] Input: User's face data

[1046] Output: Authentication request data

[1047] Step 7:

[1048] The item storage device (terminal) transmits the user's facial authentication data to the server.

[1049] Specific operation: Sends authentication data to the server.

[1050] Input: Facial recognition data

[1051] Output: Authentication data sent to the server

[1052] Step 8:

[1053] The server analyzes the facial recognition data and compares it with database information.

[1054] Specific operation: The server uses an AI algorithm to match the facial recognition data and generate a recognition result.

[1055] Input: Authentication data, database information

[1056] Output: Authentication result

[1057] Step 9:

[1058] The server notifies the item storage device (terminal) that the authentication was successful.

[1059] Specific operation: Send an authentication success message to the item storage device.

[1060] Input: Authentication result

[1061] Output: Unlock instruction data for the item storage device

[1062] Step 10:

[1063] The item storage device (terminal) unlocks the device based on the authentication result.

[1064] Specific operation: Activates the unlocking mechanism and releases the locked state.

[1065] Input: Unlock instruction data

[1066] Output: Unlocked

[1067] Step 11:

[1068] The user removes the parcel from the item storage device.

[1069] Specific operation: After unlocking, open the storage device and remove the parcel.

[1070] Input: Unlocked containment device

[1071] Output: Retrieved parcel

[1072] Step 12:

[1073] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[1074] Specific operation: A receipt completion message is sent to the user's device via push notification.

[1075] Input: Data extracted

[1076] Output: Push notification data

[1077] (Application example 2)

[1078] 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."

[1079] Modern brick-and-mortar stores require improved efficiency and security in cleaning and item pickup. However, these tasks still require a large amount of labor, and providing services that take into account the emotional state of users is difficult. Especially during stressful times, more flexible and prompt responses are needed to improve user satisfaction.

[1080] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1081] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to adjust the operation of the entire system based on user emotion data and provide flexible and efficient cleaning work and item collection.

[1082] An "autonomous mobile cleaning device" is a machine that uses sensor technology and artificial intelligence to autonomously move around inside buildings and brick-and-mortar stores and clean.

[1083] The "cleaning schedule" is a timetable or schedule information that plans which areas an autonomous mobile cleaning device will clean at which times.

[1084] A "client terminal" is a communication device used by a user, such as a smartphone, tablet, or PC, that communicates with a server to send requests and receive information.

[1085] An "item storage device" is a device that stores parcels and purchased items and allows users to receive items using authentication technology such as facial recognition.

[1086] An "authentication device" is a device for obtaining user authentication information, and includes, for example, a camera or sensor for identifying a user using facial recognition technology.

[1087] An "emotion engine" is software or a system that acquires and analyzes the user's emotional data and adjusts the operation of each device based on the results.

[1088] "User emotion data" is data that indicates the user's emotional state (for example, joy, anger, sadness, stress, etc.) based on information acquired from the user's facial expressions, voice, behavior, etc.

[1089] A "server" is a computer system that manages and controls data sent from multiple devices and terminals in an integrated manner and performs the necessary processing.

[1090] System configuration

[1091] The present invention is an integrated system consisting of the following elements:

[1092] 1. Autonomous mobile cleaning device: A device that combines sensor technology and artificial intelligence to move autonomously and clean buildings or physical stores.

[1093] 2. Item storage device: A device that stores parcels and purchased items and allows users to receive them using authentication technology such as facial recognition.

[1094] 3. Server: A computer system that centrally manages and controls data from each device and terminal and performs the necessary processing.

[1095] 4. Emotion engine: Software or a system that acquires and analyzes user emotional data and adjusts the behavior of each device based on the results.

[1096] 5. Client terminal: A communication device used by a user, such as a smartphone, tablet, or PC, that communicates with the server and sends and receives requests.

[1097] System Operation

[1098] The overall system operates as follows.

[1099] First, the autonomous mobile cleaning device uses sensor technology and artificial intelligence to detect its surrounding environment and autonomously move around buildings and physical stores to clean. Operational information is sent to a server, which generates an optimal cleaning schedule. Users can request changes to the cleaning schedule via their client device, and the server adjusts the schedule in real time if requested. Furthermore, an emotion engine analyzes the user's emotional data and optimizes the cleaning schedule and item handover behavior based on the user's specific emotional state.

[1100] Next, during the process of receiving a parcel or purchased item from the item storage device, the user's authentication information is acquired by an authentication device (such as a facial recognition camera). If authentication is successful, the item storage device is unlocked and the user can receive the item. At this time, the emotion engine analyzes the user's emotional state and adjusts its behavior to respond quickly if the user's stress level is high.

[1101] Hardware and software used

[1102] The specific hardware and software used to implement the present invention are described below.

[1103] Hardware: Facial recognition cameras (e.g., high-resolution cameras), autonomous mobile cleaning devices (e.g., high-performance robots), and storage devices (e.g., smart lockers)

[1104] Software: Emotion data analysis API (e.g., advanced electronic data analysis platform), facial recognition software (e.g., image processing library), data management server (e.g., distributed computing platform)

[1105] Examples and prompts

[1106] For example, if a user wishes to change their cleaning schedule, the following process takes place: When the user requests a "change in cleaning schedule" from the client terminal to the AI ​​chatbot, the request is sent to the server. The emotion engine analyzes the user's emotional data and determines their stress level. The server generates a new, optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine, and displays it to the user. If the user approves the new schedule, the server notifies the autonomous mobile cleaning device of the new schedule.

[1107] Prompt Sentence Examples

[1108] "Design a system that dynamically changes the schedule of a cleaning robot based on user emotional data. Also, create a program for a system that implements facial recognition functionality for an item storage device and processes handovers according to the customer's emotional state."

[1109] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1110] Step 1:

[1111] The user requests a "change in cleaning schedule" from the client device to the AI ​​chatbot.

[1112] Input: User input request

[1113] Output: Request content

[1114] Specific operation: The user opens the smartphone app and enters the desired change to the cleaning schedule into the chatbot via text.

[1115] Step 2:

[1116] The terminal transmits the request content to the server.

[1117] Input: Request content

[1118] Output: Request data sent to the server

[1119] Specific operation: The client terminal converts the request content into JSON format and sends it as an HTTP request to the server's API endpoint.

[1120] Step 3:

[1121] The server receives the request and the emotion engine retrieves the user's emotion data and analyzes their emotional state, including stress level.

[1122] Input: Request data, user emotion data

[1123] Output: Emotional state

[1124] Specific operation: The server calls the emotion data analysis API to obtain the user's emotion data, and analyzes the data to determine the stress level and emotional state.

[1125] Step 4:

[1126] The server generates a new optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine.

[1127] Inputs: Current cleaning schedule, latest sensor data, emotion engine data

[1128] Output: New cleaning schedule

[1129] Specific operation: The server retrieves the current cleaning schedule and sensor data from the database, combines it with data from the emotion engine, and uses an optimization algorithm to calculate a new cleaning schedule.

[1130] Step 5:

[1131] The server sends the new cleaning schedule to the client terminal and displays the new schedule to the user.

[1132] Input: New cleaning schedule

[1133] Output: The new schedule as displayed to the user

[1134] Specific operation: The server converts the new cleaning schedule into JSON format and sends it to the client device as an HTTP response. The client device displays the new schedule.

[1135] Step 6:

[1136] When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[1137] Input: User approval

[1138] Output: Authorization information sent to the server

[1139] Specific operation: When the user presses the confirmation button on the client terminal, approval information is sent to the server's API endpoint as an HTTP request.

[1140] Step 7:

[1141] The server notifies the autonomous mobile cleaning device of the new schedule.

[1142] Input: Approved new schedule

[1143] Output: Instructions to the autonomous cleaning device

[1144] Specific operation: The server sends the approved new schedule to the control system of the autonomous mobile cleaning device, causing it to execute the instructions.

[1145] 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.

[1146] 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.

[1147] 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.

[1148] [Third embodiment]

[1149] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1150] 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.

[1151] 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).

[1152] 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.

[1153] 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.

[1154] 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).

[1155] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1156] 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.

[1157] 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.

[1158] 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.

[1159] 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.

[1160] 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."

[1161] The present invention relates to a system including an autonomous mobile cleaning device, an item storage device, and a server and client terminals that control these devices. Specific embodiments of this system will be described below.

[1162] System Overview

[1163] This system consists of an autonomous mobile cleaning device, an item storage device, a server, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device that allows users to receive deliveries and authenticates users using facial recognition technology. The server manages and controls these devices in an integrated manner, adjusting their operation in response to user requests.

[1164] Operation of the autonomous mobile cleaning device

[1165] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on it. If the schedule needs to be adjusted, the server receives a request from the user's client terminal and updates the schedule in real time.

[1166] Operation of the article storage device

[1167] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If the authentication is successful, the item storage device unlocks and the user can collect the parcel. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[1168] Processing user requests

[1169] When a user sends a request for changing the cleaning schedule or receiving a parcel via a client terminal, the server receives the request and performs the necessary processing. For example, if a user requests a change in the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device.

[1170] Specific examples

[1171] For example, if a user wishes to change the cleaning schedule, the following process is performed.

[1172] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[1173] 2. The device sends the request to the server.

[1174] 3. The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database for analysis.

[1175] 4. The server uses AI algorithms to calculate and generate a new optimal schedule.

[1176] 5. The server sends the new cleaning schedule to the terminal and displays it to the user.

[1177] 6. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[1178] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[1179] Similarly, the system also automates and efficiently manages the collection of parcels from the item storage device.

[1180] The above is a specific embodiment of the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security.

[1181] The processing flow will be explained below.

[1182] Changes to cleaning schedules

[1183] Step 1:

[1184] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[1185] Step 2:

[1186] The device (smartphone app) sends the request to the server.

[1187] Step 3:

[1188] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[1189] Step 4:

[1190] The server uses an AI algorithm to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule and sensor data.

[1191] Step 5:

[1192] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[1193] Step 6:

[1194] The user checks the new schedule and presses the approval button.

[1195] Step 7:

[1196] The device (smartphone app) sends the approval information to the server.

[1197] Step 8:

[1198] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[1199] Step 9:

[1200] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[1201] Receiving parcels

[1202] Step 1:

[1203] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[1204] Step 2:

[1205] The terminal (item storage device) transmits the facial authentication data to the server.

[1206] Step 3:

[1207] The server analyzes the facial recognition data and determines that the authentication was successful.

[1208] Step 4:

[1209] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[1210] Step 5:

[1211] The user arrives at the item storage device and holds their face up to the face authentication camera.

[1212] Step 6:

[1213] The terminal (item storage device) transmits the user's facial authentication data to the server.

[1214] Step 7:

[1215] The server analyzes the user's facial recognition data and compares it with database information.

[1216] Step 8:

[1217] The server notifies the terminal (item storage device) that the authentication was successful.

[1218] Step 9:

[1219] The terminal (item storage device) unlocks the door based on the authentication result.

[1220] Step 10:

[1221] The user removes the parcel from the item storage device.

[1222] Step 11:

[1223] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[1224] Example 1

[1225] 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."

[1226] To efficiently and effectively clean buildings and facilities, it is necessary to optimize cleaning schedules and adjust them in real time. Furthermore, when handing over items, strict user authentication is required, and safe and prompt responses are also required. However, with current systems, it is difficult to centrally manage these requirements, making it difficult to achieve both efficiency and safety.

[1227] 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.

[1228] In this invention, the server includes means for collecting environmental data from a plurality of autonomous mobile cleaning devices and generating an optimal cleaning plan based on the environmental data, means for controlling the plurality of autonomous mobile cleaning devices in accordance with the cleaning plan, and means for receiving requests from users via communication with a terminal and adjusting the cleaning plan in real time based on the requests, thereby enabling efficient operation of cleaning activities and safe delivery of items.

[1229] An "autonomous mobile cleaning device" is a mobile device that automatically cleans buildings and facilities, and operates using sensor technology and AI.

[1230] "Environmental data" refers to information about the surrounding situation and conditions collected by sensors installed on the autonomous cleaning device, including the location of obstacles and the degree of dirt on surfaces.

[1231] "Cleaning Plan" means an optimized cleaning schedule and route that is generated based on collected environmental data.

[1232] "Control" means to instruct a specific action or movement and to supervise or operate a device so that it operates in accordance with that instruction.

[1233] "Terminal" refers to various electronic devices used by users, including smartphones, tablets, computers, etc.

[1234] A "request" refers to a request or wish made by a user to the system, and is a request for a specific operation or change.

[1235] An "item storage device" is a device for safely storing parcels and other items, allowing users to receive them after authentication.

[1236] "Authentication device" refers to equipment used to verify and authenticate a user's personal information, including facial recognition cameras and fingerprint authentication sensors.

[1237] "Authentication information" means information used to verify a user's identity, including facial images and fingerprints.

[1238] "Goods" refers to parcels and other items that are subject to delivery.

[1239] "Data" refers to various information processed and managed by the system, including environmental data, certification information, cleaning plans, etc.

[1240] The present invention is a system for efficiently managing both cleaning activities and item delivery, and is composed of an autonomous mobile cleaning device, an item storage device, a server, and a user terminal.

[1241] Operation of the autonomous mobile cleaning device

[1242] The server uses AI algorithms to generate an optimal cleaning plan based on environmental data collected from the autonomous cleaning device. This plan is generated by analyzing information obtained from sensors (e.g., LiDAR sensors and cameras) using Python machine learning libraries (e.g., scikit-learn).

[1243] The generated cleaning plan is sent to the autonomous mobile cleaning device via a communication protocol (e.g., MQTT or HTTP). The autonomous mobile cleaning device automatically cleans the building according to this plan. If the cleaning plan needs to be adjusted, the server can receive requests from the user and update the plan in real time.

[1244] Specific examples

[1245] For example, if a user wishes to change the cleaning schedule, the following process is carried out.

[1246] 1. A user requests a change to the cleaning schedule from a chatbot on a smartphone app.

[1247] 2. The device sends the request to the server.

[1248] 3. The server receives the request and generates a new, optimal plan based on the latest environmental data and the current cleaning plan.

[1249] 4. The server sends the new plan to the terminal and presents it to the user.

[1250] 5. Once the user approves the new plan, the information is sent to the server.

[1251] 6. The server notifies the autonomous mobile cleaning device of the final new plan, and the device operates according to the plan.

[1252] Operation of the article storage device

[1253] The storage device stores parcels and uses facial recognition technology to authenticate users when they come to collect them, using image processing engines such as OpenCV and Google FaceNet.

[1254] The operation of the article storage device is as follows.

[1255] 1. The user approaches the item storage device, faces the camera, and attempts authentication.

[1256] 2. The item storage device sends the captured facial image to the server.

[1257] 3. The server checks the database and determines whether the authentication is successful.

[1258] 4. If the authentication is successful, the information is sent to the item storage device and the device is unlocked.

[1259] 5. The user can retrieve the parcel.

[1260] Specific examples

[1261] For example, when a user receives a parcel, the following process is carried out.

[1262] 1. The user stands in front of the item storage device and undergoes facial authentication.

[1263] 2. The item storage device recognizes the face and sends the data to the server.

[1264] 3. The server performs authentication, and if successful, sends an unlock command to the item storage device.

[1265] 4. The item storage device is unlocked and the user receives the parcel.

[1266] Example prompts for generative AI models

[1267] "I would like to change the cleaning schedule. What is the current schedule?"

[1268] "I'd like the cleaning completed by this morning. Please reschedule."

[1269] "I would like to receive a parcel, but I would like to use facial recognition."

[1270] The above is a specific embodiment for carrying out the present invention. This system ensures the efficiency of cleaning activities and the safety of item delivery, and can provide a convenient environment for users.

[1271] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1272] Step 1:

[1273] Sensor information collection

[1274] Input: Environmental data from sensors (e.g. LiDAR sensors, cameras)

[1275] Output: Environment data sent to the server

[1276] Specific behavior:

[1277] The autonomous mobile cleaning device uses sensors to acquire real-time environmental data, such as surrounding obstacles and dirt levels, and this data is sent to a server via communication methods such as Wi-Fi or Bluetooth.

[1278] Step 2:

[1279] Generate a cleaning plan

[1280] Input: Environmental data stored on the server

[1281] Output: The generated cleaning plan

[1282] Specific behavior:

[1283] The server uses AI algorithms to generate an optimal cleaning plan based on the received environmental data, using Python machine learning libraries (e.g., scikit-learn) to calculate the optimal route and time schedule for each autonomous cleaning device.

[1284] Step 3:

[1285] Submit a cleaning plan

[1286] Input: Generated cleaning plan

[1287] Output: Cleaning plan sent to the autonomous cleaning device

[1288] Specific behavior:

[1289] The server sends the generated cleaning plan to the autonomous mobile cleaning device using a communication protocol (e.g., MQTT, HTTP). The device follows the received plan and begins cleaning according to the specified route and time schedule.

[1290] Step 4:

[1291] Receiving a user request

[1292] Input: User request (e.g., cleaning schedule change)

[1293] Output: Request sent to the server

[1294] Specific behavior:

[1295] A user uses a client terminal to input a request to change the cleaning schedule. The terminal sends this request to the server, which may include a prompt such as "Please start cleaning at 3 PM."

[1296] Step 5:

[1297] Generate a new cleaning plan

[1298] Input: User request, latest environmental data

[1299] Output: New cleaning plan

[1300] Specific behavior:

[1301] The server receives the user's request and generates a new cleaning plan using AI algorithms based on the latest environmental data, again using Python machine learning libraries (e.g., scikit-learn) to perform the calculations.

[1302] Step 6:

[1303] Submit a new cleaning plan

[1304] Input: A newly generated cleaning plan

[1305] Output: New cleaning plan sent to the autonomous cleaning device and the user terminal

[1306] Specific behavior:

[1307] The server sends the new cleaning plan to the terminal and presents it to the user. If the user approves the new plan, the approval information is sent to the server. The server then sends the final new cleaning plan to the autonomous mobile cleaning device, and the device operates based on the plan.

[1308] Step 7:

[1309] Receiving a facial recognition request

[1310] Input: User's face recognition trigger

[1311] Output: Face image data

[1312] Specific behavior:

[1313] When a user approaches an item storage device and attempts facial authentication, the item storage device uses a camera to capture an image of the user's face and transmits the data to a server.

[1314] Step 8:

[1315] Performing face recognition

[1316] Input: Facial image data

[1317] Output: Authentication result

[1318] Specific behavior:

[1319] The server uses a facial recognition algorithm (e.g., OpenCV or Google FaceNet) to match the image with a registered image in a database. If the authentication is successful, the result is sent to the item storage device.

[1320] Step 9:

[1321] Execution of goods delivery

[1322] Input: Authentication success signal

[1323] Output: Unlocked containment unit

[1324] Specific behavior:

[1325] After the item storage device receives the signal of successful authentication, it releases the electromagnetic lock, allowing the user to remove the item from the unlocked device.

[1326] The above are the specific processing steps of the entire system. This system efficiently carries out cleaning activities and item delivery, providing a convenient and safe environment for users.

[1327] (Application example 1)

[1328] 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."

[1329] Currently, efficient management of cleaning and parts supply within factories is carried out manually or through separate systems, making operations cumbersome. Furthermore, robot schedule changes and optimization cannot be performed in real time, which can lead to reduced production efficiency. Furthermore, authentication and management of parts supply are also dependent on human labor, creating security and efficiency challenges.

[1330] 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.

[1331] In this invention, the server includes means for collecting operation information from a plurality of autonomous mobile cleaning devices and part supply robots and generating optimal cleaning and supply schedules based on the operation information, means for controlling the plurality of autonomous mobile cleaning devices and part supply robots in accordance with the cleaning and supply schedules, and means for receiving requests from users via communication with client terminals and adjusting the cleaning and supply schedules in real time based on the requests. This enables integrated management of cleaning and part supply within a factory, and automation improves efficiency and strengthens security.

[1332] An "autonomous mobile cleaning device" is a mobile machine equipped with sensor technology and AI algorithms that autonomously performs cleaning tasks within a factory.

[1333] A "parts supply robot" is an autonomously operating mechanical device that has the function of automatically supplying parts to designated locations.

[1334] "Operation information" is a collection of data including the current working status and position information of the autonomous mobile cleaning device and the parts supply robot, and environmental information obtained from sensors.

[1335] A "cleaning schedule" is a planned work schedule for an autonomous mobile cleaning device to clean a specific location at a specific time.

[1336] A "supply schedule" is a planned work schedule for a parts supply robot to supply parts to a specific location at a specific time.

[1337] A "client terminal" is a communication device such as a smartphone, tablet, or PC that a user uses to send a request.

[1338] An "authentication device" is a device for acquiring authentication information of a user, and is used to verify the identity of the user using facial recognition technology or the like.

[1339] An "item storage device" is a device for storing and transferring parts and items, and allows users to take out items only after they have been authenticated.

[1340] The "server" is a computer system that manages the autonomous mobile cleaning devices and the parts supply robots in an integrated manner, and processes user requests and creates and adjusts schedules.

[1341] This invention relates to a factory system that comprehensively manages autonomous mobile cleaning devices and parts supply robots. This system efficiently manages cleaning and parts supply within a factory and can respond to user requests in real time.

[1342] System Overview

[1343] This system consists of a server, autonomous mobile cleaning devices, parts supply robots, item storage devices, authentication devices, and client terminals. The server collects operational information from each device and generates optimal cleaning and supply schedules. The server also receives requests from users through communication with the client terminals and adjusts the schedules in real time.

[1344] Hardware and software used

[1345] The autonomous cleaning mobile devices and parts supply robots operate primarily using sensor technology and AI algorithms.

[1346] The server uses a programming language such as Python and a database management system such as SQLite.

[1347] Smartphones, tablets, personal computers, etc. are used as client terminals, and applications or browser-based systems are implemented as user interfaces.

[1348] The authentication device uses facial recognition technology and incorporates a camera and facial recognition algorithms.

[1349] How it works

[1350] 1. The server collects and analyzes operational information sent from the autonomous cleaning devices and the parts supply robots to generate an optimal schedule. The server calculates the schedule based on environmental information from sensors and the current work status, and sets the schedule to ensure efficient cleaning and parts supply.

[1351] 2. Users using client devices can request schedule changes via a smartphone app or tablet. The user's request is sent to the server and processed in real time. For example, if a user requests "Please change the cleaning schedule," the server generates a new schedule based on the current schedule and sensor data and sends instructions to the autonomous mobile cleaning device.

[1352] 3. The item storage device is used by the user to receive parts or items using an authentication device. Once the user is authenticated by facial recognition, the item storage device is unlocked and the parts are handed over. The server processes the authentication information and manages the delivery history.

[1353] Specific examples

[1354] For example, if the user enters the following prompt:

[1355] "Please change the morning cleaning schedule to 1pm."

[1356] "Please provide parts to Section B."

[1357] These requests are sent from the client terminals and processed by the server, which then generates a new schedule and sends instructions to the autonomous mobile cleaning devices and the parts supply robots based on the schedule, thereby improving the overall operational efficiency within the factory.

[1358] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1359] Step 1:

[1360] The server collects operation information from the autonomous mobile cleaning device and the part supply robot.

[1361] Input: Operation information from the autonomous mobile cleaning device and the parts supply robot (current work status, location information, sensor information, etc.).

[1362] Data processing: The server analyzes the operational information and stores it in a database. Specifically, it organizes and classifies the information using an SQLite database.

[1363] Output: Operational information stored in a database.

[1364] Step 2:

[1365] The server generates optimal cleaning and supply schedules based on the collected operational information.

[1366] Input: Operation information of the autonomous mobile cleaning device and the parts supply robot stored in the database.

[1367] Data calculation: Using Python AI algorithms, the system analyzes operational information and generates an efficient schedule, taking into account each robot's operating time, travel time, and work time.

[1368] Output: Optimal cleaning and feeding schedules.

[1369] Step 3:

[1370] The server controls the autonomous mobile cleaning device and the part supply robot according to the generated schedule.

[1371] Input: Optimal cleaning and supply schedules.

[1372] Data processing: The generated schedule is sent as instructions to each robot to execute it. The instructions are sent via the network using protocols such as TCP / IP.

[1373] Output: Instructions for executing the autonomous mobile cleaning device and the parts supply robot.

[1374] Step 4:

[1375] A user uses a client terminal to send a request to a server.

[1376] Input: User request (e.g. "Please change my cleaning schedule").

[1377] Data processing: The request content is sent to the server in JSON format. The request content is entered through the terminal interface.

[1378] Output: The request data sent to the server.

[1379] Step 5:

[1380] The server adjusts the schedule in real time based on requests from users.

[1381] Input: Request data sent by the user, as well as current schedule and sensor data.

[1382] Data calculation: Recalculate and optimize new schedules using AI algorithms. Real-time schedule recalculation using Python.

[1383] Output: The new optimal schedule.

[1384] Step 6:

[1385] The server notifies the user of the new schedule and obtains confirmation.

[1386] Input: The new optimal schedule.

[1387] Data processing: Send the new schedule to the client terminal and display it to the user. Send data via TCP / IP protocol.

[1388] Output: The new schedule displayed on the client terminal.

[1389] Step 7:

[1390] The user confirms the new schedule and sends a notification of approval to the server.

[1391] Input: User confirmation and approval operation.

[1392] Data processing: Pressing the approval button sends the data to the server.

[1393] Output: The authorization data sent to the server.

[1394] Step 8:

[1395] The server notifies each autonomous mobile cleaning device and each part supply robot of the new schedule and causes them to start executing.

[1396] Input: Approval data for the new schedule.

[1397] Data processing: Based on the approved data, the final schedule is sent to each robot and instructions are given to execute it.

[1398] Output: New schedule instructions sent to each robot.

[1399] 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.

[1400] The present invention relates to a system comprising an autonomous mobile cleaning device, an item storage device, an emotion engine, and a server and client terminals that control these. Specific embodiments of this system will be described below.

[1401] System Overview

[1402] This system consists of an autonomous mobile cleaning device, an item storage device, a server, an emotion engine, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device through which users receive deliveries and authenticates users using facial recognition technology. The emotion engine acquires and analyzes user emotion data and adjusts the operation of each device based on that information. The server manages and controls each of these devices in an integrated manner, adjusting their operation in response to user requests.

[1403] Operation of the autonomous mobile cleaning device

[1404] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on this information. The emotion engine can also obtain user emotion data and adjust a new schedule based on that data. If a schedule adjustment is necessary, the server receives a request from the user's client terminal and updates the schedule in real time.

[1405] Operation of the article storage device

[1406] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotion data and can control the device to respond quickly, for example, depending on a specific emotional state. The server processes the authentication information sent from the item storage device and sends the authentication results to the item storage device.

[1407] Processing user requests

[1408] When a user sends a request via a client terminal regarding a change in cleaning schedule or delivery pickup, the server receives the request and performs the necessary processing. For example, if a user requests a change in cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[1409] Specific examples

[1410] For example, if a user requests a change in cleaning schedule to accommodate a busy time, the emotion engine analyzes the user's emotion data and detects that the user's stress level is high. In this case, the following process is performed:

[1411] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[1412] 2. The device sends the request to the server.

[1413] 3. The emotion engine acquires the user's emotional data and analyzes stress levels, etc.

[1414] 4. The server receives the request and retrieves and analyzes the current cleaning schedule, the latest sensor data, and data from the emotion engine from the database.

[1415] 5. The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[1416] 6. The server sends the new cleaning schedule to the terminal and displays the new schedule to the user.

[1417] 7. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[1418] 8. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[1419] Similarly, when a user receives a parcel from an item storage device, the emotion engine functions as follows.

[1420] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[1421] 2. The terminal (item storage device) sends the facial recognition data to the server.

[1422] 3. The server analyzes the facial recognition data and determines that the authentication was successful.

[1423] 4. The server records the fact that the parcel has been stored in the database and sends a notification of the parcel's arrival to the corresponding user.

[1424] 5. The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to that state.

[1425] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[1426] 7. The terminal (item storage device) sends the user's facial authentication data to the server.

[1427] 8. The server analyzes the user's facial recognition data and compares it with database information.

[1428] 9. The server notifies the terminal (item storage device) that the authentication was successful.

[1429] 10. The terminal (item storage device) unlocks the device based on the authentication result.

[1430] 11. The user removes the parcel from the item storage device.

[1431] 12. The server records in the database that the parcel has been picked up and sends a notification to the user that the process is complete.

[1432] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, significantly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[1433] The processing flow will be explained below.

[1434] Changes to cleaning schedules

[1435] Step 1:

[1436] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[1437] Step 2:

[1438] The device (smartphone app) sends the request to the server.

[1439] Step 3:

[1440] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[1441] Step 4:

[1442] The emotion engine acquires the user's emotional data and analyzes the user's stress level and satisfaction.

[1443] Step 5:

[1444] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule, sensor data, and analytical data from the emotion engine.

[1445] Step 6:

[1446] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[1447] Step 7:

[1448] The user checks the new schedule and presses the approval button.

[1449] Step 8:

[1450] The device (smartphone app) sends the approval information to the server.

[1451] Step 9:

[1452] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[1453] Step 10:

[1454] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[1455] Receiving parcels

[1456] Step 1:

[1457] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[1458] Step 2:

[1459] The terminal (item storage device) transmits the facial authentication data to the server.

[1460] Step 3:

[1461] The server analyzes the facial recognition data and determines that the authentication was successful.

[1462] Step 4:

[1463] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[1464] Step 5:

[1465] The emotion engine acquires the user's emotional data and analyzes the user's stress level and expectations.

[1466] Step 6:

[1467] The user arrives at the item storage device and holds their face up to the face authentication camera.

[1468] Step 7:

[1469] The terminal (item storage device) transmits the user's facial authentication data to the server.

[1470] Step 8:

[1471] The server analyzes the user's facial recognition data and compares it with database information.

[1472] Step 9:

[1473] The server notifies the terminal (item storage device) that the authentication was successful.

[1474] Step 10:

[1475] The terminal (item storage device) unlocks the door based on the authentication result.

[1476] Step 11:

[1477] The user removes the parcel from the item storage device.

[1478] Step 12:

[1479] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[1480] Step 13:

[1481] The emotion engine collects the user's emotional data again after receiving the parcel and analyzes the user's satisfaction level.

[1482] The above are the specific processing steps for changing the cleaning schedule and receiving deliveries in a system that combines an emotion engine. This section describes in detail how the server, terminal, and user operate at each step.

[1483] Example 2

[1484] 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."

[1485] In order to efficiently carry out cleaning work and deliver goods, appropriate schedule management and user authentication are necessary, but conventional systems have difficulty responding flexibly to the user's emotional state. Furthermore, the lack of utilization of emotional data has made it difficult to improve the user experience. This has led to concerns that schedule changes and authentication processes cannot be quickly implemented, especially in stressful situations, leading to a decline in user satisfaction.

[1486] 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.

[1487] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to provide a system that can optimize the cleaning schedule and the operation of item storage devices based on user emotion data and respond efficiently and flexibly.

[1488] An "autonomous mobile cleaning device" is a mobile robot that automatically performs cleaning tasks in buildings and other facilities, and operates using sensor technology and AI.

[1489] "Operation information" is information relating to the current position, operation status, cleaning progress, etc. of the autonomous mobile cleaning device.

[1490] A "cleaning schedule" is a plan for an autonomous mobile cleaning device to clean a specific area during a specific time period.

[1491] A "server" is a computing device that exchanges instructions and data with client terminals via communication and comprehensively manages and controls the operation of the autonomous mobile cleaning device and the item storage device.

[1492] A "client terminal" is a device operated by a user, including a smartphone, tablet, or PC, that communicates with a server to make requests and obtain information.

[1493] A "request" is an operation request or instruction that a user sends to the server via a client terminal, such as a request to change a cleaning schedule or receive an item.

[1494] "Emotional data" refers to data that indicates the user's psychological and physiological state, including stress levels and emotional states.

[1495] An "item storage device" is a storage device for users to receive parcels, and is a device that authenticates users using facial recognition technology and the like and safely delivers items.

[1496] "Authentication information" refers to information used by a user to access an item storage unit or other device, and may include facial recognition data.

[1497] An "authentication device" is a device that combines hardware and software to obtain user authentication information and perform authentication.

[1498] A "database" is a data storage location for systematically storing and managing various data handled within a system.

[1499] The present invention relates to an autonomous mobile cleaning system and an item storage system. Detailed embodiments for implementing the system will be described below.

[1500] System configuration

[1501] The system mainly consists of the following components:

[1502] 1. Autonomous Cleaning Vehicle - A robot that automatically performs cleaning tasks within a building and operates using sensor technology and AI.

[1503] 2. Item storage device - A device that allows users to receive parcels, and uses facial recognition technology for authentication.

[1504] 3. Server - Integrated management and control of autonomous mobile cleaning devices, item storage devices, and user client terminals.

[1505] 4. Emotion Engine - Captures and analyzes user emotional data and adjusts system behavior based on that information.

[1506] 5. Client terminal - A device operated by a user, including a smartphone, tablet, or PC.

[1507] Operation of the autonomous mobile cleaning device

[1508] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The cleaning schedule is sent from the server to the autonomous mobile cleaning devices, and the devices perform cleaning in accordance with the schedule. The emotion engine also acquires user emotion data and can adjust a new schedule based on that data. When a user requests a change to the cleaning schedule from a client terminal, the server adjusts the schedule in real time and notifies the autonomous mobile cleaning devices.

[1509] Operation of the article storage device

[1510] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotional data and responds quickly to specific emotional states. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[1511] Processing user requests

[1512] When a user sends a request via a client terminal to change the cleaning schedule or receive a package, the server receives the request and performs the necessary processing. For example, if a user requests a change to the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[1513] Specific examples

[1514] For example, if a user wants to change the cleaning schedule during a busy time, the following process occurs:

[1515] 1. The user requests a "change in cleaning schedule" from the AI ​​chatbot via a client device (e.g., a smartphone app).

[1516] Example prompt: "I'd like to change the cleaning schedule. It's difficult to clean at this time, so could you please do it later?"

[1517] 2. The client terminal sends the request to the server.

[1518] 3. The emotion engine collects the user's emotional data and analyzes their stress level.

[1519] 4. The server receives the request and generates a new schedule based on the current cleaning schedule and the latest sensor information.

[1520] 5. The server sends the new cleaning schedule to the client terminal and displays it to the user.

[1521] 6. Once the user approves the new schedule, the information is sent to the server.

[1522] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning according to the schedule.

[1523] Similarly, when a user receives a parcel from an item storage device, the following process occurs:

[1524] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[1525] 2. The item storage device sends the facial recognition data to the server.

[1526] 3. The server analyzes the facial recognition data and determines whether authentication was successful.

[1527] 4. The server notifies the user that the parcel has been stored.

[1528] Example prompt: "Please let me know that I have a parcel. I'm busy at work, so I'll come and get it later."

[1529] 5. The emotion engine analyzes the user's emotional data and adjusts its behavior.

[1530] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[1531] 7. The item storage device sends the facial recognition data to the server.

[1532] 8. The server confirms successful authentication and sends an unlock command to the item storage device.

[1533] 9. The item storage device unlocks and the user receives the delivery.

[1534] 10. The server records the completion of receipt in the database and notifies the user.

[1535] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[1536] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1537] Processing steps of the autonomous mobile cleaning device

[1538] Step 1:

[1539] The user requests a "change in cleaning schedule" from the AI ​​chatbot on the client device.

[1540] Specific action: Open the smartphone app and send a message to the chatbot saying, "Please change the cleaning schedule to one hour from now."

[1541] Input: User request

[1542] Output: The data sent to the terminal by the request statement.

[1543] Step 2:

[1544] The terminal sends the user's request to the server.

[1545] Specific operation: The client terminal creates an HTTP request and sends it to the server.

[1546] Input: User request

[1547] Output: The request data sent to the server

[1548] Step 3:

[1549] The emotion engine acquires the user's emotional data and analyzes their stress level.

[1550] What it does: The emotion engine uses the user's past behavioral history and current state (e.g., heart rate, facial recognition data) to assess stress levels.

[1551] Input: User's physiological data and behavioral history

[1552] Output: Stress level evaluation result

[1553] Step 4:

[1554] The server receives the request, retrieves the current cleaning schedule and the latest sensor information, and analyzes it.

[1555] Specific operation: The server obtains the current schedule and sensor information of the autonomous cleaning mobile device from the database.

[1556] Input: User request data, current cleaning schedule, sensor information

[1557] Output: Complete set of data required for schedule recalculation

[1558] Step 5:

[1559] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[1560] Specific operation: The schedule is recalculated and generated using a machine learning model based on the data collected by the server.

[1561] Input: Current schedule, sensor information, user emotion data

[1562] Output: New cleaning schedule

[1563] Step 6:

[1564] The server sends the new cleaning schedule to the terminal and displays it to the user.

[1565] Specific operation: The server returns new schedule data in an HTTP response, and the terminal displays this in a GUI.

[1566] Input: New cleaning schedule

[1567] Output: GUI display data on the terminal

[1568] Step 7:

[1569] When the user checks the new schedule and presses the approval button, the information is sent to the server.

[1570] Specific operation: The user taps the confirmation button on their smartphone, and the approval data is sent to the server.

[1571] Input: User approval operation data

[1572] Output: Authorization data sent to the server

[1573] Step 8:

[1574] The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning.

[1575] Specific operation: The server transmits a new schedule to the autonomous mobile cleaning device, and the device starts operating based on the schedule.

[1576] Input: New cleaning schedule

[1577] Output: Autonomous cleaning device begins operation

[1578] Processing steps of the article storage device

[1579] Step 1:

[1580] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[1581] Specific actions: The delivery person stands in front of the facial recognition camera and faces forward.

[1582] Input: Delivery person's facial data

[1583] Output: Storage reception data for storage device

[1584] Step 2:

[1585] The item storage device (terminal) transmits the facial authentication data to the server.

[1586] Specific operation: Facial recognition data is packaged into packets and sent to the server.

[1587] Input: Delivery person's facial recognition data

[1588] Output: Facial recognition data sent to the server

[1589] Step 3:

[1590] The server analyzes the facial recognition data and determines that the authentication was successful.

[1591] Specific operation: The server uses an AI algorithm to compare the facial recognition data with database information and determine the authentication result.

[1592] Input: Facial recognition data, database information

[1593] Output: Authentication result

[1594] Step 4:

[1595] The server records in a database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[1596] Specific operation: The server updates the database and sends a push notification to the user device.

[1597] Input: Delivery storage completion data, corresponding user information

[1598] Output: Push notification data

[1599] Step 5:

[1600] The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to the user's emotion state.

[1601] Specific behavior: The emotion engine detects the user's emotional state and sets behavior parameters.

[1602] Input: User emotion data

[1603] Output: Operating parameters

[1604] Step 6:

[1605] The user arrives at the item storage device and holds their face up to the face authentication camera.

[1606] Specific actions: Stand in front of the item storage device and hold your face towards the camera.

[1607] Input: User's face data

[1608] Output: Authentication request data

[1609] Step 7:

[1610] The item storage device (terminal) transmits the user's facial authentication data to the server.

[1611] Specific operation: Sends authentication data to the server.

[1612] Input: Facial recognition data

[1613] Output: Authentication data sent to the server

[1614] Step 8:

[1615] The server analyzes the facial recognition data and compares it with database information.

[1616] Specific operation: The server uses an AI algorithm to match the facial recognition data and generate a recognition result.

[1617] Input: Authentication data, database information

[1618] Output: Authentication result

[1619] Step 9:

[1620] The server notifies the item storage device (terminal) that the authentication was successful.

[1621] Specific operation: Send an authentication success message to the item storage device.

[1622] Input: Authentication result

[1623] Output: Unlock instruction data for the item storage device

[1624] Step 10:

[1625] The item storage device (terminal) unlocks the device based on the authentication result.

[1626] Specific operation: Activates the unlocking mechanism and releases the locked state.

[1627] Input: Unlock instruction data

[1628] Output: Unlocked

[1629] Step 11:

[1630] The user removes the parcel from the item storage device.

[1631] Specific operation: After unlocking, open the storage device and remove the parcel.

[1632] Input: Unlocked containment device

[1633] Output: Retrieved parcel

[1634] Step 12:

[1635] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[1636] Specific operation: A receipt completion message is sent to the user's device via push notification.

[1637] Input: Data extracted

[1638] Output: Push notification data

[1639] (Application example 2)

[1640] 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."

[1641] Modern brick-and-mortar stores require improved efficiency and security in cleaning and item pickup. However, these tasks still require a large amount of labor, and providing services that take into account the emotional state of users is difficult. Especially during stressful times, more flexible and prompt responses are needed to improve user satisfaction.

[1642] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1643] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to adjust the operation of the entire system based on user emotion data and provide flexible and efficient cleaning work and item collection.

[1644] An "autonomous mobile cleaning device" is a machine that uses sensor technology and artificial intelligence to autonomously move around inside buildings and brick-and-mortar stores and clean.

[1645] The "cleaning schedule" is a timetable or schedule information that plans which areas an autonomous mobile cleaning device will clean at which times.

[1646] A "client terminal" is a communication device used by a user, such as a smartphone, tablet, or PC, that communicates with a server to send requests and receive information.

[1647] An "item storage device" is a device that stores parcels and purchased items and allows users to receive items using authentication technology such as facial recognition.

[1648] An "authentication device" is a device for obtaining user authentication information, and includes, for example, a camera or sensor for identifying a user using facial recognition technology.

[1649] An "emotion engine" is software or a system that acquires and analyzes the user's emotional data and adjusts the operation of each device based on the results.

[1650] "User emotion data" is data that indicates the user's emotional state (for example, joy, anger, sadness, stress, etc.) based on information acquired from the user's facial expressions, voice, behavior, etc.

[1651] A "server" is a computer system that manages and controls data sent from multiple devices and terminals in an integrated manner and performs the necessary processing.

[1652] System configuration

[1653] The present invention is an integrated system consisting of the following elements:

[1654] 1. Autonomous mobile cleaning device: A device that combines sensor technology and artificial intelligence to move autonomously and clean buildings or physical stores.

[1655] 2. Item storage device: A device that stores parcels and purchased items and allows users to receive them using authentication technology such as facial recognition.

[1656] 3. Server: A computer system that centrally manages and controls data from each device and terminal and performs the necessary processing.

[1657] 4. Emotion engine: Software or a system that acquires and analyzes user emotional data and adjusts the behavior of each device based on the results.

[1658] 5. Client terminal: A communication device used by a user, such as a smartphone, tablet, or PC, that communicates with the server and sends and receives requests.

[1659] System Operation

[1660] The overall system operates as follows.

[1661] First, the autonomous mobile cleaning device uses sensor technology and artificial intelligence to detect its surrounding environment and autonomously move around buildings and physical stores to clean. Operational information is sent to a server, which generates an optimal cleaning schedule. Users can request changes to the cleaning schedule via their client device, and the server adjusts the schedule in real time if requested. Furthermore, an emotion engine analyzes the user's emotional data and optimizes the cleaning schedule and item handover behavior based on the user's specific emotional state.

[1662] Next, during the process of receiving a parcel or purchased item from the item storage device, the user's authentication information is acquired by an authentication device (such as a facial recognition camera). If authentication is successful, the item storage device is unlocked and the user can receive the item. At this time, the emotion engine analyzes the user's emotional state and adjusts its behavior to respond quickly if the user's stress level is high.

[1663] Hardware and software used

[1664] The specific hardware and software used to implement the present invention are described below.

[1665] Hardware: Facial recognition cameras (e.g., high-resolution cameras), autonomous mobile cleaning devices (e.g., high-performance robots), and storage devices (e.g., smart lockers)

[1666] Software: Emotion data analysis API (e.g., advanced electronic data analysis platform), facial recognition software (e.g., image processing library), data management server (e.g., distributed computing platform)

[1667] Examples and prompts

[1668] For example, if a user wishes to change their cleaning schedule, the following process takes place: When the user requests a "change in cleaning schedule" from the client terminal to the AI ​​chatbot, the request is sent to the server. The emotion engine analyzes the user's emotional data and determines their stress level. The server generates a new, optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine, and displays it to the user. If the user approves the new schedule, the server notifies the autonomous mobile cleaning device of the new schedule.

[1669] Prompt Sentence Examples

[1670] "Design a system that dynamically changes the schedule of a cleaning robot based on user emotional data. Also, create a program for a system that implements facial recognition functionality for an item storage device and processes handovers according to the customer's emotional state."

[1671] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1672] Step 1:

[1673] The user requests a "change in cleaning schedule" from the client device to the AI ​​chatbot.

[1674] Input: User input request

[1675] Output: Request content

[1676] Specific operation: The user opens the smartphone app and enters the desired change to the cleaning schedule into the chatbot via text.

[1677] Step 2:

[1678] The terminal transmits the request content to the server.

[1679] Input: Request content

[1680] Output: Request data sent to the server

[1681] Specific operation: The client terminal converts the request content into JSON format and sends it as an HTTP request to the server's API endpoint.

[1682] Step 3:

[1683] The server receives the request and the emotion engine retrieves the user's emotion data and analyzes their emotional state, including stress level.

[1684] Input: Request data, user emotion data

[1685] Output: Emotional state

[1686] Specific operation: The server calls the emotion data analysis API to obtain the user's emotion data, and analyzes the data to determine the stress level and emotional state.

[1687] Step 4:

[1688] The server generates a new optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine.

[1689] Inputs: Current cleaning schedule, latest sensor data, emotion engine data

[1690] Output: New cleaning schedule

[1691] Specific operation: The server retrieves the current cleaning schedule and sensor data from the database, combines it with data from the emotion engine, and uses an optimization algorithm to calculate a new cleaning schedule.

[1692] Step 5:

[1693] The server sends the new cleaning schedule to the client terminal and displays the new schedule to the user.

[1694] Input: New cleaning schedule

[1695] Output: The new schedule as displayed to the user

[1696] Specific operation: The server converts the new cleaning schedule into JSON format and sends it to the client device as an HTTP response. The client device displays the new schedule.

[1697] Step 6:

[1698] When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[1699] Input: User approval

[1700] Output: Authorization information sent to the server

[1701] Specific operation: When the user presses the confirmation button on the client terminal, approval information is sent to the server's API endpoint as an HTTP request.

[1702] Step 7:

[1703] The server notifies the autonomous mobile cleaning device of the new schedule.

[1704] Input: Approved new schedule

[1705] Output: Instructions to the autonomous cleaning device

[1706] Specific operation: The server sends the approved new schedule to the control system of the autonomous mobile cleaning device, causing it to execute the instructions.

[1707] 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.

[1708] 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.

[1709] 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.

[1710] [Fourth embodiment]

[1711] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1712] 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.

[1713] 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).

[1714] 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.

[1715] 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.

[1716] 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).

[1717] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1718] 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.

[1719] 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.

[1720] 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.

[1721] 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.

[1722] 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.

[1723] 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."

[1724] The present invention relates to a system including an autonomous mobile cleaning device, an item storage device, and a server and client terminals that control these devices. Specific embodiments of this system will be described below.

[1725] System Overview

[1726] This system consists of an autonomous mobile cleaning device, an item storage device, a server, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device that allows users to receive deliveries and authenticates users using facial recognition technology. The server manages and controls these devices in an integrated manner, adjusting their operation in response to user requests.

[1727] Operation of the autonomous mobile cleaning device

[1728] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on it. If the schedule needs to be adjusted, the server receives a request from the user's client terminal and updates the schedule in real time.

[1729] Operation of the article storage device

[1730] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If the authentication is successful, the item storage device unlocks and the user can collect the parcel. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[1731] Processing user requests

[1732] When a user sends a request for changing the cleaning schedule or receiving a parcel via a client terminal, the server receives the request and performs the necessary processing. For example, if a user requests a change in the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device.

[1733] Specific examples

[1734] For example, if a user wishes to change the cleaning schedule, the following process is performed.

[1735] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[1736] 2. The device sends the request to the server.

[1737] 3. The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database for analysis.

[1738] 4. The server uses AI algorithms to calculate and generate a new optimal schedule.

[1739] 5. The server sends the new cleaning schedule to the terminal and displays it to the user.

[1740] 6. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[1741] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[1742] Similarly, the system also automates and efficiently manages the collection of parcels from the item storage device.

[1743] The above is a specific embodiment of the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security.

[1744] The processing flow will be explained below.

[1745] Changes to cleaning schedules

[1746] Step 1:

[1747] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[1748] Step 2:

[1749] The device (smartphone app) sends the request to the server.

[1750] Step 3:

[1751] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[1752] Step 4:

[1753] The server uses an AI algorithm to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule and sensor data.

[1754] Step 5:

[1755] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[1756] Step 6:

[1757] The user checks the new schedule and presses the approval button.

[1758] Step 7:

[1759] The device (smartphone app) sends the approval information to the server.

[1760] Step 8:

[1761] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[1762] Step 9:

[1763] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[1764] Receiving parcels

[1765] Step 1:

[1766] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[1767] Step 2:

[1768] The terminal (item storage device) transmits the facial authentication data to the server.

[1769] Step 3:

[1770] The server analyzes the facial recognition data and determines that the authentication was successful.

[1771] Step 4:

[1772] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[1773] Step 5:

[1774] The user arrives at the item storage device and holds their face up to the face authentication camera.

[1775] Step 6:

[1776] The terminal (item storage device) transmits the user's facial authentication data to the server.

[1777] Step 7:

[1778] The server analyzes the user's facial recognition data and compares it with database information.

[1779] Step 8:

[1780] The server notifies the terminal (item storage device) that the authentication was successful.

[1781] Step 9:

[1782] The terminal (item storage device) unlocks the door based on the authentication result.

[1783] Step 10:

[1784] The user removes the parcel from the item storage device.

[1785] Step 11:

[1786] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[1787] Example 1

[1788] 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."

[1789] To efficiently and effectively clean buildings and facilities, it is necessary to optimize cleaning schedules and adjust them in real time. Furthermore, when handing over items, strict user authentication is required, and safe and prompt responses are also required. However, with current systems, it is difficult to centrally manage these requirements, making it difficult to achieve both efficiency and safety.

[1790] 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.

[1791] In this invention, the server includes means for collecting environmental data from a plurality of autonomous mobile cleaning devices and generating an optimal cleaning plan based on the environmental data, means for controlling the plurality of autonomous mobile cleaning devices in accordance with the cleaning plan, and means for receiving requests from users via communication with a terminal and adjusting the cleaning plan in real time based on the requests, thereby enabling efficient operation of cleaning activities and safe delivery of items.

[1792] An "autonomous mobile cleaning device" is a mobile device that automatically cleans buildings and facilities, and operates using sensor technology and AI.

[1793] "Environmental data" refers to information about the surrounding situation and conditions collected by sensors installed on the autonomous cleaning device, including the location of obstacles and the degree of dirt on surfaces.

[1794] "Cleaning Plan" means an optimized cleaning schedule and route that is generated based on collected environmental data.

[1795] "Control" means to instruct a specific action or movement and to supervise or operate a device so that it operates in accordance with that instruction.

[1796] "Terminal" refers to various electronic devices used by users, including smartphones, tablets, computers, etc.

[1797] A "request" refers to a request or wish made by a user to the system, and is a request for a specific operation or change.

[1798] An "item storage device" is a device for safely storing parcels and other items, allowing users to receive them after authentication.

[1799] "Authentication device" refers to equipment used to verify and authenticate a user's personal information, including facial recognition cameras and fingerprint authentication sensors.

[1800] "Authentication information" means information used to verify a user's identity, including facial images and fingerprints.

[1801] "Goods" refers to parcels and other items that are subject to delivery.

[1802] "Data" refers to various information processed and managed by the system, including environmental data, certification information, cleaning plans, etc.

[1803] The present invention is a system for efficiently managing both cleaning activities and item delivery, and is composed of an autonomous mobile cleaning device, an item storage device, a server, and a user terminal.

[1804] Operation of the autonomous mobile cleaning device

[1805] The server uses AI algorithms to generate an optimal cleaning plan based on environmental data collected from the autonomous cleaning device. This plan is generated by analyzing information obtained from sensors (e.g., LiDAR sensors and cameras) using Python machine learning libraries (e.g., scikit-learn).

[1806] The generated cleaning plan is sent to the autonomous mobile cleaning device via a communication protocol (e.g., MQTT or HTTP). The autonomous mobile cleaning device automatically cleans the building according to this plan. If the cleaning plan needs to be adjusted, the server can receive requests from the user and update the plan in real time.

[1807] Specific examples

[1808] For example, if a user wishes to change the cleaning schedule, the following process is carried out.

[1809] 1. A user requests a change to the cleaning schedule from a chatbot on a smartphone app.

[1810] 2. The device sends the request to the server.

[1811] 3. The server receives the request and generates a new, optimal plan based on the latest environmental data and the current cleaning plan.

[1812] 4. The server sends the new plan to the terminal and presents it to the user.

[1813] 5. Once the user approves the new plan, the information is sent to the server.

[1814] 6. The server notifies the autonomous mobile cleaning device of the final new plan, and the device operates according to the plan.

[1815] Operation of the article storage device

[1816] The storage device stores parcels and uses facial recognition technology to authenticate users when they come to collect them, using image processing engines such as OpenCV and Google FaceNet.

[1817] The operation of the article storage device is as follows.

[1818] 1. The user approaches the item storage device, faces the camera, and attempts authentication.

[1819] 2. The item storage device sends the captured facial image to the server.

[1820] 3. The server checks the database and determines whether the authentication is successful.

[1821] 4. If the authentication is successful, the information is sent to the item storage device and the device is unlocked.

[1822] 5. The user can retrieve the parcel.

[1823] Specific examples

[1824] For example, when a user receives a parcel, the following process is carried out.

[1825] 1. The user stands in front of the item storage device and undergoes facial authentication.

[1826] 2. The item storage device recognizes the face and sends the data to the server.

[1827] 3. The server performs authentication, and if successful, sends an unlock command to the item storage device.

[1828] 4. The item storage device is unlocked and the user receives the parcel.

[1829] Example prompts for generative AI models

[1830] "I would like to change the cleaning schedule. What is the current schedule?"

[1831] "I'd like the cleaning completed by this morning. Please reschedule."

[1832] "I would like to receive a parcel, but I would like to use facial recognition."

[1833] The above is a specific embodiment for carrying out the present invention. This system ensures the efficiency of cleaning activities and the safety of item delivery, and can provide a convenient environment for users.

[1834] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1835] Step 1:

[1836] Sensor information collection

[1837] Input: Environmental data from sensors (e.g. LiDAR sensors, cameras)

[1838] Output: Environment data sent to the server

[1839] Specific behavior:

[1840] The autonomous mobile cleaning device uses sensors to acquire real-time environmental data, such as surrounding obstacles and dirt levels, and this data is sent to a server via communication methods such as Wi-Fi or Bluetooth.

[1841] Step 2:

[1842] Generate a cleaning plan

[1843] Input: Environmental data stored on the server

[1844] Output: The generated cleaning plan

[1845] Specific behavior:

[1846] The server uses AI algorithms to generate an optimal cleaning plan based on the received environmental data, using Python machine learning libraries (e.g., scikit-learn) to calculate the optimal route and time schedule for each autonomous cleaning device.

[1847] Step 3:

[1848] Submit a cleaning plan

[1849] Input: Generated cleaning plan

[1850] Output: Cleaning plan sent to the autonomous cleaning device

[1851] Specific behavior:

[1852] The server sends the generated cleaning plan to the autonomous mobile cleaning device using a communication protocol (e.g., MQTT, HTTP). The device follows the received plan and begins cleaning according to the specified route and time schedule.

[1853] Step 4:

[1854] Receiving a user request

[1855] Input: User request (e.g., cleaning schedule change)

[1856] Output: Request sent to the server

[1857] Specific behavior:

[1858] A user uses a client terminal to input a request to change the cleaning schedule. The terminal sends this request to the server, which may include a prompt such as "Please start cleaning at 3 PM."

[1859] Step 5:

[1860] Generate a new cleaning plan

[1861] Input: User request, latest environmental data

[1862] Output: New cleaning plan

[1863] Specific behavior:

[1864] The server receives the user's request and generates a new cleaning plan using AI algorithms based on the latest environmental data, again using Python machine learning libraries (e.g., scikit-learn) to perform the calculations.

[1865] Step 6:

[1866] Submit a new cleaning plan

[1867] Input: A newly generated cleaning plan

[1868] Output: New cleaning plan sent to the autonomous cleaning device and the user terminal

[1869] Specific behavior:

[1870] The server sends the new cleaning plan to the terminal and presents it to the user. If the user approves the new plan, the approval information is sent to the server. The server then sends the final new cleaning plan to the autonomous mobile cleaning device, and the device operates based on the plan.

[1871] Step 7:

[1872] Receiving a facial recognition request

[1873] Input: User's face recognition trigger

[1874] Output: Face image data

[1875] Specific behavior:

[1876] When a user approaches an item storage device and attempts facial authentication, the item storage device uses a camera to capture an image of the user's face and transmits the data to a server.

[1877] Step 8:

[1878] Performing face recognition

[1879] Input: Facial image data

[1880] Output: Authentication result

[1881] Specific behavior:

[1882] The server uses a facial recognition algorithm (e.g., OpenCV or Google FaceNet) to match the image with a registered image in a database. If the authentication is successful, the result is sent to the item storage device.

[1883] Step 9:

[1884] Execution of goods delivery

[1885] Input: Authentication success signal

[1886] Output: Unlocked containment unit

[1887] Specific behavior:

[1888] After the item storage device receives the signal of successful authentication, it releases the electromagnetic lock, allowing the user to remove the item from the unlocked device.

[1889] The above are the specific processing steps of the entire system. This system efficiently carries out cleaning activities and item delivery, providing a convenient and safe environment for users.

[1890] (Application example 1)

[1891] 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."

[1892] Currently, efficient management of cleaning and parts supply within factories is carried out manually or through separate systems, making operations cumbersome. Furthermore, robot schedule changes and optimization cannot be performed in real time, which can lead to reduced production efficiency. Furthermore, authentication and management of parts supply are also dependent on human labor, creating security and efficiency challenges.

[1893] 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.

[1894] In this invention, the server includes means for collecting operation information from a plurality of autonomous mobile cleaning devices and part supply robots and generating optimal cleaning and supply schedules based on the operation information, means for controlling the plurality of autonomous mobile cleaning devices and part supply robots in accordance with the cleaning and supply schedules, and means for receiving requests from users via communication with client terminals and adjusting the cleaning and supply schedules in real time based on the requests. This enables integrated management of cleaning and part supply within a factory, and automation improves efficiency and strengthens security.

[1895] An "autonomous mobile cleaning device" is a mobile machine equipped with sensor technology and AI algorithms that autonomously performs cleaning tasks within a factory.

[1896] A "parts supply robot" is an autonomously operating mechanical device that has the function of automatically supplying parts to designated locations.

[1897] "Operation information" is a collection of data including the current working status and position information of the autonomous mobile cleaning device and the parts supply robot, and environmental information obtained from sensors.

[1898] A "cleaning schedule" is a planned work schedule for an autonomous mobile cleaning device to clean a specific location at a specific time.

[1899] A "supply schedule" is a planned work schedule for a parts supply robot to supply parts to a specific location at a specific time.

[1900] A "client terminal" is a communication device such as a smartphone, tablet, or PC that a user uses to send a request.

[1901] An "authentication device" is a device for acquiring authentication information of a user, and is used to verify the identity of the user using facial recognition technology or the like.

[1902] An "item storage device" is a device for storing and transferring parts and items, and allows users to take out items only after they have been authenticated.

[1903] The "server" is a computer system that manages the autonomous mobile cleaning devices and the parts supply robots in an integrated manner, and processes user requests and creates and adjusts schedules.

[1904] This invention relates to a factory system that comprehensively manages autonomous mobile cleaning devices and parts supply robots. This system efficiently manages cleaning and parts supply within a factory and can respond to user requests in real time.

[1905] System Overview

[1906] This system consists of a server, autonomous mobile cleaning devices, parts supply robots, item storage devices, authentication devices, and client terminals. The server collects operational information from each device and generates optimal cleaning and supply schedules. The server also receives requests from users through communication with the client terminals and adjusts the schedules in real time.

[1907] Hardware and software used

[1908] The autonomous cleaning mobile devices and parts supply robots operate primarily using sensor technology and AI algorithms.

[1909] The server uses a programming language such as Python and a database management system such as SQLite.

[1910] Smartphones, tablets, personal computers, etc. are used as client terminals, and applications or browser-based systems are implemented as user interfaces.

[1911] The authentication device uses facial recognition technology and incorporates a camera and facial recognition algorithms.

[1912] How it works

[1913] 1. The server collects and analyzes operational information sent from the autonomous cleaning devices and the parts supply robots to generate an optimal schedule. The server calculates the schedule based on environmental information from sensors and the current work status, and sets the schedule to ensure efficient cleaning and parts supply.

[1914] 2. Users using client devices can request schedule changes via a smartphone app or tablet. The user's request is sent to the server and processed in real time. For example, if a user requests "Please change the cleaning schedule," the server generates a new schedule based on the current schedule and sensor data and sends instructions to the autonomous mobile cleaning device.

[1915] 3. The item storage device is used by the user to receive parts or items using an authentication device. Once the user is authenticated by facial recognition, the item storage device is unlocked and the parts are handed over. The server processes the authentication information and manages the delivery history.

[1916] Specific examples

[1917] For example, if the user enters the following prompt:

[1918] "Please change the morning cleaning schedule to 1pm."

[1919] "Please provide parts to Section B."

[1920] These requests are sent from the client terminals and processed by the server, which then generates a new schedule and sends instructions to the autonomous mobile cleaning devices and the parts supply robots based on the schedule, thereby improving the overall operational efficiency within the factory.

[1921] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1922] Step 1:

[1923] The server collects operation information from the autonomous mobile cleaning device and the part supply robot.

[1924] Input: Operation information from the autonomous mobile cleaning device and the parts supply robot (current work status, location information, sensor information, etc.).

[1925] Data processing: The server analyzes the operational information and stores it in a database. Specifically, it organizes and classifies the information using an SQLite database.

[1926] Output: Operational information stored in a database.

[1927] Step 2:

[1928] The server generates optimal cleaning and supply schedules based on the collected operational information.

[1929] Input: Operation information of the autonomous mobile cleaning device and the parts supply robot stored in the database.

[1930] Data calculation: Using Python AI algorithms, the system analyzes operational information and generates an efficient schedule, taking into account each robot's operating time, travel time, and work time.

[1931] Output: Optimal cleaning and feeding schedules.

[1932] Step 3:

[1933] The server controls the autonomous mobile cleaning device and the part supply robot according to the generated schedule.

[1934] Input: Optimal cleaning and supply schedules.

[1935] Data processing: The generated schedule is sent as instructions to each robot to execute it. The instructions are sent via the network using protocols such as TCP / IP.

[1936] Output: Instructions for executing the autonomous mobile cleaning device and the parts supply robot.

[1937] Step 4:

[1938] A user uses a client terminal to send a request to a server.

[1939] Input: User request (e.g. "Please change my cleaning schedule").

[1940] Data processing: The request content is sent to the server in JSON format. The request content is entered through the terminal interface.

[1941] Output: The request data sent to the server.

[1942] Step 5:

[1943] The server adjusts the schedule in real time based on requests from users.

[1944] Input: Request data sent by the user, as well as current schedule and sensor data.

[1945] Data calculation: Recalculate and optimize new schedules using AI algorithms. Real-time schedule recalculation using Python.

[1946] Output: The new optimal schedule.

[1947] Step 6:

[1948] The server notifies the user of the new schedule and obtains confirmation.

[1949] Input: The new optimal schedule.

[1950] Data processing: Send the new schedule to the client terminal and display it to the user. Send data via TCP / IP protocol.

[1951] Output: The new schedule displayed on the client terminal.

[1952] Step 7:

[1953] The user confirms the new schedule and sends a notification of approval to the server.

[1954] Input: User confirmation and approval operation.

[1955] Data processing: Pressing the approval button sends the data to the server.

[1956] Output: The authorization data sent to the server.

[1957] Step 8:

[1958] The server notifies each autonomous mobile cleaning device and each part supply robot of the new schedule and causes them to start executing.

[1959] Input: Approval data for the new schedule.

[1960] Data processing: Based on the approved data, the final schedule is sent to each robot and instructions are given to execute it.

[1961] Output: New schedule instructions sent to each robot.

[1962] 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.

[1963] The present invention relates to a system comprising an autonomous mobile cleaning device, an item storage device, an emotion engine, and a server and client terminals that control these. Specific embodiments of this system will be described below.

[1964] System Overview

[1965] This system consists of an autonomous mobile cleaning device, an item storage device, a server, an emotion engine, and a user client terminal. The autonomous mobile cleaning device automatically cleans buildings and operates using sensor technology and AI. The item storage device is a device through which users receive deliveries and authenticates users using facial recognition technology. The emotion engine acquires and analyzes user emotion data and adjusts the operation of each device based on that information. The server manages and controls each of these devices in an integrated manner, adjusting their operation in response to user requests.

[1966] Operation of the autonomous mobile cleaning device

[1967] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The generated schedule is sent from the server to the autonomous mobile cleaning devices, which then operate based on this information. The emotion engine can also obtain user emotion data and adjust a new schedule based on that data. If a schedule adjustment is necessary, the server receives a request from the user's client terminal and updates the schedule in real time.

[1968] Operation of the article storage device

[1969] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotion data and can control the device to respond quickly, for example, depending on a specific emotional state. The server processes the authentication information sent from the item storage device and sends the authentication results to the item storage device.

[1970] Processing user requests

[1971] When a user sends a request via a client terminal regarding a change in cleaning schedule or delivery pickup, the server receives the request and performs the necessary processing. For example, if a user requests a change in cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[1972] Specific examples

[1973] For example, if a user requests a change in cleaning schedule to accommodate a busy time, the emotion engine analyzes the user's emotion data and detects that the user's stress level is high. In this case, the following process is performed:

[1974] 1. The user requests a "change in cleaning schedule" from the client device (smartphone app) to the AI ​​chatbot.

[1975] 2. The device sends the request to the server.

[1976] 3. The emotion engine acquires the user's emotional data and analyzes stress levels, etc.

[1977] 4. The server receives the request and retrieves and analyzes the current cleaning schedule, the latest sensor data, and data from the emotion engine from the database.

[1978] 5. The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[1979] 6. The server sends the new cleaning schedule to the terminal and displays the new schedule to the user.

[1980] 7. When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[1981] 8. The server notifies the autonomous mobile cleaning device of the new schedule, and the device begins cleaning according to the new schedule.

[1982] Similarly, when a user receives a parcel from an item storage device, the emotion engine functions as follows.

[1983] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[1984] 2. The terminal (item storage device) sends the facial recognition data to the server.

[1985] 3. The server analyzes the facial recognition data and determines that the authentication was successful.

[1986] 4. The server records the fact that the parcel has been stored in the database and sends a notification of the parcel's arrival to the corresponding user.

[1987] 5. The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to that state.

[1988] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[1989] 7. The terminal (item storage device) sends the user's facial authentication data to the server.

[1990] 8. The server analyzes the user's facial recognition data and compares it with database information.

[1991] 9. The server notifies the terminal (item storage device) that the authentication was successful.

[1992] 10. The terminal (item storage device) unlocks the device based on the authentication result.

[1993] 11. The user removes the parcel from the item storage device.

[1994] 12. The server records in the database that the parcel has been picked up and sends a notification to the user that the process is complete.

[1995] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, significantly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[1996] The processing flow will be explained below.

[1997] Changes to cleaning schedules

[1998] Step 1:

[1999] The user launches the client device (smartphone app) and requests a "change in cleaning schedule" from the AI ​​chatbot.

[2000] Step 2:

[2001] The device (smartphone app) sends the request to the server.

[2002] Step 3:

[2003] The server receives the request and retrieves the current cleaning schedule and the latest sensor data from the database.

[2004] Step 4:

[2005] The emotion engine acquires the user's emotional data and analyzes the user's stress level and satisfaction.

[2006] Step 5:

[2007] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule based on the current cleaning schedule, sensor data, and analytical data from the emotion engine.

[2008] Step 6:

[2009] The server sends the new cleaning schedule to the device (smartphone app) and displays the new schedule to the user.

[2010] Step 7:

[2011] The user checks the new schedule and presses the approval button.

[2012] Step 8:

[2013] The device (smartphone app) sends the approval information to the server.

[2014] Step 9:

[2015] The server notifies the terminal (autonomous mobile cleaning device) of the new cleaning schedule.

[2016] Step 10:

[2017] The autonomous mobile cleaning device starts cleaning work according to the new schedule.

[2018] Receiving parcels

[2019] Step 1:

[2020] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[2021] Step 2:

[2022] The terminal (item storage device) transmits the facial authentication data to the server.

[2023] Step 3:

[2024] The server analyzes the facial recognition data and determines that the authentication was successful.

[2025] Step 4:

[2026] The server records in the database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[2027] Step 5:

[2028] The emotion engine acquires the user's emotional data and analyzes the user's stress level and expectations.

[2029] Step 6:

[2030] The user arrives at the item storage device and holds their face up to the face authentication camera.

[2031] Step 7:

[2032] The terminal (item storage device) transmits the user's facial authentication data to the server.

[2033] Step 8:

[2034] The server analyzes the user's facial recognition data and compares it with database information.

[2035] Step 9:

[2036] The server notifies the terminal (item storage device) that the authentication was successful.

[2037] Step 10:

[2038] The terminal (item storage device) unlocks the door based on the authentication result.

[2039] Step 11:

[2040] The user removes the parcel from the item storage device.

[2041] Step 12:

[2042] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[2043] Step 13:

[2044] The emotion engine collects the user's emotional data again after receiving the parcel and analyzes the user's satisfaction level.

[2045] The above are the specific processing steps for changing the cleaning schedule and receiving deliveries in a system that combines an emotion engine. This section describes in detail how the server, terminal, and user operate at each step.

[2046] Example 2

[2047] 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."

[2048] In order to efficiently carry out cleaning work and deliver goods, appropriate schedule management and user authentication are necessary, but conventional systems have difficulty responding flexibly to the user's emotional state. Furthermore, the lack of utilization of emotional data has made it difficult to improve the user experience. This has led to concerns that schedule changes and authentication processes cannot be quickly implemented, especially in stressful situations, leading to a decline in user satisfaction.

[2049] 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.

[2050] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to provide a system that can optimize the cleaning schedule and the operation of item storage devices based on user emotion data and respond efficiently and flexibly.

[2051] An "autonomous mobile cleaning device" is a mobile robot that automatically performs cleaning tasks in buildings and other facilities, and operates using sensor technology and AI.

[2052] "Operation information" is information relating to the current position, operation status, cleaning progress, etc. of the autonomous mobile cleaning device.

[2053] A "cleaning schedule" is a plan for an autonomous mobile cleaning device to clean a specific area during a specific time period.

[2054] A "server" is a computing device that exchanges instructions and data with client terminals via communication and comprehensively manages and controls the operation of the autonomous mobile cleaning device and the item storage device.

[2055] A "client terminal" is a device operated by a user, including a smartphone, tablet, or PC, that communicates with a server to make requests and obtain information.

[2056] A "request" is an operation request or instruction that a user sends to the server via a client terminal, such as a request to change a cleaning schedule or receive an item.

[2057] "Emotional data" refers to data that indicates the user's psychological and physiological state, including stress levels and emotional states.

[2058] An "item storage device" is a storage device for users to receive parcels, and is a device that authenticates users using facial recognition technology and the like and safely delivers items.

[2059] "Authentication information" refers to information used by a user to access an item storage unit or other device, and may include facial recognition data.

[2060] An "authentication device" is a device that combines hardware and software to obtain user authentication information and perform authentication.

[2061] A "database" is a data storage location for systematically storing and managing various data handled within a system.

[2062] The present invention relates to an autonomous mobile cleaning system and an item storage system. Detailed embodiments for implementing the system will be described below.

[2063] System configuration

[2064] The system mainly consists of the following components:

[2065] 1. Autonomous Cleaning Vehicle - A robot that automatically performs cleaning tasks within a building and operates using sensor technology and AI.

[2066] 2. Item storage device - A device that allows users to receive parcels, and uses facial recognition technology for authentication.

[2067] 3. Server - Integrated management and control of autonomous mobile cleaning devices, item storage devices, and user client terminals.

[2068] 4. Emotion Engine - Captures and analyzes user emotional data and adjusts system behavior based on that information.

[2069] 5. Client terminal - A device operated by a user, including a smartphone, tablet, or PC.

[2070] Operation of the autonomous mobile cleaning device

[2071] The server collects sensor information from the autonomous mobile cleaning devices and generates an optimal cleaning schedule based on that operation information. The cleaning schedule is sent from the server to the autonomous mobile cleaning devices, and the devices perform cleaning in accordance with the schedule. The emotion engine also acquires user emotion data and can adjust a new schedule based on that data. When a user requests a change to the cleaning schedule from a client terminal, the server adjusts the schedule in real time and notifies the autonomous mobile cleaning devices.

[2072] Operation of the article storage device

[2073] The item storage device stores the parcel and uses facial recognition technology to authenticate the user when they come to collect it. If authentication is successful, the item storage device unlocks and the user can collect the parcel. The emotion engine adjusts its behavior based on the user's emotional data and responds quickly to specific emotional states. The server processes the authentication information sent from the item storage device and sends the authentication result to the item storage device.

[2074] Processing user requests

[2075] When a user sends a request via a client terminal to change the cleaning schedule or receive a package, the server receives the request and performs the necessary processing. For example, if a user requests a change to the cleaning schedule, the server recalculates the optimal schedule based on the current schedule and the new request, and sends instructions to the autonomous mobile cleaning device. Data from the emotion engine is also taken into account, and if the user's stress level is high, the system adjusts to respond more quickly.

[2076] Specific examples

[2077] For example, if a user wants to change the cleaning schedule during a busy time, the following process occurs:

[2078] 1. The user requests a "change in cleaning schedule" from the AI ​​chatbot via a client device (e.g., a smartphone app).

[2079] Example prompt: "I'd like to change the cleaning schedule. It's difficult to clean at this time, so could you please do it later?"

[2080] 2. The client terminal sends the request to the server.

[2081] 3. The emotion engine collects the user's emotional data and analyzes their stress level.

[2082] 4. The server receives the request and generates a new schedule based on the current cleaning schedule and the latest sensor information.

[2083] 5. The server sends the new cleaning schedule to the client terminal and displays it to the user.

[2084] 6. Once the user approves the new schedule, the information is sent to the server.

[2085] 7. The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning according to the schedule.

[2086] Similarly, when a user receives a parcel from an item storage device, the following process occurs:

[2087] 1. The delivery person places the parcel in the item storage device and holds their face in front of the facial recognition camera.

[2088] 2. The item storage device sends the facial recognition data to the server.

[2089] 3. The server analyzes the facial recognition data and determines whether authentication was successful.

[2090] 4. The server notifies the user that the parcel has been stored.

[2091] Example prompt: "Please let me know that I have a parcel. I'm busy at work, so I'll come and get it later."

[2092] 5. The emotion engine analyzes the user's emotional data and adjusts its behavior.

[2093] 6. The user arrives at the item storage device and holds their face up to the facial recognition camera.

[2094] 7. The item storage device sends the facial recognition data to the server.

[2095] 8. The server confirms successful authentication and sends an unlock command to the item storage device.

[2096] 9. The item storage device unlocks and the user receives the delivery.

[2097] 10. The server records the completion of receipt in the database and notifies the user.

[2098] The above is a specific embodiment for implementing the present invention. By using this system, cleaning work and delivery of parcels in building management can be managed in an integrated manner, greatly improving efficiency and security. Furthermore, the introduction of an emotion engine makes it possible to provide flexible services that take into account the user's emotional state.

[2099] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2100] Processing steps of the autonomous mobile cleaning device

[2101] Step 1:

[2102] The user requests a "change in cleaning schedule" from the AI ​​chatbot on the client device.

[2103] Specific action: Open the smartphone app and send a message to the chatbot saying, "Please change the cleaning schedule to one hour from now."

[2104] Input: User request

[2105] Output: The data sent to the terminal by the request statement.

[2106] Step 2:

[2107] The terminal sends the user's request to the server.

[2108] Specific operation: The client terminal creates an HTTP request and sends it to the server.

[2109] Input: User request

[2110] Output: The request data sent to the server

[2111] Step 3:

[2112] The emotion engine acquires the user's emotional data and analyzes their stress level.

[2113] What it does: The emotion engine uses the user's past behavioral history and current state (e.g., heart rate, facial recognition data) to assess stress levels.

[2114] Input: User's physiological data and behavioral history

[2115] Output: Stress level evaluation result

[2116] Step 4:

[2117] The server receives the request, retrieves the current cleaning schedule and the latest sensor information, and analyzes it.

[2118] Specific operation: The server obtains the current schedule and sensor information of the autonomous cleaning mobile device from the database.

[2119] Input: User request data, current cleaning schedule, sensor information

[2120] Output: Complete set of data required for schedule recalculation

[2121] Step 5:

[2122] The server uses AI algorithms to calculate and generate a new optimal cleaning schedule.

[2123] Specific operation: The schedule is recalculated and generated using a machine learning model based on the data collected by the server.

[2124] Input: Current schedule, sensor information, user emotion data

[2125] Output: New cleaning schedule

[2126] Step 6:

[2127] The server sends the new cleaning schedule to the terminal and displays it to the user.

[2128] Specific operation: The server returns new schedule data in an HTTP response, and the terminal displays this in a GUI.

[2129] Input: New cleaning schedule

[2130] Output: GUI display data on the terminal

[2131] Step 7:

[2132] When the user checks the new schedule and presses the approval button, the information is sent to the server.

[2133] Specific operation: The user taps the confirmation button on their smartphone, and the approval data is sent to the server.

[2134] Input: User approval operation data

[2135] Output: Authorization data sent to the server

[2136] Step 8:

[2137] The server notifies the autonomous mobile cleaning device of the new schedule, and the device starts cleaning.

[2138] Specific operation: The server transmits a new schedule to the autonomous mobile cleaning device, and the device starts operating based on the schedule.

[2139] Input: New cleaning schedule

[2140] Output: Autonomous cleaning device begins operation

[2141] Processing steps of the article storage device

[2142] Step 1:

[2143] The delivery person stores the parcel in the item storage device and holds their face up to the facial recognition camera.

[2144] Specific actions: The delivery person stands in front of the facial recognition camera and faces forward.

[2145] Input: Delivery person's facial data

[2146] Output: Storage reception data for storage device

[2147] Step 2:

[2148] The item storage device (terminal) transmits the facial authentication data to the server.

[2149] Specific operation: Facial recognition data is packaged into packets and sent to the server.

[2150] Input: Delivery person's facial recognition data

[2151] Output: Facial recognition data sent to the server

[2152] Step 3:

[2153] The server analyzes the facial recognition data and determines that the authentication was successful.

[2154] Specific operation: The server uses an AI algorithm to compare the facial recognition data with database information and determine the authentication result.

[2155] Input: Facial recognition data, database information

[2156] Output: Authentication result

[2157] Step 4:

[2158] The server records in a database that the parcel has been stored and sends a notification of the parcel's arrival to the corresponding user.

[2159] Specific operation: The server updates the database and sends a push notification to the user device.

[2160] Input: Delivery storage completion data, corresponding user information

[2161] Output: Push notification data

[2162] Step 5:

[2163] The emotion engine analyzes the user's emotion data and adjusts the operation of the item storage device according to the user's emotion state.

[2164] Specific behavior: The emotion engine detects the user's emotional state and sets behavior parameters.

[2165] Input: User emotion data

[2166] Output: Operating parameters

[2167] Step 6:

[2168] The user arrives at the item storage device and holds their face up to the face authentication camera.

[2169] Specific actions: Stand in front of the item storage device and hold your face towards the camera.

[2170] Input: User's face data

[2171] Output: Authentication request data

[2172] Step 7:

[2173] The item storage device (terminal) transmits the user's facial authentication data to the server.

[2174] Specific operation: Sends authentication data to the server.

[2175] Input: Facial recognition data

[2176] Output: Authentication data sent to the server

[2177] Step 8:

[2178] The server analyzes the facial recognition data and compares it with database information.

[2179] Specific operation: The server uses an AI algorithm to match the facial recognition data and generate a recognition result.

[2180] Input: Authentication data, database information

[2181] Output: Authentication result

[2182] Step 9:

[2183] The server notifies the item storage device (terminal) that the authentication was successful.

[2184] Specific operation: Send an authentication success message to the item storage device.

[2185] Input: Authentication result

[2186] Output: Unlock instruction data for the item storage device

[2187] Step 10:

[2188] The item storage device (terminal) unlocks the device based on the authentication result.

[2189] Specific operation: Activates the unlocking mechanism and releases the locked state.

[2190] Input: Unlock instruction data

[2191] Output: Unlocked

[2192] Step 11:

[2193] The user removes the parcel from the item storage device.

[2194] Specific operation: After unlocking, open the storage device and remove the parcel.

[2195] Input: Unlocked containment device

[2196] Output: Retrieved parcel

[2197] Step 12:

[2198] The server records in the database that the parcel has been picked up and sends a notification to the user that the process has been completed.

[2199] Specific operation: A receipt completion message is sent to the user's device via push notification.

[2200] Input: Data extracted

[2201] Output: Push notification data

[2202] (Application example 2)

[2203] 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."

[2204] Modern brick-and-mortar stores require improved efficiency and security in cleaning and item pickup. However, these tasks still require a large amount of labor, and providing services that take into account the emotional state of users is difficult. Especially during stressful times, more flexible and prompt responses are needed to improve user satisfaction.

[2205] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2206] In this invention, the server includes means for collecting operation information from multiple autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information, means for controlling the multiple autonomous mobile cleaning devices in accordance with the cleaning schedule, and means for receiving requests from users via communication with client terminals and adjusting the cleaning schedule in real time based on the requests. This makes it possible to adjust the operation of the entire system based on user emotion data and provide flexible and efficient cleaning work and item collection.

[2207] An "autonomous mobile cleaning device" is a machine that uses sensor technology and artificial intelligence to autonomously move around inside buildings and brick-and-mortar stores and clean.

[2208] The "cleaning schedule" is a timetable or schedule information that plans which areas an autonomous mobile cleaning device will clean at which times.

[2209] A "client terminal" is a communication device used by a user, such as a smartphone, tablet, or PC, that communicates with a server to send requests and receive information.

[2210] An "item storage device" is a device that stores parcels and purchased items and allows users to receive items using authentication technology such as facial recognition.

[2211] An "authentication device" is a device for obtaining user authentication information, and includes, for example, a camera or sensor for identifying a user using facial recognition technology.

[2212] An "emotion engine" is software or a system that acquires and analyzes the user's emotional data and adjusts the operation of each device based on the results.

[2213] "User emotion data" is data that indicates the user's emotional state (for example, joy, anger, sadness, stress, etc.) based on information acquired from the user's facial expressions, voice, behavior, etc.

[2214] A "server" is a computer system that manages and controls data sent from multiple devices and terminals in an integrated manner and performs the necessary processing.

[2215] System configuration

[2216] The present invention is an integrated system consisting of the following elements:

[2217] 1. Autonomous mobile cleaning device: A device that combines sensor technology and artificial intelligence to move autonomously and clean buildings or physical stores.

[2218] 2. Item storage device: A device that stores parcels and purchased items and allows users to receive them using authentication technology such as facial recognition.

[2219] 3. Server: A computer system that centrally manages and controls data from each device and terminal and performs the necessary processing.

[2220] 4. Emotion engine: Software or a system that acquires and analyzes user emotional data and adjusts the behavior of each device based on the results.

[2221] 5. Client terminal: A communication device used by a user, such as a smartphone, tablet, or PC, that communicates with the server and sends and receives requests.

[2222] System Operation

[2223] The overall system operates as follows.

[2224] First, the autonomous mobile cleaning device uses sensor technology and artificial intelligence to detect its surrounding environment and autonomously move around buildings and physical stores to clean. Operational information is sent to a server, which generates an optimal cleaning schedule. Users can request changes to the cleaning schedule via their client device, and the server adjusts the schedule in real time if requested. Furthermore, an emotion engine analyzes the user's emotional data and optimizes the cleaning schedule and item handover behavior based on the user's specific emotional state.

[2225] Next, during the process of receiving a parcel or purchased item from the item storage device, the user's authentication information is acquired by an authentication device (such as a facial recognition camera). If authentication is successful, the item storage device is unlocked and the user can receive the item. At this time, the emotion engine analyzes the user's emotional state and adjusts its behavior to respond quickly if the user's stress level is high.

[2226] Hardware and software used

[2227] The specific hardware and software used to implement the present invention are described below.

[2228] Hardware: Facial recognition cameras (e.g., high-resolution cameras), autonomous mobile cleaning devices (e.g., high-performance robots), and storage devices (e.g., smart lockers)

[2229] Software: Emotion data analysis API (e.g., advanced electronic data analysis platform), facial recognition software (e.g., image processing library), data management server (e.g., distributed computing platform)

[2230] Examples and prompts

[2231] For example, if a user wishes to change their cleaning schedule, the following process takes place: When the user requests a "change in cleaning schedule" from the client terminal to the AI ​​chatbot, the request is sent to the server. The emotion engine analyzes the user's emotional data and determines their stress level. The server generates a new, optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine, and displays it to the user. If the user approves the new schedule, the server notifies the autonomous mobile cleaning device of the new schedule.

[2232] Prompt Sentence Examples

[2233] "Design a system that dynamically changes the schedule of a cleaning robot based on user emotional data. Also, create a program for a system that implements facial recognition functionality for an item storage device and processes handovers according to the customer's emotional state."

[2234] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2235] Step 1:

[2236] The user requests a "change in cleaning schedule" from the client device to the AI ​​chatbot.

[2237] Input: User input request

[2238] Output: Request content

[2239] Specific operation: The user opens the smartphone app and enters the desired change to the cleaning schedule into the chatbot via text.

[2240] Step 2:

[2241] The terminal transmits the request content to the server.

[2242] Input: Request content

[2243] Output: Request data sent to the server

[2244] Specific operation: The client terminal converts the request content into JSON format and sends it as an HTTP request to the server's API endpoint.

[2245] Step 3:

[2246] The server receives the request and the emotion engine retrieves the user's emotion data and analyzes their emotional state, including stress level.

[2247] Input: Request data, user emotion data

[2248] Output: Emotional state

[2249] Specific operation: The server calls the emotion data analysis API to obtain the user's emotion data, and analyzes the data to determine the stress level and emotional state.

[2250] Step 4:

[2251] The server generates a new optimal cleaning schedule based on the current cleaning schedule, the latest sensor data, and data from the emotion engine.

[2252] Inputs: Current cleaning schedule, latest sensor data, emotion engine data

[2253] Output: New cleaning schedule

[2254] Specific operation: The server retrieves the current cleaning schedule and sensor data from the database, combines it with data from the emotion engine, and uses an optimization algorithm to calculate a new cleaning schedule.

[2255] Step 5:

[2256] The server sends the new cleaning schedule to the client terminal and displays the new schedule to the user.

[2257] Input: New cleaning schedule

[2258] Output: The new schedule as displayed to the user

[2259] Specific operation: The server converts the new cleaning schedule into JSON format and sends it to the client device as an HTTP response. The client device displays the new schedule.

[2260] Step 6:

[2261] When the user approves the new schedule and presses the confirmation button, the information is sent to the server.

[2262] Input: User approval

[2263] Output: Authorization information sent to the server

[2264] Specific operation: When the user presses the confirmation button on the client terminal, approval information is sent to the server's API endpoint as an HTTP request.

[2265] Step 7:

[2266] The server notifies the autonomous mobile cleaning device of the new schedule.

[2267] Input: Approved new schedule

[2268] Output: Instructions to the autonomous cleaning device

[2269] Specific operation: The server sends the approved new schedule to the control system of the autonomous mobile cleaning device, causing it to execute the instructions.

[2270] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2271] 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.

[2272] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2273] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2274] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2275] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2276] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2277] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2278] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2279] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2280] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2281] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2282] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2283] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2284] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2285] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2286] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2287] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2288] Furthermore, the hardware structure of these variou...

Claims

1. a means for collecting operation information from a plurality of autonomous mobile cleaning devices and generating an optimal cleaning schedule based on the operation information; a means for controlling the plurality of autonomous mobile cleaning devices in accordance with the cleaning schedule; means for receiving requests from users via communication with a client terminal and adjusting the cleaning schedule in real time based on the requests; a means for acquiring authentication information of a user using an authentication device installed in front of the article storage device and performing authentication when handing over an article based on the authentication information; means for collecting and managing data relating to the delivery of the goods; A system including:

2. The system according to claim 1 , wherein a sensor for detecting a surrounding environment is used to collect operational information about the plurality of autonomous mobile cleaning devices.

3. The system of claim 1 , wherein the authentication device obtains user authentication information using facial recognition technology.

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